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dissertation entitled

PROFITABILITY OF CASSAVA PRODUCTION
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ANALYSIS (COTE D’IVOIRE, GHANA AND NIGERIA)

presented by

Youssouf Camara

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PROFITABILITY OF CASSAVA PRODUCTION SYSTEMS IN WEST AFRICA:
A COMPARATIVE ANALYSIS (COTE D’IVOIRE, GHANA AND NIGERIA)

By

Youssouf Camara

A DISSERTATION

Submitted to
Michigan State University
In partial fulﬁllment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Agricultural Economics

2000

ABSTRACT

PROFIT ABILITY OF CASSAVA PRODUCTION SYSTEMS IN WEST AFRICA:
A COMPARATIVE-ANALYSIS (COTE D’IVOIRE, GHANA AND NIGERIA)

By
Youssouf Camara

Sub-Saharan Aﬁica (SSA) cassava- producing countries such as Nigeria, Ghana,
and cote d’Ivoire have developed, in recent years, an interest in cassava as an alternative
food crop. This has led to a major expansion in cassava- based production systems in
Nigeria and Ghana, whereas'there has been a slower growth in Cote d’Ivoire.

The study examines, using the Policy Analysis Matrix (PAM) framework, the
magnitude of the impact of various factors such as agricultural policies (i.e., trade and
price policies, domestic production taxes or subsidies), location and technologies
(production and processing) on the private and social proﬁtability of cassava production
and post-production processing in cote d’Ivoire, Ghana and Nigeria. The study relies
primarily on data for cote d’Ivoire, Ghana and Nigeria from the Collaborative Study of
Cassava in Aﬁica (COSCA) survey.

The study is organized in three essays. The baseline results in essay 1 (chapter 2)
show that cassava/maize systems have a competitive advantage over their competitors in
Cote d’Ivoire. That is, proﬁtabilities (ﬁnancial and social) of cassava/maize systems
signiﬁcantly exceed those of rainfed rice/maize systems. In addition, the baseline results

indicate that, farmers operating at the market located near the port city beneﬁt from a

small implicit price support whereas farmers operating in the market located far away
from the port city were subject to a small implicit tax. The simulation ﬁndings indicated
that: 1) an increase in yields per hectare of cassava and rainfed rice would not only
ﬁrrther enhance the comparative advantage of cassava/maize systems but also cause
rice/maize systems, which were unproﬁtable at the baseline, to become socially
proﬁtable; and 2) a depreciation of the equilibrium exchange rate (more fcfa per SUS)
also increased the proﬁtability of both systems.

The second essay (chapter 3) deals with the evaluation of the social proﬁtability
of cassava/maize systems, under alternative production and processing technology
combinations, in Nigeria. The baseline results show that the net social proﬁtabilities
(N SP) of systems under “Impmech” technology exceed those of systems under other
alternative technologies, namely “Locmech”, “Locman” and “Impman”. The simulation
results indicate that a depreciation of the real exchange rate (more nairas per US dollar)
would increase signiﬁcantly the proﬁtabilities of cassava/maize systems under the
technology combinations “Impmech” and “Locmech”.

The ﬁnal essay (chapter 4) compares the competitiveness of cassava/maize
systems in Cote d’lvoire, Ghana and Nigeria. The baseline results demonstrate the
similarity in efﬁciencies of production in these West African countries. The simulation
ﬁndings indicated that, in Cote d’Ivoire, farmers beneﬁted from the depreciation of the
equilibrium exchange rate while farmers in Ghana and Nigeria suffered losses.
Simulation results also indicated that Ivorian and Ghanaian cassava/maize farmers could
beneﬁt from growing IITA’s improved variety and adopting mechanized processing

methods.

Cepyn'ght by
YOUSSOUF CAMARA
2000

To Papa Mamadou Camara

To Maman Marie-Therese Delompuy

To the HUMAN RACE

ACKNOWLEDGMENTS

I express my sincere and profound thanks to the Almighty God (the Alpha and the

Omega) who has used so many individuals as instruments to shape my life.

I would also like to express my gratitude to the Rockefeller Foundation for the ﬁnancial

support. This dissertation would not have been possible without it.

My particular and sincere thanks the following individuals:

Dr. John M. Staatz, my major professor, for challenging me to always do a bit
more. His guidance and invaluable support throughout my program has been an
gratifying experience;

Dr. Allan Schmid, Dr. Eric W. Crawford, Dr. John Strauss, Dr. Carl E. Liedholm
(my dissertation committee members); their timely and constructive criticisms
improved the quality of this study;

Dr. Felix Nweke for not only providing me with the COSCA survey data but also
for “walking” me through this important data set with patience. I express my
sincere gratitude to him;

Dr Richard Brandenburg, Associate Dean of the Agricultural and Natural
Resources (ANR) school and MSU’s Graduate School for providing me with a
Dissertation Completion Fellowship and for “making sure I never go hungry
while studying at MSU”. They delivered the goods;

Dr. George Dimithe and Dr. Josue Dione for their unconditional friendship and

their brotherly love and support;

TABLE OF CONTENTS

List of Tables ....................................................................................... xi
List of Figures ...................................................................................... xvii

CHAPTER 1- INTRODUCTION

1.1 Issues and Background ................................................................. 1
1.2 Research Problem and Knowledge Gap ............................................. 1
1.3 Research Questions and Hypotheses ................................................. 3
1.4 Data ....................................................................................... 4
1.4.1. Source ........................................................................ 4
1.4.2. Collection Procedure ....................................................... 6
1.5 Methodological Framework ........................................................... 7
1.6 Speciﬁc Types of Analysis Flamed ................................................ 11

1.6.1. Financial Enterprise Budgets for Cassava Production and Post-
Production in Cote d’Ivoire, Ghana and Nigeria, as well as for Rice in
Cote d’Ivoire ....................................................................... 13

1.6.2. Comparative Analyses of the Economic Proﬁtability of Cassava-
based Production Systems in the Three Countries and of the
Competitiveness of as Compared to Rice-based Systems in Cote

d’lvoire ............................................................................. 13

1.6.3. Comparative Analysis of Policy-induced Income Transfers in Cote

d’Ivoire, Ghana and Nigeria ..................................................... 15

1.6.4. Sensitivity Analysis ....................................................... 16
1.7 Conclusion ............................................................................. 16
References .................................................................................. 19
Appendix .................................................................................... 2]

vii

CHAPTER 2- ESSAY 1: EVALUATING THE EFFECTS OF POLICIES ON THE
COMPETITIVENESS OF CASSAVA-BASED PRODUCTION SYSTEMS IN COTE

D’IVOIRE
2.1 Introduction ............................................................................ 27

2.2 Methodological Framework ......................................................... 3O

2.2.1.A Short Description of the Policy Analysis Matrix (PAM) Model..30

2.2.2. Data .......................................................................... 31

2.3 Empirical Analyses .................................................................... 32
2.3.]. Financial Proﬁtability Analysis .......................................... 33
2.3.1.1. Farm level Analysis ............................................ 34

2.3.1.2. Post-harvest Financial Analysis for Cassava ............... 36

2.3.2. Economic Proﬁtability Analysis ......................................... 39

2.3.3. Policy matrix Analysis .................................................... 41

2.3.3.1. Baseline Results ................................................ 42

2.3.3.2. Sensitivity Analysis ............................................ 51

2.4 Conclusions ............................................................................ 54

References .................................................................................. 56

Appendix 2 ................................................................................. 58

CHAPTER 3- ESSAY 2: EVALUATING THE SOCIAL PROFITABILITY OF
CASSAVA—BASED PRODUCTION SYSTEMS UNDER ALTERNATIVE
PRODUCTION AND PROCESSING COMBINATIONS IN NIGERIA

3.1 Introduction ............................................................................. 75
3.2 Methodological Framework ......................................................... 77
3.3 Empirical Analyses .................................................................... 78

viii

3.3.1. Financial Proﬁtability Analysis .......................................... 79

3.3.1.1. Fann level Analysis ............................................ 80

3.3.1.2. Post-harvest Financial Analysis for Cassava ............... 82

3.3.2. Economic Proﬁtability Analysis ......................................... 84

3.3.3. Policy matrix Analysis .................................................... 87
3.3.3.1. Baseline Results ................................................ 88

3.3.3.2. Sensitivity Analysis ............................................ 94

3.4 Conclusions ............................................................................ 97
References .................................................................................. 99
Appendix 3 ................................................................................. 101

CHAPTER 4- ESSAY 3: COMPARING THE PROFITABILITY OF CASSAVA-

BASED PRODUCTION SYSTEMS IN THREE WEST AFRICAN COUNTRIES:
COTE D’IVOIRE, GHANA AND NIGERIA

4.1 Introduction ........................................................................... 121
4.2 Methodological Framework ......................................................... 122

4.3 Empirical Analyses .................................................................. 123
4.3.1. Private Proﬁtability (PP) ................................................ 124

4.3.1.1. Farm level Analysis .......................................... 124

4.3.1.2. Post-harvest Financial Analysis for Cassava .............. 126

4.3.2. Social Proﬁtability (SP) ................................................. 129

4.3.3. Policy Matrix Analysis .................................................. 132
4.3.3.1. Baseline Results ............................................... 133

4.3.3.2. Sensitivity Analysis .......................................... 140

4.4 Conclusions ........................................................................... 143

ix

References ................................................................................. 145

Appendix 4 ................................................................................. 146

CHAPTER 5- CONCLUSIONS AND EXTENSIONS

5.1 Regarding the Impact of Various Factors (e.g., agricultural policies, location
and technologies) on the Proﬁtability of Cassava-based Production Systems in

West Aﬁica .............................................................................. 167
5.1.1. Agricultural Policies ................................................... 172
5.1.2. Technologies ............................................................ 174
5.2 Extensions ......................................... ' .................................. 175
5.3 Conclusions ......................................................................... 176
References ............................................................................... 1 78

Table 1.1.
Table 1.2.

Table Al-l.
Table A1-2.

Table Al-3.
Table A1-4.

Table A1-5.

Table 2-1.

Table 2-2.

Table 2-3.

Table 2-4.

Table 2-5.

Table 2-6.

Table 2-7.

Table 2-8.

Table 2-9.

Table 2-10.

LIST OF TABLES

Summary of Data Needs and Availability ....................................... 5
An outline of the Policy Analysis Matrix (PAM) .............................. 7
Sample Size (number of ﬁelds) by Crop and by Country .................... 22
Distribution of Households by Type of Cassava Processing and by
Country ............................................................................. 22
Distribution of Cassava-based ﬁelds by Production technology

in Nigeria ........................................................................... 22
Distribution of Cassava-based ﬁelds by Agroecological Zones

in Nigeria ........................................................................... 23
Distribution of ﬁelds by Production/Processing Technologies in Cote
d’Ivoire, Ghana and Nigeria ..................................................... 23

Farm-Level Summary Estimates of Financial Budget Indicators for
Cassava/Maize And Rainfed Rice/Maize Production Systems in Cote
d’Ivoire, 1989/91 .................................................................. 35
Estimated Average Financial Budget per hectare for Attieke Production in
Cote d’Ivoire, 1989-1991, assuming that 45% of roots production goes
into attieke production ............................................................ 37
Summary Estimates of Farm-Level Economic Budget Indicators for
Commercial Cassava/Maize and Rainfed Rice/Maize Production

Systems, by Regional Output Markets, Cote d’Ivoire: 1989/91 ............ 40
Summary Estimates of F arm-Level Economic Budget Indicators for
Subsistence Cassava/Maize and Rainfed Rice/Maize Production

Systems, by Production Zones, Cote d’Ivoire: 1989/91 ..................... 40
Policy Analysis Matrix (PAM) for Commercial Cassava/Maize and

Rainfed Rice/Maize Systems in Cote d’Ivoire: Net Financial Proﬁtability
(fcfa /ha), Net Social Proﬁtability (fcfa/ha), and Net Effects of Policy
Distortions, 1989/1991 ............................................................ 43
Policy Analysis Matrix (PAM) for Subsistence Cassava/Maize and

Rainfed Rice/Maize Systems in Cote d’Ivoire: Net Financial Proﬁtability
(fcfa /ha), Net Social Proﬁtability (fcfa/ha), and Net Effects of Policy

Distortions, 1989/1991 ............................................................ 44
Ratio Indicators for Commercial Cassava/Maize and Rainfed

Rice/Maize Systems in Cote d’Ivoire: 1989/1991 ............................ 47
Ratio Indicators for Subsistence Cassava/Maize and Rainfed

Rice/Maize Systems in Cote d’Ivoire: 1989/1991 ............................ 47
The Effects of Changes in Yields per Hectare on Selected Policy

Indicators for Commercial Production ......................................... 52
The Effects of a Change in the Shadow Exchange Rate on the Net Social
Proﬁt (N SP)/ha for Commercial Production Systems ....................... 53

Table 2-11.

Table A2-1.
Table A2-2.
Table A2-3.
Table A2-4.
Table A2-5.
Table A2-6.

Table A2-7.

Table A2-8.

Table A2-9.

Table A2-10.

Table A2-11.

Table A2-12.

Table A2-13.

Table A2-l4.

Table 3-1.

The Effects of a Change in the Shadow Exchange Rate on Selected
Policy Indicators for Commercial Production Systems, by Production

Systems for Each Regional Output Markets ................................... 53
Estimated Average Financial Budget for Cassava/Maize Production
Systems, Cote d’Ivoire: 1989/1991 ............................................. 59
Estimated Average Financial Budget for Rainfed Rice/Maize Production
Systems, Cote d’Ivoire: 1989/1991 ............................................. 60
Economic Import Parity Price of Cassava Root-For Sale in Regional
Output Markets, Cote d’Ivoire: 1989/1991 .................................... 61
Economic Import Parity Price of Paddy-For Sale in Regional Output
Markets, Cote d’Ivoire: 1989/1991 ............................................. 62
Economic Import Parity Price of Cassava Root- For Home Consumption,
Cote d’Ivoire: 1989/1991 ......................................................... 63
Economic Import Parity Price of Paddy - For Home Consumption,

Cote d’Ivoire: 1989/1991 ........................................................ 64

Estimated Economic Farm Level Budget for Commercial Cassava/Maize
Production Systems, by Regional Output Markets, Cote d’Ivoire,

1989/ 1991 .......................................................................... 65
Estimated Economic F arm Level Budget for Commercial Rainfed
Rice/Maize Production Systems, by Regional Output Markets, Cote
d’lvoire, 1989/1991 ............................................................... 66
Estimated Economic Farm Level Budget for Subsistence Cassava/Maize
Production Systems, by Regional Output Markets, Cote d’Ivoire, 1989-
1991 ................................................................................. 67
Estimated Economic Farm Level Budget for Subsistence Rainfed
Rice/Maize Production Systems, by Regional Output'Markets, Cote
d’Ivoire, 1989-1991 ............................................................... 68
Estimated Financial Farm Level Budget for Commercial Rainfed
Rice/Maize Production Systems, by Regional Output Markets, Cote
d’Ivoire, 1989/1991 ............................................................... 69
Estimated Financial Farm Level Budget for Commercial Cassava/Maize
Production Systems, by Regional Output Markets, Cote d’Ivoire,
1989/1991 .......................................................................... 70
Estimated Financial Farm Level Budget for Subsistence Rainfed
Rice/Maize Cassava/Maize Production Systems, by Regional Output

Markets, Cote d’Ivoire, 1989/1991 ............................................. 71
Estimated Financial Farm Level Budget for Subsistence Production
Systems, by Regional Output Markets, Cote d’Ivoire, 1989/1991 ......... 72

Summary Estimates (in naira) of Farm-Level Financial Budget
Indicators for Cassava/Maize Production Systems, by Production
Technologies: Nigeria, 1989/91 ................................................. 81

xii

Table 3-2.

Table 3-3.

Table 3-4.

Table 3-5.

Table 3-6.

Table 3-7.

Table A3-1.
Table A3-2.

Table A3-3.

Table A3-4.

Table A3-5.

Table A3-6.

Table A3-7.

Table A3-8.

Table A3-9.

Table A3-10.

Summary Estimates (in naira) of Postfarm-Level Financial Budget
Indicators for Gari Production, by Technology Combinations: Nigeria,
1989/91 ............................................................................. 83
Summary Estimates (in nairas) of Farm-Level Economic Budget

Indicators For Commercial Cassava/Maize Production Systems at Each
Regional Output Market, by Production and Processing Technology

Combinations, Nigeria: 1989/1991 ............................................. 85
Summary of the Net Effects (in nairas) of Policy-Induced Transfers
For Commercial Cassava/Maize Systems in Nigeria: 1989/1991 .......... 88

Ratio Indicators for Commercial Cassava/Maize Production Systems
Under alternative production and processing combinations and by

Distance in Nigeria, 1989-1991 ................................................. 91
Effects of a 286 % Change in the Shadow Exchange Rate on the Net
Social Proﬁt (N SP) ............................................................... 95
Effects of a 286 % Change in the Exchange Rate on Selected Policy
Parameters ......................................................................... 96

Estimated Average Financial Budget for Cassava/Maize Systems- For

Improved landraces in Nigeria: 1989/1991 .................................. 102
Estimated Average Financial Budget for Cassava/Maize Systems- For
Local landraces in Nigeria: 1989/1991 ....................................... 103

Estimated Average Financial Budget per hectare for Gari Production
under Technology Combination “IMPMECH”, Nigeria, 1989/1991,
assuming 80% of root production goes into gari production .............. 104
Estimated Average Financial Budget per hectare for Gari Production
under Technology Combination “LOCMECH”, Nigeria, 1989/1991,
assuming 80% of root production goes into gari production .............. 105
Estimated Average Financial Budget per hectare for Gari Production
under Technology Combination “LOCMAN”, Nigeria, 1989/1991,
assuming 80% of root production goes into gari production .............. 106
Estimated Average Financial Budget per hectare for Gari Production
under Technology Combination “IMPMAN”, Nigeria, 1989/1991,
assuming 80% of root production goes into gari production ............. 107
Economic Import Parity Price of Cassava Root, by Alternative

Technology Combinations. For Sale in the Regional Output Market of
Onitsha, Nigeria: 1989/1991 ................................................... 108
Economic Import Parity Price of Cassava Root, by Alternative

Technology Combinations. For Sale in the Regional Output Market of
Abeokuta, Nigeria: 1989/1991 ................................................. 109
Estimated Financial Budget for Commercial Cassava/Maize Systems

under Technology Combination “IMPMECH”, by Regional Output
Markets, Nigeria, 1989/1991 ................................................... 110
Estimated Economic Budget for Commercial Cassava/Maize Systems
under Technology Combination “IMPMECH”, by Regional Output
Markets, Nigeria, 1989/1991 ................................................... 111

xiii

Table A3-11.

Table A3-12.

Table A3-13.

Table A3-14.

Table A3-15.

Table A3-16.

Table A3-17.

Table 4-1.

Table 4-2.

Table 4-3.

Table 4-4.

Table 4-5.

Table 4-6.

Estimated Financial Budget for Commercial Cassava/Maize Systems
under Technology Combination “LOCMECH”, by Regional Output
Markets, Nigeria, 1989/1991 ................................................... 112
Estimated Economic Budget for Commercial Cassava/Maize Systems
under Technology Combination “LOCMECH”, by Regional Output
Markets, Nigeria, 1989/1991 ................................................... 113
Estimated Financial Budget for Commercial Cassava/Maize Systems
under Technology Combination “LOCMAN”, by Regional Output
Markets, Nigeria, 1989/1991 ................................................... 114
Estimated Economic Budget for Commercial Cassava/Maize Systems
under Technology Combination “LOCMAN”, by Regional Output
Markets, Nigeria, 1989/1991 ................................................... 115
Estimated Financial Budget for Commercial Cassava/Maize Systems
under Technology Combination “IMPMAN”, by Regional Output
Markets, Nigeria, 1989/199 .................................................... 116
Estimated Economic Budget for Commercial Cassava/Maize Systems
under Technology Combination “IMPMAN”, by Regional Output
Markets, Nigeria, 1989/1991 ................................................... 117
Policy Analysis Matrix (PAM) for Commercial Cassava/Maize Systems in
Nigeria under alternative production and processing combinations and by
distance between output markets and the village/farm: Net Financial
Proﬁtability (nairas /ha), Net Social Proﬁtability (nairas/ha), and Net
Eﬁects of Policy Distortions: 1989-1991 .................................... 118

Summary Estimates of Farm-Level Financial Budget Indicators (in US$
using prevailing Exchange Rates) for Cassava/Maize Production Systems,
by Country, 1989/91 ............................................................ 125
Summary Estimates of Post-farm Level Financial Budget Indicators (in
US$ using prevailing Exchange Rates) for Processed Products (A ttieke in
Cote d’Ivoire and Gari in Ghana and Nigeria) Production, by Country:
1989/91 ........................................................................... 127
Summary Estimates of Post-farm-Level Financial Budget Indicators

(in US$ using prevailing Exchange Rates) for Gari Production, by
Technology Combinations: Nigeria, 1989/91 ............................... 128
Summary Estimates of Farm-Level Economic Budget Indicators (in USS
using Shadow Exchange Rate) For Commercial Cassava/Maize

Production Systems at Each Regional Output Market, by Country:
1989/1991 ........................................................................ 132
Summary Estimates of Farm-Level Economic Budget Indicators (in US$
using Shadow Exchange Rates) For Commercial Cassava/Maize
Production Systems at Each Regional Output Market, by Production and
Processing Technology Combinations, Nigeria: 1989/1991 ............... 132
Summary of the Net Effects (in US$ using Shadow Exchange Rates) of
Policy-Induced Transfers For Commercial Cassava/Maize Systems, by
Country: 1989/1991 ............................................................. 135

xiv

Table 4-7.
Table 4-8.

Table 4-9.

Table 4-10.
Table 4-1 1.

Table 4-12.

Tale A4-1.

Table A4-2.

Table A4-3.

Table A4-4.

Table A4-5.

Table A4-6.

Table A4-7.

Table A4-8.

Table A4-9a.

Table A4-9b.

Table A4-10.

Table A4-1 1.

Summary of the Net Effects of Policy-Induced Transfers For Commercial

Cassava/Maize Systems in Nigeria: 1989/1991 ............................. 135
Ratio Indicators for Commercial Cassava/Maize,
by Country: 1989-1991 ......................................................... 138

Ratio Indicators for Commercial Cassava/Maize Production Systems
Under Alternative Production and Processing Combinations and by

Country in Nigeria, 1989-1991 138 ............................................ 138
Effects of Changes in Cassava Yields and Processing Costs on the DRC
for Root Production in Cote d’Ivoire and Ghana: 1989/1991 .............. 140
Effects of Change in the Shadow Exchange Rate on the Net Social Proﬁt

(NSP in $US using Shadow exchange rates), by Country: 1989/1991... .. 141
Effects of Change in the Shadow Exchange Rate on Selected Policy
Indicators, by Country: 1989/1991 ............................................ 142
Estimated Average Financial Budget for Cassava/Maize Production
Systems, Cote d’lvoire: 1989/1991 ........................................... 147
Estimated Average Financial Budget for Cassava/Maize Production
Systems, Ghana: 1989/1991 ................................................... 148
Estimated Average Financial Budget for Cassava/Maize Systems- For
Local landraces in Nigeria: 1989/1991 ....................................... 149

Estimated Average Financial Budget per hectare for Attieke Production in
Cote d’Ivoire, 1989-1991, assuming that 45 % of roots production goes
into attieke production ......................................................... 150
Estimated Average Financial Budget per hectare for Attieke Production in
Ghana, 1989-1991, assuming that 50% of roots production goes into
attieke production ............................................................... 151
Estimated Average Financial Budget per hectare for Gari Production
under Technology Combination “LOCMAN”, Nigeria, 1989/1991,
assuming 80% of root production goes into gari production ............ 152
Economic Import Parity Price of Paddy-For Sale in Regional Output
Markets, Ghana: 1989/1991 ................................................... 153
Economic Import Parity Price of Paddy-F or Sale in Regional Output
Markets, Cote d’lvoire: 1989/1991 ........................................... 154
Economic Import Parity Price of Cassava Root, by Alternative

Technology Combinations. For Sale in the Regional Output Market of
Abeokuta, Nigeria: 1989/1991 ................................................. 155
Economic Import Parity Price of Cassava Root, by Alternative

Technology Combinations. For Sale in the Regional Output Market of
Onitsha, Nigeria: 1989/1991 ................................................... 156
Estimated Economic Farm Level Budget for Commercial Cassava/Maize
Production Systems, by Regional Output Markets,

Ghana, 1989/1991 ............................................................... 157
Estimated Financial Farm Level Budget for Commercial Cassava/Maize
Production Systems, by Regional Output Markets,

Ghana, 1989/1991 ............................................................... 158

Table A4-12.

Table A4-13.

Table A4-14.

Table A4-15.

Table A4-16.

Table A4-17.

Table A4- 1 8.

Table 5-1.

Table 5-2.

Estimated Economic F arm Level Budget for Commercial Cassava/Maize
Production Systems, by Regional Output Markets, Cote d’Ivoire,

1 989/ 1991 ........................................................................ l 59
Estimated Financial Farm Level Budget for Commercial Cassava/Maize
Production Systems, by Regional Output Markets, Cote d’Ivoire,
1989/1991 ........................................................................ 160
Estimated Economic Budget for Commercial Cassava/Maize Systems
under Technology Combination “LOCMAN”, by Regional Output
Markets, Nigeria, 1989/1991 ................................................... 161
Estimated Financial Budget for Commercial Cassava/Maize Systems
under Technology Combination “LOCMAN”, by Regional Output
Markets, Nigeria, 1989/1991 162 .............................................. 162
Policy Analysis Matrix (PAM) for Commercial Cassava/Maize Systems in
Nigeria under alternative production and processing combinations and by
distance between output markets and the village/farm: Net Financial
Proﬁtability (nairas /ha),Net Social Proﬁtability (nairas/ha), and Net
Effects of Policy-Induced Transfers Distortions: 1989-1991 .............. 163
Policy Analysis Matrix (PAM) for Commercial Cassava/Maize Production
Systems in Ghana: Net Financial Proﬁtability ($US lha), Net Social
Proﬁtability ($US/ha), and Net Eﬁ‘ects of Policy-Induced Transfers,
1989/1991 ........................................................................ 164
Policy Analysis Matrix (PAM) for Commercial Cassava/Maize Production
Systems in Cote d’Ivoire: Net Financial Proﬁtability (SUS lha), Net Social
Proﬁtability ($US/ha), and Net Effects of Policy-Induced Transfers,

1989/1991 ........................................................................ 165
Financial and Economic Prices (in francs CFA) of Cassava Roots by
Output markets, Cote d’Ivoire, 1989/1991 ................................... 169
Financial and Economic Prices (in ﬁ'ancs CFA) of Paddy by

Output markets, Cote d’Ivoire, 1989/1991 ................................... 169

xvi

Figure Al-l.
Figure A1-2.

Figure A1-2.

Figure 2.1.

Figure 2.2.

Figure A2.1.

Figure A2.2.

Figure 3.1.

Figure 3.2.

Figure A3.1.

Figure A3.2.

LIST OF FIGURES

Cote d’Ivoire: Study Sites, Output Markets (Bonoua and N’douci) and
Port City (ABIDJAN) ............................................................ 24
Ghana: Study Sites, Output Markets (Koforidua and Kumasi) and Port
City (ACCRA) ..................................................................... 25
Nigeria: Study Sites, Output Markets (Abeokuta and Onitsha) and Port
City (LAGOS) ..................................................................... 26

DRC Ratios Over Space for Commercial Cassava/Maize and Rainfed
Rice/Maize Production Systems- Bonoua is the Regional Output Market,
Cote d'Ivoire: 1989/1991 ......................................................... 49
DRC Ratios Over Space for Commercial Cassava/Maize and Rainfed
Rice/Maize Production Systems- N’douci is the Regional Output Market,
Cote d'Ivoire: 1989/1991 ......................................................... 50
Farm-Level Economic Prices Over Space of Cassava Root and Rainfed
rice Paddy- For Sale in the Regional Market of Bonoua, Cote d’Ivoire:
1989/ 191 ........................................................................... 73
F arm-Level Economic Prices Over Space of Cassava Root and Rainfed
rice Paddy- For Sale in the Regional Market of N’douci, Cote d’Ivoire:
1989/191 ........................................................................... 74

DRC Ratios Over Space for Commercial Cassava/Maize Production
Systems under Alternative Technology Combinations- Abeokuta is the
Regional Output Market, Nigeria: 1989/1991 ................................. 91
DRC Ratios Over Space for Commercial Cassava/Maize Production
Systems Under Alternative Technology Combinations- Onitsha is the
Regional Output Market, Nigeria: 1989/1991 ................................. 93
F arm-Level Economic Prices of Cassava Root Under Alternative
Production and Production Technology Combinations Over Space - For
Sale in the Regional Market of Abeokuta, Nigeria: 1989/191 ............. 119
Farm-Level Economic Prices of Cassava Root Under Alternative
Production and Production Technology Combinations Over Space - For
Sale in the Regional Market of Onitsha, Nigeria: 1989/191 ............... 120

xvii

CHAPTER 1

INTRODUCTION

1.1. Issues and Background

Cassava is an important commodity in many farming systems in Sub-Saharan
Aﬁica (SSA). Its relative importance stems from its adaptability to a wide range of agro-
ecologies, including marginal lands and erratic rainfall conditions. Thus, regardless of the
production environment, compared to other crops, cassava has lower production risks,
and provides the possibility of maintaining a continuous food supply throughout the year
(Nweke et a1, 1994).

In most SSA countries, governments have avoided investing resources in the
improvement of cassava production partly because they view cassava, in the words of
Jones (1959), as “...a starchy staple that provides at best only a small part of protein
requirement and only trivial amounts of vitamins”. This has led many African policy-
makers to regard cassava solely as a means to ﬁght famine. However, this research is
based on the argument that the role of cassava in improving household food security in
SSA should be appraised not only from a nutritional point of view, but also in terms of its

potential as a cash crop.

1.2. Research Problem and Knowledge Gap
SSA cassava- producing countries such as Nigeria, Ghana, and Cote d’Ivoire have
developed, in recent years, an interest in cassava as an alternative food crop. This has led

to a major expansion in cassava- based production systems in Nigeria and Ghana, whereas

there has been a slower growth in Cote d’Ivoire (Nweke, 1998). Indeed, Theberger
(1985) and Babo (1995) have argued that the government of Cote d’Ivoire has invested
very little in improving cassava-based production systems. A major focus has been the
expansion of rice production (Adesina, 1995). The Ivorian policies have resulted in rice
being much cheaper relative to cassava products around major market centers than is the
case in either Ghana or Nigeria.

This study is based on the argument that the difference in various factors such as
agricultural policies (i.e., trade and price policies, domestic production taxes or subsidies),
location and technologies (production and processing) between cote d’Ivoire, Ghana and
Nigeria explains the difference in the level of growth in cassava-based production systems.

Trade policies include protectionism (duties or quantitative controls) or subsidies
on imports and taxes or subsidies on exports that cause the domestic price of a commodity
to differ from its international price. Another type of policy involves taxing or subsidizing
inputs in producing a commodity.

The alternative production and processing technology-combinations examined are
“Impmech”, “Locmech “Locman ” and “Impman deﬁned as follows: a) Impmech
represents IITA’s improved cassava varieties processed using a mechanized grating
method, Locmech represents local cassava varieties processed using a mechanized grating
method, Locman represents local cassava varieties processed using a manual grating
method and Impman represents IITA’s improved cassava varieties processed using a
manual grating method.

The study examines the magnitude of the impact of these factors on the private and

social proﬁtability of cassava production and post-production processing in Nigeria,

Ghana and Cote d’Ivoire. The topic has not been examined in previous studies.

1.3. Research Questions and Hypotheses

The problem and the knowledge gap discussed above raise the following research
question: What is the relative proﬁtability of cassava-based production systems in Cote
d’Ivoire, Ghana and Nigeria, and how do various factors such as agricultural policies (i.e.,
trade and price policies, domestic production taxes or subsidies), location and
technologies (production and processing) affect proﬁtability in each country?
Question 1.What is the relative ﬁnancial or social proﬁtability of cassava in Cote d’Ivoire,
Ghana and Nigeria?
Hypothesis: Cassava production is more proﬁtable (ﬁnancially and socially) in Ghana and
Nigeria relative to Cote d’Ivoire, essentially because the relative price level of cassava to
cereals (especially rice) to cassava is signiﬁcantly lower in core d’Ivoire because of cereals
import tariffs. The consequence is a lower demand for cassava and cassava products in
rural market centers. This in turn makes any investment to increase outputs not a viable
proposition for Ivorian farmers since the supply cannot be absorbed by market demand at
remunerative prices. The result is that improved production and processing technologies
are not as widely used in C6te d’Ivoire as they are in Ghana or Nigeria.
Question 2.What is the proﬁtability (ﬁnancial and social) of cassava relative to rice in Cote
d’Ivoire?
At this stage, it is not clear whichjs more proﬁtable because imported rice has negative
effects on both cassava and rice prices (substitution effects).

Question 3. What is the impact of improved production and labor-saving processing

technologies (graters) on the proﬁtability of cassava in Nigeria?

This question can be analyzed for four different scenarios:

a) Improved processing technology in combination with improved production technology
(Impmech);

b) Improved processing technology in combination with traditional production technology
(Locmech);

c) Traditional processing technology in combination with traditional production
technology (Locman);

(1) Traditional processing technology in combination with improved production technology
(Impman);
Hypothesis: The descending order of proﬁtability is likely: scenario a, scenario b,

scenario c, and scenario (I because the yields of improved cassava varieties are higher than

those of local varieties.

1.4. Data

1.4.1. Source: This study will be based on data for cote d’Ivoire, Ghana and Nigeria
from the Collaborative Study of Cassava in Aﬁica (COSCA) survey. The COSCA project
was coordinated by the project leader (Dr. Felix Nweke); two regional coordinators; one
national and one assistant national coordinator in each country, consisting of a social
scientist and a biological scientist in agriculture; and six subject matter specialists in the
areas of agricultural marketing, agro-geography, food processing technology, processing
economics, human nutrition and health, and anthropology. The funding for this project

was provided mainly by the Rockefeller Foundation. The countries covered are C6te

d’Ivoire, Ghana, Nigeria, Zaire, Uganda and Tanzania.

The aim of the COSCA study was to provide baseline information on cassava over
a wide area. Such information is needed to improve the relevance and impact of
agricultural research, extension and policies on the crop in Aﬁica in order to realize the
potential of cassava in increasing food production and the incomes of the people of Africa.
The data were collected between 1989 and 1992.

Data available in the COSCA survey that will be used will include farm-level
technical coefﬁcients, processing costs, transformation rates of cassava root into
processed products, sources of cassava roots and destination of cassava products, unit
storage cost, unit transportation costs, product and input market prices, taxes and subsidy

levels. The table below summarizes the data needs and availability for each type of

 

 

 

 

 

analysis.
Table 1.1: Summary of Data Needs and Availability
Types of Analysis Variables Data Required Where are these data
available?
Production Revenues, Variable and F arm-Level Financial COSCA Phase 2 (ﬁeld
Financial Proﬁtability Fixed Costs, Technical Budgets survey) and Phase 3
Coefficients (marketing survey) data ﬁles
Farm-Level Financial
Interest on working capital Budgets
Depreciation
Production Same variables as in F arm-Level Financial C OSCA Phase 2
Economic Proﬁtability Financial Analysis Budgets (ﬁeld survey) and Phase 3
(market informant survey)
data ﬁles
Social prices
Import parity prices
Post-Production Revenues,Variable costs COSCA Phase 1 (household
Proﬁtability (transpor- Budget for Processing survey) and Phase 3
tation, purchased inputs, Phase (Processing survey) data ﬁles
labor), and Fixed Costs
(Emlipment)
See table 1.2 Findings from above Results of above analyses
Poligy Analysis analyses

 

 

 

 

 

 

1.4.2. Collection procedure: Leaders in cassava research in the national agricultural
research systems in each country administered survey questionnaires to local farmers and
took various measurements. These researchers were knowledgeable about cassava
production systems of their respective countries and hence qualiﬁed to collect the
information.

A rapid rural appraisal technique was employed to collect village-level information
in the Phase I survey. Farmer groups consisting of men and women of various ages were
constituted and interviewed in each village. Structured questionnaires were used to collect
qualitative information. This survey was conducted in 1989-1991.

The Phase H survey was carried out at the individual ﬁeld plot level. Field size was
determined by measurement with a compass, a tape, and ranging poles. Yield estimation
was made for ﬁelds where roots were 12 months or more old, except when the farmer
harvested at less than that age. The estimation was based on a representative sample plot
of 40 m2, except when the ﬁeld was too small, in which case a 20-m2 plot was used. There
were one or two plots per ﬁeld depending on the size and heterogeneity of the ﬁelds in
terms of soil and toposequence. The ﬁeld-level information was collected in 1991.

The Phase III survey was at the household level. Relevant male and female
household members were interviewed using structured questionnaires. The household
information was collected in 1992. Phase III involves detailed studies on post harvest
issues such as: 1) Processing: i) characterization of techniques; and ii) product quality
assessment (nutritional, toxicity and quality assessment); 2) marketing; and 3)

consumption/demand.

1.5. Methodological Framework

Following Pearson et a1. (1981), the framework chosen for this study is the Policy
Analysis Matrix (PAM), which involves the following:
1. Microeconomic analyses are carried out to determine the economic efﬁciency of
alternative systems/techniques and locations of cassava-based production systems in
systems that encompass farming, proceSsing, and distribution.
2. The eﬁ‘ects of government trade, price, tax/subsidy, and investment policies on
incentives are analyzed by measuring transfers of income to or from farmers, processors,
and traders.
3. Comparative analyses are undertaken of the productive efﬁciency/proﬁtability of the
various systems/techniques and locations and of the effectiveness of government policies,
ﬁrst within individual countries and then among countries.

