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This is to certify that the

thesis entitled

EX-POST RATE OF RETURN ON MAIZE RESEARCH
AND EXTENSION IN NORTHERN CAMEROON

presented by
GEORGES DIMITHE

has been accepted towards fulfillment
of the requirements for

MS degree in Ag. Economics

 

Major professor

Date llllolm

0-7639 MS U is an Affirmative Action/Equal Opportunity Institution

 

 

LIBRARY
Mlchigan State
University

 

 

 

PLACE ll RETURN BOXtonmavothbchockommmnoord.

TO AVOID FINES Mam on or Mon duo duo.

DATE DUE DATE DUE DATE DUE

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

WWI

‘_—__, or

EX-POST RATE OF RETURN ON MAIZE RESEARCH
AND EXTENSION IN NORTHERN CAMEROON

By

Georges DIMITHE

A THESIS
Submitted to
Michigan State University
~ in partial fulfillment of the requirements
for the degree of
MASTER OF SCIENCE
Department of Agricultural Economies

1994

ABSTRACT

EX-POST RATE OF RETURN ON MAIZE RESEARCH
AND EXTENSION IN NORTHERN CAMEROON

By

Georges DIMIT HE

Facing declining output per capita, the Cameroon government has invested heavily in
agricultural research and extension. But, since 1985, support to agricultural research has
declined, due to the financial crisis. Consequently, the Institute of Agronomic Research needs
a basis for allocating this constrained budget among various programs to ensure that future
investments by IRA make a significant contribution to national development goals'as well as
for strengthening its bargaining power vis a vis policy makers. To address these issues, data
on maize research and extension in North Cameroon were collected and analyzed for the
period 1979-2000, with the general objectives to: (a) estimate the rate of return to investments
in maize research and extension, (b) identify the critical factors which have contributed to the
expansion of maize production, and (c) draw policy implications. The analysis yielded an 11.7
percent internal rate of renu'n and highlights key factors explaining maize expansion in the

North.

Copyrighted
by

Georges Dilithe

With love and caring,
for my wife, Félicité Lydie Nko’o Mebanda,

my sons Franck, Cédric and Loic, and my daughter Elaida.

ACKNOWLEDGEMENT

I take this opportunity to acknowledge my great intellectual debts to all those who
have been my teachers, from my primary school days onwards. I owe a special debt of this
kind to Dr. Richard Bernsten for serving as my major professor and research advisor. His
guidance and support throughout my program has been extremely enjoyable and gratifying
experience. Particular thanks are also due to my guidance committee members, Dr. Eric
Crawford and Dr. Russell Freed. Their careful review and constructive evaluation of this
thesis made it a much better document.

I am thankful to fellow graduate students and faculty members in the Department of
Agricultural Economics, Michigan State University, in arguments with whom a good deal of
what I learned at MSU was strengthened. I am especially thankful to James A. Stems whose
collaboration throughout this endeavor (from data collection in Cameroon to the analysis and
write up) has been invaluable.

My task during data collection was immensely facilitated by the collaboration of
USAID/Yaoundé personnel, researchers and administrative staff at IRA Maroua, Garoua and
Nkolbisson. I am grateful to them. I am especially greatful to Dr John Poku and Dr. Doyle
Baker, for encouraging and supporting me throughout this endeavor. Their contribution to
my training on the job has been extremely rewarding during my program.

Finally, my appreciation goes to my family for the invaluable sacrifices to ensure my

education and the suffering they are going through during my absence in Cameroon.

To all these people, and many others I have not listed here, much thanks.

TABLE OF CONTENTS

LIST OF TABLES ............................................ viii
LIST OF FIGURES ............................................. x
ABBREVIATIONS ............................................. xi

CHAPTER I INTRODUCTION

1.1 Problem Statement and Importance ................................ 1
1.2 Objectives ............................................... 3
1.3 Hypotheses ............................................... 3
1.4 Thesis Organization ......................................... 4

CHAPTER 2 PROBLEM SETTING

2.1 Structure and Performance of Cameroon Economy ...................... 5
2.2 Characteristics of the Agricultural Sector ............................ 6
2.2.1 Importance and Performance .............................. 6

2.2.2 Production System .................................... 7

2.2.3 Constraints ......................................... 8

2.2.4 Agricultural Policy .................................... 8

2.3 North Cameroon Farming Systems Overview ........................ 11
2.3.1 Introduction ....................................... 11

2.3.2 Climate .......................................... 14

2.3.3 Crop Production .................................... 17

2.3.4 Farming Systems .................................... 18

2.3.4.1 State-Supported Venture Systems .................... 18

2.3.4.2 Traditional Crop/livestock Sedentary Systems ' ............ 20

2.3.4.3 Traditional Pastoral Nomadic System ................. 20

2.4 Maize Research, Extension and Marketing Institutions ................... 21
2.4.1 Cameroon’ 3 Agricultural Research System .................... 21

2. 4. 2 Maize Research ..................................... 25

2.4.2.1 Introduction ................................. 25

2.4.2.2 NCRE Project ............................... 26

2.4.2.2.1 Project Overview ....................... 26

2.4.2.2.2 Maize Breeding ........................ 28

2.4.2.2.3 Maize Agronomy Research ................. 31

2.4.2.2.4 On-farm Maize Research .................. 32

2.4.2.3 SAFGRAD Projects ............................ 32

2.4.2.3.1 Introduction ........................... 32

2.4.2.3.2 SAFGRAD LP. #31 ..................... 33

2.4.2.3.3 SAFGRAD/FSR ........................ 35

2.4.3 Maize Extension .................................... 37

2.4.3.1 SODECOTON ............................... 38

2.4.3.1.1 Structure ............................ 37

2.4.3.1.2 Activities Overview ...................... 38

2.4.3.1.3 Maize Extension ........................ 42

2.4.3.2 Ministry of Agriculture .......................... 45

2.4.4 Seed Production .................................... 46
2.4.4.1 Seed Policy ................................. 46
2.4.4.2 North Cameroon Seed Multiplication Company (NCSM) ..... 47
2.4.4.3 Pioneer Agrogénétique Cameroon (PACSA) ............. 50

2.4.5 Maize Marketing .................................... 51
2.4.5.1 Office Céréalier .............................. 52
2.4.5.2 MAISCAM ................................. 52

CHAPTER 3 THEORETICAL FRAMEWORK and LITERATURE REVIEW

3.1 Theoretical Framework ...................................... 55
3.1.1 Benefit/Cost Analysis ................................. 55

3.1.1.1 Benefit and Cost Concepts ........................ 55

3.1.1.2 Benefit and Cost Items Valuation .................... 57

3.1.1.3 Benefit/Cost Analysis ........................... 60

3.1.1.4 Limitations of Benefit/Cost Analysis ................. 68

3.1.1.5 Sensitivity Analysis ............................ 70

3.1.2 Institutional Analysis ................................. 71

3.2 Review of ROR Studies in Africa ................................ 72
3.2.1 Geographical Distribution of ROR Studies .................... 72

3.2.2 Nature of ROR Studies ................................ 72

3.2.3 Magnitude of ROR Values .............................. 73

' 3.2.4 Key Determinants of the ROR Values ....................... 74
3.2.5 ROR Studies in Cameroon .............................. 76

3.2.6 Conclusion ........................................ 76

CHAPTER 4 ANALYSIS and RESULTS

4.1 Research Activities ......................................... 78
4.1.1 Identification of Research Focus .......................... 78

4.1.2 Preliminary Data Collection ........ , .................... 78

. 4.1.3 Supplemental Data Collection ............................ 79
4.2 Time Frame ............................................. 79
4.3 Costs Determination ........................................ 80
4.3.1 Research Costs ..................................... 81
4.3.1.1 NCRE Costs (ATC‘Q‘) .......................... 81

4.3.1.2 SAFGRAD Projects’ Costs ....................... 86

4.3.2 Extension and Production Costs ........................... 89

4.2.3 Benefits Determination ................................ 96

4.5 Benefit/Cost Analysis ....................................... 99
4.5.1 Base Run Analysis ................................... 100

vii

4.5.2 Sensitivity Analysis .................................. 104

4.6 Institutional Analysis ........................................ 112
4.6.1 Research and Extension ................................ 113

4.6.2 Inputs Availability and Delivery .......................... 116
4.6.2.1 Maize Seeds Production and Provision ................ 116

4.6.2.2 Open-Pollinated Versus Hybrid Maize Varieties .......... 117

4.6.2.3 Improved Maize Seeds Release ..................... 119

4.6.2.4 Fertilizer Supply System ......................... 119

4.6.3 Rural Financing ..................................... 122

4.6.4 Marketing Potential and Post-Harvest Opportunities .............. 123

4.6.5 lnfonnation System and Coordinations ...................... 123

CHAPTER 5 SUMMARY and CONCLUSIONS

5.1 Summary ............................................... 125
5.1.1 Institutional Setting .................................. 125
5.1.2 Maize Production .................................... 126
5.1. 3 Profitability and Success Factors .......................... 127
5.2 Policy Implications ......................................... 129
5.3 Limitations .............................................. 132
5.4 Future Research Needs ...................................... 134
APPENDICES . . ............................................ 135
BIBLIOGRAPHY ............................................. 145

viii

LIST OF TABLES

Table 2.1: Area Cultivated (Ha) for the Major Crops in the North Province,

Cameroon, 1984—1990. .................................... 17
Table 2.2: Maize Varieties Extended by SODECOTON, 1975-1991, North Province,

Cameroon. ............................................ 42
Table 2.3: Area (Ha) Planted for Crops Extended by SODECOTON, North Province,

Cameroon, 1979-1990. .................................... 44
Table 2.4: Area Planted (ha) for Seed Production by NCSM Project, 1979-1989,

Cameroon. ............................................ 48
Table 2.5: Seed Production“) (mt) by NCSM Project, 1979-1989, Cameroon. ....... 49
Table 4.1: Estimated NCRE Maize Breeding Expenses (Nominal F.cfa), North

Province, Cameroon, 1981-90. ............................... 85
Table 4.2: Estimated NCRE Maize Agronomy Expenses (Nominal F .cfa), North

Province, Cameroon, 1981-90. ............................... 85
Table 4.3: SAFGRAD JP #31 Expenses (Nominal F.cfa) on Maize, North Province,

Cameroon, 1979-1987. .................................... 88
Table 4.4: Estimated SAFGRAD/FSR Expenses (Nominal F.cfa) on Maize, North

Province, Cameroon, 1986-1988. .............................. 89
Table 4.5(a): Estimated Maize Extension and Production Costs (Nominal F.cfa),

North Province, Cameroon, 1979-2000. .......................... 92
Table 4.5(b): Estimated Maize Extension and Production Costs (Nominal F.cfa),

North Province, Cameroon, 1979-2000 (Cont’ed). ................... 93
Table 4.5(c): Estimated Maize Extension and Production Costs (Nominal F .cfa),

North Province, Cameroon, 1979-2000 (Cont’ed). ................... 94
Table 4.6: Estimated Maize Revenues (Nominal F .cfa), North Province, Cameroon,

1979-2000. ............................................ 97
Table 4.7: Estimated Net Revenues (Nominal F.cfa) for Maize Research, Extension

and Production, North Province, Cameroon, 1979-2000. ............... 101
Table 4.8(a): IRR for Maize Research and Extension from Alternative Values for Key

Variables, North Province, Cameroon ............................ 105
Table 4.8(b): IRR for Maize Research and Extension from Alternative Values for Key

Variables, North Province, Cameroon (Continued). ................... 106
Table 4.8(c): IRR for Maize Research and Extension from Alternative Values for Key

Variables, North Province, Cameroon (Continued) .................... 107
Table A.1: Macroeconomic Indicators for Cameroon, 1980 to 1989. ............. 135

Table A.2: Varieties DevelOped and Released by NCRE Project, Cameroon, 1981-90. . . 136
Table A.3: National NCRE Scientists Trained/in Training“ from 1982 to 1994, IRA-

Cameroon. ............................................ 137
Table A.4: Summary of Published ROR to Agricultural Research Studies for Africa

up to 1992. ............................................ 138
Table A.5: Total NCRE Expenses (Nominal $US), Cameroon, 1981-1990. ......... 139
Table A.6: NCRE Work Plans’ Budget Allocation (in Nominal value), Cameroon,

1987-1990. ............................................ 140

Table A.7: Maize Area (hectares) in the NCRE Lowland Breeding Unit’s Mandated

Zone, Cameroon, 1984-1987 ................................. 140
Table A8: SAFGRAD JP #31 Total Expenditures (in Nominal $US), North Province,

Cameroon, 1979-1988‘”. ................................... 141
Table A.9: SAFGRAD/FSR Expenses (Nominal F.cfa), North Province, Cameroon,

1986-1988. ............................................ 142
Table A. 10: SODECOTON Personel Costs (in Nominal F.cfa), Cameroon, 1979-

1990. ............................................... 143

LIST OF FIGURES

Figure 2.1: North Province Administrative Divisions ....................... 13
Figure 2.2: Average Rainfall and Temperature Distribution in Cameroon .......... 16
Figure 2.3: Organizational Structure of IRA ............................ 23
Figure 2.4: Area (ha) Planted for Major Food Crops in the SODECOTON Zone,

North Province. ......................................... 44
Figure 3.1: Graphical Representation of Individual’s Welfare .................. 62
Figure 3.2: Welfare Effect of a Single Price Change ........................ 63
Figure 3.3: Welfare Effect of a Single Price Change under Simplified Assumptions. . . . 64

Figure A.1: SODECOTON Geographical Coverage ........................ 144

xi

AMP
AVA
BCR
BIRD
CAP
CBR
CCCE
CFDT
CGIAR
CIF
CIMMYT
CRSP
CV
DIRAGRI
EEC
EEVT
EV
EVT
FAC
FAO
Fcfa
FEP
FOB
FONADER
FROR
FSAR
FSR
GDP
GVP
ICRISAT
IDRC
IFAD
IFCC
IITA
IRA
IRAT
IRCA
IRCT
IRHO
IRR
IRRI
ISNAR

ABBREVIATIONS

Agricultural Management and Planning Project
Association Villageoise Autogére’e

Benefit Cost Ratio

Banque Internationale pour la Reconstruction et le Développement
Cameroon Agricultural Policy

Completely Randomized Block Design

Caisse Centrale de Cooperation Economique
Compagnie Francaise de Developpement du Textile
Consultative Group on International Agricultural Research
Cost, Insurance, and Freight

International Maize and Wheat Improvement Center
Collaborative Research Support Project

Compensating Variation

Direction de I'Agriculture

European Economic Community

Elite Experimental Variety Trial

Equivalent Variation

Experimental Variety Trial

Fonds d 'Aide et de Cooperation

Food and Agricultural Organization

Franc de la Communauté Financiere Afi'icaine

Foreign Exchange Premium

Free on Board

Fonds National de Développernent Rural

Financial Rate of Return

Fond Special d 'Action Rurale

Farming Systems Research

Gross Domestic Product

Groupement Villageois Pré-Coopérative

International Center for Research in Serni-Arid Tropics
International Development Research Center
International Fund for Agricultural Development
Institut Francais de Café et Cacao

International Institute of Tropical Agriculture

Institut de Recherches Agronomiques »

Institut de Recherche: Agronomiques Tropicales et des Cultures Vivriéres
Institut de Recherche sur le Coton en Afrique

Institut de Researche de Coton et des Testiles Exotiques
Institut de Recherche pour les Huiles et les Oléagineux
Interml Rate of Return .

International Rice Research Institute

International Service for National Agricultural Research

xii

MAISCAM
MIDENO
MIDEVIV
MINAGRI
MSc

N CRE
NCSM
NEB
NETP

N GO

NPV

NVT

OAU
OECD
OER
ONAREF
ONAREST
ORSTOM
PASCA
PCN

PhD

R&D

RCB

ROR ‘
RUVT
SAFGRAD
SCF

SEB

SER
SEMRY

SOCOOPED

SODEBLE
SODECAO

Mai'serie du Cameroun

Mission de Développement de la Province du Nord-Ouest
Mission de De’veloppement des Semenses et des Cultures Vi vri éres
Ministére de l'Agriculture

Master of Sciences

National Cereals Research and Extension Project

North Cameroon Seed Multiplication Project

Projet Nora-Est Bénoué

National Extension and Training Program
Non-Governmental Organization

Net Present Value

National Variety Trial

Organization of African Unity

Organization for Economic Cooperation and Development
Official Exchange Rate

Ofiice National de Regeneration des Fore‘ts

Ofi‘ice National de Recherches Scientifiques et Techniques
Ofi‘ice de la Recherche Scientific et Technique d '0utre-mer
Pioneer Agrogénétique Cameroon

Projet Centre-Nord

Doctor of Philosophy

Research and Development

Randomized Complete Block Design

Rate of Return

Regional Unified Variety Trial

Semi-Arid Food Grain Research and Development Project
Standard Conversion Factor

Project Sud-Est Bénoué

Shadow Exchange Rate

Société d ’Expansion et de Modernization de la Riziculture a Yagoua
Société Cooperative de Développement

Société de Développement du Blé

Société de Développement du Cacao

SODECOTON Société de Développement du Coton

STRC
TLU
UCCAO
ULER
UN
UNIDO
US
USAID

Scientific, Technical and Research Commission
Testing and Liaison Unit

Union Centrale des Cooperatives Agricoles de l'Ouest
Unite Locale d 'Encadrement Rapproché

United Nations

. United Nations Industrial Development Organization

United States of America
United State Agency for Intemational Development

xiii

CHAPTER I INTRODUCTION

1.1 Problgm Statement and Importance

In most African countries, agriculture is the main contributor to GDP, foreign
exchange, and employment. Facing declining output per capita, these governments have
invested heavily in agricultural research in order to increase productivity and thereby meet the
expanding demand for food. Unfortunately, research investments are expensive. Since these
countries have limited financial capacities to support their national research systems, they have
relied on donors to support agricultural research.

Despite substantial investment in research, African agriculture appears to be
stagnating. A "Green Revolution" is yet to take place, as happened in Asia. As a result,
donors are increasingly concerned about the effectiveness of these investments. In addition,
recent political events in Eastern EurOpe and associated requests for foreign aid to promote a
free market system have placed increased pressure on African countries to provide evidence of
a significant investment inipact to convince donors to continue to support agricultural
research.

Since 1985, support to agricultural research in Cameroon has declined, as a result of
the financial crisis. For example, because of the government priority setting policy, the
Institute of Agronomic Research (IRA) budget was reduced by 54 percent from 1985-86 to
1988-89 (IRA, 1989). Moreover, since 1989-90, the government has failed to allocate an
effective budget to IRA. Therefore, to strengthen its bargaining power vis a vis policy
makers, IRA administration needs documented evidence that research gives high returns.

This need is reflected by increased IRA administration’s interest in impact studies and the

2

recent creation of an economic unit within IRA’s directorate with a mandate to conduct
assessment studies.

In response to the funding crisis, IRA has designed, in agreement with the
government, a five year Action Plan which called for the government to provide a stable
funding at around 4.5 billions F.cfa. But, because of the high cost of maintaining capital
investments‘ launched before the economic crisis, only 12.4 percent of this budget will be
allocated to research activities. Allocating such a constrained budget among the various
research programs will require prioritization, taking into account the relative importance of
each program, to ensure that future public investments in IRA make a significant contribution
to national development goals. In order to do this, IRA administration needs concrete
evidence of the impact of past research investments, as a basis for future budget allocations.

This study analyzes the returns to maize research and extension in the Bénoué plateau
in the North Province. The topic was selected in response to the interest of primary users of
the study’s results (IRA, USAID and NCRE). Initial interviews with administrators,
researchers and extension agents revealed considerable interest in better understanding factors
contributing to the tremendous expansion of maize in this area. In addition to estimating the
returns on the investments made, the study will also identify the critical factors that have
contributed to research impact, and generate policy implications to guide the on-going

resource allocation debate.

 

1 'From 1976-77 to 1985-86 IRA’s budget underwent a rapid expansion. Recurrent costs
(including personnel, operations and research) increased by 281 %. During the same 10 years, IRA‘s
investment budget increased by 277 %'. (IRA, 1989 p:41).

1.2 Qbiegm

The general objectives of this study are to: (a) estimate the rate of returns to

investments in maize research and extension in the Northern Province of Cameroon, (b)

identify the critical factors which have contributed to the expansion of maize production, and

(c) draw policy implications. These general objectives are addressed through five specific

objectives:

1)

Identify and describe institutions that have contributed to the development and

expansion of maize production in Northern Cameroon.

2) Estimate the costs incurred and benefits generated by these institutions in performing
their respective activities. .

3) Estimate the rate of return (ROR) to the maize research/extension investment and the
sensitivity of this ROR to reasonable changes of critical parameter values.

4) Determine the key factors that have enabled these institutions to make an effective
contribution.

5) Highlight policy implications of the thesis results.

1-3 mm

The following is hypothesized and used to guide the study:

1) Maize research and extension in the North Province of Cameroon have had a positive
economic return - that is, the net present value is greater than zero.

2) Key factors which have contributed to this positive impact include the favorable
agroclimatic environment in the target maize-producing area, strong linkages between
support institutions, and recent decline in cotton prices.

3) The IRR is highly sensitive to yield and the adoption rate of maize.

1.4 Thesis 0120M ' L1

This thesis is organized into five chapters. Chapter 1 discusses the problem addressed
and its importance, defines the objectives of the study and the hypothesis formulated to guide
the research. Chapter II describes economic, agronomic and institutional settings of the
study. Chapter 111 reviews the economic theories that guides ROR analysis and the ROR
literature. This review provided the basis for formulating the hypothesis tested, selecting the
appropriate analytical model, and identifying data required to estimate the ROR. Chapter IV
describes how the benefits and costs values are estimated and presents the analytical results,
including an analysis of the institutional circumstances which have contributed to the impact
level achieved. Finally, Chapter V summarizes the findings, draws policy implications and

proposes future research.

CHAPTER 2 PROBLEM SETTING

2.1 Structure and Performance at Cameroon Economy

Cameroon is one of the most diverse African countries, with respect to its climate,
topography, hydrology, vegetation, animal and soil types. Its extends over 475,000 kmz, with
a population of 11.2 millions inhabitants, 61 percent of whom live in rural areas (World
Bank, 1990). With a population growth rate (1989) of 3.1 percent (World Bank, 1989.;
1989,), agricultural productivity is of critical importance to continued economic growth.

With a GDP of US $920 per capita (1988), Cameroon is classified as a middle income
country. Even though Cameroon economy is very diverse, agriculture remains its backbone,
accounting for 24.8 percent of GDP (World Bank, 1990). Since independence, Cameroon
economy has gone through three distinct growth phases. During the first phase (1960-1978)
following independence, the economy grew rather slowly, but the pace picked up in the
19703.

The second phase (1978-1981) was marked by a rapid growth, as a result of the
discovery and exploitation of oil in 1978. From 1978 to 1979, the relative contribution of oil
rose abruptly from about 1 to 20 percent of GDP, reducing agriculture’s contribution from 72
to 50 percent of GDP.