Table 1.2: An Outline of the Policy Analysis Matrix (PAM)

 

 

 

 

 

 

 

 

Revenues Tradable Domestic
Inputs factors Proﬁts
Private prices A B C D
Social prices E F G H
Divergences I J K L

 

D = A - (B+C) = private proﬁts which indicate competitiveness under existing policies
H = E - (F+G) = social proﬁts which measure efﬁciency or comparative advantage

I = A - E = output transfers

J = B - F = input transfers

K = C - = factors transfers

L = D - H =1 - (J+K)= net transfers

 

 

 

Source: Adapted from Monke and Pearson (1989)
The PAM approach is a system of double-entry bookkeeping that consists of two
accounting identities. The ﬁrst identity holds that proﬁt equals revenues minus costs
measured either in ﬁnancial or economic terms. The second identity measures the eﬁ‘ects

of divergences (between ﬁnancial and economic values) as differences between observed

parameters and parameters that would exist if the divergences were removed. The main
empirical task is to construct accounting matrices of revenues, costs and proﬁts for each
selected enterprise based on representative synthetic farm-level and marketing budgets,
using data on farming, farm-to-processor marketing, processing, and processor-to-
wholesaler marketing.

The main advantages of the PAM approach are that it allows varying levels of
disaggregation, makes the analysis of policy-induced transfers (divergences between the
observed market price and prices that reﬂect opportunity costs) straightforward, and
makes it possible to identify the net effects of those policies. One of the main weaknesses
of the PAM approach is the underlying assumption of ﬁxed technical input-output
coeﬁicients. That is, the PAM model assumes that supply and demand elasticity equals
zero and there is no change in input prices.

As can be seen in the PAM matrix in table 1.2, inputs are partitioned into tradables
and domestic factors. Tradable inputs are inputs that are traded internationally (traded
tradables) or potentially could be traded (non-traded tradables). Domestic factors
(sometimes refer to as primary factors in standard DRC analyses) are factors that are not
normally traded internationally and include chieﬂy land, labor, water, and capital.

However, labor might be considered tradable in cases where seasonal migration
results in remittances of foreign exchange. Nevertheless, because the international labor
market is not well developed, labor is generally treated as a primary factor in DRC
analysis. Intermediate inputs such as fertilizers, pesticides, purchased seeds, compound
feeds, transportation, and ﬁrel are disaggregated into components of costs until all costs

items are traced back to tradable inputs, domestic factors, and transfers (taxes and

subsidies). This process is referred to in beneﬁt/cost analysis by Little and Mirrless (1974)
as complete border pricing. The complete border pricing approach has not been fully
adopted, and researchers have used several less ambitious versions. Probably the most
popular of all is the partial border pricing approach developed by Squire and Van der Tak
(1975). With this version, tracing back all costs items to tradable inputs, domestic factors,
and transfers is selective, depending on the willingness to increasingly break minor items
into cost components.

From the point of view of the society, a direct inspection of social proﬁtability may
be enough in order to assess the relative efﬁciency or comparative advantage of alternative
production systems under consideration. For an eﬂiciency-minded society, the higher the
social proﬁtability, the better. Nevertheless, when the systems produce outputs with
different capital intensity (e.g., when they produce different outputs), the domestic
resource costs (DRC) ratio is used as a proxy measure for social proﬁtability. The system
of matrices in the PAM provides the information necessary to assess the impact of policy
on competitiveness and farm-level proﬁts, the effect of new investments on economic
efﬁciency and comparative advantage (i.e., on the pattern of efﬁciency), and the inﬂuence
of agricultural research policy on changing technologies.

On the issue of farm policy impact, farm budget data (sales revenues and input
costs) are collected for the principal agricultural systems, and proﬁts are determined to
show which farmers are currently competitive and how their proﬁts may change if price
policies were changed. To deal with the issue of how additional public investment might
change the current pattern of efﬁciency, revenues, costs and proﬁts are reassessed in social

values. New investments that reduce social costs also increase social proﬁts and improve

efﬁciency.

The third issue concerns how to best allocate ﬁinds for agricultural research. The
existing levels of private and social revenues, costs and proﬁts are calculated. Then
sensitivity analyses are undertaken by projecting changes in yields and inputs resulting
from alternative research programs and examining how these changes alter private and
social proﬁts of current technologies.

These results can be used to identify what kind of farmers or production systems
are competitive under current policies aﬂ‘ecting crop and input prices, and how their
proﬁts would change as alternative policies were implemented, and thus to compare the
incentive effects associated with different policies and technologies.

At this point, it worth emphasizing a point that should be kept in nrind concerning
the results analyses. Conventionally, the PAM approach can provide analysts with a
helpful understanding of the measurements of the magnitudes of “policy transfers”. Given
these measurements, the analyst may suggest a policy change for the sake of Pareto
efﬁciency, but which of the many such points shall we refer to? Schmid (1987, 244) states,
“ it is useful to speak of the efficiency with which a given institutional rule achieves a
given performance objective. But for clarity, objectives need to be explicit.” Change rights
and you change what is efﬁcient. For example, the analyst may view a commodity (e.g.,
rice in Cote d’Ivoire) import tariff as irrational and distorting in terms of some presumed
income distribution, but the analyst has no expertise in choosing an income distribution.
Various policy outcomes may be efﬁcient given policy-makers’ deﬁnition of different
economic agents’ property rights at that point of time.

Policy-makers often justify tariff and other policies with the argument that the help

10

the poorest of the farmers. But any policy raising prices help rich (large) and poor (small)
farmers if both are net sellers of the product in question. But a lot of research in Aﬁica has
shown that many small farmers are net buyers of basic staples. In that case, higher prices
for staples help the large farmers (who are net sellers) and hurt the small farmers who are
net buyers. Therefore, this instrument used to transfer income ﬁom consumers misses the
target beneﬁciaries. The same total transfer could help the poorest farmers more if paid
directly to them.

Little and Mirrlees (1974), 224-225) regard indirect taxes/subsidies on ﬁnal
consumption goods, as correcting income distribution and thus the net of tax price is a
better measure for the social value of the good than the market price. They believe that a
lump sum tax would be the tool to redistribute income, but it is costly. Therefore taxes
may be a corrective not a distortion. In their words “taxation and subsidization of
consumers’ purchases is a useful and socially desirable weapon of policy. Project planners
and economic advisors have no general warrant to nullify the effects of that tax system.”

Policies are instruments of action that governments employ to affect change in a
given period (often one year) for a given situation. Thus, policy outcomes are situation-
speciﬁc. It would not be wise, therefore, to put too much weight upon the events of one
year, No year’s evidence should be neglected, nor should be given full weight Little and
Mirrlees (1974). The point being that an efﬁciency objective is relevant given the structure
of property rights that underlie it. A change in property rights will result in a change in
what is efﬁcient.

1.6. Speciﬁc Types of Analysis Planned

The proﬁtability and the productive efficiency in the use of domestic resources in

11

cassava- based production and post-production systems will be examined using a
combination of ﬁnancial and economic analyses. In the particular case of Nigeria, for
which number of observations are large enough (see tables Al-l, A1-2 and A1-3 in
Appendix 1), the analyses will be carried out under two scenarios: 1) the farmer produces
cassava to consume at home, and 2) the farmer produces cassava to sell in the rural
market center. Comparative ﬁnancial and economic analyses will be carried out for the
following:

1. (a) Cassava fresh root production in Cote d’Ivoire, Ghana and Nigeria

(b) Cassava processed food product production in Cé‘rte d’Ivoire, Ghana and Nigeria

2. Cassava ﬁ'esh root production and rice production in Cc‘rte d’Ivoire
3. (a) Cassava fresh root production in Nigeria for farmers who produce to sell in rural
markets
(b) Cassava processed food product production in Nigeria for farmers who produce to
sell in rural markets
(c) Cassava production and processing by alternative technologies
(i) Traditional variety and traditional processing method
(ii) Traditional variety and mechanized processing method
(iii) Improved variety and mechanized processing method
(iv) Improved variety and traditional processing method
In this study, comparisons will be made between cassava and rice systems in Cote
d’Ivoire and among cassava systems in core d’Ivoire, Ghana and Nigeria. A cassava or

rice crop system is a system of intercropping where cassava or rice is the main crop, as the

12

speciﬁed by the farmer. In each case, the costs and returns of producing the main crop as
well as the costs and returns of producing the subsidiary crops are charged or credited to
the cassava or rice system as a whole rather than developing separate budgets for each
crop. Trying to develop separate budgets for each crop produced in an intercropping
system requires arbitrary allocation of joint costs across the different crops produced in
the system.

The units for comparison of cassava-based production systems among the three
countries and for comparison between the cassava system and the rice system in Cote
d’Ivoire will be: 1) the net returns (to land or labor) from the systems based on all the
crops in the association in each country and 2) the domestic resource costs (DRC) of each
system based on all the crops in the association in each country.

1.6.1: Financial Enterprise Budgets for Cassava Production and Post-production in
C6te d’Ivoire, Ghana and Nigeria, as well as of Rice in Cote d’Ivoire

Financial budgets will use available technical coefficients from survey data to
estimate standard indicators of proﬁtability, such as gross margins and returns to family
labor and land. These will be estimated based on average market sale price in each
country. Proﬁtability measures will be based on farm-level ﬁnances.

1.6.2: Comparative Analyses of the Economic Proﬁtability of Cassava-based
Production Systems in the Three Countries and of the Competitiveness of Cassava
as Compared to Rice-based System in C6te d’Ivoire

This analysis is performed ﬁ'om the point of view of the country as a whole.
Consequently, it focuses on the analysis of the competitiveness of cassava-based

production systems in Cote d’Ivoire, Ghana and Nigeria, both in terms of the relative

proﬁtability and the eﬁiciency in the use of domestic resources.

13

First, sample data will be aggregated for: 1) each representative cassava-based
system at each country level; 2) in Nigeria, for each agroecological zone and for each
technology combination module. A policy analysis matrix for each system in will be
constructed for each point of comparison, namely: a) farm-level in the three countries, and
b) farm level and rural market center Cote d’Ivoire, Ghana and Nigeria.

Second, budgets will be calculated using economic prices (e.g., import parity
prices) to assess the economic proﬁtability of cassava based-production systems in each
country and for rice production in cote d’Ivoire.

Third, the same information used for the economic proﬁtability analysis will be
used to calculate DRC ratios of representative cassava-based production systems in each
country (and for rice in Cote d’Ivoire) as the ratio of domestic factor cost (G) to value
added in social prices (E-F)‘. The DRCs allow us to assess the relative efﬁciency or
comparative advantage of cassava production systems in each country. A direct
inspection of these ﬁnancial and social proﬁtabilities and the DRC ratios will be used to
assess the relative efﬁciency or comparative advantage of the selected cassava and rice
production systems. Minimizing the DRC ratio is equivalent to maximizing social proﬁt.
A DRC ratio between zero and one indicates that the value of domestic resources used in
production is less than the value of foreign exchange earned (export) or saved (import
substitute). Consequently, the country has a comparative advantage in production. If the
DRC ratio is more than one, this reveals that the value of domestic resources used in

production exceeds the value of foreign exchange earned (export) or saved (import

 

lSee outline of PAM in table 1.2

14

substitute). As a result, the system has no comparative advantage. Finally, a DRC ratio
less than zero indicates a negative value added domestically; consequently, foreign
exchange is being wasted. In other words, more foreign exchange is being used in
production than the commodity is worth.

1.6.3: Comparative Analysis of Policy Income Transfers in C6te d’Ivoire, Ghana
and Nigeria '

In this section, further analyses are undertaken to (I) examine the static overall
effect of policy initiatives and/or market failures, and (2) compare the incentive effects
associated with or the extent of policy transfers in each country. The static overall eﬂ’ect
of policy initiatives and/or market failures will be examined by comparing private and
social proﬁtability. A positive value of l the difference between private and social net
proﬁtability (NNP-NSP) indicates that the policy overall increases private proﬁtability,
while a negative value reveals the opposite effect. To compare the incentive eﬂ‘ects
associated with the rice and cassava-based production systems' output, four speciﬁc ratios
will be constructed: the nominal protection coefficient (NPC), the effective protection
coefﬁcient (EPC), the proﬁtability coefﬁcient (PC), and the subsidy ratio to producers
(SRP).

The NPC is the ratio of private price of the output (NPCO), or a tradable input
(NPCI), or a domestic factor (NPCF) to its social price. This ratio will indicate the degree
of the impact of the factors causing a divergence between the two prices. The EPC is the
ratio of value added in private prices (A-B) to value added in world prices (E-F). It will
measure the degree of policy transfer from product market (output and tradable-input)

policies. Because, like the NPC, the EPC ignores the transfer effects of factor market

15

policies, it is not a complete indicator of incentive. An extension of the EPC is the
proﬁtability coefﬁcient (PC), which is the ratio of private to social proﬁts and serves as a
proxy for net policy transfers (i.e., incentive effects of all policies). In terms of table 1.2,
the SRP is the net policy transfer (D-H) as a proportion of total social value (E). It shows
the proportion of revenues in world prices that would be required if a single subsidy or tax
were substituted for the entire set of commodity and macroeconomic policies; the measure
thereby allows one to see the extent to which all policies subsidize a given production
system. The SRP can be computed for output (SRPO), input (SRPI), and factors (SRPF).
1.6.4: Sensitivity Analysis

Sensitivity analysis will be carried out to test whether the DRC ratios and the
transfers calculated under the baseline scenario are likely to be affected by changes in the
values of key technical and economic parameters (e. g processing costs, labor costs,
transportation costs, output prices) whose ﬁrture behavior is diﬁicult to predict with

certainty.

1.7. Conclusion

The objectives of this study are: 1) To measure and compare the relative private
and social proﬁtability of cassava-based production systems in C6te d’Ivoire, Ghana and
Nigeria; and 2) to discuss the implications for private and public-sector policies, extension
and research interventions. The study is organized as follows. The ﬁrst essay (in chapter 2)
emphasizes the application of the PAM to evaluating the effects of government policies, in
terms of an overvalued exchange rate, on the relative proﬁtability and comparative

advantage of cassava/maize and rainfed rice/maize systems in the humid lowland zones of

16

Cote d’Ivoire.

The second essay, in chapter 3, is based on the argument that cassava products
such as tapioca are tradable and currently traded, to an extent, in Sub-Saharan Aﬁica.
Even more widely traded (as an export) are cassava chips for livestock feed. This means
that cassava-based systems have a certain potential for generating export earnings.
Furthermore, the expansion of peasant exports tends to promote economic development,
both directly, through the “vent-for-surplus” mechanism, and indirectly, by improving the
domestic economic organization of an underdeveloped country (Myint, 1979). Therefore,
a policy analysis that helps determine combinations of production and processing
technologies, under which cassava-based production systems are socially proﬁtable (e.g.,
internationally competitive), can be very beneﬁcial to policy-makers.

Following Adesina and Coulibaly (1998), this essay uses the Policy Analysis
Matrix (PAM) to examine the relative proﬁtability (ﬁnancial and social) and comparative
advantage of cassava/maize production systems under four alternative production and
processing technology-combinations in Nigeria: “Impmech”, “Locmech”, “Locman”, and
“Impman” deﬁned as follows: a) Impmech equals to IITA’s improved cassava variety
processed using a mechanized grating method, b) Locmech equals to local cassava variety
processed using a mechanized grating method, c) Locman equals to local cassava variety
processed using a manual grating method), d)1mpman equals to IITA’s improved cassava
variety processed using a manual grating method .

The third essay, in Chapter 4, compares the proﬁtability of cassava-based
production systems in three West Aﬁican countries: Cote d’Ivoire, Ghana and Nigeria.

This analysis is based on the argument that the difference in various factors such as

l7

agricultural policies (i.e., trade and price policies, domestic production taxes or subsidies),
location and technologies (production and processing) between C6te d’Ivoire, Ghana and
Nigeria explains the difference in the level of growth in cassava-based production systems
in between Nigeria, Ghana and Céte d’Ivoire explains the difference in the level of grth
in cassava-based production systems. The intent of this comparative essay is to use policy
analysis matrix (PAM) approach to push policy analysis ﬁrrther than can be done within
the context of a single country. The main advantage of carrying out similar policy studies
in a number of countries is the scope presented for obtaining comparative insights. This
essay uses the policy analysis matrix (PAM) model to examine the magnitude of the
impact of agricultural policy on the private and social proﬁtability of cassava/maize
production systems in Nigeria, Ghana and Cote d’Ivoire.

Chapter 5 summarizes the conclusions for each essay and discusses avenues for

further research.

18

REFERENCES

Adesina, AA. and Djato, K.K., AFarm Size, Relative Efﬁciency and Agrarian Policy in
Cote d’Ivoire: Proﬁt Function Analysis of Rice Farms, Agricultural Economics,
14:93-102,1995

Adesina, AA. and Coulibaly O. N., Policy and Competitiveness of agroforestry-based
technologies for maize production in Cameroon: An application of policy analysis
matrix, Agricultural Economics, 19:1-1 13,1998

Babo, Alfred, Circuits de Commercialisation et de Transformation du Manioc dans la
Region de Bouake. Memoire de Maitrise. Option: Socio-Economie du
Developpement Rural. Universite de Bouake, 1996.

Jones, W.O., Manioc in Aﬁica, Stanford University Press, Stanford, 1959.

Little, 1. M. D., and J. A. Mirrlees, 1974. Project Appraisal and Flaming for Developing
Countries. New York: BasicBooks

Monke, EA. and S. Pearson. 1989. The Policy Analysis Matrix for Agricultural
Development. Baltimore: John Hopkins University Press.

Myint, H., (1979), Exports and Economic Development of Less Developed Countries in
Economic Growth and Resources, vol. 4, edited by Irma Adelman

Nelson, G C and Panggabean, M (1991), The costs of Indonesian sugar policy: a policy
analysis matrix approach, American Journal of Agricultural Economics, 73 (3)
pp703-71 2

Nweke, F ., Dixon, R.A., Asiedu, R., Folayan, SA, A Cassava Varietal Needs of Farmers
and the Potential for Production Growth in Aﬁica, The Collaborative Study of
Cassava in Aﬁica, Working Paper No. 10, 1994

Nweke, Felix I., K. N‘Goran, A.G.O. Dixon, B.O. Ugwu, O. Ajobo, and T.
Kouadio. 1998. Cassava production and processing in Cote d'Ivoire. The
Collaborative Study of Cassava in Aﬁica, Working Paper No. 23, IITA, Ibadan,
Nigeria.

Pearson, S.R., J .D. Stryker and GP. Humphreys, (eds). Rice in West Aﬁica: Policy and
Economics. Stanford University Press, 1981

Schnrid, A. Allan, Property, Power, and Public Choice: An inquiry into Law and
Economics, Praeger Publishers, New York, 1987.

19

Squire, Lyn, and Herman G. van der Tak, 1975. Economic Analysis of Projects.

Theberger, R. Les principaux ravageurs et maladies du manioc, de l’igname , de la patate
douce et aracées en Aﬁique, IITA, 1985.

20

APPENDIX 1

21

Table Al-l: Sample size (number of ﬁelds) by crop and by country

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Cropleountries Cote d’Ivoire Ghana Nigeria Total
Cassava/maize 46 49 1 54 249
Rice/maize 35 3 25 63

Maize ‘ 17 43 69 129

TableAl-Z: Distribution of households by type of cassava processing
technology by country
ProcessinglCountries cote d’Ivoire Ghana Nigeria Total
Technologies

Graters 1 12 111 124

Pressers 45 37 43 125

Total 46 49 43 249

 

 

 

 

 

 

 

Note: Graters are labor-saving technologies

 

 

 

 

Table Al-3: Distribution of cassava based ﬁelds by production technology
in N igeria
Productionl Country Cé‘rte d’Ivoire Ghana Nigeria
Technology
Improved 1 13 53
Traditional 45 36 101
Total 46 49 154

 

 

 

 

 

 

22

TableA1-4:

Distribution of cassava-based ﬁelds by
aggrecolrgical zones in N geria

 

 

 

 

 

 

 

Zones

Humid 40

Subhunﬁd 96

Nonhumid 1 8

Total 1 54

 

 

Table Al-S: Distribution of ﬁelds by production/processing technologies in C6te
d’Ivoire, Ghana and Nigeria.

 

 

 

 

 

 

 

 

 

 

Processingl
Production Cote d’Ivoire Ghana Nigeria
Improved Manual Improved Manual Improve Manual
d
Graters O 1 10 32 54
Manual 1 44 26 20 48

 

 

Note: Graters are labor-saving technologies

23

 

Figure Al-l: Cote d’Ivoire: Study Sites, Output Markets (Bonoua and N douci)
And Port City (ABIDJAN), 1989/1991.

Cote claw-re 3;"

----lnkmauua¢ DOW-Isl) ﬁﬂ MW, 111-W

 

wpv

-- at!”

 

 

24

Figure A1-2: Ghana: Study Sites, Output Markets (Koforidua and Kumasi)
and Port City (ACCRA), 1989/1991.

 

25

Figure A1-3: Nigeria: Study Sites, Output markets ( Abeokuta and Onitsha)
And Port City (LAGOS), 1989/1991.

 

 

I .
Nigeria
n...- mecca-a My; . a swap“
—— incu- min-1m -

t rub-J m:

 

 

 

 

 

 

 

 

 

 

 

 

26

CHAPTER 2

EVALUATING THE EFFECTS OF POLICIES ON THE COMPETITIVENESS
OF CASSAVA-BASED PRODUCTION SYSTEMS IN COTE D’IVOIRE

2.1. Introduction

In cote d’Ivoire, cassava has always been an important staple food in households’
food basket and in their farming systems. A 1979 consumption survey (Enquetes-Budget-
Consommation) indicated that, on the average, each Ivorian household member consumed
about 50 kg of cassava annually, which ranked cassava as the second most consumed
staple food after rice (60kg/head/year). In 1992, another national survey (Enquetes
Prioritaires sur les Dimensions Sociales de l’Ajustement Structurel) also showed that
Ivorian households spend 13.9 percent of their income on rice, 6.0 percent on cassava and
cassava by-products and 3.4 percent on yams (Babo, 1995). Furthermore, the same study
revealed that 90.1 percent of these households consumed rice, 85.0 percent wheat bread,
60.3 percent fresh cassava, and 73.1 percent attieke, a cassava meal. More recently, the
national Statistics Bureau reported that the total cassava production in Cote d’Ivoire was
1,608,000 tons in 1995, compared to 890,000 in 1993 and 1,100,000 in 1994 (MEF,
1996)

In spite of the relative importance of cassava and cassava products in Ivorian
households’ food expenditures and cassava’s favorable agronomic characteristics for the
country, the government of Cote d’Ivoire has invested very little in improving the cassava
sub-sector (Theberger, 1985; Babo, 1995). A major focus has been the expansion of rice

production and major reliance on cereals (especially milled rice) imports to ﬁll the gap

27

created by unsatisfactory growth in the domestic supply of food. The Ivorian policies have
resulted in rice being much cheaper relative to cassava products around major market
centers than is the case in either Ghana or Nigeria: a kilogram of processed cassava cost
78 percent as much as milled rice in Cote d’Ivoire, compared with 61 percent in Ghana
and 41 percent in Nigeria. For example, although attieke is a convenient food product,
which can potentially compete with food grains in the grain market, it was not able to
express that potential because of the availability of low-cost rice, especially around market
centers (Nweke etal., 1999).

Questions have been raised about the sustainability of policies such as subsidizing
rice imports that bear heavy social costs, considering the limited ﬁnancial liquidity of the
country and rapidly increasing urban populations. On the other hand, the question arises as
to whether a policy for cassava production should be implemented to substitute for local
rice in production and/or consumption. For example, in Ghana, improvements in cassava
processing have increased food availabilities (Kreamer, 1986). However, outcomes of
government policies that tend to raise private production incentives for particular crops
against others may not be desirable for society in terms of efﬁciency of resource
allocation.

This essay uses the Policy Analysis Matrix (PAM) method developed by Monke
and Pearson (1989) to evaluate the effects of government price and macro (i.e., exchange
rate) policies on the proﬁtability and competitive advantage of cassava/maize production
systems relative to rainfed rice/maize production systems in Cote d’Ivoire. Agricultural
price policies, whether direct or indirect (via an exchange rate policy) have an important

inﬂuence on the prices farmers receive and prices consumers pay. Product and inputs

28

prices levels affect proﬁtability and, therefore, the amounts invested by producers among
competing farm enterprises.

A review of the literature on the econonrics of cassava production in Aﬁica
identiﬁes two types of analyses: the ﬁrst type focuses on the importance of cassava in
Aﬁicans’diet. Manioc in Aﬁica by W.O. Jones (1959) is one of the classic works on that
topic. Written in an easily understood style, it describes the introduction, spread, and use
of cassava throughout the Aﬁican continent.

The next major study on cassava in Africa is COSCA (Collaborative Study of
Cassava in Aﬁica), which has focused on providing baseline information on cassava in six
countries in Aﬁica: cote d’Ivoire, Ghana, Nigeria, Zaire, Uganda, and Tanzania. The
broad objective of COSCA was to improve the relevance and impact of agricultural
research on cassava by international agricultural research centers (IARC) and national
agricultural research systems (N ARS) in Africa in order to realize the potential of cassava
in raising food production and incomes in Aﬁica. Therefore, the major question addressed
in most of COSCA reports has been the beneﬁts, in terms of food security and income
generation, of investing in alternative cassava production and processing technologies in
Aﬁica. A striking feature of earlier studies on cassava in Africa (Nwajiuba, 1995; Nweke,
1996; kai and Hahn, 1989) is that none have looked at the proﬁtability and competitive
advantage of cassava /maize production systems relative to competing crop systems.

The results of this study will not only add to the stock of knowledge relative to food
commodities in Aﬁica but also inform Ivorian policy-makers of the potential contribution

of cassava and cassava by-products for national food policy objectives.

29

2.2. Methodological Framework
2.2.1. A Short Description of the Policy Analysis Matrix (PAM) Model

As mentioned earlier, the Policy Analysis Matrix (PAM) is the analytical
framework used in this essay. This methodology is developed in detail in the ﬁrst chapter;
therefore in this section, the focus is on how it is used in estimating comparative costs and
incentives for farm activities or enterprises.

The PAM is a product of two accounting identities. The ﬁrst identity holds that
proﬁt equals revenues minus costs measured either in ﬁnancial or economic terms. The
second identity measures the effects of divergences between ﬁnancial and economic values
as differences between observed parameters and parameters that would exist if the
divergences were removed. The main empirical task is to construct accounting matrices of
revenues, costs and proﬁts for each selected enterprise based on representative synthetic
farm-level and marketing budgets, using data on farming, farm-to-processor marketing,
processing, and processor-to-wholesaler marketing (Monke and Pearson, 1989).

The concept of economic proﬁt is fundamental in PAM analysis. Proﬁt, whether
calculated at observed market prices or at imputed social (efﬁciency) prices, is deﬁned as
the difference between revenues (the value of outputs) and costs of all inputs.
Measurement of costs and returns at private market prices reveals the presence of any
excess proﬁts (deﬁned as the difference between total returns and the costs of all inputs,
including capital) and the actual competitiveness of the enterprise. This may result in the
expansion of production; however, if market prices for inputs or outputs differ from their
values in alternative production or consumption uses, actual competitiveness and

proﬁtability may be misleading indicators of the potential for growth. The most common

30

source of such divergences is policies (Pearson et al., 1995).

Policy analysis can help answer the question of allocation (and hence the level) of
food production by considering food as seen ﬁ'om the standpoint of different
socioeconomic and political agents. The commercial farmer sees food mainly as a source
of income; the subsistence farmer sees food as a means of subsistence and survival; and
the policy-maker sees food as a source of government income and as a strategic
commodity, which can be used, as a means of control or as an instrument of social
welfare. Food prices are policy instruments to the government, returns to farmers and
costs to the consumer. Agricultural input prices are policy instruments to the government,
costs to the farmers, and returns to the owners of factors of production (e. g., wages for
agricultural labor).

This paper emphasizes the application of PAM in evaluating the effects of
government policies (i. e., outputs and inputs pricing and exchange rates policies) on the
relative proﬁtability and comparative advantage of cassava/maize and rainfed rice/maize
systems in the humid lowland zones of Cote d’Ivoire.

2.2.2. Data

This study is based on data for Céte d’Ivoire from the Collaborative Study of
Cassava in Africa (COSCA) survey. COSCA report number 2 provides a detailed
discussion of the data collection procedures and the associated sampling method. The
survey covered the period 1989/1991.

Data available in the COSCA survey that are used include farm-level technical
coefﬁcients, processing costs, transformation rates of cassava root into processed

products, sources of cassava roots and destination of cassava products, unit storage costs,

31

 

unit transportation costs, product and input market prices and taxes and subsidy levels. In
the case of rainfed rice and green maize, data used were obtained not only from the
COSCA survey but also ﬁom primary sources of earlier studies and from secondary
sources such as the Ofﬁce of Agricultural Statistics of the Ivorian Ministry of Agriculture.

In addition, macroeconomic data needed in the estimation of economic prices (i.e.,
import parity prices and shadow exchange prices) were obtained mostly from secondary
sources such as Statistiques des Transports Maritimes et Balance de PaLiemerLts en Cote
£11915 and from the IMF.

Unfortunately, the COSCA study did not record maize yields on its sample ﬁelds.
Therefore, in computing the enterprise budgets developed in this study, it was assumed
that those ﬁelds got the average maize yield for the country which was then converted to
the number of fresh corn ears using the “Ear-Weight Method” discussed in the appendix.

The numbers of corn ears were subsequently valued at the fresh corn price.

2.3. Empirical Analyses

Cassava/maize and rainfed rice/maize production systems are examined in this
section using a combination of ﬁnancial analysis, economic analysis and policy analysis.
The tasks involved are the following:
1. To develop enterprise budgets (ﬁnancial and economic) for each commodity system
under a “baseline scenario”.
2. To construct a Policy Analysis Matrix (PAM) for each commodity system, using the
information from the enterprise budget and estimate indicator ratios such as DRC, NPC,

etc.

32

3. To undertake sensitivity analyses in order to contrast the comparative advantage of the
two commodity systems.
2.3.1. Financial Profitability Analysis

The purpose of this subsection is to estimate crop enterprise budgets and
processed product (attieke) enterprise-budgets by system of production, and thereby
provide the database for establishing the relative proﬁtability of cassava-based systems
versus rainfed rice-based systems in Cote d’Ivoire. Separate farm-level ﬁnancial budgets
were developed for cassava/maize systems and rainfed rice/maize systems. In addition, a
post-farm level budget is constructed for the cassava/maize system only. The aim of input-
output budget analysis is to derive farm recoMendations, which are consistent with
farmers’ desires to increase expected income and to make the best possible use of the
resources available to them. Furthermore, enterprise budgets are important in farm
income analysis because they help to explain the internal structure of the farm as a whole
and to show the relative contribution of each enterprise to the whole organization.
Therefore, these enterprise studies are very instrumental in an attempt to: (i) assess the
proﬁtability of each enterprise relative to the resources used; (ii) compare relative
efficiency of various enterprises on the farm; and (iii) provide a basis for making rational
decisions about the kind and size of enterprise to be expanded.

In the ﬁnancial analysis, the main objective is to answer the question whether a
particular enterprise under a given system of production will pay its way in strict monetary
terms (Are returns greater than monetary costs?) Towards this end, inputs are valued at
the average market prices that farmers paid for each type of input, while output is valued

at the average unit price received at harvest period by farmers. For each enterprise budget,

33

ﬁnancial returns to family labor are computed. Other performance measures computed
from the budget data include gross margin per hectare, net returns to family labor, net
returns per day of family labor, total production cost and average production per
kilocalories for farm level analysis and average cost of processing per kilogram of output
in the post-farm analysis.
2.3.1.1. Farm level Analysis

Each crop system enterprise-budget in this study was calculated from households
in which that enterprise was considered important. In other words, these are: 1) households
where cassava contributed 30 percent or more of cash income from all food crops; and
2) households where cassava enterprises were an important source of subsistence (i.e.,
cassava represents 45 percent or more of the weight of the basic staple food supplies).

These budgets appear in tables A2-1 and A2-2 of the appendix. Following
Crawford (1982), data for each ﬁeld were ﬁrst checked for consistency by comparing the
mixtures implied by the planting and harvest data with mixtures reported by farmers.
However, it should be noted that very simple cluster analyses were performed to aid the
process of narrowing down the number of mixtures. Two mixtures (cassava/maize and
rainfed rice/maize) were eventually selected based on their importance (in terms of total
number of ﬁelds and total cultivated area) in the local farming system.

Table 2-1 below summarizes the results of the baseline runs of the farm-level
ﬁnancial proﬁtability analysis. The summary focuses mainly on performance measures that
can be used to identify the enterprise with the highest ﬁnancial return and lowest cost of

production.

34

Table 2-1: Farm-Level Summary Estimates of Financial Budget Indicators for
Cassava/Maize And Rainfed Rice/Maize Production Systems in Cote
d’Ivoire. 1989/91

 

 

Production Returns to Returns Total Net Average
Systems Family to System Enterprise Cost
Labor Family Production Proﬁts Of
Per ha Labor Per Costs Per ha Production
Person- Per ha Per kcal 1
day
1 f f f f f f f f
Cassava/maize 214014 1597 200961 129594 5
Rainfed
Rice/Maize 60801 640 174049 3801 13

 

Source: tables A2-1 and A2-2 in the appendix

Clearly, the cassava/maize system is the more proﬁtable crop system, since it
A generates higher returns, higher net proﬁts and lower average cost of production per
kilocalorie than rainfed rice/maize. Although the cassava/maize system has higher returns,
under both systems farmers were able to cover all their Operating costs. Therefore, both
systems are valid candidates to stay in the farming business; however, cassava/maize
systems have higher total system production costs, suggesting that cassava/maize systems
are bidding away resources (mainly family labor) from rice/maize systems.

When converted to a per person-day basis, the returns to family labor (RFL) are
1597 fcfa for the cassava/maize system and 640 fcfa for the rainfed rice/maize system.
Under both systems, the RFL per persOn—day is higher than the average wage rate paid to
the hired labor, which is 630 fcfa per person-day for cassava/maize systems and 600 fcfa

for rice/maize systems. Thus, there is no ﬁnancial advantage of family members seeking

 

‘ It is assumed that the energy content is: 146 kcal for 100 grams of fresh cassava, 359
kcal for 100 grams of rice and 247 kcal for 100 grams of fresh maize (Manuel de Nutrition
Aﬁicaine, Appendix 2).

35

wage employment in other farms, when they are needed on their farms in the village,
although the return-to the rice/maize system is close to the opportunity cost of labor.

To compute the net enterprise proﬁts (NEP), opportunity costs were assigned to
family labor and land. That is, family labor was valued at hired labor wage rate and land
was attributed a value equal to net returns to land if farmers were producing green maize
only. Both the cassava/maize enterprise and the rainfed rice/maize enterprise realized
positive NEPs of 129,594 fcfa per hectare and 3801 fcfa per hectare, respectively.

Results from table 2-1 also show that the costs of providing a kilocalorie is lower
(5 francs cfa per kcal) under cassava/maize systems than with rice/maize systems (13
francs cfa per kcal).
2.3.1.2. Post-harvest Level Financial Analysis for Cassava

It is assumed that green maize is harvested and consumed or sold at the farm level.
Therefore, only cassava roots harvested are taken to the next level (the village) to be
processed. The technology used in most villages is called traditional in the sense that most,
if not all, of the processes are carried out manually at home. This analysis also assumes, as
indicated in the COSCA (phase 2) survey data, that only 45% of the cassava goes into
attieke production. The remaining 55% is consumed either fresh or in other forms such as

foufou or kokonte.

The major form into which cassava roots are processed in Cote d’Ivoire is attieke,
which is made of steamed cassava granules. The estimated average ﬁnancial budget per
hectare for attieke production in Cote d’Ivoire is presented in table 2-2 above.

Transformation coeﬂicients were computed and used to calculate actual attieke

yields. With a conversion ratio of 56 percent, attieke yield was 2706 kilograms per

36

Table 2-2: Estimated Average Financial Budget per hectare for Attieke
Production2 in Cote d’Ivoire. 1989-1991, assuming that
45 % of roots production goes into attieke production

Budget Items

 

1. INPUT USE Family Hired
Family/Hired Labor Use (person-days)3 57 0
Raw Material (kgs of roots)4 4832
2.0UTPUTS
Transformation Rate 0.56
Kilograms of Processed Output per ha 2706
Village Market Price of Processed Output (fcfa/kg)5 47
Gross Revenues (fcfa/ha) 127169
3. COSTS
Fixed Costs (fcfa/ha)6 0
Operating costs (fcfa/ha)
Hired Labor (persondays) 0
Raw Material (roots)7 72475
Bagging Materials 16234
Firewood 2205
Transportation8 7670
Interest on Working Capital (8%) 7887
Total Operating Costs (fcfa/ha) 106471
Family Labor (valued @ hired labor wage rate) (fcfa/ha) 35910
4. PERFORMANCE MEASURES
Gross Margin (fcfa/ha) 20698
Net Returns to family Labor (fcfa/ha) 20698
Net Returns per day of Family Labor (fcfa/day) 363
Total production Costs (fcfa/ha) 142381
Net Enterprise Proﬁts (fcfa/ha) -15212
Production Costs per Kg of attieke (fcfa/kg) 53

 

Source: COSCA data

 

2 There were forty-three (43) farmers using traditional techniques versus three (3) using modern techniques. Therefore, this
budget includes only farmers using traditional (manual) processing techniques.