The third phase started in 1982, when the pace of economic growth began to slow
down (Table A.1). Since 1985, Cameroon has experienced a severe recession as a result of
both external and internal factors, including the persistent fall in export cr0p prices, the

sliding value of US dollar against the country’s currency, declining oil production, and poor

management of the economy. From 1987 to 1990, foreign exchange earnings fell by 45

6

percent, the real GDP decreased by 25 to 30 percent, and government fiscal deficit grew
rapidly (World Bank, 1990).
To address these problems, in 1990 the government, in conjunction with the World
Bank agreed to implement a structural adjustment program designed for:
(a) stabilizing public finances over the medium term (4 years) through improved
management of government resources, control over government salaries, improved
civil service management and productivity, and increased non-oil tax revenues; (b)
restructuring and rehabilitating the public enterprise and banking sectors; (c)
stabilizing agricultural financial and marketing structures 02am. 2.03); (d)
deregulating internal commerce and rationalizing external trade regulations; (e)
increasing incentive for petroleum exploration and production; (f) reorienting health
and education sectors policies to improve the quality of services; and (g) introducing
action programs to reduce the social cost of adjustments (World Bank, 1990; p. I).
But, an ongoing political crisis seriously je0pardized the successful implementation of
the structural adjustment program. Today, Cameroon faces an uncertain economic and
political future. With the projected decline in oil reserve and revenues, agriculture is
expected to regain its primary role in providing the necessary impetus to the overall economy.
The chances for Cameroon to successfully overcome the financial crisis lies not only on a
successful implementation of the structural adjustment plan and necessarycomplementary

policies, including appropriate agricultural policies, but also on the government’s ability to

reestablish a more serene political enviromnent.

2.2 WM

2.2.] Importance and Performance
The agricultural sector in Cameroon has always been the key sector for the economy.
In 1990, it employed 75 percent of the working population, accounted for 47 percent of

export earnings, and contributed 24.8 percent of the value of the country’s total production

(World Bank, 1990).

.7

Since independence, Cameroon’s agriculture sector growth rate has fluctuated
considerably. Averaging 5 .2 percent in the 19605 (compared to 1.4 percent growth rate for
the overall economy), the growth rate fell to 3.4 percent during the period 1970 to 1975.
Between 1975 and 1982, annual growth rate rose to 7 percent, the highest level ever reached,
due to expansion of export crop production. After 1983, unfavorable weather conditions,
coupled with the decline in world market of export crop2 prices drastically reduced the rate of
growth (1.9 percent from 1982 to 1988 while the economy was growing at 5.6 percent).

During 1986-1988, the economy experienced a timid come back. (World Bank, 1990).

2.2.2 Production System

The agricultural sector is made up of three distinct subsectors: a traditional sector, a
parastatal sector, and a private sector. The traditional subsector is dominated by small rural
holders, who produce over 90 percent of the total agricultural output, and account for 75
percent of the total employment. Although the traditional sector is the dominant contributor
to the total production and employment, it has received limited and inadequate investment
support from the government. The parastatal sector includes commercial agro-industrial
ventures which the government considered to be the engine of agricultural growth. Generally
speaking, they have failed to meet government’s expectations, despite heavy financial support
through public investment. Finally, the private sector is still quit weak and has yet to make a
significant contribution to the economy. These are mostly government bureaucrats and

retirees’ businesses.

 

2 The major export crops in Cameroon are cocoa (14 percent of the total export earnings), coffee
(12 percent), timber (5 percent), and cotton (2 percent). In general, while the performance of export crops
have been mixed over the past 30 years, it is claimed that, at least until recently, food crop subsector
appears to have kept the pace with population growth, and high mortality rates have seriously affected the
livestock subsector.

2.2.3 Constraints

Due to its agroclimatic diversity, Cameroon has the potential to be self-sufficient in
crop and animal productions, and to produce exportable surpluses. Although until recently
the country has been self-sufficient in many food crops, agricultural performance has been
modest, relative to the natural and human resources available (World Bank, 1990). The bulk
of the country’s production comes from a shrinking rural population, and in recent years,
productivity has failed to keep pace with 3.2 percent population growth rate.

The difficulties experienced by the agricultural sector are due to both internal and
external factors; The most important external factors have been declining commodity prices
for exports crops. Key internal factors include government policies which have failed to
provide adequate and appropriate support to the agricultural sector. These have resulted in an
aging farming population, inadequate rural infrastructures, erratic input supply, and
inadequate institutional support (e. g. research, credit and extension) to farmers. The poor
quality of the infrastructural network contributes to high distribution costs, limited regional

coverage, and high post-harvest losses.

2.2.4 Agricultural Policy

Cameroon government has sought to promote agriculture through policies designed to
support agriculture research and extension, provide farmers subsidized inputs, and create a
stable price environment particularly for export crops. Historically, the government began to
strengthen agricultural extension during the colonial period after World War II. The goal was
to promote a rapid diffusion of export crops (e.g. cocoa, coffee, palm oil, rubber tree, and
cotton) through technical support to crop-specific research stations (IFCC, IRHO). To

achieve these goals, a training center for extension agents was first created at Ebolowa in the

9

South Province. Later, a second center was created at Yaounde to provide more practical
training.

Initially, the government extension approach focussed on identifying progressive
farmers to serve as pilot farmers for demonstrations. Field visits were organized for
neighboring farmers who were expected to strictly follow the instructions provided. The
colonial government required that most of the farms be located along the road or behind
farmers’ houses in order to ensure permanent and easy policing, as well as tax collection.
Failure to conform to the instructions was severely sanctioned. In the 19403, after the
practice of forced labor was abolished, the extension service was reorganized, and training
centers strengthened. Also, the extension approach shifted to a strategy centered on State-
owned structures called Modernization Sectors. This marked the beginning of a new era in
development philosophy that prevailed until the financial crisis in the 19803, which forced the
government to publicly acknowledge the failure of this approach.

After independence, the government continued to provide extension services through
State-owned agencies and the Ministry of Agriculture’s traditional extension service, but their
nature changed over time. Initially, the extension philosophy was based on the diffusion and
community development models that were promoted in most Third World countries. Thus,
the first Five Year Development Plan relied heavily on the Modernization Sectors, alongside
the traditional extension service. In 1968, a new law allowed the government to create crop-
specific parastatals, which were introduced in the second Five Year Development Plan along
with the Modernization Sectors. Subsequently, Modernization Sectors were abolished and 14
parastatals were created, including SODECOTON in the North Province. These parastatals

were expected to be the starting point for rapid diffusion of technology.

10

Since the creation of parastatals, the government has given priority to providing
financial support to them, while neglecting the traditional extension service. During this
period, agricultural policy focused mainly on export crops as a source of foreign exchange. It
was not until the early 19705 that the government began to pay attention to food crops.

By 1980, it became evident that the diffusion and community deveIOpment models had
failed to generate a Green Revolution through a rapid increase in agricultural output. In the
19808, the agricultural extension emphasis shifted towards supporting integrated rural
development projects, as reflected in the fourth and fifth development plans. As a result, the
traditional agricultural extension service was reformed in 1987, with the creation of ULER
(Unite locale d ’Encadrement Rapproche') as a way to improve efficiency through better use of
extension staff. This was aimed at insuring that graduates from the various professional
schools of agriculture were effectively posted in the rural areas so they could provide better
technical support to the farmers.

Recent IBRD (1989) and World Bank (1990) diagnoses of the extension services
indicated that, except in the North-West Province where only MIDENO (Mission de
Developpement de la Province du Nord-Ouest) provides extension services, these policies
have led to a proliferation of inefficient institutions. Overall, these institutions have proven to
be costly, inadequately managed, and operate in a confusing policy environment with
overlapping responsibilities and obscure objectives. In addition, their staff are inadequately
trained, poorly motivated, lack logistic support, and operate under ineffective rural
communication system.

In an attempt to address the above issues, the National Agricultural Extension and
Raining Project (NAETP) was initiated in 1988, with the objective to improve the efficiency

of Cameroon’s agricultural extension services and harmonize them into a single and less

ll

costly system. The NAETP started as an 18 months pilot project in the North-West and
selected areas in the South, East and Extreme-North provinces. Subsequently, it was
extended for five years in 26 Departments in the Adamaoua, South-West, Littoral and West
provinces. Since the North Province is not included during this first phase, extension
activities were left to SODECOTON.

In 1990-91, within the context of structural adjustments, Cameroon government
designed a new agricultural policy that focused on five major goals: (1) modernization of the
production system, (2) ensuring food security, (3) encouraging and diversifying exports of
agricultural products, (4) encouraging domestic processing of agricultural products, and (5)
re—equilibrating the majors production channels. The government has placed considerable
emphasis (a) restructuring, privatizing or dissolving state-owned agencies previously
considered to be the engine of agricultural development and growth, (b) reorganizing the seed
production and distribution systems, (c) reforming the fertilizer subsector (with the help of
USAID) through a progressive reduction of government subsidies to ultimately achieve total
privatization, (d) strengthening the agricultural research system, (e) improving the
macroeconomic environment to enhance private investment, increased availability of
agricultural inputs and credit, as well as reforming the current law on cooperatives and land
tenure, and (0 further liberalizing the domestic market and promoting regional and

international markets (World Bank, 1990).

2.3 WM
2.3.] Intmdudion

The North Province became a separate Province in 1984, when the former "big

North” Province was subdivided into three Provinces: the Extreme-north, North, and

12

Adamaoua. The North Province extends over 67,798 km2 and is subdivided into four
Divisions: Bénoué, Faro, Mayo-Louti, and Mayo-Rey (Figure 2.1). Recent p0pulation data
estimate the Province has 599,000 inhabitants unevenly distributed across the Province. The
Province area and population represent 14 and 5 percent of the national statistics,

respectively.

13

 

Sunder

“N mic

{OUTI
/-

a
BENOUE /

'Ha

 

 

 

 

Pol. - - (
\/ Icrlftlilt-
a

MAYO HEY

Figure 2,1: North Province Administrative Divisions

14

The North Province benefits from relatively favorable climatical conditions, which
have made both crops and livestock the Province’s primary activities. Unfortunately, its
isolation from the major consumption and supply centers has hindered agricultural
development of this sector. However, agricultural development in the Province has been
enhanced by an integrated rural development approach promoted by the government through
various projects and institutions, some of which cover the entire country. Those with a
national mandate include " Oflice Céréalier” , Fond National de Développement Rural
(FONADER’), the North Cameroon Seed Multiplication Project (NCSM), SOCOOPED, and
the Institute of Agronomic Research (IRA). Major projects with a regional coverage include

Société de Développement du Coton (SODECOTON) and Projet Nord Est-Bénoué (N EB).

2.3.2 Climate

The Northern Provinces (Adamaoua, North, and Extreme-North) experience a tropical
climate, with a monomodal rainfall distribution which increases from north to south. Based
on annual distribution of the rains and predominant vegetation types, the North Province has
been divided into three major agro-ecological zones: (1) the Sahelian savannah zone in the
north-east region with an annual rainfall ranging from 600 to 800 mm, (2) the Sudan
savannah zone in the west region with 800 to 1000 mm of rainfall, and (3) the Guinea
savannah zone in the south region with 1000 to 1200 mm of rainfall (figure 2.2).

Unlike the southern regions of Cameroon which have two rainy seasons alternating
with two dry seasons, the North Province has only one rainy season (April-May through
October-November). The highest rains generally occur in August. The cropping period and

calendar across the Province are determined by rainfall patterns, which vary from four to six

 

3 FONADER has been restructured and transformed into a bank called Credit Agricole.

15

months. This makes planting time the busiest period for farmers, since they must plant their
principal crops during a very short time period (mid-May to mid-June). In the north and west
regions, the rainy season is shorter (mid-May and mid-June), compared to the south and east
regions (April- mid-June). The average monthly temperature varies from 26.5 °C in

November-December to 45 °C in March-April.

   
 

\_/ 150 [hum (.C)

 

\ ,I

a
o

lsohyét (on)

M: Average Rainfall and Temperature Distribution in Cameroon

17

2.3.3 Crop Production

The main traditional food cr0ps in the North Province are cereals (sorghum and
millet) and legumes (Groundnut and cowpea) as shown in Table 2.1. In most years, Sorghum
has accounted for the largest proportion of cultivated area, followed by cotton, groundnut,
and maize. However, recently, maize area has been expanding rapidly (figure 2.3), especially
in the south-east Bénoué region which is referred to as the Province’s maize belt. In this
area, maize is not only grown as a sole crop, but also intercropped, and in rotation with

cotton and/or legume crops.

Table 2.1: Area Cultivated (Ha) for the Major Crops in the North Province, Cameroon, 1984-1990.

 

 

Year Cotton Sorghum Peanut Maize Beans Cowpea Cassava Rice
lMillet
1984 35,974 60,956 27,237 10,700 3,980 2,094 761 1,448
1985 61,536 85,043 29,873 24,044 5,372 973 1,052 654
1986 51,534 101,037 36,371 15,849 5,786 1,780 1,294 642
1987 31,464 67,473 20,676 12,554 2,430 366 1,006 12
1988 38,497 102,668 18,909 17,585 5,811 1,178 124 428
1989 34,115 75,978 20,696 23,553 3,981 1,307 1,924 384

 

Source: Adapted from the 1984-1989 National Agricultural Survey.

Cereals account for 53% of households’ caloric intake (IRA, 1986; N gambeky, 1990).
These crops are generally consumed as flour, porridge, grits, and as local beverage; and the
stalks are used for fuel, fences and fodder. Maize is also consumed green during the hunger
period to fill the food deficit. Cotton has been the dominant cash crop, followed by groundnut

which also serves as food crop. However, in the last decade, maize has become an

18

increasingly important food crop and a new source of family income, particularly in the west
and south-east Bénoué regions.

The relative importance of these crops vary across the Province. Dry season sorghum
(muskwari) and cowpea are mostly grown in the west and north-east regions. Maize is mostly
grown in the south-east region while groundnut and cowpea are popular throughout the

Province (IRA, 1986; Ngambeky, 1990).

2.3.4 Farming Systems

In general, North Province farming systems can be grouped into three major
categories: the state-supported agro-industrial system, the traditional crop/livestock sedentary
system, and the traditional pastoral nomadic system. Cropping period and calendar, as well as
land clearing method, are identical in both the state-supported agro-industrial system and the
traditional crop/livestock sedentary system. The most common land clearing method is slash
and burn, especially for maize, cotton and sorghum. These systems have been extensively
described by the IRA-SAFGRAD Farming Systems Research team (IRA, 1986; N gambeky,

1990).

2. 3. 4. 1 W

This term refers to the low and high input cropping systems, both of which are being
extended by SODECOTON. They are essentially cotton based rotation systems, which vary
in terms of management level depending on the cr0p‘. SODECOTON provides the inputs

used in these systems and technical back-stopping to participant farmers.- The distinctive

 

4 The main cotton based rotations are cotton-sorghum-sorghum, cotton-sorghum-cotton-maize,
and cotton-sorghum-cotton-groundnut, cotton-maize or cotton-groundnut.

19

features of these systems, compared to the traditional systems, include the use of animal
traction for land preparation5, row planting, and the used of seed treatment, chemical
weeding, and herbicides. However, some farmers following the low systems also have
adopted these recommended practices, especially fertilizer, but at lower application rate.

Sorghum is planted under both management systems. The farmers following high
input sorghum system generally plant improved sorghum varieties, either in pure stands or in
association with maize, after cotton. In contrast, farmers following the low input system
mostly plant local varieties in pure stands, after either cotton, a cereal or legume. Unlike
with sorghum, SODECOTON promotes maize in a high input package, mostly in pure stands
but also in association with sorghum.

Generally, farmers plant cowpea and other supplementary cr0ps like millet and
vegetables between early May and mid-May, sorghum and groundnut between mid-May and
early June, cotton between early June and mid-June, maize in early May to mid-May, and rice
in mid-June.

Animal husbandry and agro-forestry are important components of both the state-
supported system, as well as of the traditional crop/livestock sedentary system. Animals are
used for land preparation (animal traction), transportation, milk and sold to meet emergency
cash needs. The most common animal found are cattle, oxen, goats and a small number of
sheep, which are fed crop residues, grain husks, tree leaves and hay.

Government’s effort to encourage tree planting through SODECOTON, ONAREF and
NEB, and CARE have increased farmers’ awareness and recognition of the economic

importance of trees, including fruit (mango and lime) and non-fruit trees (Ngambeky, 1990).

 

5 Land preparation with animal traction is used mostly for cotton, maize and groundnut, but less
so for sorghum, com and. muskwari (dry season sorghum).

20
2. 3. 4. 2 Traditional Crop/livestock Sedenta_ry Systems

In this category, farmers grow sorghum/groundnut as the main crops while raising
animals on permanent locations. These farmers adopt very few of the practices recommended
by SODECOTON. About 85% of the rural farming population practice the traditional
crop/livestock sedentary systems.

Traditional farmers generally grow food crops in rotation with cotton, in pure stands
or in association. At the Province level, 85 percent of the farmers grow pure groundnut“, 75
percent pure maize, and 75 percent pure sorghum, and 45 percent pure cowpea. The most
common associations are sorghum/cowpea, sorghum/groundnut, and
sorghum/groundnut/maize, but farmers also grow maize/millet, groundnut/cowpea,
maize/cowpea, and maize/groundnut in intercrops. The main non-cotton-based rotations are
simple rotations of sorghum-groundnut, maize-sorghum, maize-groundnut, and cowpea-maize,

or sorghum/groundnut followed by maize/sorghum, maize/groundnut or cowpea/maize.

2.3.4.3 Wm

This system involves 15 percent of the rural farming population, mostly from the
ethnic group Foulbé, who graze cattle (transhumance) over a wide-ranging area, with no
interaction with crop production. During the dry season, these farmers move further south in

the valleys in search of grazing land and water.

 

6 SAFGRAD (1986) reports that 96 percent of the farmers in the NEB, 83 percent in the SEB,
and 84 in the WEB grow groundnut in pure stand.

21
2.4 Mag Research, Extensg' n and Marketing Insg' utions

2. 4. I Cameroon ’s Agricultural Research System
The foundations of scientific research in Cameroon was laid during the colonial

period. As in most developing countries, agricultural research is organized and implemented

by governmental agencies. Since independence, both the disciplinary as well as qualitative
aspects of research have changed profoundly. Similar to the country’s general economy,

Cameroon’s research system evolution during the post-colonial period can be classified into

three distinct periods:

1) The 19603 were characterized by increased government recognition of the importance
of research. Key policy initiatives included the creation of a coordination council7
and executive bodies' which were dominated by French private interest groups.
These structures were solely responsible for promoting and implementing scientific
research activities.

2) The 19703 were characterized by increased nationalization of research structures, a
rapid expansion of research executive bodies, as well as an expansion in the number
of research disciplines and the scope of activities.

3) From the early 19803 to date, government support to agricultural research
dramatically declined due to the economic crisis.

Post-colonial agricultural research, which dates to 1963, followed the general pattern

describes above, both in terms of budgetary as well as disciplinary evolvements. Originally,

 

7 A National Council jbr Technical and Scientific Research, Studies and Surveys was created
in October 20, 1962. It was chaired by the Vice-President of the then Federal Republic of Cameroon,
assisted by five specialized committees.

8 The executive bodies include ONAREST (May 24, 1965), Federal University of Cameroon
(July 26, 1962) and associated higher schools, French institutes and Office (IRHO, IFCC, IRCA, IFAC,
IRTC, CT FT . ORSTOM). and other technical services located within various ministries.

22

research was performed by French institutes, which focused - on export crops namely cotton

(IRTC), cocoa and coffee (IFCC), oil palm (IRHO), fruits (IFAC), and wood (CTFT).
Alerted in the early 19603 by potential food shortages in the western and extreme-

northern parts of the country, the government urged the research system to expand its

mandate to include food cr0ps; As a result, two research stations were created in Dschang
and Guétale in 1965. In 1974, in accordance with a nationalization campaign undertaken in
the early 19703, Cameroon government tool: full control over agricultural research by
nationalizing the French ICVT to create the Institute of Agricultural Research (IRA).

Initially, IRA’s primary mandate was to carry out crop research in order to improve
their productivity. Subsequently, this mandate was extended to include:

a) Increased responsibility for multiplication and certification of improved seeds and
vegetative planting materials, as well as ensuring that an adequate supply of these
materials were available to farmers;

b) Ensure wide diffusion of research results by reinforcing the capacity of the Ministry
of Agriculture and relevant government agencies to extend research results; and

c) Support planning and policy making by various governmental development agencies.
Since its creation, IRA has undergone majors changes, both in terms of the Institute’s

structure as well as the scope of research conducted. These changes reflected a recognition

that agricultural research represented the country’s main vehicle for reversing declining per
capita production that characterized the 19803, the future threat of food insecurity problems
posed by a rapid urbanization and a rapid population growth. The latest structural changes in
the agricultural research system are summarized in the five year Action Plan, submitted by
IRA to Cameroon government and published in May 1991. 'Ihe current IRA structure is

summarized in the following chart:

23

 

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24

Four key features of IRA’s structure are highlighted below:

1)

2)

3)

IRA’s activities are organized within four research Centers, located to cover the
country’s major agro-ecological zones, as presented in Figure A.1 in the appendix.
IRA’s research programs are carried out by 190 researchers whose qualifications
range from "Engineer Agronome" to PhD. These researchers are distributed across a
total of 16 programs“, as opposed to 22 before the crisis. IRA supports ten
commodity programs, six of which deal with food crops, and two of which are
multiple crops oriented (Farming Systems, and Food Technology). The specific
commodity program emphasis vary across Centers, depending on the agro-ecological
zone in which the Center is located”. Cereals and roots and tubers continue to
receive top priority. Among industrial crops, cocoa and coffee receive the highest
priority, with the objective to reverse the declining trends and reduce unit production
costs for these crops (IRA, 1989).

During the past two decades, food crops research has gained increased importance in
terms of both its budget share and the scope of activities undertaken. Many projects
have been implemented to address the various problems facing farmers in an effort to
increase their welfare through the use of high yielding cereals, roots and tubers,

leguminous crops and improved agronomic practices.

 

9 Bananas and Plantain, Botanic research, Cereals, Farming Systems, Food Technology,

Forestry, Fruits, Genetic Resources, Latex Plants, Legumes, Oil Plants, Roots and Tubers, Soils, Stimulant
Plants, Textile Plants, and Vegetables.

10 Maroua: Cereals, Legumes, Textiles, Roots and tubers;

Ekona: Roots and Tubers, Fruits, Bananas and Plantain, oil Plants, Rubber, Soils, Forestry;
Foumbot: Cereals, Stimulant Plants, Roots and Tubers, and

Nkolbisson: stimulant Plants, Soils, Cereals, Roots and Tubers, Botanic research and Forestry.

25

4) In 1984, IRA initiated an adaptive research program with a farming systems
perspective at Bambui, as part of the National Cereals Research and Extension Project
(NCRE) and carried out mainly by Testing and Liaison Units (T LU). There are
currently four TLUs located in four different Centers (Bambui, Ekona, N kolbisson,
and Maroua). This focus is expected to expand in the future.

5) In addition, IRA’s Research and Development Division has among its various
responsibilities, the mandate for economic analysis of the research programs.

IRA’s Action Plan is based on ”a redefinition of the Institute’s goals, and the
identification of ten strategic objectives directed at restructuring, reprogramming, and
rehabilitating the institute. For each strategic objective, the Plan identifies a set of specific

actions which will be taken to ensure that the goal of the Plan is accomplished" (IRA, 1989).

2.4. 2 Maize Research
2. 4. 2.1 mm

Maize, rice, sorghum/millet and to some extent wheat“ are the major cereals grown
in Cameroon. While the country’s total consumption requirements of maize and
sorghum/millet are produced domestically, Cameroon import about 20% of its rice
requirements and most of the wheat consumed. Maize was introduced in coastal Cameroon
some 400 years ago by the Portuguese (Ayuk-Takem, 1991). Cultivated extensively in all ten
provinces, maize is an important part of the population’s diet. Annual production is estimated
to be over 500,000 metric tons, but yields are low and unstable, mostly due to a lack of

improved varieties for the various ecologies and limited use of improved agronomic practices.

 

1'1 The major wheat production areas were Wassandé (400 meters in the Adamaoua Province
with the former SODEBLE), and Mbui and Dongs/Mantung (more than 1600 meters) in the North-West
Province. The annual production was estimated to be below 200 mT.