3 This item includes labor for Peeling. Washing. Grating. Pressing. Sieving and Steaming.

4 This represents 45% of the average root yield per hectare (see page 23 in COSCA Working Paper No 6)

5 Weighted average village market price estimated from COSCA data

6 No mechanical equipment was used in any processing activity. Grating was performed manually (COSCA Working Paper
No.14, page 15).

7 Valued at its opportunity cost which is the weighted average farmgate price computed from the COSCA data

8 This item includes home-to—market transportation costs only.

37

hectare. This yield is valued by the average consumer price based in COSCA village
survey data. It should be noted that prices vary a lot from season to season, mainly
because of changing seasonal conditions (e. g., abundance vs. hungry seasons). To account
for this diversity, the weighted average price was estimated. Since farmers do not own
processing machines, no ﬁxed costs was assigned processing enterprises.

The budget analysis shows a positive return per day of family labor (RDFL) of 363
fcfa per day, which, however, is below the daily wage rate of 630 fcfa. The average cost
of production (53 fcfa per kilogram) is greater than the market price (47 fcfa per
kilogram) and the result is a net enterprise proﬁt (NEP) of -15212 fcfa. However, it
should be noted that the negative NEP observed does not mean that farmers are losing
incoming cash money on this crop; but rather, it means that net margin is not enough to
yield a positive return to the management factors when family labor costs are taken into
account. The NEP assuming zero opportunity cost of labor is positive.

A question that arises at this point is why farmers are staying in the attieke
business if returns are so low. The COSCA survey data indicate that women control
attieke production in Cote d’Ivoire and receive all the beneﬁts from that activity. In
addition, when asked why they were involved in this activity only, their answer was that
there is no better alternative. Therefore, the opportunity cost of attieke production, from
their point of view, is zero.

This situation reﬂects the segmentation of the rural labor market for cassava
farming systems in Cote d’Ivoire. Women manage a very important part of cassava

production systems: 1) they predominate in cassava processing and attieke preparation

38

and, 2) they devote a large amounts of time in obtaining the fuel and water required to
make cassava processed products ready for sale or home consumption. Yet this analysis
suggests that returns to women from these activities are below the rural wage rate, which
is available mainly to men.

2.3.2. Economic Profitability Analysis

The farm level economic returns were calculated using import parity prices of
cassava roots and ﬁnancial prices of green maize at selected regional markets, Bonoua and
N’douci (see tables A2-3, A2-4, A2-5 and A2-6 in appendix 2). These two markets were
selected because they are located in regions where farmers ranked cassava as the most
important crop in the farming system (Nweke et al., 1998). The economic budgets are
presented in tables A2-7 through A2-10 in the appendix.

The estimation of the economic budgets required the following assumptions: 1) it
is assumed that green maize is nontraded internationally and that its price is the observed
market price. Therefore, its ﬁnancial price (the observed market price) reﬂects its shadow
price; 2) Attieke, the main cassava product in Cote d’Ivoire, is not traded internationally,
but tapioca, another cassava product and the closest substitute of attieke is traded
internationally. Consequently, the price of imported tapioca was used to estimate the
import parity of cassava root; and 3) the ofﬁcial exchange rate (266 fcfa for $1US in
1991) was adjusted to reﬂect its equilibrium value, by using a premium of 48 percent
(Stryker, 1990)

Tables 2-3 and 2-4 summarize the results of the economic analysis for: 1) cassava
and rice farmers who are net sellers of roots or paddy in regional markets; and 2) cassava

and rice farmers who are net buyers in these markets.

39

 

Table 2-3: Summary Estimates of Farm-Level Economic Budget Indicators for
Commercial Cassava/Maize and Rainfed Rice/Maize Production
Systems,by Regional Output Markets, Cote d’Ivoire: 1989/91

 

 

 

Production Systems Returns to Returns to Total Net Social
And Production Zones Family Family System Proﬁts
Labor Labor Per Production Per ha
Per Ha Person-day Costs
Per ha
Bonoua
Cassava/maize 120778 857 210891 31948
Rice/ maize 53 206 5 78 179361 -1994
N’douci
Cassava/ maize 162823 1139 210420 72733
Rice/ maize 60845 669 177869 6245
Source: tables A2-7 and A2-8 in the appendix

 

 

Table 2-4: Summary Estimates of Farm-Level Economic Budget Indicators for
Subsistence Cassava/Maize and Rainfed Rice/Maize Production
Systems, byProduction Zones, Cote d’Ivoire: 1989/91
Production Systems Returns to Returns to Total Net Social
And Production Zones Family Family System Proﬁts
Labor Labor Per Production Per ha
Per Ha Person-day Costs
Per ha
Bonoua Zone
Cassava/mat 23 8129 1689 21 1766 149299
Rice/maize 69557 756 179361 14357
N’douci Zone
Cassava/moi 286454 2003 210420 196364
Rice/maize 71357 784 177869 16757

 

Sources: tables A2-9 and A2-10 in the appendix

An initial notable result is that the net social proﬁt (N SP) for rainfed rice/maize
systems is negative in the Bonoua market for commercial farmers. This suggests that the

Bonoua area is not able to substitute proﬁtably local production of riceg, from rainfed

 

9 The outputs from the rainfed rice Imaize system are paddy and green maize. However, green maize is not
internationally tradable nor is it traded, whereas milled rice is internationally tradable and traded.

40

rice/maize systems, for imported rice sold in that market. This lack of proﬁtability results
in the net returns per day of family labor (RDFL) being less than the average daily wage
rate of 600 fcfa for cassava farmers.

Overall, the result of the economic analysis indicates that cassava/maize production
systems are the more proﬁtable than rainfed rice/maize systems. Cassava/maize systems
generate signiﬁcantly higher net social proﬁts (N SP) at both regional output markets
(31,948 fcfa /ha in Bonoua and 72,733 fcfa/ha in N’douci) and in both production zones
(149,299 fcfa/ha in Bonoua Zone and 196,364 fcfa/ha in N’douci Zone) for subsistence
farmers. The net social proﬁt refers to the difference, valued in border and shadow prices,
between the gross value of output and the total costs of all inputs (traded and nontraded
intermediary and primary inputs). The implication is that, from society’s point of view, it
pays to expand cassava/maize production systems. That is, cassava/maize systems are a
more efﬁcient use of national resources than rainfed rice/maize systems. A more efﬁcient
use of resources means that one can produce more from what one has and attain a higher
level of welfare.

It should be noted that both systems are more proﬁtable ﬁnancially than they are
socially. That is, there are net transfers to farmers (see tables A2-11 through A2-14 in
appendix 2). The subsequent PAM analysis will help illustrate the sources of these
transfers.
2.3.3.Policy Matrix Analysis

By completing a PAM for a production system one can simultaneously determine
the economic efﬁciency of the system and the degree of transfers in the input /output

markets (Yao, 1997). First, the PAM was constructed using the information on costs and

41

returns obtained from the ﬁnancial and economic analyses. Second, the extent of policy-
induced transfers was computed. Third, six PAM policy-indicators were derived for policy
analysis. They are the Domestic Resource Cost (DRC), the Nominal Protection
Coefﬁcient on tradable output (NPCO), the Nominal Protection Coefﬁcient on tradable
Input (NPCI), the Effective Protection Coefﬁcient (EPC), the Proﬁtability Coefﬁcient
(PC), and the Subsidy to Producers (SP). These indicators are calculated as follows:
(i) DRC equals domestic factors in social prices divided by revenues in social
prices less tradable inputs in social prices.
(ii) NPCO equals revenues in private prices divided by revenues in social
prices.
(iii) NPCI equals tradable inputs in private prices divided by tradable inputs in
social prices.
(iv) EPC equals revenues in private prices less tradable inputs in private prices
divided by revenues in social prices less tradable inputs in social prices.

(v) PC equals private proﬁts divided by social proﬁts.

(vi) SP equals private proﬁts less social proﬁts divided by revenues in social
prices.
2.3.3.1.Baseline Results
The PAMs of each production system (for commercial and subsistence farmers)
are presented in tables 2-5 and 2-6 below. Results ﬁ'om table 2-5 show that, for both
production systems, the output transfers are positive for when the output is sold at the

Bonoua market but negative when the output is sold in the N’douci market. This implies

42

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43

 

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that, as a result of government pricing policies, farmers at the Bonoua market were
receiving production subsidies, whereas farmers at the N’douci market were being taxed.
Furthermore, the levels of taxation and subsidy were higher for the cassava/maize systems
than the rice/maize systems.

This is the result of farm-gate ﬁnancial prices for cassava root departing from the
estimated import parity prices (tables A2-3 in Appendix 2) of roots by +3 fcfa per
kilogram when Bonoua is used as a point of sale and -l fcfa per kilogram when N’douci is
used as a point of sale. On the other hand, the farm-gate market ﬁnancial price of paddy is
60 fcfa, which departs from its estimated import parity price (tables A2-4 in Appendix 2)
by +1 fcfa per kilogram when Bonoua is used as a point of sale and -5 fcfa per kilogram
when N’douci is used as a point of sale.

It should be emphasized that these differentials are relatively small. With this in
mind, here are some plausible explanations of why market (ﬁnancial) prices and economic
prices (import parity prices) did not equal in both markets. The divergences between these
two prices could be due to a combination of the eﬁ‘ect of the rice import tariff and the
effect of the overvaluation of the ﬁne CFA. The indirect effect of the rice import tariff
will be an increase in the ﬁnancial price of cassava root relative to the economic price in
the two markets (Bonoua and N’douci). On the other hand, the currency overvaluation
will have the effect of lowering the ﬁnancial price of tradables such as roots and transport
in both markets.

However, the magnitude of the reduction in prices will be large in N’douci and
small in Bonoua because the share of transport costs in the import parity price is relatively

large for N’douci (distant from the port city) and relatively small for Bonoua (close to the

45

port city). Transportation costs thus provide a natural protection to domestic producers
who supply markets located far from the import point.

Thus, the net effect is as follows: 1) in N’douci: an increase in the ﬁnancial price of
roots due to the import tariff and a relatively large decrease in the ﬁnancial price of roots
due to the currency overvaluation (via its impact on tradable goods such as cassava and
transport costs); and 2) in Bonoua: an increase in the price of roots due to the import tariff
and a relatively small decrease in the ﬁnancial price of roots due to the currency
overvaluation.

The results from table 2-5 are calculated using the weighted average of peak-
season and off-peak season wage rate across cassava production zones. The off-peak
season rate is two third of the peak-season rate.

As for the results presented in table 2-6, they show negative output transfers
everywhere'for both systems. This suggests that, subsistence farmers in both production
areas (Bonoua zone and N’douci zone) were being taxed. Again, highest tax on cassava
systems results from tables 2-5 and 2-6, which show negative input and domestic factors
transfers for both systems everywhere. Tables 2-5 and 2-6 also show that net policy
transfers are positive for both systems in the Bonoua market while they were negative
everywhere else. These results indicates that, overall, when outputs and inputs were
valued at their social (efﬁciency) prices, the effect of government policy was: a) some type
of support system to both cassava/maize and rainfed rice/maize systems in the Bonoua
market while they were taxed everywhere else; b) the provision of a subsidy, through an
overvalued exchange rate, on sale of all inputs (imported and produced domestically).

However, the absolute measures of net policy transfers are not appropriate for

46

comparisons among systems comparing unlike outputs. The ratios computed for this

purpose are shown in tables 2-7 and 2-8.

Table 2-7: Ratio Indicators for Commercial Cassava/Maize and Rainfed
Rice/Maize Systems in Cote d’Ivoire: 1989/1991.

 

 

Output Markets/ DRC N PCO NPCI EPC PC SP
Production Systems
Bonoua
Cassava/Maize 0.86 1.14 1.00 1.15 2.14 0.15
Rice/Maize 1.01 1.01 1.00 1.02 -0.81 0.02
N’douci
Cassava/Maize 0.74 0.95 1.00 0.96 0.83 -0.04
Rice/Maize 0.96 0.97 1.00 0.98 ' 0.32 -0.02

 

 

Source: PAM Model constructed by the author
Note: DRC= Domestic Resource Cost, NPCO= Nominal Protection Coefficient on
Tradable Output, NPCI= Nominal Protection Coefficient on Tradable Input,
EPC= Effective Protection Coefﬁcient, PC= Proﬁtability Coefﬁcient
and SP= Subsidy to Producers

Table 2-8: Ratio Indicators for Subsistence Cassava/Maize and Rainfed
Rice/Maize Systems in Cote d’Ivoire: 1989/1991.

’ H in o ‘7 7|: ' C . i _' '
BonouaZone

 

CassavaMaize 0.58 0.77 0.99 0.77 0.46 -0.22
Rice/Maize 0.92 0.92 1.00 0.93 0.1 1 -0.07
N’douci Zone
CassavaMaize 0.51 0.66 1.00 0.66 0.31 -0.33
Rice/Maize 0.91 0.91 1.00 0.92 0.12 -0.08

 

Source: PAM Model constructed by the author

Note: DRC= Domestic Resource Cost, NPCO= Nominal Protection Coefficient on
Tradable Output, NPCI= Nominal Protection Coefficient on Tradable Input,
EPC= Effective Protection Coefficient, PC= Proﬁtability Coefﬁcient
and SP= Subsidy to Producers.
The domestic resource cost ratio (DRC) assesses social returns to domestic

factors, and is the social cost of domestic resources required to produce a unit of value

added to tradable goods and services. The DRC ratio indicates the efficiency of domestic

47

production of an export or of an import substitute. The computed values for the DRC
ratios are consistent with the results of the economic analysis. Whether farmers are
involved in subsistence farming or commercial farming, cassava/maize production systems
have a clear comparative advantage over rainfed rice/maize production systems.

A word of caution: the result discussed above is based on output prices in speciﬁc
markets. However, shadow prices vary (ﬁgures A2-1 and A2-2 in appendix 2), depending
on the point of sale. As ﬁgures 2-1 and 2-2 below demonstrate, the corresponding DRC
ratios vary also over space. These ﬁgures indicate the following: 1) the outputs from
commercial cassava/maize systems harvested beyond 100 kilometers from the regional
markets, are not competitive at either regional market; 2) the ﬁrrther away the point of
harvest from the output market, the less competitive cassava/maize systems become; and
3) distance has less impact on the competitivity of rainfed rice/maize systems

These results suggest that only local expansion of cassava systems may be socially
proﬁtable. However, it is worth noting that the graphs above refer only to DRCs in the
Bonoua and N’douci markets. Cassava systems may be proﬁtable in other markets.

The nominal protection coefficient in the output/inputs markets (NPCO/NPCI) is a
summary measure of incentives provided by government pricing policy on outputs or
inputs respectively. The computed NPCOs indicate that only commercial cassava/maize
farmers and commercial rainfed rice/maize farmers operating in the Bonoua market have
enjoyed a private price 1 to 14 percent higher than they would have received without
government policy. This suggests that the actual policy was a trade-restrictive policy,
which had an effect equivalent to that of an import tariff of l to 14 percent. On the other

hand, computed NPCIs are equal unity everywhere, suggesting that the input market was

48

totally unprotected.

As mentioned earlier, the observed prices for both commodities are higher than
their shadow prices when Bonoua is the regional market. This difference in prices serves
as an implicit tariff to reallocate resources in the economy. That is, consumers reduce their
consumption of the commodity, production expands in response to the higher domestic

price, consumers transfer part of their surplus to producers.

Figure 2-1: DRC Ratios Over Space for Commercial Cassava/Maize and
Rainfed Rice/Maize Production Systems- Bonoua is the Regional Output
Market, Cote d'Ivoirezl989/l99l

 

2.50

 

2.00

 

1.50

rat-P3—
1.00-

DRC Ratios

 

0.50

 

 

 

0.00 . . r . 4 I . , . f I ﬂ
0 50 100 150 200 250 300 350 400 450 500 550 600

Distance Output Mkt- Village
[-I—DRCroot —A -DRCricej

 

 

49

ﬁgrreZ-ZzDRCRatiosOverSpaceforConmercialCassava/Maizeand
RainfedRice/NhizeProrhctionSystam—N‘doud istheRegimalOutput

 

 

    

 

 

 

160 Market, Cote d'Ivoirezl989/l991
r 40
1 20 r

**
Pu?
r

 

  

 

 

DRC Ratios
g

 

 

 

020

 

 

 

0.m Y ﬁr 1' Y 1 T T V Y f Y r
0 50 1(1) l 50 2(1) 250 3(1) 350 4(1) 450 5(1) 550 6CD

DistanceQrtthtt-Village

 

 

The effective protection coefficient (EPC) best measures the combined effects
discussed earlier. The computed EPCs are between 1.02 and 1.15 for commercial
production systems at the Bonoua market, suggesting that those production systems are
enjoying a slight positive protection in that market. On the other hand, results show that
the net effects of policy have been negative (EPCs are less unity) for all farmers under
both systems everywhere else, with cassava systems being taxed more than rice systems.

The other ratios shown in tables 2-7 and 2-8 are the proﬁtability coefficient (PC)
ratio and the subsidy to producers (SP) ratio. The PC ratio shows the extent to which net
transfers have caused private proﬁts to exceed social proﬁts, while the SP ratio shows the
level of transfers from divergences as a proportion of the production system’s social

revenues (Monke and Pearson, 1989). The computed values of these two ratios lie

50

between —0.81 and 2.14 for the PC ratios and between -.02 and 0.15 for the SP ratio. It
should be noted that no clear interpretation of the PC ratio is possible when its value is
negative. Therefore, the focus will be on positive value of computed PC ratios, which
indicate that: a) at the Bonoua market, policy transfers have permitted private proﬁts
nearly 2.14 times higher than social proﬁts; b) everywhere else, private proﬁts represent
only 11 to 83 percent of social proﬁts. The computed SP ratios indicate that distorting
policies such as the pricing policies discussed earlier, have caused social revenues from
both systems (commercial and subsistence) to be lower by 2 to 33 percent everywhere.
2.3.3.2. Sensitivity Analysis

Sensitivity analysis carried out in this sub-section aims to test the robustness of the
results under the baseline scenario. Two scenarios are considered: the ﬁrst scenario
simulates increases in cassava and rice yields per hectare; and the second considers the
effects of change in the shadow exchange rate. All the sensitivity analyses are done for
commercial production systems.

Yields per hectare. The results of sensitivity analysis of the selected baseline-
policy parameter to changes in yields per hectare are shown in table 2-9 below. The effect
of possible ﬁrture changes in production technology was modeled by increasing yields of
the main crops (cassava roots and rice paddy) of the production systems. Yields were
increased 5 percent, 10 percent and 15 percent to examine the extent to which the
increases would alter the comparative advantage of both systems. The increases in yields
may appear large but they are attainable using modern technology (Barry, 1994 and
Nweke, 1996). As table 2-9 demonstrates, the simulation ﬁndings indicate that a 5 to 15

percent increase in yields per hectare of cassava would not only further enhance the

51

comparative advantage of cassava/maize systems but also cause rice/maize systems, which
were unproﬁtable at the baseline, to become socially proﬁtable (DRC less than unity) in
the Bonoua region.

Table 2-9: The Effects of Changes in Yields per Hectare on Selected Policy
Indicators for Commercial Production

 

 

 

 

 

 

 

 

 

—
Mitts/Systems Policy Parameters
. DRC Ratio EPC Ratio
Bonoua Yield Baseline % Simulation Baseline % Simulation
Increase Change Clingc
+5% .86 -6 0.81 1.15 -3 1.12
Cassava/maize +10% .86 -10 0.77 1.15 -5 1.09
+15% .86 -15 0.73 1.15 -7 1.07
+5% 1.01 -2 0.99 1.02 -4 0.98
Rice/maize +10% 1.01 -4 0.97 1.02 -6 0.96
+15% 1.01 -6 0.95 1.02 -10 0.92
N’douci
+5% 0.74 -5 0.70 0.96 -2 0.94
Cassava/maize +10% 0.74 -9 0.67 0.96 -4 0.92
+15% 0.74 -14 0.64 0.96 -5 0.91
+5% 0.96 -2 ' 0.94 0.98 -l 0.97
Rice/maize +10% 0.96 -4 0.92 0.98 -4 0.94
' +15% 0.96 -6 0.90 0.98 -7 0.91

 

 

 

Shadow Exchange Rates. In 1989/91 the shadow exchange rate was 394 ﬁ'ancs
cfa. By 1994, it has declined by 35 percent (from 394 fcfa to 532 fcfa), and the
consequence was the devaluation of the franc cfa in January 1994. The second scenario of
the sensitivity analysis is designed to examine the effects of this 35 percent decline in the
shadow exchange rate between 1989/91 and 1994, on the net social proﬁtability (N SP)
and selected policy parameters (DRC, EPC and PC) ratios. The import parity prices were
recalculated using the post-devaluation exchange rate of 532 fcfa to one US dollar. Post-
devaluation studies (Camara, 1996; Babo, 1996) have shown that market prices have

changed with devaluation: from 60 fcfa to 77 fcfa a kilogram for rice and from 15 fcfa to

52

18 fcfa for kilogram of cassava. Furthermore, these studies also show that devaluation had
an impact on the prices of non-tradable inputs such as labor. Rural wage rates increased by
15 to 20 percent. These post-devaluation market prices were used in can'ying this
analysis. Tables 2-10 and 2-11 present the results.

Table 2-10: The Effects of a Change in the Shadow Exchange Rate on the Net

Social Profit (NSP)/ha for Commercial Production Systems

 

 

Markets/ Systems of Production Baseline Simulation Proﬁt
. p . . 10
Bonoua Cassava/maize 31948 141960 9.83
Rice/maize -1994 8200 NA.
N’douci Cassava/maize 72733 175529 4.03
Rice/maize 6245 18716 5.69

 

Note: This analysis is based on a 35 % decline in the Shadow Exchange Rate

Table 2-11: The Effects of a Change in the Shadow Exchange Rate on Selected
Policy Indicators for Commercial Production Systems, by Production
Systems for Each Regional Output Markets.

 

 

 

 

Markets/ Systems Policy Indicators

DRC Ratio EPC Ratio
Bonoua Baseline % Simulation Baseline % Simulation

Change Change

Cassava/maize 0. 86 -25 0.64 1. 1 5 -32 0.78
Rice/maize 1.01 -5 0.96 1.02 -3 0.98
N’douci
Cassava/maize 0.74 -20 0.59 .96 -27 0.70
Rice/maize 0.96 -5 0.91 .98 -4 0.94

 

 

Note: This analysis is based on a 35 % decline in the Shadow Exchange Rate

As the proﬁt elasticities (in absolute terms) in table 2-10 indicate, social
proﬁtability levels are very sensitive to a decline in the shadow exchange rate. Following
the 74 percent decrease in the shadow exchange rate, each production system offered

large social proﬁts.

 

10 The proﬁt elasticity is computed as follows: percentage changes in NSF/percentage change in exchange rate.

53

The results of table 2-11 show the effect of the exchange rate depreciation on the
DRC and the EPC ratios. Two notable results: ﬁrst, the EPC estimates are less than unity,
suggesting that farmers are being implicitly taxed. That is, they could have received a
higher return if they faced border prices instead of domestic prices on both outputs and
inputs. However, it should be noted that values of EPC ratios for rice/maize production
systems are all close to unity. This implies low government interference in the Ivorian
rainfed rice/maize economy.

Second, the simulated values of the domestic resource cost (DRC) ratios are less
than unity in Bonoua and N’douci. This result has one signiﬁcant policy implication. One
objective of the Ivorian government is the substitution of domestic production for imports,
with the goal of saving foreign exchange. The DRC ratio is an indicator of the efficiency
of a commodity production system in converting domestic resources into foreign
exchange. Thus, the results of this sensitivity analysis indicate that, if the farmgate price of
green maize did not change, the decline in the shadow exchange rate would cause

resources used both systems to have a positive impact on Cote d’Ivoire balance of

payments.

2.4. Conclusions

This essay is an application of the policy analysis matrix (PAM) for two competing
production systems (cassava/maize and rainfed rice/maize) in Cote d’Ivoire. The purpose
was to analyze the competitiveness of cassava/maize systems relative to rainfed rice/maize
systems. The baseline results indicate that cassava/maize systems have a competitive

advantage over their competitors. That is, proﬁtabilities (ﬁnancial and social) of

54

cassava/maize systems signiﬁcantly exceed those of rainfed rice/maize systems. This result
indicates that cassava/maize production systems are efficient given current technologies.
PAM is a static model, which cannot capture changes in prices and productivity
(Yao, 1998); therefore, a sensitivity analysis was carried out. The simulation ﬁndings
indicate that a 5 to 15 percent increase in yields per hectare and a decline in the
equilibrium exchange rate would: a) enhance the comparative advantage of cassava/maize

systems; and b) cause rice/maize systems to become socially proﬁtable also.

55

REFERENCES

Babo, Alﬁ'ed, Circuits de Commercialisation et de Transformation du Manicc dans la
Region de Bouake. Memoire de Maitrise. Option: Socio-Economie du
Developpement Rural. Universite de Bouake, 1996.

Barry, A.W., 1994, Comparative Advantage,Trade Flows and Prospects for Regional
Agricultural Market Integration in West Africa: The Case of Cote d’Ivoire and
Mali, Ph.D. Dissertation. Department of Agricultural Economics, Michigan State
University.

Camara, A, La F iliere Riz en Cote d’Ivoire, Etude PRISAS/CIRES, Centre Ivoirien de
Recherches Economiques et Sociales, 1996.

Crawford, E., A simulation Study of Constraints on Traditional Farming Systems in
Northern Nigeria. Department of Agricultural Economics, Michigan State
University, MS U International Development Paper No.2, 1982.

Ikpi Anthony E., 1989, “Economic Considerations of Cassava Development” in Ikpi
Anthony E. and Hahn Natalie D. (eds.). Cassava, Lifeline for the Rural
Household, Book Builders Limited, Ibadan, Nigeria.

IMF, 1989-1992, Various issues
Jones, W.O., Manioc in Aﬁica, Stanford University Press, Stanford, 1959.

Ministere de l’Economie et des Finances, Direction de la Statistique. Etudes des
Evolutions recentes des Revenus Agricoles, Abidjan, 1996.

Monke, EA. and S. Pearson. 1989. The Policy Analysis Matrix for Agricultural
Development. Baltimore: John Hopkins University Press.

Nweke, F.I., Cassava: A Cash Crop in Aﬁica, Working Paper No. 14, The Collaborative
Study of Cassava in Africa, 1996.

Nweke, Felix I., K. N'Goran, A.G.O. Dixon, B.O. Ugwu, O. Ajobo, and T.
Kouadio. 1998, Cassava production and processing in Cote d'Ivoire. COSCA
Working Paper No. 23, The Collaborative Study of Cassava in Africa, IITA,
Ibadan, Nigeria.

Nwajiuba, C.U., Socioeconomic Impact of Cassava Postharvest Technologies on
Smallholders in Southeastern Nigeria, Farming Systems and Resource Economics
in the Tropics, Vol 20, 1995.

Pearson, Scott, Monke, Eric. 1995. “ A Framework for Analyzing Policy Options” in

56

Buttel Frederick H., DeWalt Billie R. and Pinstrup-Anderson Per (eds).
Agg'cutural Policy in Kenya. Cornell University Press. pp. 1 1- 28.

Theberger, R. Les principaux ravageurs et maladies du manioc, de l’igname , de la patate
douce et arace'es en Aﬁique, HTA, 1985.

Kreamer, R. G. , Gari Processing in Ghana: A Study of Entrepreneurship and Technical
Change in Tropical Aﬁica, Cornell/International Agricultural Economics Study,
86-30, December 1986.

Ministere de l’Economie et des Finances, Direction de la Statistique: Etude des évolutions
récentes des revenus agricoles, Abidjan, 1996.

Monke, EA. and S. Pearson. 1989. The Policy Analysis Matrix for Agricultural
. Development. Baltimore: John Hopkins University Press.

Stryker J. Dirck, “ Trade, Exchange Rate, and Agricultural Pricing Policies in Ghana,”
World Bank Comparative Studies, 1990.

Yao, Shujie, 1997. “Rice Production in Thailand Seen Through a Policy Analysis
Matrix”. Food Policy, 22(6):547-560.

57

APPENDIX 2

58

Table A2-l:

 

1. INPUT USE Family Hired
Family/Hired Labor Use (person-days )
Land Clearing 18 14
Seedbed Preparation 22 20
Weeding 12 14
Planting
Cassava 17 15
Maize 15 O
Harvesting
Cassava 27 ll
Maize 23 0
Total 134 74
2. OUTPUTS 10737
Average Root Yield (kg/ha) 6780
Average Maize Yield (ears/ha)1 15
Market Price of Root (fcfa/kg)2 25
Market Price of Green Maize (fcfa/ears)3 169500
Revenues from Green Maize (fcfa/ha) 161055
Revenues from Cassava Roots (fcfa/ha) 330555
Gross Revenues (fcfa/ha)
3. COSTS 0
Fixed Costs (fcfa/ha)4
Operating costs (fcfa/ha)
Hired Labor (146966200
Transportation ﬁeld-to-home (fcfa/ton) 4126
Interest on Working Capital (8%) 55706
Total Operating Costs (fcfa/ha) 84420
Family Labor (valued @ hired labor wage rate) 60835
Opportunity Cost of land
4. PERFORMANCE MEASURES 274349
Gross Margin (fcfa/ha) 214014
Net Returns to family Labor (fcfa/ha) 1597
Net Returns per day of Family Labor (fcfa/day) 200961
Total System Production Costs (fcfa/ha) 129594

Net Enterprise Proﬁts (fcfa/ha)

Estimated Average Financial Budget for Cassava/Maize Production
Systems, Cote d’Ivoire: 1989/1991

 

 

ISlource: COSCA survey data

 

 

‘ Estimated using the “Ear Weight Method” discussed in Appendix 2. In West Africa, maize, which has a
short cycle, is harvested before cassava establishes. Hence competition between maize and cassava is
minimized, while sole plant density is maintained for both crops (COSCA Working Paper No.10, page 84).
2 Weighted average farmgate price based on COSCA data

3 Farrngate price based on personal communication with Centre Ivoirien de Recherches Economiques et
Sociales (CIRES).

4 Farmers did not purchase planting materials of food crops; they produced their own: for cassava, only one
ﬁfth of the stems from previous harvest are retained for replanting and for maize, only 2 to 3 percent of the
harvest is retained for seed. Therefore, the opportunity cost of planting materials, which is relatively
insigniﬁcant, is not counted.

59

Table A2-2: Estimated Average Financial Budget for Rainfed Rice/Maize
Production Systems,Cote d’Ivoire: 1989/1991

 

 

 

 

 

Budget Items
1. INPUT USE Family Hired
Family/Hired Labor Use (person-days)
Land Clearing 10 15
Seedbed Preparation 11 14
Weeding 23 18
Planting
Paddy 19 15
Maize 7 0
Harvesting
Paddy 15 17
Maize 10 0
Total 95 79
2. OUTPUTS 1300
Average Paddy Yield (kg/ha) 3994
Average Maize Yield (ears/ha)‘ 60
Market Price of Paddy (fcfa/kg)2 2 5
Market Price of Green Maize (fora/ears)3 99850
Revenues ﬁ'om Green Maize (fcfa/ha) 73000
Revenues from Paddy (fcfa/ha) 177850
Gross Revenues (fcfa/ha)
3. COSTS 0
Fixed Costs (feta/la)“
Operating costs (fcfa/ha)
Hired Labor 4476452)O
Transportation ﬁeld-to-home (fcfa/ton) 4164
Interest on Working Capital (8%) 56214
Total Operating Costs (fcfa/ha) 57000
Family Labor (valued @ hired labor wage rate) 60835
Opportunity Cost of land (fcfa)
3. PERFORMANCE MEASURES 121636
Gross Margin (fcfa/ha) 60801
Net Returns to family Labor (fcfa/ha) 640
Net Returns per day of Family Labor (fcfa/day) 174049
Total System Production Costs (fcfa/ha) 3301
Net Enterprise Proﬁts (fcfa/ha)

 

 

Source: COSCA survey data

 

‘ Estimated using the “Ear Weight Method” discussed in Appendix 2. In West Africa. maize, which has a
short cycle, is harvested before cassava establishes. Hence competition between maize and cassava is
minimized, while sole plant density is maintained for both crops. (COSCA Working Paper No.10, page 84)
2 Weighted average farmgate price based on COSCA data

3 Farmgate price based on personal communication with Centre Ivoirien de Recherches Economiques et
Sociales (CIRES).

4 Farmers did not purchase planting materials of food crops; they produced their own: for rice, only 2 to 3
percent of the previous harvest is retained for replanting and for maize, only 2 to 3 percent of the previous
harvest is retained for seed. Therefore, the opportunity cost of planting materials, which is relatively
insigniﬁcant, is not counted

60

Table A2-3: Economic Import Parity Price of Cassava Root
For Sale in Regional Output Markets, Cote d’Ivoire: 1989/1991

 

 

 

Items Regional Ouput Markets
Bonoua N’douci

1. World Price (F OB-SUS/mt tapioca) 221 221

2. Freight and insurance ($US/mt tapioca) 48 48

3. CIF, port in Abidjan ($US/mt tapioca) (1+2) 269 269

4. Shadow Exchange rate (fcfa/ $US) 394 394

5. CIF price at the port in Abidjan ( fcfa/mt

tapioca) (3 *4) 105998 105998

6. Domestic costs (fcfa/mt tapioca)

a. Port charges (fcfa/mt tapioca) 700 700

b. Transit and Transport (fcfa/mt tapioca) 2000 2000

c. Storage and Handling (fcfa/mt tapioca) 2000 2000
7. Abidjan gate price (5+ 6a. . .c ) (fcfa/mt tapioca) 110698 110698
8. Importer marketing margin (%) 5% 5%
9. Wholesale price in Abidjan (7* (1+ 8)) 116233 116233
10. Abidjan to Regional Market Center

a Distance (km) 75 130

b. Transport cost (fcfa/mt tapioca) 2625 4550

c. Handling (fcfa/mt tapioca) 2000 2000
11. Regional Market Center (Reference Price)

Farmgate price (fcfa/mt tapioca) (9 + 10a..c ) 120858 122783
12. Wholesale marketing margin (%) 5% 5%
13. Wholesale price

in Regional Market ( fcfa/mt tapioca) (1 1* 126901 128922
(1+12))
14. Regional Market Center to Village
a. Distance (kms) 37 56
b. Transport and Handling cost (fcfa/mt 3665 4520
tapioca)
15. Village gate price (fcfa/mt tapioca) (13-14b) 123236 124402
16. Semi-wholesale marketing margin (%) 5% 5%
17. Village Level Semi-wholesale price ((1-
16)*15)/1000 117 118
18.Transformation rate (kg of tapioca / kg of root) .5 .5
19. Processing cost (fcfa/kg of root) 46 43
20. Import Parity Price in the Village (fcfa /kg of
root) (17*18)-19 12 16

 

Source: COSCA data, Institut de Documentaion de Recherches et d’Etudes Maritimes of the
Ivorian Marine Ministry; UN Economic and Social Commission For Asia and the Paciﬁc, Reports

of 1989 through 1991.

61

Table A2-4: Economic Import Parity Price of Paddy
For Sale in Regional Outputs Markets, Cote d’Ivoire: 1989/1991.

 

 

 

 

Items Regional Outputs Markets
Bonoua N ’douci

1. World Price (F OB-$US/mt milled rice) 201 201

2. Freight and insurance ($US/mt milled rice) 48 48

3.CIF, port in Abidjan ($US/mt milled rice) (1+2) 249 249

4. Shadow Exchange rate (fcfa / $US) 394 394

5. CIF price at the port in Abidjan ( fcfa/mt milled rice)

(3 *4) 98026 98026

6. Domestic costs (fcfa/mt milled rice)

a. Port charges (fcfa/mt milled rice) 700 700

b. Transit and Transport (fcfa/mt milled rice) 2000 2000

c. Storage and Handling (fcfa/mt milled rice) 2000 2000
7. Abidjan gate price (5+ 6a.. .c) (fcfa/mt milled rice) 102726 102726
8. Importer marketing margin (%) 5% 5%
9. Wholesale price in Abidjan (7* (1+ 8)) 107863 107863
10. Abidjan to Regional Market Center

a Distance (km) 75 130

b. Transport cost(fcfa/mt milled rice) 2625 4550

c. Handling (fcfa/mt milled rice) 2000 2000
11. Regional Market Center (Reference Price)

Farmgate price (fcfa/mt milled rice) (9 +10a..c) 112488 122783
12. Wholesale marketing margin (%) 5% 5%
13. Wholesale price

in Regional Market ( fcfa/mt milled rice) (11* 118112 128922

(1+12))
14. Regional Market Center to Village

a. Distance (kms) 37 56

b. Transport and Handling cost (fcfa/mt milled 3665 4520
rice)
15. Village gate price (fcfa/mt milled rice) (13-14b) 114447 124402
16. Semi-wholesale marketing margin (%) 5% 5%
17. Village Level Semi-wholesale price ((1-16
)*15)/1000 109 118
18.Milling Rate (kg of milled rice / kg of paddy) 0.65 0.65
19. Processing cost (fcfa/kg of paddy) 12 12
20. Import Parity Price in the Village (cfaf /kg of paddy)
(17*18)-19 59 65

 

Source: COSCA data, Institut de Documentaion de Recherches et d’Etudes Maritimes of the

Ivorian Marine Ministry; UN Economic and Social Commission For Asia and the Paciﬁc, Reports

of 1989 through 1991.

62

 

Table A2-S: Economic Import Parity Price of Cassava Root
For Home Consumption, Cote d’Ivoire: 1989/1991.