26

Research on cereals began in the early 19603 and was concentrated on maize, rice,
and sorghum/millet. Ayuk-Takem (1991) identified several important periods in the evolution
of maize research in Cameroon. From 1961 to 1965, most research activities were aimed at
testing introduced materials in the highlands. The year 1965-66 marked the beginning of
applied research, when the former French institute, IRAT, introduced varieties from West and
East Africa, France, and Israel at Dschang and Maroua (200 meters). In 1971, a systematic
breeding program was started at Bambui (1600 meters) based on new introductions from
USA, West, East and Southern Africa (Zimbabwe and Zambia), Zaire, and Central America.
However, maize research program did not become a major research activity until 1981 when
the NCRE Project was started. Today, maize research in the North Province is primarily
conducted by IRA through two projects: the NCRE Project, and the Semi-Arid Food Grain

Research and Development Projects (SAFGRAD).

2.4-2.2 mm
2.4.2.2.1 Prgjg megiew

While Cameroon began receiving US foreign aSsistance after signing a bilateral
agreement in 1961, prior to 1978 USAID’s assistance to Cameroon was relatively small
(Jaeger, 1987). For example, in the 19603, Cameroon received about 1.5 percent of total US
assistance in Africa. This share then fell to 0.2 percent in 1975, but increased to 3-5 percent
in the late 1970s and 19803 (Jaeger, 1987). Agriculture became the major focus of USAID in
the early 1980s when the share of its assistance going to the agricultural sector grew from 25
percent in 1977 to 80 percent in 1982 (Jaeger, 1987). The NCRE Project (631-0013) is the

most important component of this contribution.

27

The NCRE Project began in August 1979 as a five-year $7.697 million grant to the
government of Cameroon. Implemented by IRA, it was designed to develop the institutional
capacity of the Cameroon Institute of Agronomic Research to provide high-quality research on
maize, rice, sorghum, and millet, as well as develop linkages to facilitate the transmission of
research results. The International Institute of Tropical Agriculture (IITA) was contracted to
provide technical assistance, limited supplies and short-term training, with USAID/Cameroon
responsible for long-term training and major infrastructure. The Project is composed of four
technical units, namely: Maize Improvement and Agronomy, Rice Improvement and
Agronomy, Sorghum Improvement and Agronomy, and Testing and Liaison Units ('l'LU)".
Maize and rice were chosen partly because significant research directly applicable to the
Cameroon environment has been done on these crops, while sorghum and millet were chosen
because they are the dominant food crops in one of the most deprived part of the country, the
northern provinces.

A 1983 evaluation of Phase I of the Project determined that the output and quality of
the research were encouraging, and that the farmers (clients) were receptive to the research-
generated recommendations. Therefore, a ten-year extension phase (N CR5 [1) was
recommended and approved for $39 million, including a US $3.6 millions loan. The second
phase built upon the first phase’s accomplishments and continues to develop IRA’s
institutional capacity and facilitate the transmission of research results to farmers. Over this

period, Cameroon government contributed an additional $25.4 million.

 

12 The TLU is a multidisciplinary research unit created to perform a testing function and to
increase the likelihood of farmer adoption by fine tuning the technology developed on station through the
use of a farming system methodology. This unit therefore completes the research process and enables
researchers to deve10p relevant problem-solving programs and to develop technologies appropriate to farmer
circumstances. The first TLU was created at Bambui in 1982. Later, three additional TLUs were created
to serve the different agroeeological regions of Cameroon: the Nkolbisson TLU (1986), for the subhumid
forest and part of the forest-savanna transition zones, the Bkona TLU (1984), and the Maroua TLU (1988).

28

The project has successfully developed links with other international research institutes
such as ICRISAT, CIMMYT and IRRI. In North Cameroon, NCRE researchers collaborate
with the Beans/Cowpea CRSP on cowpea research, and with SAFGRAD for on-farm testing
of NCRE/IITA varieties. SAFGRAD has also brought varieties from their headquarter in
Burkina Fasso to the attention of NCRE team. The NCRE maize Agronomy unit works
closely with SODECOTON. To date, NCRE has released about 11 open-pollinated maize
varieties, four rice varieties, and five sorghum varieties (see Table A.2). A major component
of the NCRE Project is the training program for national scientists. Overall, when the project
terminates in 1994, 35 nationals will have been trained in various US universities (23 MSc

and 12 PhD) in 12 different disciplines (Table A.3).

2.4.2.2-2 mm:

The NCRE maize breeding program’s main objective is to develop stable, high—
yielding maize varieties with good agronomic characteristics that are adapted to the Cameroon
environment and satisfy consumers’ requirements. The first year of the project was viewed as
an observational and testing experience (NCRE, 1982). Maize breeding activities focused on
screening introduced materials (Early Variety Trials) from IITA and CIMMYT, and
comparing them to IRA and farmers’ varieties. A total of 22 trials were implemented,
including three maize/fertilizer trials and three evaluation trials. The single maize research
unit which covers the three major agro-climatical zones where maize is grown (lowland rain
forest, lowland savanna, and mid-altitude subtropics) was initially managed by a team of three

researchers ".

 

13 The team was made up of two nationals (Dr. Jacob Ayuk-Takem at Bambui, and Mr. Jean-
Bosco Zangue at Nkolbisson) and one expatriate (Dr. Jay Chung at Nkolbisson).

29

In 1984, an additional IITA breeder (Leslie Everret) joined this team. The unit was
then divided into low and mid-altitude units. The low altitude unit (also referred to as the
lowland program) covers areas less than 1,000 meters above sea level, which encompasses all
of the forest zone, and the Sudanian and Guinea savanna. Administratively, these zones
include the Center, South, East, South-West, the North and Extreme North provinces. The
mid-altitude area corresponds to locations 2,000 meters above sea level.

Since its beginning, the major constraints that the lowland breeding program has
sought to address include diseases (mainly maize streak virus), pests infestation (mainly stem
borers), soil acidity in the forest zone, and shortness of the rainy season, and striga in the
savanna area. Some of the program’s specific objectives have been to develop maize varieties
that are: (a) tolerant to drought and shade, (b) early maturing and have a deep root system,
(c) suitable to intercropping, (d) streak resistant, and (e) soft endosperm.

The lowland breeding program comprises five major activities: variety screening of
introduced material, population improvement, inbred line development, variety breeding, and
breeder and foundation seed production. These activities are carried out in eight locations in
the forest zone, and nine in the savanna. Since 1988, the intent has been to reduce the
amount of germplasm introduced each year and to put more emphasis on population and
hybrid development (NCRE, 1990). In general, before any new introduction is released for
agronomic and on—farm testing, it is tested for a minimum of three years within the program.
The first step is the Experimental Variety ma (EVT) stage, followed by Elite Experimental
Variety Dials (EEVT), and finally the National Variety Trials (NVT).

Experimental variety trials are designed to evaluate newly introduced varieties. These
are grown in various ecologies to identify the best genotypes/location combinations. Superior

or promising varieties identified at this stage are then advanced to the EEVT level. Each of

30

the EEVT generally includes 12 entries, six of which are superior varieties selected from the
previous year’s EVT while the other six are the best selection from the previous year’s
EEVT. The most promising varieties at the EEVT stage are then advanced to the NVT stage
and, ultimately, to an Advanced Variety Trials stage, before being released for agronomic
trials.

In addition, the unit carries out Regional Unified Variety Trials (RUVT), which are
cooperative variety screening trials provided by international research institutions. Variety
development has basically involved testing families in each of the female gene pool
populations which have undergone one generation of random mating with the objective to
produce experimental varieties. This generally happens in the first season. In the second
season, the effect of random mating on yield, and resistance to disease is evaluated. This
effort is complemented by line development, diallel evaluation, and variety evaluation“.

Most of the maize variety developed by the program are Open pollinated varieties.
Although a hybrid program was started in 1984, it has expanded slowly mainly because of
reluctance to promote the use of hybrids among small farmers. The traditional justification

for this perspective has been that: (a) small farmers cannot profitably adopt hybrids under

 

1'4 W is an attempt to develop high-yielding and good combiner inbred line for
synthetic and hybrid varieties development, and to identify new trait donor sources for pepulation
improvement.

mm essentially aims at studying varieties’ potentials as new trait donor sources for
population improvement.

Qiallel evaluatigg consists of testing (in the second season) direct and reciprocal crosses (and
parents) made in a diallel fashion among a number of parents in the first season. The objective is to study
the breeding value and heterotic relationships of the lowland maize papulation found adapted to the
Cameroon environment.

W is designed to restore high-yielding capacity and improve some agronomic
characteristics. It is achieved through traditional intra-population breeding methods and mass selection for
local adaptability. -

31

risky and low input conditions“, (b) small farmers will not be willing or cannot afford to
replace their seeds each season, and (c) the successful introduction of hybrids requires the
existence of a well-established seed industry. The validity of these assumptions are further

discussed in Chapter 4.

2.4.2.2.3 WW

Maize agronomy research in the North Province is carried out by the NCRE’s Cereal
Agronomy Unit based at Garoua. The unit is responsible for maize, sorghum, and pearl millet
agronomic experiments in the semi-arid lowland savanna (Extreme North Province), the

subhumid lowland savanna (North Province), and the highland plateau of Adamaoua. The

main research objectives are to: (a) better understand the main agronomic constraints to cereal .

production in this mandate area, and (b) test different agronomic practices in an effort to
alleviate these constraints.

When the unit started in 1982, its activities were limited to conducting fertilizer and
variety trials, especially on maize and mainly in the western provinces. Since 1985, it has
established an extensive production-oriented research program, devoting about 70 percent of
its research efforts to maize and 30 percent to sorghum, especially since 1985 (NCRE, 1986
p.190; NCRE, 1988. p.63. Unlike other NCRE’s agronomy units, the cereal agronomy
program in the North operates to a considerable degree as an extension agronomy unit, due to
the nonexistence of a TLU in the Province. It also helps manage maize and sorghum

breeding trials in the Province. Due to the wide diversity of agroclimatic conditions in the

 

15 It is often argued that hybrid production potential can only be achieved under favorable
climatic conditions and with the use of a complementary input package including fertilizer. Therefore,
small farmers, who are believed to be operating under risky and low input conditions and rarely adopt the
entire package cannot recovers their expenses.

32

ecologies the unit covers, field research activities are conducted at ten IRA substations and on
many farmers’ fields. The unit develops its work plan with considerable inputs from

SODECOTON .

2.4.2.2.4 Qn-farm Maize Resgaggh

On-farm research ’started in Cameroon in 1977 when SAFGRAD JP #26 was
established at Maroua under the leadership of Alex Bouchette. Following the creation of the
first NCRE Project TLU at Bambui in 1981, the program took a completely new dimension.
The success of this TLU in the first phase of the NCRE project led to the creation of more
TLUs, as discussed in the project overview section. SAFGRAD Projects and the TLU have
addressed various research themes, including: date of planting, plant density, fertilizer
response, weed control, planting methods, intercropping, and crop rotation trials.
SAFGRAD’s activities were concentrated in the North Province while the TLU/NCRE
operates in the Extreme-North. Since 1982, the NCRE maize agronomy research team based

at Garoua has carried out extensive on-farm testing in collaboration with SODECOTON.

0

2.4.2.3 Wm
2.4.2.3.1 W

Three SAFGRAD projects have operated in the North Province since 1977, namely: _
SAFGRAD Joint Project #26“, SAFGRAD Joint Project #31, and SAFGRAD/Farming
Systems Research. All these projects are collaborative projects with the Scientific, Technical

and Research Commission (0311:.) of the Organization of Afiican Unity (AOU). SAFGRAD

 

1'6 This project started in Maroua in 1977 under the management of Alex Bouchette. Virtually
no written document about this project is available.

 

33

activities are coordinated from its headquarter in Burkina Fasso. Generally speaking,
SAFGRAD provides funds to IITA and ICRISAT to (a) support food crop research programs
with a regional scope in the semi—arid area of Africa, (b) improve communications among
food crop scientists in this region by funding visits, conferences and seminars, (c) test
research station results under farmers’ circumstances”, and ((1) support long-term training in
the US, as well as short-term training at ICRISAT and IITA. The major source of
SAFGRAD’s financial support has been USAID. Some funding have been provided by FAC,

IDRC, IF AD, and national governments.

2.4.2.3.2 SAFQRAD LP. #31

SAFGRAD J .P. #31 started in 1979 as a continuation and extension of the LP. #26
with the arrival of Owen Gwathmey, assisted by a national (Martin Fobasso). In 1984,
Fobasso went for training in the US and was replaced by Jean Zoning, who unfortunately died
on February 1986. During this same period, Jerry Johnson took over from Owen in 1984.
Until the early 19803, SAFGRAD LP. #31 research activities focused on station varietal trials
on sorghum, millet, maize and cowpea. The project progressively shifted to emphasize on-
farm testing, as the number of food crop scientists at IRA Maroua increased. By 1983, their
entire research program was on-farm oriented.

The variety screening process followed by SAFGRAD LP. #31 involved a minimum
of five steps:
1) Regional Variety Dials (RVT) for newly introduced material, which were

implemented on research stations.

 

1'7 On-farm research was the focus of SAFGRAD’s Accelerated Crap Production (ACPO)
program which was implemented in four member countries, namely Mali, Togo, Burkina Fasso, and
Cameroon.

34

2) Advanced Variety Trials (AVT) which were theme—specific adaptive trials for
promising varieties identified in the RVTs.

3) Pre—extension Trials (PET), which were on-farm multilocational trials.

4) Taste Tests of varieties retained at the PET stage. Varieties selected at this level were
called "elite varieties".

5) Premultiplication plots of foundation seeds for extension services and specialized seed
multiplication companies. The multiplication process followed FAO’s
recommendations.

The on-farm testing program’s objective was to make both research and extension
stronger and more effective by establishing a link between station research and
SODECOTON. In the framework of this institutional collaboration, IRA had the
responsibility to provide an annual work plan with SODECOTON input. In return,
SODECOTON made available over 300 field agents to supervise the implementation and
inputs to be used, and formulated new extension themes based on on-farm test results. In
addition, farmers contributed to the program by providing the ”local" variety to be used as a
check in the trial, as well as labor.

Each January, in annual planning meeting IRA-SODECOTON is held. The
SAFGRAD on-farm research team submit a preliminary report, which summarized last year
results and proposed new test themes. The results and theme pr0posals are discussed by all
participants, and a final report of test results and revised pr0posals are made available for the
agronomists research meeting. To implement the agreed upon research, each SODECOTON
sector head chooses the field agents best qualified to conduct each test.

At the end of April or early May, the selected agents meet with IRA scientists in

groups from three to four sectors. During these meetings, the tests implementation process is

35

explained and discussed, and the necessary inputs distributed. Specifically, these field agents
are instructed on how to choose an appropriate farmer and field, when to plant the trial (late
May early June), and how to prepare the land and supervise seeding.

The research team visits the selected sites a minimum of two times. The first field
tour is made in June-July to check the choice of the fields, the status of land preparation and
seeding, and to discuss and solve early season problems. Another field tour is made around
the end of July or early September. This tour is the most important one because during this
visit researchers gather detailed information regarding plant density, treatments and operations
performed for each treatment; check the consistency of what the field supervisors did with the
guidelines on the instruction sheet; make agronomic observations; and collect rainfall data.

At the end of the visit, instructions for harvest are discussed.

2.4.2.3-3 W

SAFGRAD/FSR was established in 1986 with the following objectives:

1) To develop agricultural production technologies adapted to the conditions and need of
small-scale farmers, with emphasis on soil-water, soil-moisture, soil-fertility and other
conservation techniques.

2) To strengthen the national Fanning systems Research Program by working together
with national researchers and extension agents.

3) To foster the transfer of agricultural research results by conducting on-farm trials and
socioeconomic studies in collaboration with farmers , and by providing feedback
between station researchers, development agents, and farmers.

SAFGRAD/FSR followed a multidisciplinary approach to research implemented by a

team of scientists from three disciplines (agricultural economy, agronomy, and agro-forestry),

all hit

mndu:

SAFGi

filliO-l

mini;

SODE

midi

36

and had a mandate to cover the five northern-most regions of SODECOTON. The team
conducted on-farm research with both SODECOTON and non-SODECOTON farmers.
SAFGRAD/FSR operates in primary and secondary villages selected using a multistage
random sampling procedure".

Research activities carried out can be grouped into four categories: (1) research-
managed agronomic trials and (2) on-farm trials conducted in collaboration with
SODECOTON and farmers that are implemented in the primary sites, (3) on-farm trials
conducted in collaboration with farmers only in the secondary sites, and (4) socioeconomic
studies". In 1986, a large number of tertiary sites were used for farmer-managed trials.
Both agronomic and economic evaluation of the trials (partial budget analysis) were done.

Researchers’ interaction with SODECOTON starts with a planning meeting in early
February, during which previous results are discussed and new themes (mostly variety trial)
for on-farm testing are identified. After agreement, the SAFGRAD team’s responsibility is to
prepare the trials’ protocols, to provide seed, to visit the trial sites, and analyze the collected

data. SODECOTON selects sites and farmers, and assigns monitors to the selected farmers.

 

18 The SAFGRAD team divided its mandated area into three agroecological zones (Sahelian
savanna, Sudan savanna, and Guinea savanna), which are further divided into geographical regions, based
on cropping patterns, soil types, and farmers’ socioeconomic setting. A sample of 2-3 primary villages
and 2-3 secondary villaga around each primary villages were randomly selected in each region from the
list of villages in that region. The primary villages are selected based upon soil types, accessibility, relative
location and size, and local public support programs. A field research assistant was posted in each of the
primary villager. He compiled a list of farmers in each village, including their affiliation with
SODECOTON. From each of these lists, 5-10 farmers were randomly selected, depending on the size
of the farming population. A total of 220 farmers were selected from these villages. Non-SODECOTON
farmers are selected on a voluntary basis during a meeting with the farmers, presided over by the village
chief. During this meeting, the project and proposed research themes objectives are explained and
discussed.

1'9 Numerous socio-economic surveys were conducted. A sample made up of the 200 farmers
selected was used in a baseline survey of the Province. Various subsets of this sample were included as
respondents for specific studies, including verification, farm resources use, marketing and storage,
transportation facilities, and farmers organizations.

37

More specifically, a chief of sector selects 2-3 zones. The selected zones chiefs in turn select
1-3 villages. In each village, a farmer is identified for the trial. Each farmer is treated as a
replication within a sector.

Before planting in each region, a series of meetings were held between the
SAFGRAD team, chief of sectors, chief of zones, and monitors. The SAFGRAD team visited
the trials at least four times: (1) before planting to distribute planting material, (2) between
planting and harvest to record observations, (3) close to harvest to distribute harvesting

material and provide instructions, and (4) at harvest to weigh and collect harvest samples.

2.4.3 Maize Extension

Maize extension activities in North Cameroon are performed by various institutions,
most of which are state owned. Socioeconomic economic surveys conducted by the
SAFGRAD/FSR team in 1986 revealed that the most important of these institutions is
SODECOTON with a coverage of about 39 percent of the North Province farming population.
The other institutions which are marginal include the Ministry. of Agriculture’s extension

service (9 percent) and 'Société de Développement du Bl?“ (SODEBLE).

2.4.3-1 SQQLCQIQN

2.4.3.1.1 mm
SODECOTON is a rural development-oriented agro-industrial agency created in 1974

to take over from the French cotton company, CFDT. It is co-founded by the Cameroon

government and France, and supervised by the Ministry of Commerce. However,

 

2° Officially created for wheat production, SODEBLE ended up engaging in maize production.
It was however terminated in the late 19803.

38
SODECOTON agreed to collaborate with the Ministry of Agriculture’s extension service.

Geographically, SODECOTON’s activities cover both the Extreme-North and North
provinces, as presented in Figure A.2 in appendix.

SODECOTON’s activities are organized in two main Divisions: the Division of Rural
Development, and the Division of Industries and Equipments. The Division of Industries and
Equipments manages industrial activities of nine physical degraining plants. The Division of
Rural Development, headed by a Director and Deputy Director, carries out production
extension activities. At the bottom level of the Division of Rural Development structure are
markets, managed by one field agents (monitors) per market or two if the market is large (i.e.
300 to 350 ha). These markers are grouped into zones (5-14 per zone), which in turn are
grouped into sectors (3—5 per sector). The sectors are also grouped into regions (3-5 per
region). Each of these substructures is headed by a Chief, assisted by a training service.

Over time, the size of the Division of Rural Development has undergone various
changes in an attempt to ensure effective and close monitoring at reasonable costs. The
current regions are: Mora-Mokolo-Diamare, Kaele, and Mayo Daney in the Extreme-North;
Mayo Louti, North-East Benoué (NEB), West Bénoué, and South-East Bénoué (SEB) in the

North Province.

2.4.3-1.2 W

SODECOTON extension service follows a modified Training and Visit extension

system approach. Over time, these activities have been organized within various rural

39

development projects”, either as one of many participants responsible for implementation or

as the sole participant. SODECOTON performs numerous activities, including:

1)

2)

3)

Extension. Food crops and cotton production extension program serves about
180,000 participant farmers.

Inputs supply. Inputs for the packages extended include fertilizer, improved seeds,
herbicides, pesticides and animal traction supplies. These inputs are not subsidized,
but they are given to farmers as a loan, which must be repaid in cash after farmers
sell their cotton to SODECOTON. As a result, only cotton farmers are eligible to
receive the loans.

Promotion of farmers’ c00peratives. This activity, initiated in 1980, is aimed at
organizing farmers into producer associations for the commercialization of cotton and
cereals. SODECOTON monitors the program and in return the associations pay a
management fee to SODECOTON . The first associations were called Pre-cooperative
Farmers’ Groups (GVP), but SODECOTON gradually transfers responsibilities to

farmers.

 

b)
C)
e)

21 These include:

Project South-East Benoué phase I, II and 111: It was initiated in late 1974 with funding from the
government, the National Product Marketing Board, and SODECOTON. The second phase
(1983/84-1987) was sponsored by CCCE, BIP, and SODECOT ON. In 1987, the CCCE gave
F.cfa 6.42 billion to continue finance, among others (i) crop diversification in relation with the
creation of a research station at Garoua and the growing importance of maize in the North, (ii)
Self-Managed Farmers Associations, (iii) 120 Km of rural roads and 43 wells, and (iv) the
relocation of 6,000 migrants in area suitable to farming.

Project North East Benoué: participated from 1975 to 1979-80 by providing technical support to
farmers.

Project West Benoue (1983- ): sponsored by FAC, BIP, and SODECOT ON .

Project Centre-Nord (1981-1988): sponsored by BIRD, USAID, BIP, and SODECOTON.
Project Motorintion (1981/82-1985/86): sponsored by CCCE, BIP, and SODECOTON. ,
Project FSAR II (1985- ): designed by FONADER and sponsored by BIRD, and BIT.
SODECOTON participate by implementing the functional alphabetization of farmers, storage and
degraining of groundnuts.

4)

5)

6)

7)

40
In 1987/88, the GVP were replaced by the Self-managed Farmers’

Associations (AVA), with activities extended to inputs management (acquisition and
distribution) and field monitoring. Wherever an AVA is created, SODECOTON field
agents are phased out and replaced by farmers selected by the AVA members.
However, SODECOTON does not completely abandon the area; It continues to
provide training to the 'AVAs’ leaders and supply inputs that are warehoused in some
villages. AVAs are responsible to get the inputs from SODECOTON (as loans) and
ensure their distribution to its members. In 1990/91, there were 471 AVAs with
93,716 members.

Commercialization. Cotton is the main crop commercialized by SODECOTON.
Maize commercialization started in 1981-82 through GVP. However, food crops sales
or purchases are marginal. The GVP maize price to SODECOTON ranges from 45
to 65 F .cfa/kg. In general, commercialization activities are carried out either directly
or through farmers cooperatives.