 

Items

 

 

1. World Price (FOB-$US/mt tapioca)

2. Freight and insurance ($US/mt tapioca)

3. CIF, port in Abidjan ( $US/mt tapioca) (1+2)
4. Shadow Exchange rate (fcfa / $US)

5. CIF price at the port in Abidjan (fcfa/mt tapioca) (3*4)

6. Domestic costs (fcfa/mt tapioca)
a. Port charges (fcfa/mt tapioca)
b. Transit and Transport (fcfa/mt tapioca)
c. Storage and Handling (fcfa/mt tapioca)
7. Abidjan gate price (5+ 6a. . .c ) (fcfa/mt tapioca) 8.
Importer marketing margin (%)
9. Wholesale price in Abidjan (7* (1+ 8))
10. Abidjan to Regional Market Center
a Distance (km)
b. Transport cost (fcfa/mt tapioca)
c. Handling (fcfa/mt tapioca)
11. Regional Market Center (Reference Price)
Farmgate price (fcfa/mt tapioca) (9 + 10a..c)
12. Wholesale marketing margin (%)
13. Wholesale price
in Regional Market ( fcfa/mt tapioca) (11* (1+12))
14. Regional Market Center to Village
a. Distance (kms)
b. Transport and Handling cost (fcfa/mt tapioca)
15. Village gate price (fcfa/mt tapioca) (13+14b)
16. Semi-wholesale marketing margin (% )
17. Village Level Semi-wholesale price ((1+16
)* 1 5)/ 1000
18.Transformation rate (kg of tapioca / kg of root)
19. Processing cost (fcfa/kg of root)
20. Import Parity Price in the Village (cfaf /kg of root)
(17*18)-19

Production Zones
Bonoua N’douci
.Zone IZone
221 221
48 48
269 269
394 394
105998 105998
700 700
2000 2000
2000 2000
110698 110698
596 596
116233 116233
75 130
2625 4550
2000 2000
120858 122783
596 596
126901 128922
37 56
3665 4520
130566 133442
596 596
137 140
(15 (15
46 43
22 27

 

-S-orurce: COSCA data. Institut de Documentaion de Recherches et d’Etudes Maritimes of the Ivorian—

Marine Ministry; UN Economic and Social Commission For Asia and the Paciﬁc, Reports of 1989

through 1991.

63

Table A2-6: Economic Import Parity Price of Paddy- For Home Consumption,

Cote d’Ivoire: 1989/1991.

 

Production Zones

 

 

Items
Bonoua N ’douci

Zone Zone
1. World Price (FOB-$US/mt milled rice) 201 201
2. Freight and insurance ($US/mt milled rice) 48 48
3. CIF, port in Abidjan ( $US/mt milled rice) (1+2) 249 249
4. Shadow Exchange rate ( fcfa / $US) 394 394
5. CIF price at the port in Abidjan ( fcfa/mt milled rice) 98026 98026
(3*4)
6. Domestic costs (fcfa/mt milled rice)

a. Port charges (fcfa/mt milled rice) 700 700

b. Transit and Transport (fcfa/mt milled rice) 2000 2000

c. Storage and Handling (fcfa/mt milled rice) 2000 2000
7. Abidjan gate price (5+ 6a. . .c) (fcfa/mt milled rice) 102726 102726
8. Importer marketing margin (%) 5% 5%
9. Wholesale price in Abidjan (7* (1+ 8)) 107863 107863

10. Abidjan to Regional Market Center
a Distance (km) 75 130
b. Transport cost (fcfa/mt milled rice) 2625 4550
c. Handling (fcfa/mt milled rice) 2000 2000
11. Regional Market Center (Reference Price)

Farmgate price (fcfa/mt milled rice) (9 + 10a..c) 112488 122783
12. Wholesale marketing margin (%) 5% 5%
13. Wholesale price

in Regional Market ( fcfa/mt milled rice) (11* 118112 128922
(1+12))
14. Regional Market Center to Village
a. Distance (kms) 37 56
b. Transport and Handling cost (fcfa/mt milled 3665 4520
rice)
15. Village gate price (fcfa/mt tapioca) (13+14b) 121777 124402
16. Semi-wholesale marketing margin (%) 5% 5%
17. Village Level Semi-wholesale price
((1+16)*15)/1000 128 131
18.Milling Rate (kg of milled rice / kg of paddy) 0.65 0.65
19. Processing cost (fcfa/kg of paddy) 12 12
20. Import Parity Price in the Village (cfaf /kg of paddy)
(17*18) -19 71 73

 

Source: COSCA data. Institut de Documentaion de Recherches et d’Etudes Maritimes of the Ivorian

Marine Ministry; UN Economic and Social Commission For Asia and the Paciﬁc, Reports of 1989 through

1991.

64

Table A2-7: Estimated Economic Farm Level Budget for Commercial
Cassava/Maize Production Systems, by Regional Output Markets,
Cote d’Ivoire. 1989-1991

 

 

 

Budget Items Regional Oumut Markets
Bonoua N ’douci
l. OUTPUTS
Average Root Yield (kg/ha) 1 1811 11274
Average Green Maize Yield (ears/ha)l 3994 3994
Market Price of root (fcfa/kg)2 12 16
Market Price of Green Maize (fcfa/ear)3 25 25
Revenues from Root (fcfa lha) 142989 183303
Revenues from Green Maize (fcfa /ha) 99850 99850
Gross Revenues (fcfa /ha) 242839 283153
2. COSTS
Fixed Costs (/ha)4
Operating costs (/ha) 0 0
Hired Labor5
Transportation ﬁeld-to-home (fcfa) 49140 47880
Tradable
Nontradable 6460 6166
Interest on Working Capital (8%) 1091 1042
Total Operating Costs (fcfa lha) 4535 4247
Family Labor (valued @ hired labor wage rate) 61226 57335
(fcfa /ha) 88830 90090
Opportunity Cost of Land6 (fcfa/ha) 60835 60835
3. PERFORMANCE MEASURES
Gross Margin (fcfa /ha) 181613 223658
Net Returns to family Labor (fcfa lha) 120778 162823
Net Returns per day of Family Labor (fcfa /day) 857 1139
Total production Costs (fcfa /ha) 210891 210420
Net Social Proﬁts (fcfa /ha) 31948 72733

 

Source: COSCA survey data

 

' Estimated Farmgate price using the “Ear Weight Method” discussed in Appendix 2.

2 Estimated farm level import parity price of root

3 Farmgate price based on personal communication with Centre Ivoirien de Recherches Economiques et
Sociales (CIRES).

4 Farmers did not purchase planting materials of food crops: they produced their own: for cassava, only one
ﬁfth of the stems from previous harvest is retained for replanting and for maize, only 2 to 3 percent of the
harvest is retained for seed. Therefore, the opportunity cost of planting materials, which is relatively
insigniﬁcant, is not counted

5 Although rural labor markets in West Africa are complex, it is reasonable to assume that market wages
offer good approximations to shadow wages (Hurnphreys in Rice in West Africg, p. 80, 1981).

6 Land is very rarely sold or rented. In this budget, the opportunity cost of land is estimated as the net return
to land that farmers would enjoy if they produced green maize only.

65

Table A2-8: Estimated Economic Farm Level Budget for Commercial Rainfed
Rice/Maize Production Systems, by Regional Output Markets,

Cote d’Ivoire, 1989/1991

 

 

 

Budget Items Regional Ouput Markets
- Bonoua N ’douci
l. OUTPUTS
Average paddy Yield (kg/ha) 1320 1300
Average Green Maize Yield (ears/ha)l 3994 3994
Market Price of paddy (fcfa/kg)2 59 65
Market Price of Green Maize (fora/ear)3 25 25
Revenues from Paddy (fcfa lha) 77446 84326
Revenues from Green Maize (fcfa /ha) 99850 99850
Gross Revenues (fcfa /ha) 177367 184114
2. COSTS
Fixed Costs (/ha)4 0 0
Operating costs (lha)
Hired Labor5 52200 51000
Transportation ﬁeld-to-home (fcfa/ton)
Tradable 5506 5825
Nontradable 930 984
Interest on Working Capital (8%) 4691 4625
Total Operating Costs (fcfa lha) 63326 62434
Family Labor (valued @ hired labor wage rate) (fcfa /ha) 55200 54600
Opportunity Cost of Land6 (fcfa/ha) 60835 60835
4. PERFORMANCE MEASURES
Gross Margin (fcfa /ha) 114041 121680
Net Returns to family Labor (fcfa lha) 53206 60845
Net Returns per day of Family Labor (fcfa /day) 578 669
Total production Costs (fcfa lha) 179361 177869
Net Social Proﬁts (fcfa /ha) -1994 6245

Source: COSCA survey data

 

‘ Estimated Farmgate price using the “Ear Weight Method” discussed in Appendix 2.

2 Estimated Farm level import parity price of paddy

3 Farmgate price based on personal communication with Centre Ivoirien de Recherches Economiques et
Sociales (CIRES).

4 Farmers did not purchase planting materials of food crops; they produced their own: for rice, only 2 to 3
percent of the previous harvest is retained for replanting and for maize, only 2 to 3 percent of the previous
harvest is for seed.Therefore, the opportunity cost of planting materials, which is relatively insigniﬁcant, is
not counted

5 Although niral labor markets in West Africa are complex, it is reasonable to assume that market wages
offer good approximations to shadow wages (Humphreys in Rice in West Africa. p. 80, 1981).

6 Land is very rarely sold or rented. In this budget the opportunity cost of land is estimated as the net return
to land that farmers would enjoy if they produced green maize only.

66

Table A2—9: Estimated Economic Farm Level Budget for Subsistence

Cassava/Maize Production Systems, by Production Zones,

Cote d’Ivoire, 1989-1991

 

 

 

 

Budget Items Production Zones
Bonoua N ’douci
Zone Zone
1. OUTPUTS
Average Root Yield (kg/ha) 11811 11274
Average Green Maize Yield (ears/ha)l 3994 3994
Market Price of root (feta/kg)2 22 27
Market Price of Green Maize (fcfa/ear)3 25 25
Revenues ﬁ'om Root (fcfa /ha) 261215 306934
Revenues from Green Maize (fcfa lha) 99850 99850
Gross Revenues (fcfa /ha) 361065 406784
2. COSTS
Fixed Costs (/ha)4 0 0
Operating costs (/ha)
Hired Labor’ 49140 47880
Transportation (fcfa)
Tradable 6460 6166
Nontradable 1091 1042
Interest on Working Capital (8%) 4600 4407
Total Operating Costs (fcfa lha) 62101 59495
Family Labor (valued @ hired labor wage rate) (fcfa /ha) 88830 90090
Opportunity Cost of Land6 (fcfa/ha) 60835 60835
3. PERFORMANCE MEASURES
Gross Margin (fcfa lha) 298964 347289
Net Returns to family Labor (fcfa /ha) 238129 286454
Net Returns per day of Family Labor (fcfa /day) 1689 2003
Total production Costs (fcfa lha) 211766 210420
Net Social Proﬁts (fcfa lha) 149299 196364

 

 

Source: COSCA survey data

 

‘ Estimated Farmgate price using the “Ear Weight Method” discussed in Appendix 2.

2 Estimated farm level import parity price of root

3 Farmgate price based on personal communication with Centre Ivoirien de Recherches Economiques et
Sociales (CIRES).

4 Farmers did not purchase planting materials of food crops; they produced their own: for cassava, only one
ﬁfth of the stems is retained for replanting and for maize. only 2 to 3 percent of the harvest is retained for
seed. Therefore, the opportunity cost of planting materials, which is relatively insigniﬁcant, is not counted.
sAlthough rural labor markets in West Africa are complex, it is reasonable to assume that market wages
offer good approximations to shadow wages (Humphreys in Rice in West Africg, p. 80, 1981).

6 Land is very rarely sold or rented. In this budget, the opportunity cost of land is estimated as the net return
to land that farmers would enjoy if they produced green maize only.

67

Table A2-10: Estimated Economic Farm Level Budget for Subsistence Rainfed
Rice/Maize Production Systems, by Production Zones,
Cote d’Ivoire, 1989/1991

 

 

 

Budget Items Production Zones
Bonoua N’douci
Zone Zone
1. OUTPUTS
Average paddy Yield (kg/ha) 1320 1300
Average Green Maize Yield (ears/ha)l 3994 3994
Market Price of paddy (fcfa/kg)2 71 73
Market Price of Green Maize (fcfa/ear)3 25 25
Revenues from Paddy (fcfa fha) 93 869 94776
Revenues from Green Maize (fcfa lha) 99850 99850
Gross Revenues (fcfa /ha) 193719 194626
2. COSTS
Fixed Costs (fcfa/ha)4 0 0
Operating costs (fcfa/ha)
Hired Labor’ 52200 51000
Transportation (fcfa)
Tradable 5506 5825
Nontradable 930 984
Interest on Working Capital (8%) 4691 4625
Total Operating Costs (fcfa lha) 63326 62434
Family Labor (valued @ hired labor wage rate) (fcfa /ha) 55200 54600
Opportunity Cost of Land6 (fcfa/ha) 60835 60835
3. PERFORMANCE MEASURES
Gross Margin (fcfa /ha) 130392 132192
Net Returns to family Labor (fcfa lha) 69557 71357
Net Returns per day of Family Labor (fcfa /day) 756 784
Total production Costs (fcfa /ha) 179361 177869
Net Social Proﬁts (fcfa /ha) 14357 16757

 

 

Source: COSCA survey data

 

' Estimated farmgate price using the “Ear Weight Method” discussed in Appendix 2.

2 Estimated farm level import parity price of paddy

3 Farmgate price based on personal communication with Centre Ivoirien de Recherches Economiques et
Sociales (CIRES).

4 Farmers did not purchase planting materials of food crops; they produced their own: for rice, only 2 to 3
percent of the previous harvest is retained for seed and for maize. only 2 to 3 percent of the previous
harvest is retained for seed. Therefore, the opportunity cost of planting materials, which is relatively
insigniﬁcant. is not counted.

6Although rural labor markets in West Africa are complex, it is reasonable to assume that market wages
offer good approximations to shadow wages (Humphreys in Rice in West Aﬁiﬁca, p. 80, 1981).

6 Land is very rarely sold or rented. In this budget, the opportunity cost of land is estimated as the net retum
to land that farmers would enjoy if they produced green maize only.

68

Table A2-ll: Estimated Financial Farm Level Budget for Commercial Rainfed
Rice/Maize Production Systems, by Regional Output Markets,

Cote d’Ivoire, 1989/1991

 

 

 

 

 

Budget Items Regional Output
Markets
Bonoua N ’douci
l. OUTPUTS
Average paddy Yield (kg/ha) 1320 1300
Average Green Maize Yield (ears/ha)l 3994 3994
Market Price of paddy (fcfa/kg)2 60 60
Market Price of Green Maize (fcfa/ear)3 25 25
Revenues ﬁom Paddy (fcfa /ha) 79200 78000
Revenues from Green Maize (fcfa fha) 99850 99850
Gross Revenues (fcfa lha) 179050 177850
2. COSTS
Fixed Costs (/ha) 0 0
Operating costs (fha)
Hired Labor“ 52200 51000
Transportation (fcfa)
Tradable 3720 3936
Nontradable 930 984
Interest on Working Capital (8%) 4548 4474
Total Operating Costs (fcfa /ha) 61398 60394
Family Labor (valued @ hired labor wage rate) (fcfa /ha) 55200 54600
Opportunity Cost of Land5 (fcfa/ha) 60835 60835
3. PERFORMANCE MEASURES
Gross Margin (fcfa /ha) 1 17652 1 17456
Net Returns to family Labor (fcfa /ha) 56817 56621
Net Returns per day of Family Labor (fcfa /day) 618 622
Total production Costs (fcfa lha) 177433 175829
Net Enterprise Proﬁts (fefa lha) 1617 2021

SEce: COSCA survey data

 

‘ Estimated Farmgate price using the “Ear Weight Method” discussed in the appendix.

2 Weighted average farmgate price based on COSCA data

3 Farmgate price based on personal communication with Centre Ivoirien de Recherches Economiques et
Sociales (CIRES).

3 Although rural labor markets in West Africa are complex, it is reasonable to assume that market wages
offer good approximations to shadow wages (Humphreys in Rice in West Aﬁicg, p. 80, 1981).

3 Land is very rarely sold or rented. In this budget, the opportunity cost of land is estimated as the net return
to land that farmers would enjoy if they produced green maize only.

69

Table A2-12: Estimated Financial Farm Level Budget for Commercial

Cassava/Maize Production Systems, by Regional Output Markets,

Cote d’Ivoire, 1989-1991

 

 

 

Budget Items Regional Output
Markets
Bonoua N ’douci
l. OUTPUTS
Average Root Yield (kg/ha) 11811 11274
Average Green Maize Yield (ears/ha)l 3994 3994
Market Price of root (fcfa/kg)2 15 15
Market Price of Green Maize (fcfa/ear)3 25 25
Revenues from Root (fcfa lha) 177161 169108
Revenues from Green Maize (fcfa lha) 99850 998 50
Gross Revenues (fcfa lha) 277011 268958
2. COSTS
Fixed Costs (lha)4 0 0
Operating costs (/ha)
Hired Labor 49140 47880
Transportation (fcfa)
Tradable 4365 4166
Nontradable 1091 1042
Interest on Working Capital (8%) 4368 4247
Total Operating Costs (fcfa lha) 58964 57335
Family Labor (valued @ hired labor wage rate) (fcfa /ha) 88830 90090
Opportunity Cost of Land5 (fcfa/ha) 60835 60835
3. PERFORMANCE MEASURES
Gross Margin (fcfa /ha) 218047 211623
Net Returns to family Labor (fcfa lha) 157212 150788
Net Returns per day of Family Labor (fcfa /day) 1115 1054
Total production Costs (fcfa lha) 208629 208260
Net Enterprise Proﬁts (fcfa lha) 68382 60698

 

Sturce: COSCA survey (lat:

 

‘ Estimated Farmgate price using the “Ear Weight Method” discussed in Appendix 2.

2 Weighted average farmgate price based on COSCA data.

3 Farmgate price based on personal communication with Centre Ivoirien de Recherches Economiques et
Sociales (CIRES).

4 Farmers did not purchase planting materials of food crops; they produced their own: for cassava, only one
ﬁfth of the stems from previous harvest is retained for replanting and for maize, only 2 to 3 percent of
harvest. Therefore. the opportunity cost of planting materials, which is relatively insigniﬁcant, is not
counted.

5 Land is very rarely sold or rented. In this budget, the opportunity cost of land is estimated as the net return
to land that farmers would enjoy if they produced green maize only.

70

Table A2—13: Estimated Financial Farm Level Budget for Subsistence

Cassava/Maize Production Systems, by Regional Output Markets,

Cote IIId’Ivoire. 1989391

 

 

 

Budget Items Regional Output
Markets
Bonoua N’douci
1. OUTPUTS
Average Root Yield (kg/ha) 11811 11274
Average Green Maize Yield (ears/ha)l 3994 3994
Market Price of root (fcfa/kg)2 15 15
Market Price of Green Maize (fcfa/ear)3 25 25
Revenues ﬁom Root (fcfa fha) 177161 169108
Revenues from Green Maize (fcfa /ha) 99850 99850
Gross Revenues (fcfa /ha) 277011 268958
2. COSTS
Fixed Costs (/ha)4 0 0
Operating costs (fha)
Hired Labor 49140 47880
Transportation (fcfa)
Tradable 4365 4166
Nontradable 1091 1042
Interest on Working Capital (8%) 4368 4247
Total Operating Costs (fcfa /ha) 58964 57335
Family Labor (valued @ hired labor wage rate) (fcfa /ha) 88830 90090
Opportunity Cost of Lands (fcfa/ha) 60835 60835
3. PERFORMANCE MEASURES
Gross Margin (fcfa /ha) 218047 211623
Net Returns to family Labor (fcfa /ha) 157212 150788
Net Returns per day of Family Labor (fcfa /day) 1 115 1054
Total production Costs (fcfa /ha) 208629 208260
Net Enterprise Proﬁts (fcfa /ha) 683 82 60698

 

Source: COSCA survey data

 

‘ Estimated Farmgate price using the “Ear Weight Method” discussed in Appendix 2.

2 Weighted average farmgate price based on COSCA data.

3 Farmgate price based on personal communication with Centre Ivoirien de Recherches Economiques et
Sociales (CIRES).

" F anners did not purchase planting materials of food crops; they produced their own: for cassava, only one
ﬁfth of the stems from previous harvest is retained for replanting and for maize, only 2 to 3 percent of
harvest. Therefore, the opportunity cost of planting materials, which is relatively insigniﬁcant, is not
counted.

5 Land is very rarely sold or rented. In this budget, the opportunity cost of land is estimated as the net return
to land that farmers would enjoy if they produced green maize only.

71

Table A2-14: Estimated Financial Farm Level Budget for Subsistence Rainfed
Rice/Maize Production Systems, by Regional Output Markets,

Cote d’Ivoire, 1989/1991

 

 

 

Budget Items Regional Output
Markets
Bonoua N’douci
1. OUTPUTS
Average paddy Yield (kg/ha) 1320 1300
Average Green Maize Yield (ears/ha)l 3994 3994
Market Price of paddy (fcfa/kg)2 60 60
Market Price of Green Maize (fcfa/ear)3 25 25
Revenues from Paddy (fcfa lha) 79200 78000
Revenues ﬁ'om Green Maize (fcfa lha) 99850 99850
Gross Revenues (fcfa /ha) 179050 177850
2. COSTS
Fixed Costs (/ha) 0 0
Operating costs (lha)
Hired Labor4 52200 51000
Transportation (fcfa)
Tradable 3720 3936
Nontradable 930 984
Interest on Working Capital (8%) 4548 4474
Total Operating Costs (fcfa /ha) 61398 60394
Family Labor (valued @ hired labor wage rate) (fcfa /ha) 55200 54600
Opportunity Cost of Land5 (fcfa/ha) 60835 60835
3. PERFORMANCE MEASURES
Gross Margin (fcfa lha) 117652 117456
Net Returns to family Labor (fcfa lha) 56817 56621
Net Returns per day of Family Labor (fcfa /day) 618 622
Total production Costs (fcfa /ha) 177433 175829
Net Enterprise Proﬁts (fcfa lha) 1617 2021

 

Source: COSCA survey data

 

' Estimated Farmgate price using the “Ear Weight Method” discussed in Appendix 2.

2 Weighted average farmgate price based on COSCA data

3 Farmgate price based on personal communication with Centre Ivoirien de Recherches Economiques et
Sociales (CIRES).

4 Although rural labor markets in West Africa are complex, it is reasonable to assume that market wages
offer good approximations to shadow wages (Humphreys in Rice in West Africa. p. 80, 1981).

5 Land is very rarely sold or rented. In this budget, the opportunity cost of land is estimated as the net return
to land that farmers would enjoy if they produced green maize only.

72

 

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74

CHAPTER 3
EVALUATING THE SOCIAL PROFIT ABILITY OF CASSAVA-BASED

PRODUCTION SYSTEMS UNDER ALTERNATIVE PRODUCTION-
PROCESSING TECHNOLOGY COMBINATION S IN NIGERIA

3.1. Introduction

The Collaborative Study of Cassava in Africa (COSCA) found that processing by
a mechanized cassava processing method reduces the cost of the processed product by
saving labor, thereby extending the market for the product. The COSCA study also found
that under manual processing methods, high yields attained through planting of improved
varieties might not have substantial cost—saving advantage because the cost constraint
will be shifted to the processing stage (Nweke et al., 1994). The study concludes that
improvement in the processing technology would have as much effect on cassava
production expansion as improvement in yield.

This essay builds on this conclusion to hypothesize that cassava-based production
systems, under a combination of improved production technologies with modern
processing technologies, are the most proﬁtable (ﬁnancially and socially) of all cassava-
based systems in Nigeria.

A few studies have examined the impact of technologies on cassava production in
Nigeria. Nweke (1994) estimated costs and returns for cassava root production and gari
making in southeast Nigeria. They found that overall cost-saving advantage of yield
increasing technology might not fully translate into expanded production if there is no

cost-saving technology at processing stage.

75

Nwajiuba (1995) has analyzed the socioeconomic impact of the introduction
cassava postharvest technologies in southeastern Nigeria. He concluded that the ﬁnancial
proﬁtability of gari production has increased with the improvement of processing
technologies.

However, no study has addressed the issue of the social proﬁtability of cassava-
based production systems under alternative combinations of production and processing
technologies in Nigeria. Such an issue is important because the experience in bringing
technical change to small-farm agriculture in Sub-Saharan Africa suggests that when
human and ﬁnancial resources are limited there are distinct advantages to focusing on a
few, well chosen regions, staple crops and simple technologies. (Byerlee and Heisey,
1993)

This study is based on the fact that cassava products such as tapioca are tradable
and currently traded, to an extent, in Sub-Saharan Aﬁica. This means that cassava-based
systems have a certain potential for generating export earnings. Therefore, a policy
analysis that helps determine combinations of production and processing technologies,
under which cassava-based production systems are socially proﬁtable (e. g.,
internationally competitive), can be very useful to policy-makers.

Following Adesina and Coulibaly (1998), this essay uses the Policy Analysis
Matrix (PAM) to examine the relative proﬁtability (ﬁnancial and social) and comparative
advantage of cassava/maize production systems under four alternative production and
processing technology-combinations inlNigeria: “Impmech”, “Locmec ”, “Locman”, and
“Impman” deﬁned as follows: a) Impmech refers to IITA’s improved cassava variety

processed using a mechanized grating method, b) Locmech refers to local cassava variety

76

processed using a mechanized grating method, c) Locman refers to local cassava variety
processed using a manual grating method), d) Impman refers to IITA’s improved cassava

variety processed using a manual grating method.

3.2. Methodological Framework

The Policy Analysis Matrix (PAM) is the analytical framework used in this essay.
This methodology is developed in detail in the ﬁrst chapter; therefore in this section, the
focus is on how it is used in estimating comparative social returns and costs to production
and processing technology combinations.

This study is based on data for Nigeria, from the Collaborative Study of Cassava
in Aﬁica (COSCA) survey. COSCA report number 2 provides a detailed discussion of
the data collection procedures and the associated sampling method. The survey covered
the period 1989/1991.

The COSCA survey data that are used include farm-level technical coefﬁcients,
processing costs, transformation rates of cassava root into processed products, sources of
cassava roots and destination of cassava products, unit storage cost, unit transportation
costs, product and input market prices, taxes and subsidy levels. In the case of green
maize, data used were obtained not only from the COSCA survey but also from primary
sources of earlier studies and from secondary sources such as the agricultural statistics
report of the Ofﬁce of Agricultural Statistics (Nigerian Ministry of Agriculture). In
addition, macroeconomic data needed in the estimation of economic prices (i.e. import
parity prices and shadow exchange prices) were obtained mostly from secondary sources

such as the Nigeria Port Authority Statistical Reports (1989 through 1992) and the IMF.

77

3.3. Empirical Analyses

Cassava/maize production systems considered in this study can be represented by
three separate activities. The ﬁrst activity, farm production, consists of root and green
maize production and transportation to the village. Green maize is either consumed on
farm or sold. The second activity involves the processing of cassava into gari.
Transportation of gari to be sold at regional markets is the third activity.

Information contained in the COSCA data base for Nigeria were used to classify
households surveyed into four categories, based on production zones:

(i) Farmers who grow improved cassava varieties and produce gari using a

mechanized grating method

(ii) Farmers who grow local landrace varieties and produce gari using a

mechanized grating method

(iii) Farmers who grow local landrace varieties and produce gari using a manual

grating method

(iv) Farmers who grow improved cassava varieties and produce gari using a

manual grating method

Cluster analysis conﬁrmed that, in Nigeria, many important technical factors (e. g
soil texture, types of processing equipment available) affecting the choice of cassava
production and processing technologies are highly correlated with production zones.
Thus, the classiﬁcation approach indeed grouped together households, most of which use
similar technologies. However, some intra-zone variability was found; therefore, the

results of the empirical analyses should be considered applicable to “average” households

78

in each production zone. Cassava/maize production systems under each technology
combinations are examined in this section using a combination of ﬁnancial analysis,
economic analysis and policy analysis. The tasks involved are the following:
1. To develop enterprise budgets (ﬁnancial and economic) for each technology
combination under a “baseline scenario”.
2. To construct a Policy Analysis Matrix (PAM) for each commodity system, using the
information from the enterprise budget and estimate ratio indicators such as DRC, NPC,
etc.
3. To undertake sensitivity analyses in order to contrast the comparative advantage of the
four technology combinations.
3.3.1. Financial Proﬁtability Analysis

The purpose of this sub-section is to estimate crop enterprise budgets, processed
product (gari) enterprise budgets by production and processing technology, and thereby
provide the information for establishing the relative proﬁtability of alternative cassava
production and processing technology combinations. Separate farm—level ﬁnancial
budgets were developed for each production technology. In addition, a post-farm level
budget was constructed for each combination of production and processing technologies.
The aim of input-output budget analysis is to derive farm recommendations, which are
consistent with farmers’ desires to increase expected income and to make the best
possible use of the resources available to them. Furthermore, enterprise budgets are
important in farm income analysis because they help to explain the internal structure of
the farm as a whole and to show the relative contribution of each enterprise to the whole

organization. Therefore, these enterprise studies are very instrumental in an attempt to:

79

(i) assess the proﬁtability of each enterprise relative to the resources used; (ii) compare
relative efﬁciency of various enterprises on the farm; and (iii) provide a basis for making
rational decisions about the kind and size of enterprise to be expanded.

In the ﬁnancial analysis, the main objective is to answer the question whether a
particular enterprise under a given system of production will pay its way in strict
monetary terms.(Are returns greater than monetary costs?) Towards this end, inputs are
valued at the average market prices that farmers paid for each type of input, while output
is valued at the average unit price received at harvest period by farmers in each country.
For each enterprise budget, ﬁnancial returns to family labor were computed. Other
performance measures computed from the budget data include gross margin per hectare,
net returns to family labor, net returns per day of family labor, total production cost per
hectare and average cost of processing per kilogram of output in the post-farm analysis.
3.3.1.1. Farm level Analysis

Cassava/maize enterprise budgets were constructed for each production
technology. These budgets are presented in tables A3-l and A3-2 of appendix 3. Table 3-
1 below summarizes the results of the “baseline” runs of the farm level ﬁnancial
proﬁtability analysis. The summary focuses mainly on performance measures that can be
used to identify the enterprise with the highest ﬁnancial return and lowest cost of
production. The results in table 3-1 indicate clearly that, on average, cassava/maize
systems with the IITA’s improved cassava variety are the most proﬁtable systems. They

generate the highest returns and the highest net proﬁts.

80

Table 3-1: Summary Estimates (in naira) of Farm-Level Financial Budget
Indicators for Cassava/Maize Production Systems, by Production
Technologies: Nigeria, 1989/91

 

 

 

 

Technologies Returns to Returns to Net
. . Total .
Family Family S stem Enterprise
Labor Labor Per y . Proﬁts
Per Ha Person-day Production
Costs/ha
II TA ’3
Improved 12626 73 16357 9014
Varieties
Local
landraces 8834 55 15361 5453

 

Source: tables A3-1 and A3-2 in appendix 3

When converted to a per person-day basis, the returns to family labor (RFL) are
73 nairas for IITA’s improved varieties and 55 nairas for local landraces. Under both
systems, the RFL per person-day is higher than the average wage rate paid to the hired
labor, which is 21 nairas per person-day. Thus, there is no ﬁnancial advantage of family
members seeking wage employment in urban areas or other farms, when they are needed
on their farms in the village.

To compute the net enterprise proﬁts (NEP), opportunity costs were assigned to
family labor and land. That is, family labor was valued at hired labor wage rate and land
was attributed a value equal to net returns to land if farmers were growing green maize
only. Both technologies realized positive NEPs of 9014 nairas for the IITA variety and
5453 nairas for the local landrace variety.

Unfortunately, the COSCA study did not record maize yields on its sample ﬁelds.
Therefore, in computing the enterprise budgets developed in this study, it was assumed

that those ﬁelds got the average maize yield for the country which was then converted to

81

the number of fresh corn ears using the “Ear-Weight Method” discussed in the appendix
of chapter 2. The number of corn ears were subsequently valued at the fresh corn price.
3.3.1.2. Post-harvest Level Financial Analysis

It is assumed that green maize is harvested and consumed on farm or sold at the
farm level. Therefore, only cassava roots harvested are taken to the next level (the
village) to be processed. Cassava processing methods involve a combination of activities
such as peeling, grating and toasting. Of these activities, grating is the most labor
intensive. In this study, a process is deﬁned as traditional if grating is performed
manually. Mechanized grating involves the use of various types of mechanical cassava
graters, which are driven by electrical, petrol, or diesel engines. The major form into
which cassava roots are processed in Nigeria is gari, which is made of toasted cassava
granules.

Transformation coefﬁcients were computed and used to calculate actual gari
yields under each technology combination. These yields were valued by the average
consumer price of gari based on COSCA village survey data. It should be noted that
prices vary a lot from season to season, mainly because of changing season conditions
(e.g., abundance vs. hungry seasons). To account for this diversity, the weighted average
price was estimated. Since farmers do not own processing machines, no ﬁxed costs were
assigned processing enterprises. Table 3-2 summarizes the results of the post farm-level

budget analysis.

82

 

Table 3-2: Summary Estimates (in naira) of Post-farm-Level Financial Budget
Indicators for Gari Production, by Technology Combinations:
Nigeria, 1989/91

 

 

Technologies Returns to Returns to T Average Net
. . . . otal .

Combinations Family Family S stem Costs of Enterprrse

Labor Labor Per y . Production Proﬁts

Production
Per Ha Person-day Costs Per Kg of
Gari
Impmech 2310 33 14120 2.96 840
Locmech 1 127 20 8761 3.15 -28
Locman 1003 17 8891 3 .23 -257
-555hih .................................... 1.0.9.4. .......................... 1. .3.. ....................... 1.5.65.0 ...................... 328-691 ...........

 

Source: tables A3-3 through A3-6 in Appendix 3.

Results in table 3-2 show that only cassava/maize systems under the “Impmech”
technology combination had a positive net enterprise proﬁts (NEP). These results also
show that mechanized processing methods have a deﬁnite cost-saving advantage over
traditional processing methods. The “Impmech” technology combination has the lowest
cost of production per kilogram of gari (2.97 nairas) followed by the “Locmech”
technology combination (3.15nairas). This implies that farmers have incentives to adopt
that technology combination. These ﬁndings are consistent with farmers’ incentives
behavior. In fact, COSCA data for Nigeria show that in the 65 villages representing
cassava-growing areas, 56 percent of farmers grow the improved varieties. Of these
farmers, 54 percent used mechanized processing method to produce gari.

However, it should be noted that the negative NEPs observed under the other
technology combinations do not mean that farmers are losing money. Rather, they mean
that the net margin is not enough to yield a positive return to the management factor

when the costs of other factors are taken into account. In fact, the postfarm level ﬁnancial

83

budgets presented in tables A3-3 through A3-6 in appendix 3 show that all the NEPs,
assuming zero opportunity cost of labor, are positive.

This situation reﬂects the segmentation of the rural labor market for cassava
farming systems in Nigeria. Women manage a very important part of cassava production
systems: 1) they predominate in cassava processing and gari preparation and, 2) they
devote a large amounts of time in obtaining the fuel and water required to make cassava
processed products ready for sale or home consumption. Yet this analysis suggests that
returns to women ﬁ'om these activities are below the rural wage rate, which is available
mainly to men.

3.3.2. Economic Proﬁtability Analysis

Two cassava root production technologies (IITA’s improved variety and local
landraces) were analyzed, with alternative combinations of gari (a cassava product)
production with mechanized processing method or with manual processing method. This
gives the four alternative production and processing technologies deﬁned earlier. The
COSCA data indicate that about 79 percent of farmers who produce gari are net sellers;
therefore, this analysis focuses only on commercial cassava/maize systems.

The farm level economic returns were calculated using import parity prices
(tables A3-7 and A3-8 in appendix 3) of cassava roots and ﬁnancial prices of green maize
at selected regional markets, Abeokuta and Onitsha. These two markets were selected
because they are located in regions where farmers ranked cassava as the most important
crop in the farming system (Nweke etal., 1996).

The economic budgets are presented in tables A3-10, A3-12, A3-14 and A3—16 in

Appendix 3. The tables show the returns to root (not gari) and maize production

 

assuming root was valued at the import parity price for each technology, as calculated in
tables A3-7 and A3-8 in Appendix 3.

The estimation of the economic budgets required the following assumptions: 1) it'
is assumed that green maize is nontraded and that its price is not affected by government
policies. Therefore, its ﬁnancial price (the observed market price) reﬂects its shadow
price; 2) gari, the main cassava product in Nigeria, is not traded internationally, but
tapioca, another cassava product and the closest substitute of gari, is traded
internationally. Consequently, the price of imported tapioca was used to estimate the
import parity of cassava root; and 3) the ofﬁcial exchange rate (17 nairas for $1US) was
adjusted to reﬂect its equilibrium value, by using a premium of 30% (Stryker, 1990).

Table 3-3 summarizes the results of the economic analysis for commercial farmers.

 

Table 3-3: Summary Estimates (in nairas) of Farm-Level Economic Budget
Indicators For Commercial Cassava/Maize Production Systems at
Each Regional Output Market, by Production and Processing
Technolo Combinations, Ni eria: 1989/1991
Regional Markets/ Returns to Returns to Total System Net Social
Technology Family Family Labor Production Proﬁts
Combinations Labor Per Person-day Costs Per Ha Per I-Ia
Per Ha
Abeokuta Impmech 10137 57 17473 6378
Locmech 6666 52 14845 3978
Locman 5174 40 14845 2486
Impman 2470 14 17473 -1289
Onitsha
Impmech 18877 104 17225 15055
Locmech 1 1088 67 15898 7602
Locman 9239 56 15898 5753
Impman 8627 47 17225 4805

 

Source: tables A3-10, A3-12, A3-14 and A3-16 in the appendix.

85

At this point it is important to make clear what is going on. Although these are
returns to roots (not gari) production, the economic price of roots depends on the import
parity price of tapioca and the assumed processing technology. The more efﬁcient
processing is assumed to bid up the price of the root, as more processed product
(represented by tapioca) can be obtained from each kilogram of roots.

As the results from table 3-3 indicate, cassava/maize systems in Nigeria have
positive net social proﬁts (N SP) under each type of technology combination except for
the “Impman” technology combination. The net social proﬁt refers to the difference,
valued in border and shadow prices, between the gross value of output and the total costs
of all inputs (traded and nontraded intermediary and primary inputs). This implies that,
from society’s point of view, it pays to expand cassava/maize systems only under three
technology combinations: “Impmech”, “Locmech” and “Locman”. However, the systems
under the “Impmech” technology combination are the most efﬁcient use of national
resources. They generate signiﬁcantly higher NSPs at both regional output markets
(6,378 nairas in Abeokuta and 15,055 nairas in Onitsha). A more efﬁcient use of
resources means that one can produce more from what one has and attain a higher level
of welfare

It should be noted that the results from table 3-3 are calculated using the weighted
average of peak-season and off-peak season wage rate across cassava production zones.
The off-peak season rate is half of the peak-season rate.

Overall, the rankings of technology combinations in order of decreasing

proﬁtability are as follows: “Impmech”, “Locmech”, “Locman” and “Impman”. This

86

difference in the ranking order can be explained by the average processing cost used in
the estimation of the import parity prices (tables A3-7 and A3-8 in appendix 3).

. Measures of NSP, like DRC, may give an idea of the comparative advantage in
the agricultural commodity system. Thus NSP measures are very informative for
decision-makers and allocators of research ﬁrnds, if the technical changes they might
introduce would attempt to break labor or other constraints in cassava/maize systems.

It should be noted that all technology combinations (except “impman” at the
Abeokuta market) are more proﬁtable ﬁnancially than they are socially. That is, there are
net transfers to farmers (see tables A3-1, A3-2 and A3-10 through A3-16 in appendix 3).
The subsequent PAM analysis will help illustrate the sources of these transfers.
3.3.3.Policy Matrix Analysis

By completing a PAM for a production system, one can simultaneously determine
the economic efﬁciency of the system, the degree of distortions on the input loutput
markets, and the extent to which resources are transferred among agents (Yao, 1997).
First, the PAM was constructed using the information on costs and returns obtained from
the ﬁnancial and economic analyses. Second, the extent of policy-induced transfers was
computed. Third, six PAM policy-parameters were derived for policy analysis. They are:
the Domestic Resource Cost (DRC), the Nominal Protection Coefficient on Tradable
Output (NPCO), the Nominal Protection Coefﬁcient on Tradable Input (NPCI), the
Eﬁ‘ective Protection Coefﬁcient (EPC), the Proﬁtability Coefﬁcient (PC), and the

Subsidy to Producers (SP)1.

 

' DRC= domestic factors in social prices/ (revenues in social prices - tradable inputs in social prices), NPCO =
revenues in private prices / revenues in social prices, NPCI= tradable inputs in private prices! tradable inputs in social
prices, EPC= (revenues in private prices —tradable inputs in private pricesy (revenues in social prices —tradable
inputs in social prices), PC= private proﬁts/ social proﬁts, SP= (private proﬁts- social proﬁts)/ revenues in
social prices.

87

3.3.3.1.Baseline Results

The PAM of cassava/maize production systems under each technology
combination are presented in table A3-1 7 of Appendix 3. The policy-induced transfers (in
the output and input markets) are summarized in table 3-4 below.

Table 3-4: Summary of the Net Effects (in nairas) of Policy-Induced Transfers
For Commercial Cassava/Maize Systems in Nigeria: 1989/1991.

 

 

Markets/Technology Output Tradable Domestic Net Policy
Combinations Transfers Inputs Factors Transfers
Transfers Transfers
Abeokuta
Impmech 2614 -500 -40 3154
Locmech 2630 -3 55 -28 3013
Locman 4121 -355 -28 4505
Impman 10282 -500 -40 10822
Onitsha
Impmech -6362 -470 -38 -5855
Locmech -23 67 -340 -27 -2000
Locman -518 -340 -27 -151
Impman 3 888 -500 -3 8 43 96

 

Source: table A3-17 in Appendix 3.

Results from table 3-4 show the following: ﬁrst, tradable inputs and domestic
factors transfers are negative everywhere, suggesting that, through an overvalued
exchange rate, the government provided some subsidies on all sales of inputs, whether
they were imported or supplied domestically. Second, output transfers are positive under
all the technology combinations when outputs are sold in Abeokuta. On the other hand,
outputs transfers for the Onitsha market are all negative except for the “Impman”
technology combination.

This is the result of farm-gate ﬁnancial prices (0.57 nairas) for cassava root

departing from the estimated import parity prices under each technology (tables A3-7 and

88

A3-8 in the appendix) depending on whether Abeokuta or Onitsha is used as the point of
sale.

It should be emphasized that these differentials are relatively small. With this in
mind, here are some plausible explanations of why market (ﬁnancial) prices and
economic prices (import parity prices) did not equal in both markets. The divergences
between these two prices could be due to a combination of the effect of the ban on cereals
import and the effect of the overvaluation of the naira. The indirect effect of the ban on
cereals import will be an increase in the ﬁnancial price of cassava root relative to the
economic price in the two markets (Abekuta and Onitsha). On the other hand, the naira
overvaluation will have the effect of lowering the ﬁnancial price of tradables such as
roots and transport in both markets.

However, the magnitude of the reduction in prices will be large in Onitsha and
small in Abeokuta because the share of transport costs in the import parity price is
relatively large for Onitsha (distant from the port city) and relatively small for Abeokuta
(close to the port city). Transportation costs thus provide a natural protection to domestic
producers who supply markets located far from the import point.

Thus, the net effect is as follows: 1) in Onitsha: an increase in the ﬁnancial price
of roots due to the import tariff and a relatively large decrease in the ﬁnancial price of
roots due to the currency overvaluation (via its impact on tradable goods such as cassava
and transport costs); and 2) in Abeokuta: an increase in the ﬁnancial price of roots due to
the import tariff and a relatively small decrease in the ﬁnancial price of roots due to the

currency overvaluation.

89

This result indicates that: 1) cassava/maize farmers selling their product in
Abeokuta enjoyed a subsidy; and 2) cassava/maize systems around the Onitsha market,
except for systems under “Impman” technology combination, suffered a tax. Third, while
net policy transfers are positive at the Abeokuta market, they are negative at the Onitsha
market except for systems under the “Impman” combination. This suggests that when
outputs and inputs were valued at their social (efﬁciency) prices, the effect of government
price policy was: 1) some support to cassava/maize systems under each technology
combination at the Abeokuta market. That is, the actual policy was a trade-restrictive
policy that had an effect equivalent to that of an import tariff of of 11 to 64 percent as
indicated by NPCO values in table 3-5. As mentioned earlier, the observed price for roots
is higher than its shadow prices under different technology combinations when Abeokuta
is the regional market. This difference in prices serves as an implicit tariff to reallocate
resources in the economy. That is, consumers reduce their consumption of the
commodity, production expands in response to the higher domestic price, consumers
transfer parts of their surplus to producers; and 2) some tax on systems at the Onitsha
market, except for systems under “Impman” combination. It is worth noting that the
largest tax on producers occurs under the “Impmech” combination. In other words, this
reﬂects the impact of the overvalued exchange rate, which taxes farmers in proportion to
what they sell. Comparisons between commodity systems under alternative technologies
are also possible through policy-impact ratios, which cancel all units of measure. These

ratios are presented in the table 3-5 below.

90

 

Table 3—5: Ratio Indicators for Commercial Cassava/Maize Production Systems
Under alternative production and processing combinations and by
Distance in Nigeria, 1989-1991.

 

 

[Was/Tech. Comb. DRC NPCO NPCI EPC PC SP
Abeokuta
Impmech 0.71 1.11 0.77 1.14 1.49 0.13
Locmech 0.77 1.14 0.77 1.17 1.76 0.16
Locman 0.84 1.24 0.77 1.28 2.81 0.26
Impman 1.09 1.64 0.77 1.77 -7.39 0.67
Onitsha
Impmech 0.50 0.80 0.77 0.80 0.61 -0.81
Locmech 0.65 0.90 0.77 0.91 0.74 -0.09
Locman 0.71 0.98 0.77 0.99 0.97 -0.01
1W W 1 9‘ 11.29—

 

 

 

Source: PAM Model constructed by the author
Note: DRC= Domestic Resource Cost, NPCO= Nominal Protection Coefﬁcient on
Tradable Output, NPCI= Nominal Protection Coefﬁcient on Tradable Input,
EPC= Effective Protection Coefﬁcient, PC= Proﬁtability Coefﬁcient and SP=
Subsidy to Producers
The domestic resource cost ratio (DRC) assesses social returns to domestic
factors, and is the social cost of domestic resources required to produce a unit of value
added to tradable goods and services. The DRC ratio indicates the efﬁciency of a
domestic production as an export or as an import substitute. The computed values for the
DRC ratios are consistent with the results of the net social proﬁt (N SP) analysis. Even
though cassava/maize production systems under the technology combinations
“Impmech”, “Locmech” and “Locman” all have a domestic cost ratio (DRC) less than
unity, systems under “Impmech” have a clear comparative advantage over those under the
other two technology combinations.
The results discussed above are based on output prices in speciﬁc markets;
however, shadow prices vary (ﬁgures A3-1 and A3-2 in Appendix 3), depending on the

point of sale. As ﬁgures 3-1 and 3-2 below demonstrate, the corresponding DRC ratios

vary also over space. These ﬁgures indicate the following: 1) if the regional market is

91

 

Abeokuta, cassava/maize systems under technology combinations “Impmech”,
“Locmech”, “Locman” and “Impman” are not competitive beyond 220 kilometers, 176
kilometers, 174 kilometers and 112 kilometers respectively, from Abeokuta; 2) if the
output market is Onitsha, cassava/maize systems under technology combinations
“Impmech”, “Locmech”, “Locman” and “Impman” are not competitive beyond 525
kilometers, 476 kilometers, 425 kilometers and 300 kilometers respectively, from
Onitsha. These results imply that for cassava systems around Abeokuta, only local

expansion may be socially proﬁtable for sale in Abeokuta.

Figure 3-1: DRC Ratios Over Space for Commercial Cassava Root
Production Systems under Alternative Technology Combinations -
Absolute is the Regional Output Maker, Nigeria:198911991

 

1.9

1.7

 

 

1.5

 

.5
(A)

 

 

DRC Ratios

 

0.9

 

 

0.7 «

 

 

 

 

0.5 "—r T T T T T I
0 50 100 150 200 250 300 350

momma Mkt- Village
F—I—DRCIocman —¢—DRCIom_e:c - 0- DRCimpman —-o—DRCimpmecl

 

92

 

Figure 3-2: DRC Ratios Over Space for Commercial Cassava Root
Production Systems Under Alternative Production-Prooﬁng
Technology Combinations-Onitsha is the lhgional Output
Wm: 1939/1991 ,

 

1}—

 

 

 

 

 

 

 

 

DRC Ratios

 

 

 

 

 

 

 

o I I V I I I ﬂ I ﬂ I I I T
o 50 100 150 200 250 300 350 400 450 500 550 600 650
lh'stance Output Mkt- Village

 

-°—DRClocman ~--A--DRClcmec “NODRCimpmm +DRCimpmec

 

 

 

The nominal protection coefﬁcient in the output/input markets (NPCO/NPCI) is a
summary measure of incentives provided by government policy on outputs or inputs
respectively. The computed NPCOs indicate that, in general, commercial farmers
operating in the Abeokuta market have enjoyed a private price 12 to 40 percent higher
than they would have received without government protection policy. On the other hand,
at the Onitsha market, the NPCOs are less than unity, except for cassava/maize systems
under the technology combination “Impman”, implying that government policy is to
some extent discriminating against farmers operating in that market. Computed NPCIs
are lower than unity everywhere, suggesting that government policy has permitted input

costs to be lower than they would be under open trade.

93

 

The effective protection coefficient (EPC) best measures the combined effects
discussed earlier. The computed EPCs support the conclusions of the NPCO/NPCI
analysis above. The other ratios shown in table 3-5 are the proﬁtability coefﬁcient (PC)
ratio and the subsidy to producers (SP) ratio. The PC ratio shows the extent to which net
transfers have caused private proﬁts to exceed social proﬁts, while the SP ratio shows the
level of transfers ﬁ'om divergences as a proportion of the production system’s social
revenues (Monke and Pearson, 1989). The computed values of these two ratios lie
between -7.39 and 2.81 for the PC ratios at both markets, whereas the computed values
of SP ratios lie between 0.13 and 0.67 at the Abeokuta market and between -0.81 and
0.20 at the Onitsha market. These results indicate that overall, policy transfers have
resulted in private proﬁt exceeding social proﬁts by 1.49 to 2.81 times for technology
combinations “Impmech”, “Locmech”, “Locman” in Abeokuta.
3.3.3.2. Sensitivity Analysis

The sensitivity analysis carried out in this sub-section aims to test the robustness
of the results under the “baseline” scenario. The simulation considers the effects of
change in the shadow exchange rate.

Shadow Exchange Rates. In December 1985, the Nigerian government banned the
importation of various foods such as wheat, rice and maize. At the time, the government
put a ban on the export of certain foods, essentially yarn and cassava products, which
have alternative markets in neighboring West African countries (Nweke, 1999). The
overall impact of such widespread protection is to create an overvalued exchange rate. In
fact, in the late 1990’s, the Nigerian government accepted to administer the Nigerian

naira through the auction mechanism. From 1989 to 1991, the shadow exchange rate was

94

22 nairas for one US dollar. Since 1991, the shadow exchange rate has declined by 286
percent. This led to its devaluation in 1995 when one US dollar was worth 85 nairas.

The sensitivity analysis undertaken here is designed to examine the impact of the
appreciation of the real exchange rate on net social proﬁtabilities (N SP) and selected
policy parameters (DRC and EPC) ratios. The import parity prices were recalculated
using the post-devaluation exchange rate of 85 nairas to one US dollar, assumed to
approximate the new equilibrium exchange rate. Furthermore, COSCA data collected in
1995 indicate that market prices changed with devaluation. The market price of roots rose
to 1.72 nairas from 0.57 nairas in 1991. In addition, rural wages increased from 21 nairas
to 200 nairas. It should be noted that these changes reﬂect overall inﬂation, which in turn
affects the exchange rate. The post-devaluation market prices were used in carrying this
analysis. Tables 3-6 and 3-7 present the results.

Table 3—6: Effects of a 286 % Change in the Shadow Exchange Rate on the Net

 

 

Social Profit (NSP).

Market/ Technologies Baseline Simulation Proﬁt Elasticity

Abeokuta Impmech . 63 78 43306 2.02
Locmech 3978 14017 0.88
Locman 2486 1568 NA
Impman -1289 943 NA

Onitsha Impmech 15055 4981 1 0.80
Locmech 7602 18329 0.49
Locman 5753 1670 NA
Impman 4805 -1399 NA

 

 

Note: The proﬁt elasticity is computed as follows: percentage changes in NSP/percentage
change in exchange rate. It should be interpreted in absolute terms.

95

Table 3-7: Effects of a 286 % Change in the Shadow Exchange Rate on Selected
Policy Parameters

 

 

 

Mitts/Techno. Policy Impact Parameters
Combinations
DRC Ratio EPC Ratio
Abeokuta Baseline % Simulation Baseline % Simulation
Change Change
Impmech 0.71 -13 0.62 1.14 -59 0.47
Locmech 0.77 6 0.82 1.17 -51 0.57
Locman 0.84 17 0.98 1.28 -50 0.64
Impman 1.09 -10 0.98 1.77 -38 1.09
Onitsha
Impmech 0.50 16 0.58 1.80 -76 0.43
Locmech 0.65 18 0.77 0.91 -45 0.50
Locman 0.71 37 0.97 0.99 -36 0.63
Impman 0.76 34 1.02 1.22 -70 0.36

 

 

The results from table 3-6 show that the 286 percent decline in the shadow
exchange rate would increase substantially the social proﬁtabilities especially of
technology combinations “Impmech” and “Locmech” at the Abeokuta market. Clearly,
increased tradable input costs at that market do little to decrease the beneﬁts from the
decline in the shadow exchange rate because such costs are a small proportion of total
inputs costs. On the other hand, the decline in the equilibrium exchange rate has caused
cassava/maize systems under “Impman” to become economically unproﬁtable at the
Onitsha market. This is due to the fact that these are returns to roots (not gari)
production, but the economic price of roots depends on the import parity price of tapioca
and the assumed processing technology. The more efﬁcient processing technology (the
mechanized method) is assumed to bid up the price of the root, as more processed

product (represented by tapioca) can be obtained from each kilogram of roots.

96

 

Results from table 3—7 indicate the following: First, at the Abeokuta market, the
effective protection coefﬁcients (EPC) for all technology combinations except “Impman”
have become less than unity. This suggests that with the appreciation of the real exchange
rate, farmers are receiving negative protection. That is, they could have received higher
return if they faced border prices instead of domestic prices on both outputs and inputs.
Second, the naira devaluation has not altered the ranking (in terms of comparative
advantage) of the technology combinations at the Abeokuta market; however, it has
caused the “Impman” technology to lose its comparative advantage at the Onitsha market.

However, simulation should be interpreted as short-term changes in incentives.

3.4 Conclusions

The methodology used in this study is the policy analysis matrix (PAM). The
purpose of the study was to evaluate the social proﬁtability of cassava/maize
systems, under alternative production and processing technology combinations, in
Nigeria. The baseline results show that proﬁtabilities of systems under “Impmech”
technology exceed those of systems under other alternative technologies, namely
“Locmech”, “Locman” and “Impman”.

The PAM analysis is a static partial equilibrium analysis (Nelson and
Paggabean. 1991); therefore, a sensitivity analysis carried out. The simulation results
indicate the following: a 286 percent decline in the shadow exchange rate increases
signiﬁcantly the proﬁtabilities of cassava/maize systems under the technology
combinations “Impmech”, and “Locmech”, suggesting that the large growth in

proﬁtability should encourage use of improved inputs especially at the post farm level.

97

The ﬁnancial incentives (at farm-level and post-farm level) for cassava/maize
systems under the “Impmech” technology combination suggest that one reason so many
farmers have adopted the new technology package is because it is proﬁtable (return to
family labor for Impmech is almost triple of that of Impman). COSCA data indicate that
in Nigeria, most farmers are not only growing the IITA variety but also using mechanical
grating at the processing stage. The results also clearly show the higher economic proﬁts
generated by the new IITA cassava variety in combination with mechanical processing

technology.

98

REFERENCES

Adesina, AA. and Coulibaly O. N., Policy and Competitiveness of agroforestry-based
technologies for maize production in Cameroon: An application of policy analysis
matrix, Agricultural Economics, 19: 1-1 13,1998

Byerlee Derek and Heisey Paul. 1993. “Strategies for Technical Change in Small-Farm
Agriculture, with Particular Reference to Sub-Saharan Aﬁica” in Russell Nathan
C. and Christopher R.Dowswell, Policy Options For Agricultural Development in
Sub-Saharan Africa, CASIN/SAA/GLOBAL 2000.

IMF, 1989-1992. Various issues.
Jones, W.O., Maniac in Aﬁica, Stanford University Press, Stanford, 1959.

Monke, EA. and 8. Pearson. 1989. The Policy Analysis Matrix for Agricultural
Development. Baltimore: John Hopkins University Press.

Myint, H., (1979), Exports and Economic Development of Less Developed Countries in
Economic Growth and Resources, vol. 4, edited by Irma Adelman.

Nwajiuba, C.U., Socioeconomic Impact of Cassava Postharvest Technologies on
Smallholders in Southeastern Nigeria, Farming Systems and Resource Economics
in the Tropics, Vol 20, 1995.

Nelson, G C and Panggabean, M (1991), The costs of Indonesian sugar policy: a policy
analysis matrix approach, American Journal of Agricultural Economics, 73 (3) pp
703-712.

Nigerian Port Authority Statistical Reports, 1989- 1992, Various issues.

Nweke, F 1, Processing Potential for Cassava Production Growth in Aﬁica, Working
Paper No. 11, The Collaborative Study of Cassava in Africa, 1994.

Nweke, Felix 1., BO. Ugwu, C.L.A. Asadu, and P. Ay., Production costs
in the yam-based cropping systems of southeastern Nigeria, RCMP Research
Monograph No. 6., Resource and Crop Management Program, International
Institute of Tropical Agriculture (IITA), Ibadan, 1991.

Nweke, Felix 1., BO Ugwu, and A.G.O. Dixon, Spread and performance
of improved cassava varieties in Nigeria. C OSCA Working Paper No. 15 ., The
Collaborative Study of Cassava in Africa, IITA, Ibadan, Nigeria. 1996.
Stryker J. Dirck, “ Trade, Exchange Rate, and Agricultural Pricing Policies in
Ghana,” World Bank Comparative Studies, 1990.

99

Yao, Shujie, 1997. “Rice Production in Thailand Seen Through a Policy Analysis
Matrix”. Food Policy, 22(6):547-560.

100

APPENDIX 3

101

Table A3-l: Estimated Average Financial Budget for Cassava/Maize Systems
For Improved landraces in Niggria: 1989/1991

 

 

Met Items
1. INPUT USE Family Hired
Family/Hired Labor Use (person-days )
0 Land Clearing 28 22
o Seedbed Preparation 23 21
o Weeding 23 18
o Planting
Cassava 19 16
Maize 15 O
O Harvesting
Cassava 41 31
Maize 23 0
Total
2. OUTPUTS 19210
Average Root Yield (kg/ha) 9614
Average Maize Yield (ears/ha)l 0.57
Market Price of Root (nairas/kg)2 1.5
Market Price of Green Maize (nairas/ears)3 14421
Revenues from Green Maize (nairas/ha) 10950
Revenues from Cassava Roots (nairas/ha) 25371
Gross Revenues (nairas/ha)
3. COSTS 0
Fixed Costs (nairas/ha)4
Operating costs (nairas/ha) 2268
Hired Labor 1790
Transportation ﬁeld-to-home (nairas) 325
Interest on Working Capital (8%) 4333
Total Operating Costs (nairas/ha) 3612
Family Labor (valued @ hired labor wage rate) 8362
Opportunity Cost of land (nairas)
4. PERFORMANCE MEASURES
Gross Margin (nairas/ha) 20988
Net Retums to family Labor (nairas/ha) 12626
Net Returns per day of Family Labor (nairas/day) 73
Total System Production Costs (nairas/ha) 16357
Net Enterprise Proﬁts (nairas/ha) 9014

 

Source: COSCA survey data

 

‘ Estimated using the “Ear Weight Method” discussed in the appendix of chapter 2. In West Africa, maize.
which has a short cycle, is harvested before cassava establishes. Hence competition between maize and
cassava is minimized, while sole plant density is maintained for both crops. ( COSCA Working Paper
No.10, page 84)

2 Weighted average farmgate price based on COSCA data

3 Farmgate price based on secondary source of information (personal communication with IITA)

‘ Farmers did not purchase planting materials of food crops; they produced their own: for cassava, only one
ﬁfth of the stems from previous harvest are retained for replanting and for maize, only 2 to 3 percent of
harvest are saved for seed. Therefore, the opportunity cost of planting materials, which is relatively
insigniﬁcant. is not counted.

102

Table A3—2: Estimated Average Financial Budget for Cassava/Maize Systems
For Local Landraces, N igria: 1989/1991

 

 

 

Budget Items
1. INPUT USE Family Hired
Family/Hired Labor Use (person-days)
0 Land Clearing 28 22
O Seedbed Preparation 23 21
o Weeding 23 18
o Planting
Cassava 19 16
Maize 15 0
o Harvesting
Cassava 30 22
Total J 99
2. OUTPUTS 11215
Average Root Yield (kg/ha) 9614
Average Maize Yield (ears/ha)l 0.57
Market Price of Root (nairas/kg)2 1.5
Market Price of Green Maize (nairas/ears)3 14421
Revenues from Green Maize (nairas/ha) 6393
Revenues from Cassava Roots (nairas/ha) 20314
Gross Revenues (nairas/ha)
3. COSTS 0
Fixed Costs (nairas/ha)“
Operating costs (nairas/ha) 2079
Hier Labor 1271
Transportation (nairas) 268
Interest on Working Capital (8%) 3613
Total Operating Costs (nairas/ha) 3381
Family Labor (valued @ hired labor wage rate) 8362
Opportunity Cost of land (nairas)
4. PERFORMANCE MEASURES
Gross Margin (nairas/ha) 17196
Net Returns to family Labor (nairas/ha) 8834
Net Returns per day of Family Labor (nairas/day) 55
Total System Production Costs (nairas/ha) 15361
Net Enterprise Proﬁts (nairas/ha) 5453

 

Source: COSCA survey data

 

‘ Estimated using the “Ear Weight Method” discussed in the appendix 2 of chapter 2. In West Africa,
maize. which has a short cycle, is harvested before cassava establishes. Hence competition between maize
and cassava is minimized, while sole plant density is maintained for both crops. (COSCA Working Paper
No.10. page 84)

2 Weighted average farmgate price based on COSCA data

3 Farmgate price based on secondary source of information (personal communication with IITA)

4 Farmers did not purchase planting materials of food crops; they produced their own: for cassava, only one
fifth of the stems from previous harvest are retained for replanting and for maize, only 2 to 3 percent of
harvest is used for seed. Therefore. the opportunity cost of planting materials, which is relatively
insigniﬁcant, is not counted.

103

 

Table A3-3: Estimated Average Financial Budget per hectare for Gari Production
under Technology Combination “IMPMECH’”, Nigeria, 1989/1991,
assumin 80% 0 root production goes into ganjroduction

 

 

 

 

W
1. INPUT USE Family Hired
F amily/Hired Labor Use (person-days)2 70 12
Raw Material (kgs of roots)3 15368
2. OUTPUTS
Transformation Rate 0.31
Kilograrns of Processed Output per ha 4764
Village Market Price of Processed Output (nairas/kg)4 3.14
Gross Revenues (nairas/ha) 14959
3. COSTS
Fixed Costs (nairas/ha)S 0
Operating costs (nairas/ha)
Hired Labor and grating fees 450
Raw material6 8760
Bagging Materials 398
Firewood 986
Transportation 7 1119
Interest on Working Capital (8%) 937
Total Operating Costs (nairas/ha) ‘ 12650
Family Labor (valued @ hired labor wage rate) (nairas/ha) 1470
4. PERFORMANCE MEASURES
Gross Margin (nairas/ha) 2310
Net Returns to family Labor (nairas/ha) 2310
Net Returns per day of Family Labor (nairas/day) 33
Total production Costs (nairas/ha) 14120
Net Enterprise Proﬁts (nairas/ha) 840
Production Costs per Kg of gari (nairas/kg) 2.96

 

Source: COSCA data

 

' Improved variety and mechanical processing
2 This item includes labor for manual activities (washing, cleaning and roasting) as well as labor for
mechanical processing operations such as grating.
:This represents 80% of the average root yield per hectare (see page 128 in COSCA Working Paper No.20)
:Weighted average village market price estimated from COSCA data
Inputs used 1n the production process are external to the household. For example, cassava grating
machines were available to individual farmers on custom basis ( COSCA Working Paper No.14, page 15)
:13me at its opportunity cost, which is the weighted average farmgate price computed from the COSCA
ta
This item includes home-to-market transportation costs only

104

Table A3—4: Estimated Average Financial Budget per hectare for Gari Production
under Technology Combination “LOCMECH”‘, Nigeria, 1989/1991,

_ assuming 80% 0: root production goes into gari production.

 

 

 

Wm:
1. INPUT USE Family Hired
F amily/Hired Labor Use (person-days)2 55 7
Raw Material (kgs of roots)3 8972
2. OUTPUTS
Transformation Rate 0.31
Kilograms of Processed Output per ha 2781
Village Market Price of Processed Output (nairas/kg)4 3.14
Gross Revenues (nairas/ha) 8733
3. COSTS
Fixed Costs (nairas/ha)5 0
Operating costs (nairas/ha)
Hired Labor erson-days and grating fees) 242
Raw material 51 14
Bagging Materials 259
Firewood 676
Transportation7 752
Interest on Working Capital (8%) 563
Total Operating Costs (nairas/ha) 7606
Family Labor (valued @ hired labor wage rate) (nairas/ha) 1155
4. PERFORMANCE MEASURES
Gross Margin (nairas/ha) 1127
Net Returns to family Labor (nairas/ha) 112720
Net Returns per day of Family Labor (nairas/day) 20
Total production Costs (nairas/ha) 8761
Net Enterprise Proﬁts (nairas/ha) -28
Production Costs per Kg of gari (nairas/kg) 3.15

 

Source: COSCA data

 

‘ Local variety and mechanical processing

2 This item includes labor for manual activities (washing, cleaning and roasting) as well as fees for

mechanical processing operations such as grating.

3 This represents 80% of the average root yield per hectare (see page 128 in COSCA Working Paper No.20)

4 Weighted average village market price estimated from COSCA data

5 Inputs used in the production process are external to the household. For example, cassava grating
machines were available to individual farmers on custom basis (COSCA Working Paper No.14, page 15)
6 Valued at its opportunity cost, which is the weighted average farmgate price computed from the COSCA

data.
7 This item includes home-to—market transportation costs only.

105

Table A3-5: Estimated Average Financial Budget per hectare for Gari Production
under Technology Combination “LOCMAN’”, Nigeria, 1989/1991,
assuming 80% root production goes into gari production.

W

 

1. INPUT USE Family Hired
F amily/Hired Labor Use (person-days)2 60 17
Raw Material (kgs of roots)3 8972
2. OUTPUTS
Transformation Rate 0.31
Kilograms of Processed Output per ha 2781
Village Market Price of Processed Output (nairas/kg)4 3.14
Gross Revenues (nairas/ha) 8733
3. COSTS
Fixed Costs (nairas/ha)5 0
Operating costs (nairas/ha)
Hired Labor (person-days) 357
Raw material 5114
Bagging Materials 259
Firewood 676
Transportation7 752
Interest on Working Capital (8%) 573
Total Operating Costs (nairas/ha) 7731
Family Labor (valued @ hired labor wage rate) (nairas/ha) 1260
4.PERFORMANCE MEASURES
Gross Margin (nairas/ha) 1003
Net Returns to family Labor (nairas/ha) 1003
Net Returns per day of Family Labor (nairas/day) 17
Total production Costs (nairas/ha) 8891
Net Enterprise Preﬁts (nairas/ha) -257
Production Costs per Kg of gari (nairas/kg) 3.23

 

Source: COSCA data

 

1 Local variety and manual Processing

2 This item includes labor for washing, cleaning, grating, pressing sieving and roasting.

3 This represents 80% of the average root yield per hectare (see page 128 in COSCA Working Paper No.20)
4 Weighted average village market price estimated from COSCA data

5 No mechanical equipment was used in any processing activity. Grating was done manually ( COSCA
Working Paper No.14, page 15)

6 Valued at its opportunity cost, which is the weighted average farmgate, price computed from the COSCA
data.

7 This item includes home-to-market transportation costs only.

106

 

TabIeA3-6:

Estimated Average Financial Budget per hectare for Gari Production

under Technology Combination “IMPMAN’”, Nigeria, 1989/1991,

assuming 80% 0: root production goes into gari production.

 

Budget Items
1. INPUT USE Family Hired
F amily/Hired Labor Use (person-days)2 85 75
Raw Material (kgs of roots)3 15368
2. OUTPUTS
Transformation Rate 0.31
Kilograms of Processed Output per ha 4764
Village Market Price of Processed Output (nairas/kg)4 3.14
Gross Revenues (nairas/ha) 14959
3. COSTS
Fixed Costs (nairas/ha)5 0
Operating costs (nairas/ha)
Hired Labor (person-days) . 1575
Raw material 8760
Bagging Materials 398
Firewood 986
Transportation7 1 1 19
Interest on Working Capital (8%) 1027
Total Operating Costs (nairas/ha) 13865
Family Labor (valued @ hired labor wage rate) (nairas/ha) 1785
4. PERFORMANCE MEASURES
Gross Margin (nairas/ha) 1094
Net Returns to family Labor (nairas/ha) 1094
Net Returns per day of Family Labor (nairas/day) 13
Total production Costs (nairas/ha) 15650
Net Enterprise Proﬁts (nairas/ha) -691
Production Costs per Kg of gari (nairas/kg) 3.28

SEce: COSCA data

 

' Improved variety and manual processing

2 This item includes labor for washing, cleaning, grating, pressing, sieving and roasting.

3 This represents 80% of the average root yield per hectare (see page 128 in COSCA Working Paper No.20)
" Weighted average village market price estimated from COSCA data

5 No mechanical equipment was used in any processing activity. Grating was done manually (COSCA
Working Paper No. 14, pageIS).

6 Valued at its opportunity cost, which is the weighted average farmgate price computed from the COSCA
data.

7 This item includes ﬁeld-to-home and home-to-market transportation costs

107

Table A3-7: Economic Import Parity Price of Cassava Root, by Alternative
Technology Combinations. For Sale in the Regional Output Market of
Onitsha, Nigeria: 1989/1991.

 

 

 

Items
Onitsha
Inqimech Locmech Locman Impman
1. World Price ( FOB-$US/mt tapioca) 221 221 221 221
2. Freight and insurance ($US/mt tapioca) 48 48 48 48
3. CIF, port in Lagos ( $US/mt tapioca) (1+2) 269 269 269 269
4. Shadow Exchange rate ( nairas / $US) 22 22 22 22
5. CIF price at the port in Lagos (3*4) 5950 5950 5950 5950
6. Domestic costs (nairas/mt tapioca)
a. Port charges (nairas/mt tapioca) 95 95 95 95
b.Transit and Transport (nairas/mt tapioca) 206 206 206 206
c. Storage and Handling (nairas/mt tapioca) 203 203 203 203
7.Lagos gate price (5+ 6a.c)(nairas/mt
tapioca) 6454 6454 6454 6454
8. Importer marketing margin (%) 5% 5% 5% 5%
9. Wholesale price in Lagos (7* (1+ 8)) 6777 6777 6777 6777
10. Lagos to Regional Market Center
a Distance (km) 420 420 420 420
b. Transport cost (nairas/mt tapioca) 1512 1512 1512 1512
c. Handling (nairas/mt tapioca) 114 114 114 114
l 1. Regional Market Center (Reference Price)
Farmgate p1ice(nairas/mt tapioca) (9 + 10a..c) 8403 8403 8403 8403
12. Wholesale marketing margin (%) 5% 5% 5% 5%
13. Wholesale price in Regional Market
(nairas/mt tapioca) (11* (1+12)) 8823 8823 8823 8823
l4.Regional Market Center to Village
a. Distance (kms) _ 97 97 97 97
b. Transport and Handling cost (nairas/mt 497 497 497 497
tapioca)
15.Village gate price (nairas/mt tapioca)13- 8326 8326 8326 8326
14b) .
16. Semi-wholesale marketing margin (%) 5% 5% 5% 5%
17.Village Level Semi-wholesale price((1-16
)*15)/1000 8 8 8 8
18.Transformation rate (kg tap./ kg of root) .50 .50 .50 .50
19. Processing cost (nairas/kg of root) 3.09 3.21 3.36 3.60
20. Import Parity Price in the Village (nairas
lkg ofroot) (17*18) -19 0.89 0.77 0.61 0.38

 

Source: COSCA data, UNCTAD’s Review of Maritime Transport 1989-1992, Nigerian
Port Authority Statistical Reports (1989-1992), UN Economic and Social Commission
For Asia and the Paciﬁc, Reports of 1989 through 1991.

108

 

Table A3-8: Economic Import Parity Price of Cassava Root, by Alternative
Technology Combinations. For Sale in the Regional Output Market of
Abeokuta, Ngeria: 1989/1991.

 

 

 

 

Items Regional Capt Market
Abeokuta
Impmech Locmech Locman Impman

1. World Price (FOB-$US/mt tapioca) 221 221 221 221

2. Freight and insurance ($US/mt tapioca) 48 48 48 48

3. CIF, port in Lagos ( $US/mt tapioca) (1+2) 269 269 269 269

4. Shadow Exchange rate ( nairas / $US) 22 22 22 22
5. CIF price at the port in Lagos ( nairas/mt

tapioca) (3 *4) 5950 5950 5950 5950

6. Domestic costs (nairas/mt tapioca)

a. Port charges (nairas/mt tapioca) 95 95 95 95
b. Transit and Transport (nairas/mt tapioca) 206 206 206 206
c. Storage and Handling (nairas/mt tapioca) 203 203 203 203
7. Lagos gate price (5+ 6a. . .c ) (nairas/mt

tapioca) 6454 6454 6454 6454
8. Importer marketing margin (%) 5% 5% 5% 5%

9. Wholesale price in Lagos (7* (1+ 8)) 6777 6777 6777 6777
10. Lagos to Regional Market Center ‘

a Distance (km) 80 80 80 80
b. Transport cost (nairas/mt tapioca) 288 288 288 288
c. Handling (nairas/mt tapioca) 114 114 114 114

11. Regional Market Center (Reference Price)

Farmgate price (nairas/mt tapioca) (9 +10a..c) 7179 7179 7179 7179

12. Wholesale marketing margin (%) 5% 5% 5% 5%
13. Wholesale price in Regional Market
(nairas/mt tapioca) (11* (1+12)) 7538 7538 7538 7538
14. Regional Market Center to Village

a. Distance (kms) 34 34 34 34
b. Transport and Handling cost (nairas/mt 176 176 176 176
tapioca)

15. Village gate price (nairas/mt tapioca) 7362 7362 7362 7362
(13-14b)

16. Semi-wholesale marketing margin (%) 5% 5% 5% 5%
17. Village Level Semi-wholesale price
(1-16 )*15)/1000 6.99 6.99 6.99 6.99
18.Transformation rate (kg of tap./ kg of root) 0.50 0.50 0.50 0.50
19. Processing cost (nairas/kg of root) 3.05 3.14 3.26 3.41
20. Import Parity Price in the Village (nairas
/kg of root) (17*18) -19 0.45 0.36 0.24 0.08

 

Source: COSCA data, UNCTAD’s Review of Maritime Transport 1989-1992, Nigerian
Port Authority Statistical Reports 1989-1992, UN Economic and Social Commission For
Asia and the Paciﬁc, Reports of 1989 through 1991.