Promotion of animal traction for land preparation. This effort is supported through
sales of supplies, veterinary products and training for animal feeding and dairy animal
management.

Promotion of agricultural mechanization. This is supported through sales or rent of
tractors and equipments, including training and maintenance. This activity was
initiated in 1978 in the Benoue area.

Collaboration with research (IRA). Collaboration, especially on the on-farm research
activities, is implemented through IRA/SODECOTON annual planning meetings and
on-farm trials. During annual planning meetings held at the beginning of the cropping

season, researchers present and discuss new results (if any) and work plans for the

41

coming season. SODECOTON gives suggestions to improve the work plans and

ensure that the research conducted is appropriate, and also provide feedback on the

on-farm performance of previous research results.

Initially, SODECOTON participated in on-farm research activities, at no cost
to IRA. But since 1989, SODECOTON has charged 50,000 F .cfa for every CRB
trial conducted and 52,250 F .cfa for every RCB trial, which has considerably reduced
the number of trials implemented.

8) Infrastructure. These activities include building rural roads, warehouses, schools,
hospitals, dispensaries, schools, and wells, and relocating migrants in areas suitable to
farming.

SODECOTON involvement in food crop extension began in 1974-75 with rainfed rice
and maize extension activities followed a year later. The objective of these food crop
extension activities was to progressively encourage farmers to replace sorghum with more
productive crops, so that farmers could devote more of their time and larger portions of their
land to cotton production (SODECOTON, 197s77; p.20). Also, SODECOTON expected
that these crops would provide farmers with a secure and adequate food supply during the
hunger period before sorghum is harvested. Food crop extension was later expended to
cowpea, sorghum and groundnut through a World Bank project (Project Centre-Nord), which
was managed and implemented by SODECOT ON in collaboration with IRA. Since 1990,
food cr0p activities have been reduced in an effort to fulfil the Performance Contract

agreements signed with the government in an attempt to improve the financial results.

42

2.4.3.1.3 Maize Extension

As reported earlier, SODECOTON initiated its maize extension activities in 1976-77.
In that year, two maize varieties imported from Nigeria (Samura 123 or $123 and Upper
Volta Early) were tested over about 100 hectares. Since then, numerous varieties have been

evaluated under farmers’ conditions and extended as summarized in Table 2.2.

Table 2.2: Maize Varieties Extended by SODECOTON, 1975-1991, North Province, Cameroon.

 

Variety Extended ‘ Year of Last Year in Variety Origin
Introduction Extension

Samura 123 1975-76 1983-84 Nigeria
Upper Volta Early 1975-76 1975-76 Nigeria

NCA 1977-78 1077-78 IRAF

TZPB 81 1982-83 (a) IRAF
Mexican 17 Early 1984-85 ' (a) IRAF

CMS 8501 198889 (a) NCRE

CMS 8704 1990-91 (a) NCRE

 

(a) Still being extended.
So_u__rce: Adapted from SODECOTON Annual Reports 1976-77 to 1990-91.

In the North Province, maize is extended under low input and high input systems.
These two systems differ not only in terms of the inputs use but also in terms of
SODECOTON monitoring. The high input system is characterized by SODECOTON field
agents supervision, mechanical land preparation (oxen and tractor), seed treatment, herbicide
and fertilizer application, and a specific plant stand (0.80 x 0.25 m, one plant per hill).
Farmers participating in the intensive system have little choice but to follow SODECOTON’s

guidelines. For example, land is prepared with either oxen or tractors. Cotton farmers who

43

do not use treated seeds are not eligible to receive the fertilizer loan. Herbicide and fertilizer
recommendations are monitored closely. Planting is strictly done during the recommended
period.

By contrast, the low input system is characterized by minimal use of these inputs and
no SODECOTON monitoring. The varieties planted in the low input system are those
extended by SODECOTON, either the same year or in some recent years ago. Row and
manual plantings, as well as a cotton/maize crop rotation, are very common in both systems,
and in 70-85 percent of the cases, maize follows cotton, a crop sequence recommended to
take advantage of the residual effect of the fertilizer applied on cotton.

Originally, the high input system was extended for maize grown in a pure stand.
Beginning in 1983-84, this system was also extended for maize grown in association with
sorghum (the initial pattern which alternate planting within a row, was later replaced by
alternate single rows). This association is intended to provide farmers with food (maize)
during the August-September hunger period before sorghum harvest. Under this cropping
pattern, a different herbicide (sorghoprim) and a lower fertilizer application rate (50 kg/ha of
urea for maize and 50 kg/ha of urea for sorghum) are recommended.

. Over the last decade, the maize area in the northern part of Cameroon has expanded
tremendously. This can be seen using SODECOTON data presented in Table 2.3 and Figure
2.4 below, even though SODECOTON does not deal with all farmers in the Province.
However, a comparison of SODECOTON and census data (Table 2.1) shows no significant

difference.

Table 2.3: Area (Ha) Planted for Crops Extended by SODECOTON, North Province, Cameroon, 1979-1990.

 

 

 

E Maize Sorghum Peanut Rice Cotton
1979-80 6, 160 md md 747 56,594
1980-81 6,152 md md 347 65,340
1981-82 6,691 md 23,043 546 63,343
1982-83 6,870 143,529 26,943 826 54,629
1983-84 7,621 120,049 28,772 941 71,092
1984-85 9,319 140,659 34,467 1,078 73,319
1985-86 13,877 149,480 43,447 867 89,232
1986-87 15,592 151,660 42,589 644 94,461
1987-88 13,291 142,017 35,578 414 94,744
1988-89 18,657 158,442 42,786 181 1 1 1,604
1989-90 27,232 173,314 45,100 223 89,004
1990-91 24,985 158,504 40,290 161 93,835

 

“md” stands for missing data.
3.013.991 Adapted from SODECOT ON Annual Reports, 1976-77 to 1990-91.

 

 

 

 

 

Thousands
200
1504
*Malaa
+80rghum
10° *Paanut
' +Cotton
‘ *Riea
ml

 

m e: :1 :1 e: e: e: = :
1N2 1m 1”! race rose rear 188 1“ 1990

W: Area (ha) Planted for Major Food Crops in the
SODECOT ON Zone, North Province.

45

While SODECOTON considers maize area expansion to be a success, it recognizes
that it has been taking place at the expense of sorghum and cotton (1978-79, p.15; 1982-83,
p.32). This expansion has occurred mainly in the North Province (about 70-96 percent of the
area), especially in the Tcholliré subdivision, while the area under sorghum and cotton has
been expending in the extreme-north. In 1983-84, SODECOTON decided to stop maize
extension activities in the north-most part of its mandated area (i.e., current Extreme-North
Province) because of poor yield resulting from unfavorable climatic conditions. In contrast,

the southern area proved to have good potential for maize production thanks to favorable

 

rains. Over time, maize yield under the high input system in farmers’ fields has averaged'2.3

metric tons per hectare, ranging from 2.0 to 3.0 mt/ha.

24.32 W

The Ministry of Agriculture is comprised of eight Directorates, one of which is the
Directorate of Agriculture (DIRAGRI). The DIRAGRI has the responsibility for delivering
extension services for agricultural production and plant protection through Provincial
Delegations in each of the country’s ten provinces.

Overall, the extension activities from Agricultural Provincial Delegation (North
Province) has been marginal and their liaison with IRA has been weak. The main reasons are
partly the weaknesses of the majority of the extension services within the DIRAGRI referred
to in the agricultural policy section of this chapter. Thus, most of the effective extension .
activities in this Province has been carried out by SODECOTON, which delivers extension

support primarily to cotton farmers.

 

d}

dill

imifi

Wm

Wig

2.4.4 Seed Production

2.4.4.1 Seed Policy
Since the 19703, various government institutions have carried out seed multiplication,

either as full time activities or as a complementary activity, including:

a) NCSM operating in the northern part of the country and sponsored by USAID;

b) MIDEVIV (Mission de Developpement et des Semences et des Cultures Vivrieres)
seed multiplication center at Ntui, operating in the South, with FAO technical
assistance;

c) UCCAO (Union Centrale des Cooperatives Agricoles de l’Ouest), operating in the
West (Bafole), with World Bank founding;

d) ‘ MIDENO (Mission de Développement de la PrOvince du Nord-Quest) operating in the
North-West, with limited donors’ support;

e) French technical assistance, which provided contributions for procurement and the
training of nationals.

Despite the impressive number of institutions involved in seed production and
distribution, Cameroon has no clear seed policy, even though MIDEVIV was given the
mandate to promote the development of food crops and seed production. In an attempt to
improve seed production policy, the government created a seed council in 1990 and liquidated
MIDEVIV. This council is now responsible for establishing the procedures for seed
certification and registration, varieties release and publishing a seed catalog.

Among the institutions involved in seed production and distribution, NCSM has

performed best based on the amount of seed distributed”. But due to the ongoing economic

 

22 A total of 300 mt of maize and groundnut seeds were distributed by NCSM up to 1989, as
oppose to a total of only 15 to 40 mt for the other institutions.

dui
phi
pro}
muli

Mm

47

crisis faced by the country, the poor financial performance of NCSM, and the increasing
demand for seed, the government decided to privatize the seed production and distribution
sector. As a result, Pioneer established a subsidiary in Cameroon and initiated operations in

1991.

2.4.4.2 N rth r n Mul' icati n Co on

The NCSM project was created on June 15, 1975 to serve the northern part of
Cameroon through a bilateral agreement between USAID and the government of Cameroon.
The objectives assigned to the project were: (1) to improved farmers’ productivity through the
production and distribution of improved seeds, as well as training, and (2) to reduce market
prices of cereals and legumes by increasing market supply. Its parent organization is the Seed
and Food Development Authority (MIDEVIV).

The NCSM project lasted 15 years before being terminated in 1989/1990. It went ’
through two phases. Phase I lasted five years (1975-1980), followed by an intermediate phase
(1980-1982) which was entirely financed by Cameroon government. The goals in phase I
were not achieved in part because “the project tried to undertake too many activities at the
same time with limited resources" (Jaeger, 1987).

NCSM did not make a serious effort to address seed production requirement until
during its second phase, when it was included as a component of Project Centre-Nord. This
phase went from 1983 to 1990, including three years extension after the original end of
project date. Under Project Centre-Nord, NCSM was redesigned to broaden its scope of seed
multiplication activities, to institutionalize a functioning seed flow program including linkages

with research, and to ensure delivery of improved seed to farmers (Johnson, 1987). The

48

NCSM carried out seed production in six multiplication fields located in the Extreme-North

(Kousseri, Guetale, Gazawa), North (Garoua, Sanguéré) and Adamaoua (W akwa) provinces.

NCSM initially focused on producing sorghum. It was not until 1978-79 that its

expanded its production to maize. The maize varieties grown are open pollinated. Table 2.4

and 2.5 below present crops dealt with by the NCSM project, the area cultivated and

production of each of these crops over the years.

Table 2,4: Area Planted (ha) for Seed Production by NCSM Project, 1979-1989, Cameroon.

 

 

Year Sorghum Maize” Groundnut Cowpea Onion Coton Sweet P.
1979 53.10 11.40 348.40 0 0 0 0
1980 41.40 68.10 139.10 0 0 87.00 0
1981 31.00 43.00 122.00 0 0 0 0
1982 28.00 59.00 116.00 0 0 0 0
1983 16.70 56.00 137.00 7.00 1.00 0 O
1984 35.00 57.25 235.50 27.00 1.20 0 0.10
1985 41.20 136.00 130.00 15.50 1.70 0 0.50
1986 79.20 128.40 104.70 30.00 7.30 ‘ 0 O
1987 49.00 84.00 98.50 24.50 6.50 0 O
1988 6.16 59.60 70.64 14.01 0 0 0
1989 45.00 109.00 75.25 3.50 0 0 0

 

"’ 5.57 hectares of maize were planted in 1978 and none before 1978.
55mm: Adapted from the NCSM Annual Reports and Evaluation Documents.