109

Table A3-9: Estimated Financial Budget for Commercial Cassava/Maize Systems
under Technology Combination “IMPMECH”, by Regional Output

Markets, N iggria, 1989/1991

 

 

 

Budget Items Regional 011mm Markets
Abeokuta Onitsha
l. OUTPUTS
Average Root Yield (kg/ha) 21131 20171
Average Green Maize Yield (ears/ha)2 9614 9614
Market Price of root (nairas/kg)3 0.57 0.57
Market Price of Green Maize (nairas/ear)4 1.5 1.5
Revenues from Root (nairas /ha) 12045 11497
Revenues from Green Maize (nairas lha) 14421 1442]
Gross Revenues (nairas /ha) 26466 25918
2. COSTS
Fixed Costs (lha)5 O 0
Operating costs (/ha)
Hired Labor 2373 2205
Transportation (nairas)
Tradable 1666 1 594
Nontardable 417 399
Interest on Working Capital (8%) 356 336
Total Operating Costs (nairas /ha) 4812 4534
Family Labor (@ hired labor wage rate) (nairas lha) 3759 3822
Opportunity Cost of Land (nairas/ha) 8362 8362
3. PERFORMANCE MEASURES
Gross Margin (nairas /ha) 21653 21384
Net Returns to family Labor (nairas /ha) 13291 13022
Net Returns per day of Family Labor (nairas /day) 74 72
Total production Costs (nairas /ha) 16933 16718
Net Enterprise Proﬁts (nairas /ha) 9532 9200

 

Source: COSCA survey data

 

1 Improved variety and mechanical processing

2 Estimated using the “Ear Weight Method” discussed in Appendix 2.

3 Weighted average farmgate price based on COSCA data.

4 Farmgate price based on secondary source of information (personal communication with [IT A).

5Farmers did not purchase planting materials of food crops but produced their own: for cassava, only one
fifth of the stems from previous harvest are retained for replanting and for maize, only 2 to 3% of the
previous harvest is saved for seed. Therefore, the opportunity cost of planting materials, which is relatively
insigniﬁcant, is not counted.

110

Table A3-10: Estimated Economic Budget for Commercial Cassava/Maize Systems
under Technology Combination “IMPMECH”‘, by Regional Output
Markets, Nigeria, 1989/1991

 

 

 

 

Budget Items Regional Output Markets
Abeokuta Onitsha

l. OUTPUTS
Average Root Yield (kg/ha) 21131 20171
Average Green Maize Yield (ears/ha)2 9614 9614
Import Parity Price of root (nairas/kg)3 0.45 0.89
Market Price of Green Maize (nairas/ear)4 1.5 1.5
Revenues from Root (nairas /ha) 8816 17840
Revenues from Green Maize (nairas lha) 14421 14421
Gross Revenues (nairas lha) 23851 32281
2. COSTS
Fixed Costs (/ha)5 0 0
Operating costs (/ha)

Hired Labor6 23 73 2205

Transportation (nairas)
Tradable 2166 2064
Nontardable 41 7 399

Interest on Working Capital (8%) 396 373
Total Operating Costs (nairas /ha) 53 52 5041
Family Labor (@ hired labor wage rate) (nairas /ha) 3759 3822
Opportunity Cost of Land7 (nairas/ha) 8362
3.PERFORMANCE MEASURES
Gross Margin (nairas /ha) 18499 27239
Net Returns to family Labor (nairas /ha) 10137 18877
Net Returns per day of Family Labor (nairas /day) 57 104
Total production Costs (nairas /ha) 17473 17225
Net Social Proﬁts (nairas /ha) 63 78 15055

 

Source: COSCA survey data

 

‘ Improved variety and mechanical processing

2 Estimated using the “Ear Weight Method” discussed in Appendix 2.

3 Estimated Farm Level Import Parity Price of root

4 Farmgate price based on secondary source of information.

5Farmers did not purchase planting materials of food crops but produced their own: for cassava, only one
ﬁfth of the stems from previous harvest are retained for replanting and for maize. only 2 to 3% of the
previous harvest is saved for seed. Therefore, the opportunity cost of planting materials, which is relatively
insigniﬁcant, is not counted.

6 Although rural labor markets in West Africa are complex, it is reasonable to assume that market wages
offer good approximations to shadow wages (Humphreys in Rice in West Africa. p. 80, 1981).

7 Land is very rarely sold or rented. In this budget, the opportunity cost of land is estimated as the net return
to land that farmers would enjoy if they produced green maize only.

111

 

Table A3-l 1: Estimated Financial Budget for Commercial Cassava/Maize Systems
under Technology Combination “LOCMECH”, by Regional Output
Markets, Nigeria, 1989/1991

 

 

 

Budget Items Regional Output Markets
Abeokuta Onitsha
l. OUTPUTS
Average Root Yield (kg/ha) 12337 11776
Average Green Maize Yield (ears/ha)2 9614 9614
Market Price of root (nairas/kg)3 0.57 0.57
Market Price of Green Maize (nairas/ear)4 1.5 1.5
Revenues from Root (nairas lha) 7032 6712
Revenues from Green Maize (nairas lha) 14421 14421
Gross Revenues (nairas /ha) 21453 21133
2. COSTS
Fixed Costs (nairas/ha)5 O 0
Operating costs (nairas/ha)
Hired Labor 1680 1995
Transportation (nairas)
Tradable 1183 1132
Nontradable 296 283
Interest on Working Capital (8%) 253 273
Total Operating Costs (nairas /ha) 3412 3683
Family Labor (@ hired labor wage rate) (nairas /ha) 2688 3486
Opportunity Cost of Land6 (nairas/ha) 8362 8362
3. PERFORMANCE MEASURES
Gross Margin (nairas lha) 18041 17450
Net Returns to family Labor (nairas /ha) 9679 9088
Net Returns per day of Family Labor (nairas /day) 76 55
Total production Costs (nairas /ha) 14462 15531
Net Enterprise Proﬁts (nairas /ha) 6991 5602

 

Source: COSCA survey data

 

' Local variety and mechanical processing

2 Estimated using the “Ear Weight Method” discussed in Appendix 2 of chapter 2.

3 Weighted average farmgate price based on COSCA data.

4 F arrngate price based on secondary source of information.

5 Farmers did not purchase planting materials of food crops but produced their own: for cassava, only one
ﬁfth of the stems from previous harvest are retained for replanting and for maize. only 2 to 3% of the
previous harvest is used for seed. Therefore. the opportunity cost of planting materials, which is relatively
insigniﬁcant, is not counted.

6 Land is very rarely sold or rented. In this budget, the opportunity cost of land is estimated as the net retum
to land that farmers would enjoy if the produce green maize only.

112

Table A3-12: Estimated Economic Budget for Commercial Cassava/Maize Systems
under Technology Combination “LOCMECH”', by Regional Output

Markets, Ni eria, 1989/1991

 

 

 

Budget Items Regional Ouput Markets
Abeokuta Onitsha
l. OUTPUTS
Average Root Yield (kg/ha) 12337 11776
Average Green Maize Yield (ears/ha)2 9614 9614
Market Price of root (nairas/kg)3 0.36 0.77
Market Price of Green Maize (nairas/ear)4 1.5 1.5
Revenues from Root (nairas lha) 4402 9079
Revenues from Green Maize (nairas lha) 14421 14421
Gross Revenues (nairas /ha) 18823 23500
2. COSTS
Fixed Costs (nairas/ha)5 0 0
Operating costs (nairas/ha)
Hired Labor6 1680 1995
Transportation (nairas)
Tradable 1 538 1472
Nontradable 296 283
Interest on Working Capital (8%) 281 300
Total Operating Costs (nairas lha) 3795 4050
Family Labor (hired labor wage rate) (nairas /ha) 2688 3486
Opportunity Cost of Land7 (nairas/ha) 8362 8362
3. PERFORMANCE MEASURES
Gross Margin (nairas lha) 15028 19450
Net Returns to family Labor (nairas /ha) 6666 11088
Net Returns per day of Family Labor (nairas /day) 52 67
Total production Costs (nairas lha) 14845 15898
Net Social Proﬁts (nairas /ha) 3978 7602

 

Source: COSCA survey data

 

‘ Local Variety and Mechanical Processing

2 Estimated using the “Ear Weight Method” in Appendix 2.
3 Estimated Farm Level Import Parity Price of root

4 Farmgate price based on secondary source of information.

5Farmers did not purchase planting materials of food crops but produced their own: for cassava, only one
ﬁfth of the stems from previous harvest are retained for planting and for maize, only 2 to 3% of the
previous harvest is saved for seed. Therefore, the opportunity cost of planting materials, which is relatively

insigniﬁcant, is not counted.

6 Although rural labor markets in West Africa are complex, it is reasonable to assume that market wages
oﬁ'er good approximations to shadow wages (Humphreys in Rice in West Africa, p. 80, 1981).

7 Land is very rarely sold or rented. In this budget, the opportunity cost of land is estimated as the net return
to land that farmers would enjoy if the produce green maize only.

113

Table A3-13: Estimated Financial Budget for Commercial Cassava/Maize Systems
under Technology Combination “LOCMAN’”, by Regional Output
Markets, Nigeria, 1989/1991

 

 

 

Budget Items Regional Ougut Markets
Abeokuta Onitsha
l. OUTPUTS
Average Root Yield (kg/ha) 12337 11776
Average Green Maize Yield (ears/ha)2 9614 9614
Market Price of root (nairas/leg)3 0.57 0.57
Market Price of Green Maize (nairas/ear)4 1.5 1.5
Revenues from Root (nairas /ha) 7032 6712
Revenues from Green Maize (nairas /ha) 14421 14421
Gross Revenues (nairas /ha) 21453 21133
2. COSTS
Fixed Costs (nairas/ha)5 0 0
Operating costs (nairas/ha)
Hired Labor 1680 1995
Transportation (nairas)
Tradable 1 183 1 132
Nontradable 296 283
Interest on Working Capital (8%) 253 273
Total Operating Costs (nairas lha) 3412 3683
Family Labor (@ hired labor wage rate) (nairas lha) 2688 3486
Opportunity Cost of Land6 (nairas/ha) 83 62 8362
3. PERFORMANCE MEASURES
Gross Margin (nairas /ha) 18041 17450
Net Returns to family Labor (nairas lha) 9679 9088
Net Returns per day of F arnily Labor (nairas /day) 76 55
Total production Costs (nairas /ha) 14462 15531
Net Enterprise Proﬁts (nairas /ha) 699] 5602

 

Source: COSCA survey data

 

' Loan variety and manual processing

2 Estimated using the “Ear Weight Method” in Appendix 2 of chapter 2.

3 Weighted average farmgate price based on COSCA data.

4 Farmgate price based on secondary source of information (personal communication with IITA).

5Farmers did not purchase planting materials of food crops but produced their own: for cassava, only one
fifth of the stems from previous harvest are retained for replanting and for maize, only 2 to 3% of the
previous harvest is saved for seed. Therefore, the opportunity cost of planting materials, which is relatively
insigniﬁcant. is not counted.

6 Land is very rarely sold or rented. In this budget, the opportunity cost of land is estimated as the net return
to land that farmers would enjoy if the produce green maize only.

114

Table A3-l4: Estimated Economic Budget for Commercial Cassava/Maize Systems
under Technology Combination “LOCMAN”', by Regional Output
Markets, Nigeria, 1989/1991

 

 

I
‘w-c’. .‘K— ' ‘.

 

 

Budget Items Regional Oumut Markets
Abeokuta Onitsha
l. OUTPUTS
Average Root Yield (kg/ha) 12337 11776
Average Green Maize Yield (ears/ha)2 9614 9614
Market Price of root (nairas/kg)3 0.24 0.61
Market Price of Green Maize (nairas/ear)4 1.5 1.5
Revenues from Root (nairas lha) 2911 7230
Revenues from Green Maize (nairas /ha) 14421 14421
Gross Revenues (nairas lha) 17332 21651
2. COSTS
Fixed Costs (nairas/ha)5 0 0
Operating costs (nairas/ha)
Hired Labor6 1680 1995
Transportation (nairas)
Tradable 1 538 1472
Nontradable 296 283
Interest on Working Capital (8%) 281 300
Total Operating Costs (nairas lha) 3795 4050
Family Labor (@ hired labor wage rate) (nairas /ha) 2688 3486
Opportunity Cost of Land7 (nairas/ha) 8362 8362
4. PERFORMANCE MEASURES
Gross Margin (nairas lha) 13536 17601
Net Returns to family Labor (nairas lha) 5174 9239
Net Returns per day of F arnily Labor (nairas /day) 40 56
Total production Costs (nairas /ha) 14845 15898
Net Economic Proﬁts (nairas lha) 2486 5753

 

Source: COSCA survey data

 

‘ Local variety and manual processing

2 Estimated using the “Ear Weight Method” discussed Appendix 2 of chapter 2.

3 Estimated Farm Level Import Parity Price of root

4 Farmgate price based on secondary source of information (personal communication with IITA).
5Farmers did not purchase planting materials of food crops but produced their own: for cassava, only one
ﬁfth of the stems from previous harvest are retained for replanting and for maize, only 2 to 3% of the
previous harvest is saved for seed. Therefore, the opportunity cost of planting materials, which is relatively
insigniﬁcant, is not counted.

6 Although rural labor markets in West Africa are complex, it is reasonable to assume that market wages
offer good approximations to shadow wages (Humphreys in Rice in West Africa. p. 80, 1981).

7 Land is very rarely sold or rented. In this budget, the opportunity cost of land is estimated as the Gross
Margin that farmers would enjoy if the produce green maize only.

115

 

Table A3-15: Estimated Financial Budget for Commercial Cassava/Maize Systems
under Technology Combination “IMPMAN”‘, by Regional Output

Markets, Nigeria, 1989/1991

 

 

 

Budget Items Regional Output Markets
Abeokuta Onitsha
l. OUTPUTS
Average Root Yield (kg/ha) 21131 20171
Average Green Maize Yield (ears/ha)2 9614 9614
Market Price of root (nairas/kg)3 0.57 0.57
Market Price of Green Maize (nairas/ear)4 1.5 1.5
Revenues from Root (nairas lha) 12045 11497
Revenues from Green Maize (nairas /ha) 14421 14421
Gross Revenues (nairas /ha) 26466 25918
2. COSTS
Fixed Costs (nairas/ha)5 0 0
Operating costs (nairas/ha)
Hired Labor 23 73 2205
Transportation (nairas)
Tradable l 666 1 594
Nontradable 417 399
Interest on Working Capital (8%) 356 336
Total Operating Costs (nairas lha) 4812 4534
Family Labor (@ hired labor wage rate) (nairas /ha) 3759 3822
Opportunity Cost of Land6 (nairas/ha) 8362 8362
3. PERFORMANCE MEASURES
Gross Margin (nairas /ha) 21653 21384
Net Returns to family Labor (nairas /ha) 13291 13022
Net Returns per day of Family Labor (nairas /day) 74 72
Total production Costs (nairas fha) 16933 16718
Net Enterprise Proﬁts (nairas /ha) 9532 9200

 

Source: COSCA survey data

 

' Improved variety and manual processing

3 Estimated using the “Ear Weight Method” discussed in Appendix 2 of chapter 2.

3 Weighted average farmgate price based on COSCA data.

4 Farmgate price based on secondary source of information (personal communication with IITA).
’Farmers did not purchase planting materials of food crops but produced their own: for cassava, only one
ﬁfth of the stems from previous harvest are retained for replanting and for maize, only 2 to 3% of the
previous harvest is saved for seed. Therefore, the opportunity cost of planting materials, which is relatively
insigniﬁcant, is not counted.

6 Land is very rarely sold or rented. In this budget, the opportunity cost of land is estimated as the net return
to land that farmers would enjoy if the produce green maize only.

116

 

Table A3-l6: Estimated Economic Budget for Commercial Cassava/Maize Systems
under Technology Combination “IMPMAN’”, by Regional Output
Markets, Nigeria, 1989/1991

 

 

 

Budget Items Regional Ougrut Markets
Abeokuta Onitsha
1. OUTPUTS
Average Root Yield (kg/ha) 21131 20171
Average Green Maize Yield (cars/ha)2 9614 9614
Market Price of root (nairas/kg)3 0.08 0.38
Market Price of Green Maize (nairas/ear)4 1.5 1.5
Revenues from Root (nairas /ha) 1763 7609
Revenues from Green Maize (nairas lha) 14421 14421
Gross Revenues (nairas /ha) 16184 22030
2. COSTS
Fixed Costs (nairas/ha)5 0 0
Operating costs (nairas/ha)
Hired Labor6 2373 2205
Transportation (nairas)
Tradable 2166 2064
Nontradable 41 7 399
Interest on Working Capital (8%) 396 373
Total Operating Costs (nairas /ha) 5362 5041
Family Labor (@ hired labor wage rate) (nairas lha) 3759 3822
Opportunity Cost of Land7 (nairas/ha) 8362 83 62
3. PERFORMANCE MEASURES
Gross Margin (nairas /ha) 10832 16989
Net Returns to family Labor (nairas /ha) 2470 8627
Net Returns per day of Family Labor (nairas /day) 14 47
Total production Costs (nairas /ha) 17473 17225
Net Social Proﬁts (nairas lha) -1289 4805

 

Source: COSCA survey data

 

‘ Improved variety and manual processing

2 Estimated using the “Ear Weight Method” discussed in the appendix.

3 Estimated Farm Level Import Parity Price of root

4 Farmgate price based on secondary source of information (personal communication with IIT A).
sFarmers did not purchase planting materials of food crops but produced their own: for cassava, only one
ﬁfth of the stems from previous harvest are retained for replanting and for maize, only 2 to 3% of the
previous harvest is saved for md. Therefore, the opportunity cost of planting materials, which is relatively
insigniﬁcant, is not counted.

6 Although rural labor markets in West African are complex, it is reasonable to assume that market wages
offers good approximations to shadow wages (Humphreys in Rice in West Africa. p. 80, 1981).

7 Land is very rarely sold or rented. In this budget, the opportunity cost of land is estimated as the Gross
Margin that farmers would enjoy if the produce green maize only.

117

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120

CHAPTER 4
COMPARING THE PROF ITABHJTY OF CASSAVA-BASED PRODUCTION

SYSTEMS IN THREE WEST AFRICAN COUNTRIES: COTE D’IVOIRE,
GHANA AND NIGERIA.

4.1. Introduction

In most Sub-Saharan African countries, the agricultural sector has always, and still
accounts for the major share of GDP, foreign exchange, and employment. Yet, per capita
food production has not been able to keep pace with a rapidly expanding demand for food.
As a result, Sub-Saharan African (SSA) countries have become increasingly dependent on
commercial imports and food aid (World Bank, 1996). To reverse this trend, most Sub-
Saharan African (SSA) governments have been designing research programs and policy
initiatives aimed at achieving national food security. One of the many food crops being
considered currently in this effort in SSA is cassava, both in terms of its potential to
ensure adequate food supply for all and generate rural household income, thereby
increasing access to food. While this has led to a major expansion in cassava- based
production systems in Nigeria and Ghana, there has been a slower grth in Cote d’Ivoire
(Nweke, 1998).

Cassava is an important commodity in many farming systems in Sub-Saharan
Africa (Nweke et al., 1994). Its relative importance stems from its adaptability to a wide
range of agro-ecologies, including marginal lands and erratic rainfall conditions (Nweke et
al., 1994). Regardless of the production environment, compared to other crops, cassava
has lower production risks, and provides the possibility of maintaining a continuous food

supply throughout the year (Nweke et al, 1994).

121

This study is based on the argument that the difference in various factors such as
agricultural policies (i.e., trade and price policies, domestic production taxes or subsidies),
location and technologies (production and processing) between Nigeria, Ghana and C6te
d’Ivoire explains the difference in the level of growth in cassava-based production
systems. The study uses the policy analysis matrix (PAM) model to examine the
magnitude of the impact of these various factors on the private and social proﬁtability of
cassava/maize production systems in Nigeria, Ghana and Cote d’Ivoire.

The intent of this comparative essay is to use policy analysis matrix (PAM)
approach to push analysis of the factors inﬂuencing proﬁtability ﬁrrther than can be done
within the context of a single country. The main advantage of carrying out similar policy

studies in a number of countries is the scope presented for obtaining comparative insights.

4.2. Methodological Framework

As mentioned earlier, the Policy Analysis Matrix (PAM) is the analytical
framework used in this essay. This methodology is presented in detail in the ﬁrst chapter;
therefore in this section, the focus is on how it is used in estimating comparative costs and
incentives for farm activities or enterprises.

As an empirical framework, the PAM provides measures of economic efﬁciency
and of transfer effects of policy on particular commodities, technologies, and regions. This
information is used to explore several topics of interest to policymakers, such as the
pattern of competitiveness and the potential for the government to exploit competitive
advantage; the formulation of public investment policy to support particular commodities,

regions and farm types; and the allocation of public research and development

122

expenditures within the agricultural sector. PAM results thus serve as an information
baseline for monitoring and evaluating the effects of policy and for identifying policy-
relevant research needs.

In this essay, ﬁrst, private and social proﬁtability of cassava/maize production
systems in each country are presented and analyzed under a baseline scenario. This is
followed by the discussion policy analysis matrix (PAM) results for each country. These
results are organized by country to provide a basis for cross-country comparisons of
technologies that dominate cassava/maize production in West Aﬁica and comparisons of
technologies within Nigeria. Comparisons between similar systems in diﬁ‘erent countries
are also possible through a further extension of the PAM analysis, ﬁ'om which policy-
impact ratios (e. g. DRC, EPC) are produced.

Finally, these “baseline” results are analyzed ﬁrrther by considering the implications
of two scenarios for ﬁiture change in selected technical parameters. The ﬁrst scenario
simulates increases in yields in Cote d’Ivoire and Ghana. The second scenario considers

the effects of changes in the foreign exchange rates in the three countries.

4.3. Empirical Analyses
Cassava/maize production systems are examined in this section using a
combination of ﬁnancial analysis, economic analysis and policy analysis. The tasks
involved are the following:
1. To identify and select relevant estimates of private proﬁtability (farm level and post-
farrn level) and social proﬁtability ﬁ'om the ﬁrst two essays on Cote d’Ivoire and
Nigeria.

123

2. To develop enterprise budgets (ﬁnancial and economic) for cassava/maize systems in

Ghana under a “baseline scenario”.

3. To construct a Policy Analysis Matrix (PAM) for Ghana, using the information ﬁom the

enterprise budgets and estimate ratio indicators such as DRC, NPC, etc.

4. To undertake sensitivity analyses in order to contrast the relative comparative
advantage of each country in cassava/maize production.
4.3.1. Private Proﬁtability (PP)

In this subsection, separate ﬁnancial farm—level and post-farm level budgets are
developed for Ghana, whereas estimates of private proﬁtability (PP) indicators are taken
from the previous essays on Cote d’Ivoire and NigeriaThis provides the database for
establishing the relative proﬁtability of cassava/maize production systems in each country.
Previous chapters not only present a summary of the rationale that underlies farm budgets
analysis, but also discuss in detail the construction of farm budgets. The PP indicator
shows the incentives, for each production system, to alter the existing allocation of
resources. If PP is positive, resources are encouraged to ﬂow into the activity. IfPP is
negative, the direction of the ﬂow is likely to be away.
4.3.1.1. Farm level Analysis

Cassava/maize enterprise budgets for the three countries are presented in tables
A4-1 through A4-3 in appendix 4. Table 4-1 below summarizes the results of the baseline
runs of the farm level ﬁnancial proﬁtability analysis for Cote d’Ivoire, Ghana and Nigeria.
The summary focuses mainly on performance measures that can be used to identify the

country where enterprises have the highest ﬁnancial return and lowest cost of production.

124

Table 4- 1: Summary Estimates of Farm-Level Financial Budget Indicators (in
USS using prevailing Exchange Rates) for Cassava/Maize Production
Systems, by Country,l989/9l

 

 

 

CountrieS/Produc Returns to Returns to Family Total Net Enterprise

tion Technologies Family Labor Labor Production Proﬁts/ha
Per Ha Per Person- day Costs/ha

COTE

D’IVOIRE

Local/maize 804.56 6.00 755.49 487.20

UTA/maize NA NA NA NA

GHANA

Local/maize 742.58 5.34 1266.50 419.33

IITA/maize NA NA NA NA

NIGERIA

Local/maize 519.65 3 .24 903.60 320.80

IITA/maize 742.70 4.29 962.18 530.24

 

Source: tables A4-1, A4-2 and A4-3 in Appendix 4
Note: in terms of prevailing exchange rates, lUS dollar= 266 fcfa (in Cote d’Ivoire) = 430
cedis (in Ghana) = 17 nairas (in Nigeria)

Results in table 4-1 clearly show that the production system that is common to the
three countries is the local landrace variety /maize system. However, the PP estimates as
shown in table 4-1 also clearly indicates that IITA’s improved cassava varieties generate
the highest net proﬁts.

When converted to a per person-day basis, the returns to family labor for local land
race variety/maize systems (RFL) are US $ 6.00 in Cote d’Ivoire, US $ 5.34 in Ghana and
US $ 3.24 dollars in Nigeria. In the three countries, the RFL per person-day is higher than
the average daily wage rate paid to the hired labor, which are $2.40 in Cote d’Ivoire,
$2.33 in Ghana and $1.23 in Nigeria. Thus, there is no ﬁnancial advantage to family
members in any of these countries to seek wage employment in urban areas or other farms,

when they are needed on their farms in the village. Furthermore, results in table 4-1

underline the remarkable stability of the RFL per person-day as a proportion of

125

agricultural wage rates across countries (ranging from 2.3 to 2.6 times the agricultural
wage rates).

Results in table 4-1 also indicate that price incentives have enabled local landrace
variety/maize systems to earn positive private proﬁts per hectare that do not vary
enormously across countries: US $ 487.20 in Cote d’Ivoire, US $ 419.33 in Ghana and
US $ 320.80 in Nigeria.

Unfortunately, the COSCA study did not record maize yields on its sample ﬁelds.
Therefore, in computing the enterprise budgets developed in this study, it was assumed
that those ﬁelds got the average maize yield for the country which was then converted to
the number of fresh corn ears using the “Ear-Weight Method” discussed in the appendix of
chapter 2. The number of corn ears were subsequently valued at the fresh corn price.
4.3.1.2. Post-harvest Level Financial Analysis

It is assumed that green maize is harvested and consumed or sold at the farm
level. Therefore, only cassava roots harvested are taken to the next level (the village) to
be processed. Cassava processing methods involve a combination of activities such as
peeling, grating and toasting. Of these activities, grating is the most labor intensive. In this
study, a process is deﬁned as traditional if grating is performed manually. Mechanized
processing method involves the use of various types of mechanical cassava graters, which
are driven by electrical, petrol, or diesel engines. The major form into which cassava roots
are processed in Nigeria and Ghana is gari, which is made of toasted cassava granules. In
Cote d’Ivoire, attieke (steamed cassava granules) is the major form into which roots are

processed.

126

Transformation coefﬁcients were computed and used to calculate actual attieke
and gari yields under each technology combination. The technology combination common

”1

to the three countries was the “Locman . Yields were valued by the weighted average
consumer price based on COSCA village survey data. It should be noted that prices vary a
lot ﬁom season to season, mainly because of changing season conditions (e. g., abundance
vs. hungry seasons). To account for this diversity, the weighted average price was
estimated. Since farmers do not own processing machines, no ﬁxed costs was assigned
processing enterprises. Table 4-2 summarizes the results of the post-farm level budget
analysis for the three countries under the technology combination “Locman”. Table 4-3
summarizes the results of the post-farm level budget analysis for Nigeria under alternative
technology combinations.
Table 4-2: Summary Estimates of Post-farm Level Financial Budget Indicators
(in USS using prevailing Exchange Rates) for Processed Products

(Attieke in Cote d’Ivoire and Gari in Ghana and Nigeria) Production,
by Country: 1989/91

 

 

Returns toFamily Average Costs of Net Enterprise
Countries Labor Per Person-day Production Per Kg of Proﬁts
Attieke/Cari Per ha
COTE D’IVOIRE 1.36 0.18 -57.20
GHANA 2.12 0.27 -6.65
NIGERIA 1.00 0.19 -15.12

 

Source: tables A4- 4, A4-5 and A4-6 in Appendix 4.
Note: using the prevailing exchange rates, 1 US dollar= 266 fcfa (in Cote d’Ivoire) = 430
cedis (in Ghana) = 17 nairas (in Nigeria)

 

l The production and processing technology combination “Locman " is deﬁned as follows: local
cassava variety + manual grating method

127

Table 4-3: Summary Estimates of Postfarm-Level Financial Budget Indicators
(inUS$ using prevailing Exchange Rates) for Gari Production, by
TechnolowCombinations: Nigeria, 1989/91

Technology Returns to Family Labor Per Average Costs of Net Enterprise

 

Combinations Person-day Production Per Proﬁts
KgofGari Per ha

Impmech 1 .94 0. 16 49.41
Locmech 1.18 0.18 -1.65
Locman 1.00 0.19 -15.12

 

Source: table 3-2 in chapter 3

Results in table 4-2 indicate that processing costs differ slightly between the three
countries. Attieke production in Cote d’Ivoire is cheaper than gari production in Ghana or
Nigeria. However, proﬁts are negative in the three countries.

Results in table 4-3 show that in Nigeria, only cassava/maize systems under
“Impmech” technology combination had a positive net enterprise proﬁts (NEP). These
results also show that mechanized processing methods have a deﬁnite cost-saving
advantage over traditional processing methods. The “Impmech” technology combination
has the lowest cost of production per kilogram of gari ($0.16 US/kg). This implies that
farmers have incentives to adopt that technology combination. In fact, these ﬁndings are
consistent with farmers’ behavior in Nigeria. As mentioned earlier, COSCA data for
Nigeria show that, in the 65 villages representing cassava-growing areas, most farmers (85
percent) grew the improved varieties. Of these farmers, 54 percent used mechanized
processing method.

However, it should be noted that the negative NEPs observed under the other
technology combinations do not mean that farmers are losing money. Rather, they mean

that net margin is not enough to yield a positive return to the management factor when the

128

costs of other factors are taken into account. In fact, the post-farm level ﬁnancial budgets
presented in tables A4-4 through A4-6 in appendix 4 show that all the NEPs, assuming
zero opportunity cost of labor, are positive.

The COSCA survey data indicate that women control post-harvest activities in the
three countries and receive all the beneﬁts from those activities. In addition, when asked
why they were involved in this activity only, their answer was that there is no better
alternative. That is, they have fewer or no opportunities for employment at the assumed
“prevailing” rural wage.

This situation reﬂects the segmentation of the rural labor market for cassava
farming systems in West Aﬁica. Women manage a very important part of cassava
production systems: 1) they predominate in cassava processing and attieke and gari
preparation and, 2) they devote a large amounts of time in obtaining the fuel and water
required to make cassava processed products ready for sale or home consumption. . Yet
this analysis suggests that returns to women from these activities are below the rural wage
rate, which is available mainly to men.

4.3.2. Social Proﬁtability (SP)

The COSCA data indicate that, in Nigeria, about 79 percent of farmers who
produce gari are net sellers, in Ghana about 70 percent of farmers who produce gari are
net sellers, and in Cote d’Ivoire about 65 percent of farmers who produce attieke are net
sellers. Therefore, this analysis focuses on commercial cassava/maize systems only.

The farm level economic returns for Ghana were calculated using import parity
prices (tables A4-7 and A4-8 in appendix 4) of cassava roots and ﬁnancial prices of green

maize at selected regional markets, Koforidua and Kumasi. These two markets were

129

selected because they are located in regions where farmers ranked cassava as the most
important crop in the farming system (Nweke etal., 1998). The estimates of social
proﬁtability (SP) indicators for Cote d’Ivoire and Nigeria are taken from previous essays.
The economic budgets are presented in tables A4-10 through A4-15 in appendix 4.

As already discussed in previous essays, the economic budgets were estimated
according to the following assumptions: 1) It is assumed that green maize is nontraded
and that its price is not distorted by government policies. Therefore, its ﬁnancial price (the
observed market price) reﬂects its shadow price; 2) Gari, the main cassava product in
Nigeria and Ghana, and attieke, the main cassava product in Cote d’Ivoire, are not traded
internationally, but tapioca, another cassava product and the closest substitute of attieke
and gari is traded internationally. Consequently, the price of imported tapioca was used to
estimate the import parity of cassava root; and 3) the oﬂicial exchange rates (266 francs
cfa to $1US for Cote d’Ivoire, 430 cedis to $1US for Ghana and 17 nairas to $1US for
Nigeria) were adjusted to reﬂect their equilibrium values net of distortions. The premium
used for this adjustments were 48 percent for Cote d’Ivoire, 50 percent for Ghana and 30
percent for Nigeria respectively (Stryker, 1990).

Net social proﬁt (SP), measured in world prices or their equivalent, in fact,
diverges widely from the PP. The SP indicators shown in tables 4-4 and 4-5 below
indicate that there is signiﬁcant variation in SP among countries and between techniques.
However, these SP indicators also suggest that all countries are able to substitute
proﬁtably local production of cassava/maize for imports. The only exceptions are systems
under the technology combination “Impman” in Nigeria when outputs are sold in

Abeokuta.

130

However, as already discussed in chapter 3, the systems under the “Impmech”
technology combination in Nigeria, are clearly the most efﬁcient use of national resources.
They generate signiﬁcantly higher net social proﬁts (N SP) per hectare at both regional
output markets (U S$ 290.00 in Abeokuta and US$ 684.32 in Onitsha). The net social
proﬁt (N SP) refers to the difference, valued in border and shadow prices, between the
gross value of output and the total costs of all inputs (traded and nontraded intermediary
and primary inputs).

A more efﬁcient use of resources means that one can produce more from what
one has and attain a higher level of welfare. Measures of NSP, like DRC, may give an idea
of the comparative advantage in the agricultural commodity system. In addition, measures
of NSP may give an idea of the comparative advantage or efﬁciency in the agricultural
commodity system. Thus, NSP measures are very informative for decision-makers and
allocators of research funds, if the technical changes they might introduce would attempt
to break labor or other constraints in cassava/maize systems.

It should be noted that all systems are more proﬁtable ﬁnancially than they are
socially. That is, there are net transfers to farmers (see tables A4-11 through A4-15 in
appendix 4). The subsequent PAM analysis will help illustrate the sources of these

transfers.

131

Table 4-4: Summary Estimates of Farm-Level Economic Budget Indicators (in
USS using Shadow Exchange Rate) For Commercial Cassava/Maize

Production Systems at Each Regional Output Market,

 

 

by Country:l989/l99l
Countries/Regional Markets Returns Returns to Total System Net Social
to Family Production Proﬁts
Family Labor Per Costs Per Ha Per Ha
Labor Person-day
Per Ha
COTE D’IVOIRE Bonoua 306.54 2.18 535.30 81.08
N’douci 413.26 2.89 534.06 184.60
GHANA Koforidua 417.36 2.87 846.62 192.56
Kumassi 557.60 3.52 858.90 311.83
NIGERIA Abeokuta 235.18 1.81 647.80 113.00
Onitsha 420.00 2.51 722.64 261 .50

 

Source: tables A4-10, A4-12 and A4-l4 in Appendix 4.
Note: using the shadow exchange rates, 1US $ equals 394 fcfa (in 0].), equals 645cedis
(in Ghana), equals 22 nairas (in Nigeria)

Table 4-5: Summary Estimates of Farm-Level Economic Budget Indicators (in USS
using Shadow Exchange Rates) For Commercial Cassava/Maize
Production Systems at Each Regional Output Market, by Production and
Processing Technolog Combinations, Nigeria: 1989/1991

 

 

 

Regional Markets/ Returns to Returns to Total System Net Social
Technology Combinations Family Family Production Proﬁts
Labor Labor Per Costs Per Ha Per Ha
Per Ha Person-day
Abeokuta
Impmech 460.80 2.60 794.23 290.00
Locmech 303.00 2.40 674.80 180.82
Locman 235.20 1.81 674.80 113.00
Impman 112.30 0.64 794.23 -3.5
Onitsha
Impmech 858.04 4.73 783.00 684.32
Locmech 504.00 3.05 722.64 345.60
Locman 420.00 2.54 722.64 261.50
Impman 392.14 2.13 783.00 218.41

 

4.3.3.Policy Matrix Analysis

By completing a PAM for a production system one can simultaneously determine
the economic efﬁciency of the system, the degree of policy-induced transfers on the input

132

loutput markets, and the extent to which resources are transferred among agents (Yao,
1997). First, the PAM was constructed using the information on costs and returns
obtained from the ﬁnancial and economic analyses. Second, the extent of policy-induced
transfers is computed. Third, six PAM policy-indicators were derived for policy analysis.
They are: the Domestic Resource Cost (DRC), the Nominal Protection Coefﬁcient on
Tradable Output (NPCO), the Nominal Protection Coefﬁcient on Tradable Input (NPCI),
the Effective Protection Coefﬁcient (EPC), the Proﬁtability Coefﬁcient (PC), and the
Subsidy to Producers (SP)?

4.3.3.1.Baseline Results

The PAM of cassava/maize production systems for each country is presented in
tables A4-16 through A4-19 in Appendix 4. The policy-induced transfers (in the output
and input markets) are summarized in tables 4-6 and 4—7 below. Results from these two
tables indicate that there are substantial differences between countries in the magnitudes of
public incentives offered to encourage cassava/maize production systems.

However, all countries display the same patterns. The baseline results indicated
that, farmers operating at the Bonoua markets near urban centers (i.e., Bonoua in Cote
d’Ivoire, Koforidua in Ghana and Abeokuta in Nigeria), beneﬁted ﬁom a small implicit
price support whereas farmers operating in markets distant from urban centers (N ’douci in

Cote d’Ivoire, Kumasi in Ghana and Onitsha in Nigeria) were subject a small implicit tax.

 

2 DRC= domestic factors in social prices/ (revenues in social prices - tradable inputs in social prices), NPCO =
revenues in private prices / revenues in social prices, NPCI= tradable inputs in private prices/ tradable inputs in
social prices, EPC= (revenues in private prices -tradable inputs in private prices)/ (revenues in social prices -
tradable inputs in social prices), PC= private proﬁts/ social proﬁts, SP= (private proﬁts- social proﬁtsy revenues in
social prices

133

This is the result of farm-gate ﬁnancial prices (15 fcfa in Cote d’Ivoire, 22 cedis in
Ghana and 0.57 nairas in Nigeria) for cassava root departing ﬁom the estimated import
parity prices in each country (tables A4-7 through A4-9b in the appendix) depending on
the point of sale.

It should be emphasized that these diﬂ‘erentials are relatively small. With this in
mind, here are some plausible explanations of why market (ﬁnancial) prices and economic
prices (import parity prices) did not equal in markets close to port cities and markets
distant from port cities. The divergences between these two prices could be due to a
combination of the effect of the food import policies (i.e., ban on cereals import in
Nigeria, rice import tariffs in Ghana and Cote d’Ivoire) and the effect of the overvaluation
of each country’s local currency. The indirect effect of such food import policies will be an
increase in the ﬁnancial price of cassava root relative to the economic price in all the
markets. On the other hand, the currency overvaluation will have the effect of lowering
the ﬁnancial price of tradables such as roots and transport in both markets.

However, the magnitude of the reduction in prices will be large in markets far
away ﬁ'om port cities and small in the ones close to port cities because the share of
transport costs in the import parity price is relatively large for N’douci, Kumassi and
Onitsha (distant ﬁ'om port cities) and relatively small for Bonoua, Koforidua and
Abeokuta (close to port cities). Transportation costs thus provide a natural protection to
domestic producers who supply markets located far from the import point.

Thus, the net effect is as follows: 1) in N’douci, Kumassi and Onitsha : an increase
in the ﬁnancial price of roots due to the import tariff and a relatively large decrease in the

ﬁnancial price of roots due to the currency overvaluation (via its impact on tradable goods

134

such as cassava and transport costs); and 2) in for Bonoua, Koforidua and Abeokuta: an

increase in the ﬁnancial price of roots due to the import tariff and a relatively small

decrease in the ﬁnancial price of roots due to the currency overvaluation.

It should be noted that the results ﬁ'om tables 4-6 and 4-7 are calculated using the

weighted average of peak-season and off-peak season wage rate across cassava

production zones. The off-peak season rate is two third of the peak-season rate in Cote

d’Ivoire, halfof the peak-season rate in Ghana and. half of the peak-season rate in Nigeria.

Table 4-6: Summary of the Net Effects (in USS using Shadow Exchange Rates) of
Policy-Induced Transfers For Commercial Cassava/Maize Systems, by

Country: 1989/1991.

 

 

 

 

 

Regional Output Output Tradable Inputs Domestic Factors Net Policy
Markets Transfers Transfers Transfers Transfers
COTE D’IVOIRE

Bonoua 87.00 -5.00 -O.4 92.00

N’douci -36.00 -5.00 -0.4 -31.00
GHANA

Koforidua 129.00 -7.00 -1.00 137.00

Kumassi -25.00 -7.00 -1.00 -17.00
NIGERIA

Abeokuta 187.00 -16.00 -1.00 205.00

Onitsha -24.00 -l6.00 -1.00 -95.00

 

 

Source: tables A4-16, A4-l7 and A4-18 in Appendix 4

 

 

 

Table 4-7: Summary of the Net Effects of Policy-Induced Transfers For Commercial

Cassava/Maize Systems in Nigeria: 1989/1991.

Domestic Factors
Transfers

[Mkts/ Technology Output Tradable Inputs
Combinations Transfers Transfers
Abeokuta

Impmech l 1 9.00 -23 .00
Locmech 120.00 -l6.00
Locman 187.00 -16.00
Impman 467.00 -23.00
Onitsha

Impmech -289.00 -21.00
Locmech -108.00 -15.00
Locman -24.00 -15.00
lmgman L177.00 -21 .00

 

 

Source: table A4-16 in Appendix 4

135

-2.00
-1.00
-1.00
-2.00

-2.00
-1.00
-1.00
-2.00

 

Net Policy
Transfers

143.00
137.00
205.00
492.00

-266.00
-91 .00
-7.00
200.00

As for the tradable inputs and domestic factor transfers, they are negative
everywhere. However, it should be noted that these transfers are relatively smaller
compared with the transfers occurring in the outputs markets. The reason is that while the
output (cassava roots) is assumed to be tradable, only 20 percent of the inputs (e. g., local
transportation) used in its production process is treated as such. The key difference is that,
compared with a nontradable commodity or resource, the domestic price formation of
tradable commodity or resource is inﬂuenced to greater extent by the world market for
that commodity or resource.

Thus, results in table 4-6 imply that, when outputs and inputs were valued at their
social (efﬁciency) prices, the effect of government policy was: a) some type of support
system to both cassava/maize systems in regional output markets closer capital cities, a tax
to cassava/maize farmers selling at remote regional output markets; b) the provision of a
subsidy, through an overvalued exchange rate, on sale of all inputs (imported and
produced domestically).

Within Nigeria, some generalizations can be made concerning policy-induced
transfers of different technology combinations. Results in table 4-7 suggest that when
outputs and inputs were valued at their social (efficiency) prices, the effect of government
policy was: 1) some support to cassava/maize systems under each technology combination
at the Abeokuta market and 2) some tax on systems at the Onitsha market, except for
systems under “Impman” combination. It is worth noting that the largest amount of
negative transfers to producers occurs under the “Impmech” combination. In other words,
farmers growing improved cassava varieties and producing gari using modern technology

have been taxed more compared to other cassava/maize farmers. This difference can be

136

explained as follows: COSCA data indicate that the average farm-gate market price for
cassava root was 0.57 nairas in Nigeria during the survey period. This price departs ﬁ'om
the estimated import parity prices under each technology (tables A3-7 and A3-8 in
Appendix 3 of chapter 3) of roots when Abeokuta or Onitsha is used as a point of sale. As
already discussed above, overvalued large transportation costs combined with the cereals
imports ban of 1985 explain this difference.

The calculation of domestic resource cost (DRC) coefﬁcients for different
countries permits a ranking of relative efficiencies in production. For example, given a
desire to expand cassava/maize production systems in West Aﬁica, the country with the
lowest DRC is the most efﬁcient avenue for expansion. Thus, DRC rankings indicate
which country can expect the highest social rate return on its investment in farm and post
farm technologies. Two main types of prices policy instruments can be used to alter prices
of agricultural outputs and inputs. Quotas tariffs, or subsidies on imports and quotas,
taxes, or subsidies on exports directly decrease or increase amounts traded internationally
and thus raise or lower domestic prices. Domestic taxes or subsidies, in contrast, create
transfers between the government treasury and domestic producers or consumers.

In addition to price and macro policies, governments inﬂuence their agricultural
sectors through public investment policy. Government budgetary resources can be
invested in agriculture to increase productivity and reduce costs ( Monke and Pearson,

1989)

137

Table 4-8: Ratio Indicators for Commercial Cassava/Maize, by Country: 1989-

 

 

1991.
Countries/ DRC NPCO N PCI EPC PC SP
Reg’onal Output

COTE D’IVOIRE
Bonoua 0.86 1.14 1.00 1.15 2.14 0.15
N’douci 0.74 0.95 1.00 0.96 0.83 -0.04
GHANA
Koforidua 0.81 1.12 0.67 1.13 1.71 0.13
Kumassi 0.73 0.98 0.67 0.98 0.95 -0.01
NIGERIA
Abeokuta 0.84 1.24 0.77 1.28 2.81 0.26
Onitsha 0.71 0.98 0.77 0.99 0.97 -0.01

 

Source: PAM Model constructed by the author

Note: DRC= Domestic Resource Cost, NPCO= Nominal Protection Coefﬁcient on
Tradable Output, NPCI= Nominal Protection Coefﬁcient on Tradable Input ,
EPC= Effective Protection Coefﬁcient, PC= Proﬁtability Coefﬁcient
and SP= Subsidy to Producers

Table 4-9: Ratio Indicators for Commercial Cassava/Maize Production Systems
Under Alternative Production and Processing Combinations and by
distance in ﬁgeria, 1989-1991.

 

 

Mitts/Tech. Comb. DRC NPCO NPCI EPC PC SP
Abeokuta
Impmech 0.71 1.11 0.77 1.14 1.49 0.13
Locmech 0.77 1.14 0.77 1.17 1.76 0.16
Locman 0.84 1.24 0.77 l 28 2.81 0.26
Impman 1.09 1.64 0.77 1 77 -7.39 0.67
Onitsha
Impmech 0.50 0.80 0.77 0.80 0.61 —0.81
Locmech 0.65 0.90 0.77 0.91 0.74 -0.09
Locman 0.71 0.98 0.77 0.99 0.97 -0.01
o 76 1 13 Q 17 1;; 1 91 m

 

 

 

Source: PAM Model constructed by the author

Note: DRC= Domestic Resource Cost, NPCO= Nominal Protection Coefﬁcient on
Tradable Output, NPCI= Nominal Protection Coefﬁcient on Tradable Input ,
EPC= Effective Protection Coefﬁcient, PC= Proﬁtability Coeﬁicient
and SP= Subsidy to Producers
The DRC coefﬁcients presented in table 4-8 clearly show that, not only they are

less than unity in all three countries, but also the three countries have similar comparative

advantage in cassava/maize production in West Aﬁica using local varieties. DRC

138

coeﬂicients taken from the essay on Nigeria are presented in table 4-9 to push the
efﬁciency comparisons ﬁrrther. They indicate that, cassava/maize systems under the
“Impmech” technology have a greater comparative advantage when outputs are sold in
Onitsha.

Given that governments in West Africa are involved extensively in their agriculture
economies, it is of interest to describe how overvalued exchange rate policies create
private incentives. An overvalued exchange rate is an implicit tax on producers of tradable
products because too little domestic currency is earned by exports or paid out for imports.
In the absence of commodity price policy, the world price of a tradable good determines
its domestic price. When the exchange rate is overvalued, the domestic price is lower than
its efﬁciency level and domestic producers are effectively taxed.

To examine the relationships between government policy and the cassava/maize
economy in Cote d’Ivoire, Ghana and Nigeria, policy-impact ratios, which cancel all units
of measure, were calculated. These ratios are presented in the tables 4-8 and 4-9 above.
The analysis that follows will focus on the NPCO, the NPCI and the EPC.

Of the three countries, Cote d’Ivoire demonstrates the lowest level of government
interference on both the input and the output sides in N’douci, a market located farther
away from the capital city. The NPCO, the EPC and the NPCI all are close to unity unity.
In all three countries, the NPCO and the EPC assume the same patterns in markets located
closer to capital cities: they are greater than unity, suggesting a certain positive protection
to cassava/maize farmers in those markets. However, in Ghana and Nigeria the NPCI are
less than unity everywhere, implying government policies in those countries have

permitted inputs prices to be lower than they would be under open trade.

139

4.3.3.2. Sensitivity Analysis

The sensitivity analysis carried out in this sub-section aims to test the robustness of
the results under the baseline scenario. Two scenarios are considered: the ﬁrst scenario
simulates a change in yields of cassava and a change in processing costs; and the second
considers the effects of change in the shadow exchange rate.

Yields and Processing Cost. This sensitivity analysis is broken into two parts: the
ﬁrst part investigates the effects of an increase in cassava yields in Cote d’Ivoire and
Ghana on the DRC ratios. It is assumed that farmers in both countries have adopted the
IITA variety; therefore cassava yields equal ITTA variety yields in Nigeria (19,210
kilograms of roots per hectare).

In the essay on Nigeria, post-farm budgets analyses show that mechanized
processing technology decreases processing cost by 6 percent for farmers who grow local
landrace cassava varieties, varieties that are common to all three countries. Therefore, in
the second part of the sensitivity analysis, the impact of a decrease in processing costs is
considered. The results are shown in table 4-10.

Table 4-10: Effects of Changes in Cassava Yields and Processing Costs on the
DRC for Root Production in Cote d’Ivoire and Ghana: 1989/1991

 

 

 

Countries/ Effects of Increase (79% for CI Effects of a 6% Decrease in
Markets and 43% for Ghana) in Cassava Processing Costs

Yields

DRC Ratio

Baseline Elasticity Simulation Baseline Elasticity Simulation
COTE
D’IVOIRE
Bonoua 0.86 -O.60 0.46 0.86 -1.94 0.76
N’douci 0.74 -0.57 0.41 0.74 -1.58 0.67
GHANA
Koforidua 0.81 -0.57 0.61 0.81 -2.26 0.70
Kumassi 0.74 -0.63 0.54 0.74 -1.80 0.66

 

 

Source: PAM Model constructed by the author
140

To help in assessing comparative costs across the three countries, DRC elasticties
were calculated. They are deﬁned as the percentage change in DRC divided by percentage
change in yield or processing costs. Results of table 4-10 show that DRC elasticity values
with respect to yields and processing cost range from -0.57 to -0.60 and from -1.58 to -
2.26 in Cote d’Ivoire and Ghana, respectively. The larger the value of the elasticity, the
more effect the relevant parameter has on the DRC coefﬁcient. However, the question is
how much it costs get a 1 percent change in yield versus a 1 percent in processing cost in
order to evaluate whether it would be better to invest in yields or processing method.

Shadow Exchange Rates. The sensitivity analysis undertaken here is designed to
examine the effects of an appreciation of the real exchange rate on net social proﬁtabilities
(N SP) and selected policy—indicators (DRC and EPC) ratios. Previous studies (Babo,
1996; Barry, 1998; and Nweke, 1998) have shown that market prices in Cote d’Ivoire,
Ghana and Nigeria have changed with a decline in the shadow exchange rate, which led to
recent currency devaluation in all three countries. Therefore, these post-devaluation prices
were used in carrying out this analysis. Tables 4-11 and 4-12 present the results.

Table 4-11: Effects of Change in the Shadow Exchange Rate on the Net Social Proﬁt
(NSP in SUS using Shadow exchange rates), by Country: 1989/1991

 

 

 

Countries/Regional Mkts Baseline Simulation 1Proﬁt Elastich
COTE D’IVOIRE
Bonoua 81.06 266.84 6.55
N’douci 184.60 329.94 2.25
GHANA
Koforidua 192.55 -152.45 -0.85
Kumasi 311.83 -250.63 —0.86
NIGERIA
Abeokuta 1 13.00 1 8 .44 -0.29
Onitsha 261.50 19.65 -0.32

 

Source: PAM Model constructed by the author
Note: it is assumed that the percentage changes in the equilibrium exchange rates are: 35%
for Cote d’Ivoire, 210% for Ghana and 280% for Nigeria.

141

Table 4-12: Effects of Change in the Shadow Exchange Rate on Selected Policy
Indicators, by Country: 1989/1991

 

 

 

 

 

 

Countries/Mitts Policy Indicators
DRC Ratio EPC Ratio
Baseline % Simulation Baseline % Simulation
Change Change
COTE
D’IVOIRE
Bonoua 0.86 -25 0.64 1.15 -32 0.78
N’douci 0.74 -20 0.59 0.96 -28 0.70
GHANA
Koforidua 0.81 62 1.31 1.71 -18 1.40
Kumassi 0.73 119 1.60 0.97 64 1.59
NIGERIA
Abeokuta 0.84 17 0.98 1.28 -50 0.64
Onitsha 0.71 37 0.97 0.99 -36 0.63

 

 

Source: PAM Model constructed by the author
Note: it is assumed that the percentage changes in the equilibrium exchange rates are:35%
for Cote d’Ivoire, 210% for Ghana and 280% for Nigeria.

As the proﬁt elasticities in table 4-10 indicate, social proﬁtability levels are very
sensitive to changes in the shadow exchange rates. Following 35 percent, 210 percent and
286 percent decline in the equilibrium exchange rate in Cote d’Ivoire, Ghana and Nigeria
respectively, results ﬁ'om table 4-11 show that, while cassava/maize systems show
considerable beneﬁt from the exchange rate depreciation in Cote d’Ivoire, systems in
Ghana suffered a huge loss. This result can be explained by the fact that in Ghana, farm
level wage rates rose from 1000 cedis to 4000 cedis (a 300 percent increase) while output
price rose from 22 cedis to 65cedis (a 195 percent increase).

The results of table 4-12 show the effect of changes in the exchange rates on the
DRC, the EPC. The simulated values of the domestic resource cost (DRC) ratios are
greater than unity in Ghana, suggesting that the decrease in the equilibrium exchange rate

combined with the increased valued of domestic labor have caused that country to suffer a

142

comparative disadvantage. However, the EPC estimates are also greater unity, suggesting
that farmers are receiving positive protection. That is, they could have received a lower

return if they faced border prices instead of domestic prices on both outputs and inputs.

4.4. Conclusions

This essay is an application of the policy analysis matrix (PAM) for cassava/maize
production systems in Cote d’Ivoire, Ghana and Nigeria. The purpose was to analyze and
compare the competitiveness of cassava/maize systems in these three West African
countries. The baseline results compared in this study demonstrate the narrow range of
efﬁciencies of production. All three countries have almost similar comparative advantage
in cassava/maize production systems, although labor input for Nigeria and Ghana is 15 to
30 percent higher than for Cote d’Ivoire.

However, PAM is a static model which cannot capture changes in prices and
productivity (Yao, 1998); therefore, a sensitivity analysis was carried out. The simulation
ﬁndings indicate that, in most instances, the decline in the equilibrium exchange rate has
allowed the differences in efﬁciencies across countries to be maintained.

The results of this study have several implications for the three West African
countries’ goal of reaching regional self-sufﬁciency in food crops in West Aﬁica. First, all
cassava/maize systems under existing techniques are ﬁnancially and socially proﬁtable if
the output substitutes for imports on-farm or in markets near the site of production.
Second, the extent of divergences (especially for tradable inputs and factor prices)
observed in the three countries is relatively small (see tables A4-16 through A4-18 in

appendix 4); therefore, there is little scope for achieving easy improvements by removing

143

signiﬁcant price distortions.

Third, the simulation results indicate that the potential for governments to assist in
income growth lies in areas other than commodity market price policy. In Nigeria and
Ghana, protectionism can be viewed as an expression of an inward-looking import-
substitution strategy. Thus, the realization of income gains for cassava/maize farmers in
Nigeria and Ghana depended in the 1980s and the early 19905 on a change in foreign
exchange rate policy.

In Cote d’Ivoire and Ghana, simulation results indicate that cassava/maize farmers
could beneﬁt from growing IITA’s variety and adopting mechanized processing methods.
Baseline results for Nigeria clearly indicate that the Impmech technology combination
reduces labor costs, which is good in case of labor constraints. The proﬁtability of
cassava/maize systems will encourage their expansion and the reduction of the area
planted. One option is to invest in research and development programs that would

facilitate the adoption of the ITTA’s variety and mechanized processing methods.

144

REFERENCES

Babo, Alfred, Circuits de Commercialisation et de Transformation du Manioc dans la
Region de Bouake. Memoire de Maitrise. Option: Socio-Economie du
Developpement Rural. Universite de Bouake, 1996.

FAO, 1989-1992, Various issues

Monke, EA. and S. Pearson. 1989. The Policy Analysis Matrix for Agricultural
Development. Baltimore: John Hopkins University Press.

Nelson, G C and Panggabean, M (1991), The costs of Indonesian sugar policy: a policy
analysis matrix approach, American Journal of Agricultural Economics, 73 (3) pp
703-712

Nweke, F .I., Cassava Distribution in Sub-Saharan Aﬁica The Collaborative Study of
Cassava in Africa, Working Paper No. 12, 1994

Nweke, Felix I., K. N‘Goran, A.G.O. Dixon, B.O. Ugwu, O. Ajobo, and T.
Kouadio. 1998, Cassava production and processing in Cote d'Ivoire. COSCA
Working Paper No. 23, The Collaborative Study of Cassava in Aﬁica, IITA,
Ibadan, Nigeria.

Stryker J. Dirck, “ Trade, Exchange Rate, and Agricultural Pricing Policies in Ghana,”
World Bank Comparative Studies, 1990

Yao, Shujie, 1997. “Rice Production in Thailand Seen Through a Policy Analysis
Matrix”. Food Policy, 22(6):547-560

World Bank. 1993. World Development Report 1996.

145

APPENDIX 4

146

 

 

 

Net Enterprise Proﬁts (fcfa/ha)

 

 

Table A4-l: Estimated Average Financial Budget for Cassava/Maize Production
r Systems, Cote d’Ivoire: 1989/1991
1. INPUT USE Family Hired
F arnily/Hired Labor Use (person-days )
Land Clearing l8 l4
Seedbed Preparation 22 20
Weeding 12 14
Planting
Cassava 17 15
Maize 15 0
Harvesting
Cassava 27 ll
Maize 23 0
Total 134 74
2. OUTPUTS 10737
Average Root Yield (kg/ha) 6780
Average Maize Yield (ears/ha)! 15
Market Price of Root (fern/kg)2 25
Market Price of Green Maize (fcfa/ears)3 169500
Revenues from Green Maize (fcfa/ha) 161055
Revenues from Cassava Roots (fcfa/ha) 330555
Gross Revenues (fcfa/ha)
3. COSTS 0
Fixed Costs (fcfa/ha)4
Operating costs (fcfa/ha)
Hired Labor 446966200
Transportation ﬁeld-to-home (fcfa/ton) 4126
Interest on Working Capital (8%) 55706
Total Operating Costs (fcfa/ha) 34420
Family Labor (valued @ hired labor wage rate) 6083 5
Opportunity Cost of land
4. PERFORMANCE MEASURES 274349
Gross Margin (fcfa/ha) 214014
Net Returns to family Labor (fcfa/ha) 1597
Net Returns per day of Family Labor (fcfa/day) 200961
Total System Production Costs (fcfa/ha) 129594

 

Source: COSCA survey data

 

' Estimated using the “Ear Weight Method” discussed in Appendix 2. In West Africa, maize, which has a
short cycle, is harvested before cassava establishes. Hence competition between maize and cassava is
minimized, while sole plant density is maintained for both crops (COSCA Working Paper No.10, page 84).
2 Weighted average farmgate price based on COSCA data

3 Farmgate price based on personal communication with Centre Ivoirien de Recherches Economiques et
Sociales (CIRES).

4 Farmers did not purchase planting materials of food crops; they produwd their own: for cassava, only one
ﬁﬁh of the stems from previous harvest are retained for replanting and for maize, only 2 to 3 percent of the
harvest is retained for m. Therefore. the opportunity cost of planting materials, which is relatively
insigniﬁcant, is not counted.

147

Table A4-2: Estimated Average Financial Budget for Cassava/Maize Production

Systems, Ghana: 1989/1991
W ‘

 

J r

1. INPUT USE Family Hired
Family/Hired Labor Use (person-days)
Land Clearing 21 19
Seedbed Preparation 19 16
Weeding 17 21
Planting
Cassava 20 18
Maize l 7 0
Harvesting
Cassava 22 31
Maize 23 0
Total 139 105
12‘. OUTPUTS . 13042
verage Root Yield (kg/ha)
Average Maize Yield (ears/ha)‘ l 1526
Market Price of Root (cedis/kg)2 22
Market Price of Green Maize (cedis/ears)3 38
Revenues from Green Maize (cedis/ha) 2323;:
Revenues from Cassava Roots (cedis/ha) 724912
Gross Revenues (cedis/ha)
3. COSTS
Fixed Costs (cedis/ha)4 0
Operating costs (cedis/ha)
Hired Labor 105000
Transportation ﬁeld-to-home (cedis/ton of roots) 1902862:
Interest on Working Capital (8%) 125091
Total Operating Costs (cedis/ha) 139000
Family Labor (valued @ hired labor wage rate) 80508
Opportunity Cost of Land (cedis) 2
4. PERFORMANCE MEASURES 599821
Gross Margin (cedis/ha) 319313
Net Returns to family Labor (cedis/ha) 2297
Net Returns per day of Family Labor (cedis/day) 544599
Total System Production Costs (cedis/ha) 180313

Net Enterprise Proﬁts (cedis/ha)
Source: COSCA survey data

 

 

' Estimated using the “Ear Weight Method” described in Appendix 2 of chapter 2. In West Africa, maize,
which has a short cycle, is harvested before cassava establishes. Hence competition between maize and
cassava is minimized, while sole plant density is maintained for both crops. (COSCA Working Paper
No.10, page 84)

2 Weighted average farmgate price based on COSCA data

3 Farmgate price based on secondary source of information : the Dept. of Planning, Monitoring and
Evaluation (Ministry of Food and Agriculture, Accra, Ghana)

4 Farmers did not purchase planting materials of food crops; they produced their own: for cassava, only one
ﬁﬂh of the stems from previous harvest is retained for replanting, and for maize only 2 to 3 percent of the
harvest is retained for seed. Therefore, the opportunity cost of planting materials, which is relatively
insigniﬁcant, is not counted.

148

Table A4-3: Estimated Average Financial Budget for Cassava/Maize Systems
For Local Landraces, Nigeria: 1989/1991

ITBudget Items

1. INPUT USE Family Hired

Family/Hired Labor Use (person-days )

 

0 Land Clearing 23 22
e Seedbed Preparation 23 21
e Weeding 23 18
0 Plan ‘
ggsava l 9 l6
Maize 15 0
e Harvesting
Cassava 30 22
Maize 23 0
Total 99
2. OUTPUTS l 1215
Average Root Yield (kg/ha) 9614
Average Maize Yield (ears/ha)1 0.57
Market Price of Root (nairas/kg)2 1.5
Market Price of Green Maize (nairas/ears)3 14421
Revenues ﬁ'om Green Maize (nairas/ha) 63 93
Revenues from Cassava Roots (nairas/ha) 20314
Gross Revenues (nairas/ha)
3. COSTS 0
Fixed Costs (nairas/ha)4
Operating costs (nairas/ha) 2079
Hired Labor 1271
Transportation (nairas) 268
Interest on Working Capital (8%) 3613
Total Operating Costs (nairas/ha) 3381
Family Labor (valued @ hired labor wage rate) 3362
Opportunity Cost of land (nairas)
4. PERFORMANCE MEASURES
Gross Margin (nairas/ha) 17196
Net Returns to farme Labor (nairas/ha) 8334
Net Returns per day of Family Labor (nairas/day) 55
Total System Production Costs (nairas/ha) 15361
Net Enterprise Proﬁts (nairas/ha) r 5453

 

 

Source: COSCA survey data

 

' Estimated using the “Ear Weight Method” discussed in the appendix 2 of chapter 2. In West Africa,
maize, which has a short cycle, is harvested before cassava establishes. Hence competition between maize
and cassava is minimized, while sole plant density is maintained for both crops. (COSCA Working Paper
No.10, page 84)

2 Weighted average farmgate price based on COSCA data

3 F armgate price based on secondary source of information (personal communication with IITA)

‘ Farmers did not purchase planting materials of food crops; they produced their own: for cassava, only one
ﬁfth of the stems from previous harvest are retained for replanting and for maize, only 2 to 3 percent of
harvest is used for seed. Therefore, the opportunity cost of planting materials, which is relatively
insigniﬁcant, is not counted.

149

Table A4-4: Estimated Average Financial Budget per hectare for Attieke
Productionl in Cote d’Ivoire, 1989-1991, assuming that 45 % of roots

production goes into attieke production

 

 

Budget Items
1. INPUT USE Family Hired
Family/Hired Labor Use (person-days)2 57 0
Raw Material (kgs of roots)3 4832
2. OUTPUTS
Transformation Rate 0.56
Kilograms of Processed Output per ha 2706
Village Market Price of Processed Output (fcfa/kg)4 47
Gross Revenues (fcfa/ha) 127169
3. COSTS
Fixed Costs (fcfa/ha)5 0
Operating costs (fcfa/ha)
Hired Labor (persondays) 0
Raw Material (roots)6 72475
Bagging Materials 16234
Firewood 2205
Transportation7 7670
Interest on Working Capital (8%) 7 887
Total Operating Costs (fcfa/ha) 106471
Family Labor (valued @ hired labor wage rate) (fcfa/ha) 35910
4. PERFORMANCE MEASURES
Gross Margin (fcfa/ha) 20698
Net Returns to family Labor (fcfa/ha) 20698
Net Returns per day of Family Labor (fcfa/day) 363
Total production Costs (fcfa/ha) 142381
Net Enterprise Proﬁts (fcfa/ha) -15212
Production Costs per Kg of attieke Sfcfa/kg) 53

Source: COSCA data

 

' There were forty-three (43) farmers using traditional techniques versus three (3) using modern
techniques. Therefore, this budget includes only farmers using traditional (manual) processing
techniques.

2 This item includes labor for Peeling, Washing, Grating. Pressing, Sieving and Steaming.

3 This represents 45% of the average root yield per hectare (see page 23 in COSCA Working
Paper No 6)

4 Weighted average village market price estimated from COSCA data

5 No mechanical equipment was used in any processing activity. Grating was performed manually
(COSCA Working Paper No.14, page 15).

6 Valued at its opportunity cost which is the weighted average farmgate price computed from the
COSCA data

7 This item includes home-to-market transportation costs only.

150

Table A4-5: Estimated Average Financial Budget per hectare for Gari Production1
in Ghana, 1989-1991, assuming that 50% of roots production goes into

 

 

 

gari production L
3W—
1. INPUT USE Family Hired
Family/Hired Labor Use (person-days)2 32 19
Raw Material (kgs of roots)3 6521
2. OUTPUTS
Transformation Rate 0.31
Kilograms of Processed Output per ha 2022
Village Market Price of Processed Output (cedis/kg)4 117
Gross Revenues (cedis/ha) 236517
3. COSTS
Fixed Costs (cedis/ha)5 0
Operating costs (cedis/ha)
Hired Labor (persondays) 19000
Bagging Materials 1738
Raw Material (roots)6 143462
Firewood 1961
Transportation7 25855
Interest on Working Capital (8%) 15361
Total Operating Costs (cedis/ha) 2073 77
Family Labor (valued @ hired labor wage rate) (cedis/ha) 32000
4. PERFORMANCE MEASURES
Gross Margin (cedis/ha) 29139
Net Returns to family Labor (cedis/ha) 29139
Net Returns per day of Family Labor (cedis/day) 911
Average Total production Costs (cedis/ha) 2393 77
Net Enterprise Proﬁts (cedis/ha) -2861
Average Production Costs per Kg of gari (cedis/kg) 118

 

Source: COSCA data

 

‘ There were thirty-six (36) farmers using traditional techniques versus six (6) farmers using modern
techniques. Therefore, this budget includes only farmers using traditional (manual) processing techniques.
3 This item includes labor for peeling, washing, grating, pressing, sieving and roasting.

3 This represents 50% of the average root yield per hectare (see page 23 in COSCA Working Paper No 6)
3 Weighted average village market price estimated from COSCA data

5 No mechanical equipment was used in any processing activity. Grating was performed manually (COSCA
Working Paper No.14, page 15)

6 Valued at its opportunity cost which is the weighted average farmgate price computed from the COSCA
data.

7 This item includes home-to-market transportation costs only.

151

Table A4-6: Estimated Average Financial Budget per hectare for Carl Production
under Technology Combination “LOCMAN”, Nigeria, 1989/1991,

assuming 80% root eroduction goes into gari Broduction.

 

 

W
1. INPUT USE Family Hired
Family/Hired Labor Use (person-days)2 60 17
Raw Material (kgs of roots)3 8972
2. OUTPUTS
Transformation Rate 0.31
Kilograms of Processed Output per ha 2781
Village Market Price of Processed Output (nairas/kg)4 3.14
Gross Revenues (nairas/ha) 8733
3. COSTS
Fixed Costs (nairas/ha? 0
Operating costs (nairas/ha)
Hired Labor erson-days) 357
Raw material 51 14
Bagging Materials 259
Firewood 676
Transportation7 7 52
Interest on Working Capital (8%) 573
Total Operating Costs (nairas/ha) 7731
Family Labor (valued @ hired labor wage rate) (nairas/ha) 1260
4.PERFORMANCE MEASURES
Gross Margin (nairas/ha) 1003
Net Returns to family Labor (nairas/ha) 1003
Net Returns per day of Family Labor (nairas/day) 17
Total production Costs (nairas/ha) 8891
Net Enterprise Proﬁts (nairas/ha) ~257
Production Costs per Kg of gari (nairas/kg) 3.23

 

 

 

Source: COSCA data

 

‘ Local variety and manual Processing

2 This item includes labor for washing. cleaning, grating, pressing sieving and roasting.

3 This represents 80% of the average root yield per hectare (see page 128 in COSCA Working Paper
No.20)

4 Weighted average village market price estimated from COSCA data

3 No mechanical equipment was used in any processing activity. Grating was done manually ( COSCA
Working Paper No.14, page 15)

'3 Valued at its opportunity cost, which is the weighted average farmgate, price computed ﬁom the COSCA
data.

7 This item includes home-to-market transportation costs only.

152

Table A4-7: Economic Import Parity Price of Cassava Root

For Sale in Regional Output Markets, Ghana: 1989/1991.

 

 

Items Regional Output
Markets
Koforidua Kumassi

1. World Price ( FOB-$US/mt tapioca) 221 221

2. Freight and insurance ($US/mt tapioca) 8 48

3. CIF, port in Accra ( $US/mt tapioca) (1+2) 269 269

4. Shadow Exchange rate ( cedis / $US) 645 645

5. CIF price at the port in Accra ( cedis/mt tapioca) (3 *4) 173666 173666
6. Domestic costs (cedis/mt tapioca)

a. Port charges (cedis/mt tapioca) 47227 47227

b. Transit and Transport (cedis/mt tapioca) 7233 7233

c. Storage and Handling (cedis/mt tapioca) 15276 15276
7. Accra gate price (5+ 6a. . .c ) (cedis/mt tapioca) 243402 243402
8. Importer marketing margin (%) 5% 5%
9. Wholesale price in Accra (7* (1+ 8)) 255572 255572
10. Accra to Regional Market Center

a Distance (km) 75 254

b. Transport cost (cedis/mt tapioca) 6828 23114

c. Handling (cedis/mt tapioca) 4233 4233
11. Regional Market Center (Reference Price)

Farmgate price (cedis/mt tapioca) (9 + 10a..c ) 266630 282919
12. Wholesale marketing margin (%) 5% 5%
13. Wholesale price

in Regional Market (cedis/mt tapioca) (11* (1+12)) 279962 297065
14. Regional Market Center to Village
a. Distance (kms) 47 83
b. Transport and Handling cost (cedis/mt tapioca) 5076 8964
15. Village gate price (cedis/mt tapioca) (13-l4b) 274886 288101
16. Semi-wholesale marketing margin (%) 5% 5%
17. Village Level Semi-wholesale price ((1-
16)*15)/1000 261 274
18.Transformation rate (kg of tapioca / kg of root) 0.50 0.50
19. Processing cost (cedis/kg of root) 114 114
20. Import Parity Price in the Village (cedis /kg of root)
(17*18) -19 16 23

 

Source: COSCA data, Ghana Yearly Statistical Digests (1989-1991), Economic and Social Commission

for Asia and the Paciﬁc, Reports of 1989 through 1991.

153

Table A4-8: Economic Import Parity Price of Cassava Root- For Home

Consumtion, Cote d’Ivoire: 1989/1991.

 

 

Items Production Zones
Bonoua N’douci
Zone Zone
1. World Price (F OB-SUS/mt tapioca) 221 221
2. Freight and insurance ($US/mt tapioca) 48 48
3. CIF, port in Abidjan ($US/mt tapioca) (1+2) 269 269
4. Shadow Exchange rate (fcfa / $US) 394 394
5. CIF price at the port in Abidjan (fcfa/mt tapioca) (3*4) 105998 105998
6. Domestic costs (fcfa/mt tapioca)
a. Port charges (fcfa/mt tapioca) 700 700
b. Transit and Transport (fcfa/mt tapioca) 2000 2000
c. Storage and Handling (fcfa/mt tapioca) 2000 2000
7. Abidjan gate price (5+ 6a. . . c ) (fcfa/mt tapioca) 8. 110698 110698
Importer marketing margin (%) 5% 5%
9. Wholesale price in Abidjan (7* (1+ 8)) 116233 116233
10. Abidjan to Regional Market Center
a Distance (km) 75 130
b. Transport cost (fcfa/mt tapioca) 2625 4550
c. Handling (fcfa/mt tapioca) 2000 2000
11. Regional Market Center (Reference Price)

Farmgate price (fcfa/mt tapioca) (9 + 10a..c) 120858 122783
12. Wholesale marketing margin (%) 5% 5%
13. Wholesale price

in Regional Market ( fcfa/mt tapioca) (11* (1+12)) 126901 128922
14. Regional Market Center to Village
a. Distance (kms) 37 56
b. Transport and Handling cost (fcfa/mt tapioca) 3665 4520
15. Village gate price (fcfa/mt tapioca) (13+14b) 130566 133442
16. Semi-wholesale marketing margin (% ) 5% 5%
17. Village Level Semi-wholesale price ((1+16
)*15)/1000 137 140
18.Transformation rate ( kg of tapioca / kg of root) 0.5 0.5
19. Processing cost (fcfa/kg of root) 46 43
20. Import Parity Price in the Village (cfaf /kg of root)
(17*18) -19 22 27

 

Source: COSCA data. Institut de Documentaion de Recherches et d’Etudes Maritimes of the Ivorian
Marine Ministry; UN Economic and Social Commission For Asia and the Paciﬁc, Reports of 1989 through

1991.

154

 

Table A4-9a: Economic Import Parity Price of Cassava Root, by Alternative

Technology Combinations. For Sale in the Regional Output Market of

Abeokuta, Nigeria: 1989/1991.

 

Items

 

1. World Price (F OB-$US/mt tapioca)
2. Freight and insurance ($US/mt tapioca)
3. CIF, port in Lagos ( $US/mt tapioca) (1+2)
4. Shadow Exchange rate ( nairas / $US)
5. CIF price at the port in Lagos ( nairas/mt
tapioca) (3*4)
6. Domestic costs (nairas/mt tapioca)
a. Port charges (nairas/mt tapioca)

b. Transit and Transport (nairas/mt tapioca)
c. Storage and Handling (nairas/mt tapioca)
7. Lagos gate price (5+ 6a.. .c ) (nairas/mt
tapioca)

8. Importer marketing margin (%)
9. Wholesale price in Lagos (7* (1+ 8))
10. Lagos to Regional Market Center

a Distance (km)

b. Transport cost (nairas/mt tapioca)

c. Handling (nairas/mt tapioca)
11. Regional Market Center (Reference Price)
Farmgate price (nairas/mt tapioca) (9 +10a..c)
12. Wholesale marketing margin (%)

13. Wholesale price in Regional Market
(nairas/mt tapioca) (11* (1+12))

14. Regional Market Center to Village

a. Distance (kms)

b. Transport and Handling cost (nairas/mt

tapioca)

15. Village gate price (nairas/mt tapioca)
(13-14b)

16. Semi-wholesale marketing margin (%)
17. Village Level Semi-wholesale price
(1-16 )*15)/1000

18.Transformation rate (kg of tap./ kg of root)
19. Processing cost (nairas/kg of root)
20. Import Parity Price in the Village (nairas
/kg ofroot) (17*18) -19

 

Source: COSCA data, UNCTAD’s Review of Maritime Transport 1989-1992, Nigerian

Regional Oumut Market

 

 

221
48
269
22

5950
95
206
203
6454
5%
6777
80
288
1 14

7179
5%

7538

34
176

7362
5%
6.99
0.50
3.05

0.45

 

 

lAbeokuut
221 221
48 48
269 269
22 22
5950 5950
95 95
206 206
203 203
6454 6454
596 596
6777 6777
80 80
288 288
114 114
7179 7179
596 596
7538 7538
34 34
176 176
7362 7362
596 596
(399 (599
(150 (150
314 2126
(136 (124

I mech Locmech Locman I man

221
48
269
22

5950
95
206
203
6454
5%
6777
80
288
l 14

7179
5%

7538

34
176

7362
5%
6.99
0.50
3.4]

0.08

Port Authority Statistical Reports 1989-1992, UN Economic and Social Commission For

Asia and the Paciﬁc, Reports of 1989 through 1991.

155

Table A4-9b: Economic Import Parity Price of Cassava Root, by Alternative
Technology Combinations. For Sale in the Regional Output Market of

Onitsha, Nigeria: 1989/1991.

 

 

 

 

 

 

 

Source: COSCA data, UNCTAD’s Review of Maritime
Port Authority Statistical Reports (1989-1992), UN Economic and Social Commission

For Asia and the Paciﬁc, Reports of 1989 through 1991.

156

Items RegionaLQutpuLMazket
Onitsha
_ Impmech Locmech Locman [mm—an-
1. World Price ( F OB-SUS/mt tapioca) 221 221 221 221
2. Freight and insurance ($US/mt tapioca) 48 48 48 48
3. CIF, port in Lagos ( $US/mt tapioca) (1+2) 269 269 269 269
4. Shadow Exchange rate ( nairas / $US) 22 22 22 22
5. CIF price at the port in Lagos (3 *4) 5950 5950 5950 5950
6. Domestic costs (nairas/mt tapioca)
a. Port charges (nairas/mt tapioca) 95 95 95 95
b.Transit and Transport (nairas/mt tapioca) 206 206 206 206
c. Storage and Handling (nairas/mt tapioca) 203 203 203 203
7.Lagos gate price (5+ 6a.c)(nairas/mt
tapioca) 6454 6454 6454 6454
8. Importer marketing margin (%) 5% 5% 5% 5%
9. Wholesale price in Lagos (7 * (1+ 8)) 6777 6777 6777 6777
10. Lagos to Regional Market Center
a Distance (km) 420 420 420 420
b. Transport cost (nairas/mt tapioca) 1512 1512 1512 1512
c. Handling (nairas/mt tapioca) 114 114 114 114
11. Regional Market Center (Reference Price)
Farmgate price(nairas/mt tapioca) (9 + 10a..c) 8403 8403 8403 8403
12. Wholesale marketing margin (%) 5% 5% 5% 5%
13. Wholesale price in Regional Market
(nairas/mt tapioca) (11* (1+12)) 8823 8823 8823 8823
14.Regiona1 Market Center to Village
a. Distance (kms) 97 97 97 97
b. Transport and Handling cost (nairas/mt 497 497 497 497
tapioca)
15.Village gate price (nairas/mt tapioca)13- 83 26 8326 8326 8326
14b)
16. Semi-wholesale marketing margin (%) 5% 5% 5% 5%
1 7. Village Level Semi-wholesale price(( 1 -1 6
)*15)/1000 8 8 8 8
18.Transformation rate (kg tap./ kg of root) .50 .50 .50 .50
19. Processing cost (nairas/kg of root) 3.09 3.21 3.36 3.60
20. Import Parity Price in the Village (nairas
/kg ofroot) (17*18)-19 0.89 0.77 0.61 0.38

 

Transport 1989-1992, Nigerian

Table A4-10: Estimated Economic Farm Level Budget for Commercial
Cassava/Maize Production Systems, by Regional Output Markets,
Ghana, 1989/1991

 

 

Budget Items Regional Output Markets
Koforidua Kumassi
l. OUTPUTS
Average Root Yield (kg/ha) 14346 13694
Average Green Maize Yield (ears/ha)l 11526 11526
Market Price of root (cedis/kg)2 16 23
Market Price of Green Maize (cedis/ear)3 38 38
Revenues ﬁ'om Root (cedis lha) 232278 317113
Revenues from Green Maize (cedis lha) 437988 43 7988
Gross Revenues (cedis /ha) 670266 755101
2. COSTS
Fixed Costs (/ha)4
Operating costs (/ha) 0 O
Hired Labor5 95000 91000
Transportation (cedis/ton)
Tradable 14256 13640
Nontradable 23 76 2273
Interest on Working Capital (8%) 8931 8553
Total Operating Costs (cedis /ha) 120563 115466
Family Labor (@ hired labor wage rate) (cedis /ha) 145000 158000
Opportunity Cost of Land6 (cedis/ha) 280508 280508
3. PERFORMANCE MEASURES
Gross Margin (cedis /ha) 549703 639636
Net Returns to family Labor (cedis /ha) 269195 359128
Net Returns per day of Family Labor (cedis /day) 1857 2273
Total production Costs (cedis /ha) 546071 553974
Net Economic Proﬁts (cedis lha) 124195 201128

 

Source: COSCA survey data

 

1 Estimated Farmgate price using the “Ear Weight Method” discussed in Appendix 2 of chapter.

3 Estimated farm level import parity price of root.

3 Farmgate price based on secondary source of information: the Dept. of Planning, Monitoring and
Evaluation (Ministry of food and Agriculture, Accra, Ghana).

4 Farmers did not purchase planting materials of food crops; they produced their own: for cassava, only one
ﬁfth of the stems from previous harvest is retained for replanting and for maize, only 2 to 3 percent of the
harvest is retained for seed. Therefore, the opportunity cost of planting materials, which is relatively
insigniﬁcant, is not counted.

3 Although niral labor markets in West Aﬁica are complex, it is reasonable to assume that market wages
offer good approximations to shadow wages (Humphreys in Rice in West Africa, p. 80, 1981).

6 Land is very rarely sold or rented. In this budget, the opportunity cost of land is estimated as the net return
to land that farmers would enjoy if they produced green maize only.

157

TableA4-l 1:

Ghana, 1989/1991

 

Estimated Financial Farm Level Budget for Commercial
Cassava/Maize Production Systems, by Regional Output Markets,

 

 

 

 

Budget Items Regional Output Markets
Koforidua Kumassi

l. OUTPUTS .
Average Root Yield (kg/ha) 14346 13694
Average Green Maize Yield (ears/ha)l 11526 11526
Market Price of root (cedis/kg)2 22 22
Market Price of Green Maize (cedis/ear)3 38 38
Revenues from Root (cedis /ha) 315616 301270
Revenues from Green Maize (cedis /ha) 43 7988 43 7988
Gross Revenues (cedis lha) 753604 739258
2. COSTS
Fixed Costs (fha)4
Operating costs (/ha) 0 0

Hired Labor5 95000 91000

Transportation (cedis/ton)

Tradable 9504 9093
Nontradable 2376 2273
Interest on Working Capital (8%) 8550 8189

Total Operating Costs (cedis /ha) 115430 110555
Family Labor (@ hired labor wage rate) (cedis /ha) 145000 158000
Opportunity Cost of Land6 (cedis/ha) 280508 280508
3. PERFORMANCE MEASURES
Gross Margin (cedis /ha) 638174 628703
Net Returns to family Labor (cedis lha) 357666 348195
Net Returns per day of Family Labor (cedis /day) 2467 2204
Total production Costs (cedis /ha) 540938 549063
Net Economic Proﬁts (cedis /ha) 212666 190195

 

Source: COSCA survey data

 

‘ Estimated Farmgate price using the “Ear Weight Method" discussed in appendix 2 of chapter 2.

3 Weigthed average farmgate price based on COSCA data.

3 Farmgate price based on secondary source of information: the Dept. of Planning, Monitoring and
Evaluation (Ministry of food and Agriculture, Accra, Ghana).

4 Farmers did not purchase planting materials of food crops; they produced their own: for cassava, only one
ﬁfth of the stems from previous harvest per hectare and for maize only 1 to 2 percent of harvest. Therefore,
the opportunity cost of planting materials, which is relatively insigniﬁcant, is not counted.

3 Given that available labor in West African rural areas are mostly unskilled, it is assumed that ﬁnancial
labor cost per day reﬂects the economic cost of labor.

6 Land is very rarely sold or rented. In this budget, the opportunity cost of land is estimated as the return to
land that farmers would enjoy if they produced green maize only.

158

 

Table A4-12: Estimated Economic Farm Level Budget for Commercial
Cassava/Maize Production Systems, by Regional Output Markets,

Cote d’Ivoire, 1989-1991

 

 

 

 

 

Budget Items Regional Output
Markets

J ﬁr Bonoua N’douci
l. OUTPUTS
Average Root Yield (kg/ha) 11811 11274
Average Green Maize Yield (ears/ha)l 3994 3994
Market Price of root (fcfa/kg)2 12 16
Market Price of Green Maize (fcfa/ear)3 25 25
Revenues from Root (fcfa /ha) 142989 183303
Revenues from Green Maize (fcfa /ha) 99850 99850
Gross Revenues (fcfa lha) 242839 283153
2. COSTS
Fixed Costs (lha)4 0 0
Operating costs (lha)

Hired Labor5 49140 47880

Transportation ﬁeld-to-home (fcfa)

Tradable 6460 6166
Nontradable 1091 1042
Interest on Working Capital (8%) 4535 4247

Total Operating Costs (fcfa lha) 61226 57335
Family Labor (valued @ hired labor wage rate) (fcfa lha) 88830 90090
Opportunity Cost of Land6 (fcfa/ha) 60835 60835
3. PERFORMANCE MEASURES
Gross Margin (fcfa /ha) 181613 223658
Net Returns to family Labor (fcfa /ha) 120778 162823
Net Returns per day of Family Labor (fcfa /day) 857 1139
Total production Costs (fcfa /ha) 210891 210420
Net Social Proﬁts (fcfa /ha) 31948 72733

 

Source: COSCA survey data

 

' Estimated Farmgate price using the “Ear Weight Method” discussed in Appendix 2 of chapter 2.

2 Estimated fartn level import parity price of root

3 Farmgate price based on personal communication with Centre Ivoirien de Recherches Economiques et
Sociales (CIRES).

4 Farmers did not purchase planting materials of food crops; they produced their own: for cassava, only one
ﬁfth of the stems from previous harvest is retained for replanting and for maize, only 2 to 3 percent of the
harvest is retained for seed. Therefore, the Opportunity cost of planting materials, which is relatively
insigniﬁcant. is not counted

3 Although rural labor markets in West Africa are complex, it is reasonable to assume that market wages
offer good approximations to shadow wages (Humphreys in Rice in West Africa, p. 80, 1981).

6 Land is very rarely sold or rented. In this budget, the opportunity cost of land is estimated as the net return
to land that farmers would enjoy if they produwd green maize only.

159

Table A4-13: Estimated Financial Farm Level Budget for Commercial
Cassava/Maize Production Systems, by Regional Output Markets,
Cote d’Ivoire, 1989-1991

 

 

 

 

Budget Items Regional Output
Markets
Bonoua- N’douci

l. OUTPUTS
Average Root Yield (kg/ha) 11811 11274
Average Green Maize Yield (ears/ha)l 3994 3994
Market Price of root (fcfa/kg)2 15 15
Market Price of Green Maize (fcfa/ear)3 25 25
Revenues ﬁ'om Root (fcfa /ha) 17 7161 169108
Revenues from Green Maize (fcfa /ha) 99850 99850
Gross Revenues (fcfa /ha) 277011 268958
2. COSTS
Fixed Costs (lha)4 0 0
Operating costs (/ha)

Hired Labor 49140 47880

Transportation (fcfa)

Tradable 4365 4166
Nontradable 1091 1042
Interest on Working Capital (8%) 4368 4247

Total Operating Costs (fcfa /ha) 58964 57335
Family Labor (valued @ hired labor wage rate) (fcfa /ha) 88830 90090
Opportunity Cost of Land3 (fcfa/ha) 60835 60835
3. PERFORMANCE MEASURES
Gross Margin (fcfa lha) 218047 211623
Net Returns to family Labor (fcfa lha) 157212 150788
Net Returns per day of Family Labor (fcfa /day) 1115 1054
Total production Costs (fcfa /ha) 208629 208260
Net Enterprise Proﬁts (fcfa /ha) 683 82 60698

 

Source: COSCA survey data

 

‘ Estimated Farmgate price using the “Ear Weight Method” discussed in Appendix 2 of chapter 2.

2 Weighted average farmgate price based on COSCA data.

3 Farmgate price based on personal communication with Centre Ivoirien de Recherches Economiques ct
Sociales (CIRES).

4 Farmers did not purchase planting materials of food crops; they produced their own: for cassava, only one
ﬁfth of the stems from previous harvest is retained for replanting and for maize, only 2 to 3 percent of
harvest. Therefore, the opportunity cost of planting materials, which is relatively insigniﬁcant, is not
counted.

3 Land is very rarely sold or rented. In this budget, the opportunity cost of land is estimated as the net return
to land that farmers would enjoy if they produced green maize only.

160

Table A4-l4: Estimated Economic Budget for Commercial Cassava/Maize Systems
under Technology Combination “LOCMAN’”, by Regional Output
Markets, Nigeria, 1989/1991

 

 

 

Budget Items Regional OuQut Markets
Abeokuta Onitsha
1. OUTPUTS
Average Root Yield (kg/ha) 12337 11776
Average Green Maize Yield (ears/ha)2 9614 9614
Market Price of root (nairas/kg)3 0.24 0.61
Market Price of Green Maize (nairas/ear)4 1.5 1.5
Revenues from Root (nairas /ha) 2911 7230
Revenues from Green Maize (nairas /ha) 14421 14421
Gross Revenues (nairas /ha) 17332 21651
2. COSTS
Fixed Costs (nairas/ha)3 0 0
Operating costs (nairas/ha)
Hired Labor6 1680 1995
Transportation (nairas)
Tradable 1538 1472
Nontradable 296 283
Interest on Working Capital (8%) 281 300
Total Operating Costs (nairas /ha) 3795 4050
Family Labor (@ hired labor wage rate) (nairas lha) 2688 3486
Opportunity Cost of Land7 (nairas/ha) 8362 8362
4. PERFORMANCE MEASURES
Gross Margin (nairas lha) 13536 17601
Net Returns to family Labor (nairas /ha) 5174 9239
Net Returns per day of Family Labor (nairas /day) 40 56
Total production Costs (nairas lha) 14845 15898
Net Economic Proﬁts (nairas /ha) 2486 5753

 

Source: COSCA survey data

 

‘ Local variety and manual processing

2 Estimated using the “Ear Weight Method” discussed Appendix 2 of chapter 2.

3 Estimated Farm Level Import Parity Price of root

4 Farmgate price based on secondary source of information (personal communication with UTA).

3F armers did not purchase planting materials of food crops but produced their own: for cassava, only one
ﬁfth of the stems from previous harvest are retained for replanting and for maize, only 2 to 3% of the
previous harvest is saved for md. Therefore, the opportunity cost of planting materials, which is relatively
insigniﬁcant. is not counted.

3 Although rural labor markets in West Aﬁica are complex, it is reasonable to assume that market wages
offer good approximations to shadow wages (Humphreys in Rice in West Africa, p. 80, 1981).

7 Land is very rarely sold or rented. In this budget, the opportunity cost of land is estimated as the Gross
Margin that farmers would enjoy if the produce green maize only.

161

Table A4-15: Estimated Financial Farm Level Budget for Subsistence
Cassava/Maize Production Systems, by Regional Output Markets,
Cote d’Ivoire, 1989-1991

 

 

 

Budget Items Regional Output
Markets
_ Bonoua N’douci
l. OUTPUTS
Average Root Yield (kg/ha) 11811 11274
Average Green Maize Yield (ears/ha)l 3994 3994
Market Price of root (fcfa/kg)2 15 15
Market Price of Green Maize (fcfa/ear)3 25 25
Revenues ﬁ'om Root (fcfa lha) 177161 169108
Revenues from Green Maize (fcfa /ha) 99850 99850
Gross Revenues (fcfa /ha) 277011 268958
2. COSTS
Fixed Costs (lha)4 0 0
Operating costs (/ha)
Hired Labor 49140 47880
Transportation (fcfa)
Tradable 43 65 4166
Nontradable 1091 1042
Interest on Working Capital (8%) 4368 4247
Total Operating Costs (fcfa /ha) 58964 57335
Family Labor (valued @ hired labor wage rate) (fcfa /ha) 88830 90090
Opportunity Cost of Land3 (fcfa/ha) 60835 60835
3. PERFORMANCE MEASURES
Gross Margin (fcfa lha) 218047 211623
Net Returns to family Labor (fcfa lha) 157212 150788
Net Returns per day of Family Labor (fcfa /day) 1115 1054
Total production Costs (fcfa /ha) 208629 208260
Net Enterprise Proﬁts (fcfa /ha) 683 82 60698

 

 

Source: COSCA survey data

 

' Estimated Farmgate price using the “Ear Weight Method” discussed in Appendix 2.

2 Weighted average farmgate price based on COSCA data.

3 Farmgate price based on personal communication with Centre Ivoirien de Recherches Economiques et
Sociales (CIRES).

4 Farmers did not purchase planting materials of food crops; they produced their own: for cassava, only one
ﬁfth of the stems from previous harvest is retained for replanting and for maize, only 2 t0 3 percent of
harvest. Therefore, the opportunity cost of planting materials, which is relatively insigniﬁcant, is not
counted.

3 land is very rarely sold or rented. In this budget, the opportunity cost of land is estimated as the net return
to land that farmers would enjoy if they produced green maize only.

162

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163

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164

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165

CHAPTER 5

CONCLUSIONS AND EXTENSIONS

Sub-Saharan Africa (SSA) cassava- producing countries such as Nigeria, Ghana,
and cote d’Ivoire have developed, in recent years, an interest in cassava as an alternative
food crop. This has led to a major expansion in cassava- based production systems in
Nigeria and Ghana, whereas there has been a slower growth in Céte d’Ivoire (Nweke et
al., 1998).

This study was based on the argument that the difference in various factors such
as agricultural policies (i.e., trade and price policies, domestic production taxes or
subsidies), location and technologies (production and processing) between Nigeria,
Ghana and C6te d’Ivoire explain the difference in the level of grth in cassava-based
production systems.

The main objective of this study was to examine the magnitude of the impact of
these factors on the private and social proﬁtability of cassava production and post-
production processing in Cote d’Ivoire, Ghana and Nigeria.

The topic has not been examined in previous studies. The study relied primarily
on data for cote d’Ivoire, Ghana and Nigeria from the Collaborative Study of Cassava in

Africa (COSCA) survey. The data were collected between 1989 and 1992.

166

5.1. Regarding the Impact of Various Factors (e.g., agricultural policies, location
and technologies) on the Profitability of Cassava-based Production Systems in West
Africa

In the preceding chapters, the policy analysis matrix (PAM) model was used in
three essays: 1) to evaluate the effects of government policies (i e., outputs and inputs
pricing policies and trade policies) and location of production on the relative proﬁtability
and comparative advantage of cassava/maize and rainfed rice/maize systems in the humid
lowland zones of Cote d’Ivoire; 2) to examine the relative proﬁtability (ﬁnancial and
social) and comparative advantage of cassava/maize production systems under four
alternative production and processing technology-combinations in Nigeria: “Impmech”,
“Locmech”, “Locman”, and “Impman” deﬁned as follows: a) Impmech refers to IITA’s
improved cassava variety processed using a mechanized grating method, b) Locmech
refers to local cassava variety processed using a mechanized grating method, c) Locman
refers to local cassava variety processed using a manual grating method), (1) Impman
refers to IITA’s improved cassava variety processed using a manual grating method; and
3) to compare the magnitude of the impact of agricultural policies, technologies
(production and processing) and location of production on the private and social
proﬁtability of cassava/maize production systems in three West Aﬁican countries (Cote
d’Ivoire, Ghana and Nigeria). The intent of this comparative essay was to use the PAM
approach to push the proﬁtability analysis ﬁirther than can be done within the context of
a single country. A summary of the principal conclusions presented in each essay
follows. However, at this point, it is worth noting the limitations of this study:

1. The economic import parity prices of cassava roots used in the analyses

were estimated, based on the import parity price of tapioca, a close substitute of attieke,

167

which is not internationally traded. This was considered more appropriate than valuing
cassava as a nontraded good, based on the domestic market price. However, these import
parity prices may not reﬂect the true economic price of cassava roots in Cote d’Ivoire.

2. Unfortunately, the COSCA study did not record maize yields on its sample
ﬁelds. Therefore, in computing the enterprise budgets developed in this study, it was
assumed that those ﬁelds got the national average maize yield, which was then converted
to the number of fresh corn ears using the “Ear-Weight Method” discussed in the
appendix of chapter 2. Corn ears were subsequently valued at the fresh corn price per ear.

3. At the market level, the PAM does not consider supply and demand
interactions involving changes in input and output prices. Furthermore, it is assumed that
market prices are given. This assumption implies that changes in the scale of the
productive activity have no effect on either price paid or received.

The baseline results in essay 1 (chapter 2) showed that cassava/maize systems
have a competitive advantage over their competitors in Cote d’Ivoire. That is,
proﬁtabilities (ﬁnancial and social) of cassava/maize systems signiﬁcantly exceed those
of rainfed rice/maize systems. These results indicated that cassava/maize production
systems were efﬁcient given current technologies. In addition, the baseline results
indicated that, farmers operating at the Bonoua market (near urban center) beneﬁt from a
small implicit price support whereas farmers Operating in N’douci (distant from urban

center) were subject to a small implicit tax (table 5.1).

168

Table 5.1: Financial and Economic Prices (in francs CFA) of cassava roots by
Output markets, Cote d’Ivoire, 1989/1991

 

 

 

 

Prices lMarkets Bonoua N ’douci
Financial Prices 15 1 5
Economic Prices 12 16
Differentials +3 - 1

 

 

 

 

 

Source: COSCA data and table A2-3 in Appendix 2

Table 5.2: Financial and Economic Prices (in francs CFA) of paddy,
Cote d’Ivoire, 1989/1991

 

 

 

 

Prices \Markets Bonoua N’douci

(Close to the port city) (Distant from the port city)
Financial Prices 60 60
Economic Prices 59 65
Differentials +1 -5

 

 

 

 

 

Source: COSCA data and table A2-4 in Appendix 2

On the other hand, the farm-gate market ﬁnancial price of paddy is 60 fcfa which
departs from its estimated import parity price by +1 fcfa per kilogram when Bonoua is
used as a point of sale and -5 fcfa per kilogram when N’douci is used as a point of sale
(table 5.2).

It should be emphasized that these differentials are relatively small. With this in
mind, here are some plausible explanations of why market (ﬁnancial) prices and
economic prices (import parity prices) did not equal in both markets. The divergences
between these two prices could be due to a combination of the effect of the rice import
tariff and the effect of the overvaluation of the franc CFA. The indirect effect of the rice
import tariff will be an increase in the ﬁnancial price of cassava root relative to the
economic price in the two markets (Bonoua and N’douci). On the other hand, the
currency overvaluation will have the effect of lowering the ﬁnancial price of tradables

such as roots and transport in both markets.

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However, the magnitude of the reduction in prices will be large in N’douci and
small in Bonoua because the share of transport costs in the import parity price is
relatively large for N’douci (distant from the port city) and relatively small for Bonoua
(close to the port city). Transportation costs thus provide a natural protection to domestic
producers who supply markets located far from the import point.

Thus, the net effect is as follows: 1) in N’douci: an increase in the ﬁnancial price
of roots due to the import tariﬁ and a relatively large decrease in the ﬁnancial price of
roots due to the currency overvaluation (via its impact on tradable goods such as cassava
and transport costs); and 2) in Bonoua: an increase in the price of roots due to the import
tariﬁ‘ and a relatively small decrease in the ﬁnancial price of roots due to the currency
overvaluation.

During the period of the survey, Ivorian farmers only grew local landrace cassava
variety. To test the robustness of the baseline results, a sensitivity analysis was carried
out under the assumption that farmers would adopt the HTA improved variety. The
simulation ﬁndings indicated that: l) a 5 to 15 percent increase in yields per hectare of
cassava and rainfed rice would not only ﬁirther enhance the comparative advantage of
cassava/maize systems but also cause rice/maize systems, which were unproﬁtable at the
baseline, to become socially proﬁtable; and 2) a 35% depreciation of the equilibrium
exchange rate (more fcfa per $US) also increased the proﬁtability of both systems.

The second essay (chapter 3) dealt with the evaluation of the social proﬁtability of
cassava/maize systems, under alternative production and processing technology
combinations, in Nigeria. The baseline results show that the net social proﬁtabilities

(N SP) of systems under “Impmech” technology exceed those of systems under other

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alternative technologies, namely “Locmech”, “Locman” and “Impman”. That is, systems
under “Impmech” are the most efﬁcient use of national resources. This is an important
ﬁnding in the sense that it indicates clearly that returns to both the better cultivars (IITA’s
variety) and the better processing method (mechanical graters) are higher than adopting
either one separately.

Baseline results were reestimated under alternative scenarios. The simulation
results indicated that a depreciation of the real exchange rate (more nairas per US dollar)
would increase signiﬁcantly the proﬁtabilities of cassava/maize systems under the
technology combinations “Impmech” and “Locmec ”. The lack of proﬁtability of
“Impman” and “Locman” is due to the fact that these are returns to roots (not gari)
production, but the economic price of roots depends on the import parity price of tapioca
and the assumed processing technology. The more efﬁcient processing technology (the
mechanized method) is assumed to bid up the price of the root, as more processed
product (represented by tapioca) can be obtained from each kilogram of roots. With a
higher economic value of output (in local currency terms), the returns to the more
technically efﬁcient mechanical processing increases.

The ﬁnal essay (chapter 4) borrowed results ﬁom the ﬁrst two essays and
constructed a PAM for Ghana to compare the competitiveness of cassava/maize systems
in Cote d’Ivoire, Ghana and Nigeria. The baseline results compared in this study
demonstrated the similarity in efﬁciencies of production in these West African countries.
The difference between the DRCs (table 4-8) of the three countries is minimal, although
labor input (in monetary terms) for Nigeria and Ghana is 15 to 30 percent higher than for

Cote d’Ivoire. This is due to the fact that higher output prices in Nigeria and Ghana

171

overcome the high labor inputs cost (higher wages). Overall, the baseline results showed
that the extent of divergences between ﬁnancial and economic prices (especially for
tradable inputs and domestic factors prices) observed in the three countries is relatively
small.

Again, a sensitivity analysis was carried out. The simulation ﬁndings indicated
that, in Cote d’Ivoire, farmers beneﬁted from the depreciation of the equilibrium
exchange rate while farmers in Ghana and Nigeria suffered losses. The impact of this
change in shadow exchange rates was of greater magnitude in Ghana, causing cassava
production systems to become inefﬁcient (tables 4-11 and 4-12 in Chapter 4). This
counter-intuitive result can be explained by the fact that in Ghana, farm level wage rates
rose from 1000 cedis to 4000 cedis (a 300 percent increase) while output price rose from
22 cedis to 65cedis (a 195 percent increase). Simulation results also indicated that Ivorian
and Ghanaian cassava/maize farmers could beneﬁt from growing HTA’s improved
variety and adopting mechanized processing methods.

5.1.1. Agricultural Policies

The results of this study have several implications for the three West Aﬁican
countries’ goal of reaching regional self-sufﬁciency in food crops in West Aﬁica.

First, the simulation results indicated that the potential for governments to assist
in income growth lies in areas other than commodity market price policy. In Nigeria and
Ghana, protectionism can be viewed as an expression of an inward-looking import-
substitution strategy. Thus, the realization of income gains for cassava/maize farmers in
Nigeria and Ghana depended in the 19805 and the early 1990s on a change in foreign

exchange rate policy.

172

Second, in Cote d’Ivoire and Ghana, simulation results indicated that
cassava/maize farmers could beneﬁt ﬁ'om growing lITA’s variety and adopting
mechanized processing methods. Baseline results for Nigeria clearly indicated that the
“Impmech ” technology combination reduces labor costs, which is good in case of labor
constraints. The greater proﬁtability of cassava/maize systems compared to rainfed
rice/maize systems should encourage their expansion and the reduction of the area
planted.

Another policy implication that can be drawn from this study relate to the ﬁnding
that in Cote d’Ivoire, the cost of kilocalorie production is considerably lower via
cassava/maize systems than it is via rainfed rice/maize systems. What this conclusion
means is that, in terms of food security, cassava/maize systems have a huge potential to
help the poor. Therefore, Ivorian policymakers could capitalize on this potential. One
option is to invest in research and development programs that would facilitate the
adoption of the ITTA’s variety and mechanized processing methods.

However, as already discussed in chapter 1, various policy outcomes may be
efﬁcient given policy-makers’ deﬁnition of different economic agents’ property rights at
that point of time. Policies are instruments of action that governments employ to effect
change in a given period (often one year) for a given situation. Thus policy outcomes are
situation-speciﬁc and time-speciﬁc. The point being that an efficiency objective is
relevant given the structure of property rights that underlie it. A change in property rights

will result in a change in what is efﬁcient.

173

5.1.2. Technologies

Simulation results in essay 3 (chapter 4) indicated that cassava farmers in Cote
d’Ivoire and Ghana could beneﬁt from growing IITA’s improved variety and adopting
mechanized processing methods. However, COSCA data indicate that mechanized
processing methods were available in Cote d’Ivoire but Ivorian farmers made very little
use of them. Farmers claim, according to the survey, that the wet paste obtained from
manual grating resulted in better quality attieke (called A gbodjama) than the attieke from
the paste obtained from motorized graters.

This suggests that improved processing technologies are needed but they must ﬁt easily
into farmers crop and food production systems and consumer preferences. For example,
graters must meet local post-harvest requirements in terms of cooking quality. The
question that arises for technology generation and transfer institutions is whether national
research institutions in Cote d’Ivoire are working on the production of an adequate
stream of processing technologies that meet the characteristics above.

Although, the development of appropriate technology is necessary, it is not a
sufficient condition for ensuring its adoption. One must design a system of technology
transfer that provides farmers with inputs and information they need to enhance
productivity. The adoption of mechanized graters, for example, will be conditioned by
the elasticity of supply of cassava roots, the availability of farm credit, and price policies.
There is ample evidence that small-scale farmers in Africa do accept well-adapted
technologies, once these are made available, along with appropriate institutional support

(Byerlee and Heisey, 1992).

174

5.2. Extensions

There are three other areas of interest for ﬁirther research. One important issue is
the marketing systems for processed cassava products. The marketing system for these
products is deﬁned here as a distribution system ﬁom processors to consumers. The
performance of this system needs to be evaluated in term of its emciency with respect to
various factors such as time, space and its capacity and ﬂexibility to handle varying
quantities of outputs. The internal marketing system transmits world prices to domestic
cassava markets and allocates cassava production among its various domestic and
international uses. The efﬁciency of the marketing system helps to determine incentives
to cassava producers and costs to consumers of cassava products. Particularly important
would be to examine how cassava marketing has changed since the end of the COSCA
studies in 1991, with the increase in the export of cassava chips to Europe for livestock
feed.

The second issue, that needs to be studied, is the lack of adoption of improved
production and processing technologies in Cote d’Ivoire and Ghana. COSCA data
indicate that new IITA production technologies have not been widely introduced to
farmers in both countries. As already mentioned, in Nigeria, production systems under
the “Impmech” technology (IITA’s improved cassava variety processed using
mechanized grating) generate returns far higher than systems under the other
technologies. The incentives for farmers to adopt technology are determined in large part
by the expected proﬁtability of the innovation. Therefore, there is a need for a study that
will examine the relationship between markets and incentives for technology adoption in

Cote d’Ivoire and Ghana.

175

The third and ﬁnal area for further research concerns the effect of currency
devaluation and market liberalization policies on the cassava sub-sector in West Africa.
The COSCA survey took place between 1989 and 1992. Since then, a number of policy
reforms have occurred. For example, in January 1994, the CFA franc was devalued from
1 French ﬁ'anc= 50 franc cfa to 1 French franc= 100 franc cfa .As Staatz (1994) put it,
“the devaluation was a dramatic event, but is part of much longer process of structural
change in the Francophone West Aﬁican economies”. Therefore, Francophone West
Aﬁican policy-makers, producers and consumers could beneﬁt greatly from empirical
information and analyses about the effects of devaluation on a very important source of

sustenance in the region such as cassava and cassava products.

5.3. Conclusions

Recent impact simulations indicate that roots and tubers will play important and
increasingly diversiﬁed roles in developing —country food systems over the next two
decades (Scott et al., 2000). Furthermore, simulation results indicate that in Sub-Saharan
Aﬁica, continued high rates of population grth and urbanization, combined with
comparatively low level of per capita income and limited economic growth, will promote
growth in the use of cassava as food and catalyze its sustained penetration in urban
markets.

It is hoped that the results of this study can help guide national investment
decisions in agricultural research and extensions to make cassava roots and cassava
processed products more marketable in the region of West Aﬁica. An example of such

investments would the ﬁnancing of national or regional research programs that involve

176

market appraisals and the identiﬁcation of linkages between producers, processors and

policy-makers that capitalize on cassava’s potential for expanded use in processed form.

177

REFERENCES

Byerlee Derek and Heisey Paul. 1993. “Strategies for Technical Change in Small-Farm
Agriculture, with Particular Reference to Sub-Saharan Africa” in Russell Nathan
C. and Christopher R. Dowswell, Policy Options For Agricultural Development
in Sub-Saharan Africa, CASIN/SAA/GLOBAL 2000.

Nweke, Felix 1., K. N'Goran, A.G.O. Dixon, B.O. Ugwu, O. Ajobo, and T.
Kouadio. 1998. Cassava production and processing in Cote d'Ivoire. The
Collaborative Study of Cassava in Aﬁica, Working Paper No. 23, HTA, Ibadan,
Nigeria.

Scott G. J ., Rosegrant M. W., Ringler C., 2000. Roots and Tubers for the 21“ Century:
Trends, Projections, and Policy Options, Food, Agriculture, and the Environment

Discussion Paper 31, International Food Policy Research Institute, Washington,
DC, USA. '

Staatz, John. “ Designing Food Security Strategies in a Rapidly Changing Social,
Political, and Economic Environment: Challenges for the Sahel (with special
emphasis on the CF A devaluation)” Presentation to AlD/W-Aﬁica Bureau,
Sahel/West Aﬁica Office and ARTS/FARA. February 17, 1994.

178

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