49
Table 2.5: Seed Production“) (mt) by NCSM Project, 1979—1989, Cameroon.

 

 

Year Sorghum Maize Grouflnut Cowpea Onion Cotton Sweet P.
1979 39.10 11.40 280.94 0 0 0 0
1980 35.44 89.45 121.75 0 0 108.00 0
1981 29.88 60.76 183.08 0 0 0 0
1982 33.60 141.20 167.70 0 0 0 0
1983 17.00 147.00 203.00 11.00 0.35 0 0
1984 50.30 113.50 1,445.66 15.52 0.87 0 0.55
1985 74.30 242.60 163.22 18.20 0.85 0 3.00
1986 164.77 340.40 191.49 32.56 80.56 0 0
1987 md md md md md 0 0
1988 0.00 62.30 113.36 md 0 0 0
1989 md md md md 0 0 0

 

9’ Does not include purchases from contractual farmers.
'md" stands for missing data.
M: Adapted from the NCSM Annual Reports and Evaluation Documents.

The NCSM project seeds were produced either by the project itself” or through
contract farming. These seeds were mainly sold to SODECOTON for distribution, and less
so to NEB and SODEBLE. NCSM did not have a clearly defined seed price policy (NCSM,
1986,). While project officials favored differentiating prices from grain prices,
SODECOTON staff claimed a high seed price would curtail farmers’ demand. Consequently,
certified seed prices were subsidized (60% subsidy). Later, during the mid-term evaluation in

July 1980, NCSM was advised to carry out a market study and farm survey to estimate

farmers reactions to and effective demand for improved seeds (Johnson, 1987).

 

23 Maize, sorghum, com and groundnut were produced at Sanguere, Guetale and Gazawa,
onionatKousseriand fmitsatKarewsandWskwa.

llie
implement
pinup-int
do too mu
the projez
entrain
m in
guilty
lint.
consid

in d

2.4.4.

by P10

1991.

projea

50

The NCSM was terminated in 1983 because of poor financial performance, slow
implementation of most project activities, poor management and coordination among
participant government agencies (IRA, SODECOTON, MIDEVIV), and the project attempt to
do too much in such a short time (Jaeger, 1987). In addition, the evaluation team criticized
the project design by commenting that "several Optimistic assumptions were made and that
constraints to the project’s long-term objective were not properly considered. These include
poor farm size selection, lack of research results, inadequate marketing systems, lack of
quality control, and uncertainty about the capacity of the private sector" (J aeger, 1987).

Thus, the project poor performance was in part due to the failure of the project designers to
consider that research on breeder seeds required is a long-term effort for which the outcome

was difficult to predict.

2.4.4.3 WWW

Following the decision to privatize the NCSM project, seed production was taken over
by Pioneer Cameroon (PACSA) under an agreement signed with the Government in March
1991. This agreement handed over all facilities previously used by the defunct the NCSM
project to Pioneer Cameroon in exchange of a symbolic franc.

1 Unlike the NCSM project, Pioneer Cameroon operated on a profit-making basis. In
order to achieve this goal, the company planed to expand geographically, increase the number
of commodities produced, as well as gradually phaseout Open-pollinated varieties for hybrids.
Soybean, sunflower, and alfalfa will be added to the cr0ps traditionally grown by NCSM
(maize, sorghum, cowpea and onion). In addition, suitable hybrids were expected to be
developed or identified to replace the open—pollinated maize varieties. PACSA’s first target

area was the northern part of Cameroon. Its first produced open-pollinated seeds in 1991.

51

Seed production activities were expected to expend over time in the South, North-west, South-
west provinces, and ultimately, in all Central Africa economic union countries“.

While in its developmental stage, PASCA’s managers strongly believed there is a high
potential to achieve their goal, given the large market, guaranteed support from the Ministry
of Agriculture if needed, and a well-structured research system with which they will be
. collaborating. Unfortunately, all hopes raised by Pioneer’s involvement in seed production in
Cameroon ended up as broken promises as the company closed down in July 1993, leaving
behind a vacuum that will have to be filled if Cameroon is to expend its production to satisfy

the demand.

2.4.5 Maize Marketing

Unlike for export crops, the government intervenes minimally in support of food
crops commercialization. Due to high product market prices during the hunger period
(resulting from precarious climatical conditions) especially in the northern provinces, the
government has attempted to control the cereal market through Ofi‘ice Céréalier. Yet, the
maize market in the North Province is dominated by individual buyers and sellers and
MAISCAM. Although SODECOTON and SODEBLE also purchased grains, their impact on

the market has however been marginal.

 

2" This union known as UDEAC (Union Douaniere des Etats de l’Afrique Centrale) includes
Cameroon, Chad, Congo, Gabon, Guinea Bissau, and RCA.

52
2.4.5.1 ce réali r

Created in 1974, Office Céréalier has a national mandate to intervene (buy and sell) in
the market in order to guarantee reasonable prices” to both producers and consumers, and to
create a food security stock of 6000 mt of cereals. Unfortunately, this project has failed to
influence market prices, as the prescribed 10 to 15 percent market coverage at both sales and
purchases level was never achieved. Up to 1985, the coverage rates were 6.7 to 9.9 percent

of purchases, and 4.7 to 7.5 percent of sales.

2.4.5.2 MAISCAM

MAISCAM, a private agro-industrial enterprise owned by a national, is located 20
kilometers north of N gaoundére in the Adamaoua Province. Its activities includes the
production and purchased of maize grain, which it processes into flour, grits, and oil for
households’ consumption, and flour and maize cake for animal feeding.

MAISCAM’s opened in 1984 and produced 100 hectares of maize. Since then, the
firm has expanded tremendously. In 1985, it cultivated 500 hectares, and in each of the last
three years, it planted 3,000 hectares, with two crops annually. These 3,000 hectares are
cropped in maize (2,300 ha), soybean (500 ha), and sunflower (200 ha). Sunflower and
soybean are planted mainly in rotation with maize in an attempt to maintain good soil fertility.
All maize seeds used are hybrids, imported from Zimbabwe and Kenya.

MAISCAM produced a total of 12,500 mt of maize in 1990. With a milling capacity
of 40,000 mt, the firm has engaged in a vast campaign to purchase maize from traditional
farmers throughout the North, Adamaoua, and West provinces in order to run its plant

economically. This campaign started slowly in 1989 with only 3,000 tones of maize grain

 

25 Cereal market prices increase by about 46% during the hunger period.

if

I“!

f?

S3

bought. As farmers became aware of the existence of MAISCAM and their interest in maize
production grew, purchases increased to 6,000 mt in 1989. In 1990, the firm intends to buy
10,000 to 12,000 mt of maize from traditional farmers.

The ultimate objective of MAISCAM is to expand its farm to 5,000 hectares, to be
complemented by about 20,000 mt of grain purchased from traditional farmers. The firm’s
management believes that the pace at which this targeted ceiling will be reached largely
depends on the experience they acquire over time, particularly their aptitude to maintain soil
fertility on the available land, and their financial capacity to make the investments required to
expand their enterprise.

- MAISCAM’s main maize suppliers are small size traditional farmers and retailers.
Nevertheless, they occasionally buy maize from cooperatives, Office Céréalier and
SODECOTON. The average price of the grain purchased is 50 F .cfa per Kilogram with a
ceiling of 75 F.cfa. The firm’s products are mainly sold in big cities like Yaounde, Douala
and Bafoussam, but attempts to expand the market area are being considered.

MAISCAM’s manager forecast for maize expansion in the region is very optimistic.
The arguments given to support this positive perception are the fact that MAISCAM buys in
cash large amounts of grain at a relatively attractive price. Furthermore, maize is an easy
crop to produce, the climatical environment is favorable, and the possibility of fresh

consumption during hungry periods provides incentive for farmers to grow the crop.

CHAPTER 3 THEORETICAL FRAMEWORK and LITERATURE REVIEW

3.1 Theoretical Framework
This section reviews the literature on the economic theory behind the analytical model
used in this thesis. Definitions of benefits and costs are discussed, as well as the criterion for

their valuation.

3.1.1 Benefit/Cost Analysis

Benefit/Cost analysis is a tool for evaluating changes in public welfare resulting from
an investment in a project. This analytical approach was developed during the 19505 and
19603 to evaluate social benefits and costs of investments in large scale projects" (Little and
Mirrlees, 1979). There has been numerous refinements in Benefit/Cost analysis methodology
over time. The most important development led to an expansion in the scope of benefits and

costs that are considered in the analysis, including equity, employments, and training impacts.

3.1.1.1 Wm

In general, project successes are measured by quantifying the costs incurred and

benefits generated by the project, and weighing them against each other in order to determine

 

2‘ The benefit/com analysis approach originated in the United States as an element of the 1933 Flood
Control Act, as amended in 1936 (Pearce & Nash, 1981; Krutilla, 1981; Bromley, 1990). This Act
basically required that flood control projects be analyzed in terms of their benefits and costs (explicit
estimtion of expected gains and losses), and should only be implemented if the benefits accrued are in
excess of the estimated costs. Early efforts to refine benefit/cost analysis methodology were led by the
Organization for Economic Cooperation and Development (OECD,1969) and United Nations (UN, 1972).
Applications to project appraisal in developing countries were refined during the 19703 by the World Bank
(Gittinger, 1972; Squire and Van Der Tak, 1972).

55

the returns to the investment made. This section defines what is considered as a cost and
what is considered as a benefit.

Benefits and costs are defined with respect to one or more objectives. In a simplistic
way, anything that contributes negatively to the objective is considered as a cost, and anything
that contributes positively is considered as a benefit. According to Gittinger (1982), "in most
developing countries, increased income is probably the single most important objective of
individual economic effort, and increased national income is probably the most important
objective of national economic policy”. Consequently, in this study, costs include all the
investments incurred by various institutions involved in maize research and extension in the
Northern Province, as well as investments made by farmers (adoption costs). The benefits
correspond to the monetary value of all of the maize production in the area originating from
the project activities. Consumers’ valuation is the basis for attributing values to the benefits
items identified. 'Iheir valuation is assumed to accurately represent consumers’ willingness to
pay for the goods and services provided.

The problem with such an approach is that, in actual fact, individuals have multiple
objectives and projects generate externalities. For examme, an individual may have objectives
including securing adequate food supply, particularly during hunger periods, and generating
enough money for children’s education or household members’ medical care expenses. For _
the country as a whole, project benefits can be judged in terms of increased national income,
but also as pointed out by Gittinger (1982), in terms of their impact on income distribution,
job opportunities, increased savings, and broader economic consideration such as regional
integration.

Indeed, no formal impact study could possibly measure or take into account all the

various costs and benefits of an investment. Furthermore, there is a need to express all of

56

57

them in a common unit. Thus, as Gittinger (1982) points out, analytical approaches that have
been used focus on the projects contribution to national income. To the extent possible, all
benefits and costs expressed in a common units are included, and the importance of other
potential costs and benefits associated with the investment but which cannot be quantified
and/or valued are recognized and discussed qualitatively. Only a few recent studies have
included in the analysis extemalities generated by and the distributional impact from the
project. In fact, it is often assumed that the income distribution or equity objective will be
taken care of by various state fiscal policies. But, this assumption has been challenged in the
literature on the grounds that virtually all developing countries have been unable to adopt

strong macroeconomic policies that could successfully address this issue”.

3.1.1.2 WWW
3.1.1.2.1 Financial am Emngmic Angysis

Once all benefit and cost items have been identified, the next step in project appraisal
is their valuation. The valuation procedure depends on whether one does the analysis from
the point of view of individual farmers (financial analysis) or from the point of view of the
nation as a whole (economic analysis). Financial analysis is generally done first, followed by
economic analysis.

A distinctive feature of economic analysis is that actual benefits and costs are adjusted
to better reflect social gain or real resource costs (Little and Mirrlees, 1974). Two key

adjustments are made. First, as in financial analysis, all benefits and costs are discounted to

 

’7 In fact, Amin (1978) argues that practically all national plans 'pay lip Service“ to these issues, but
the rest of the plan rarely has anything to do with addressing thom issues. In practice, projects specifically
designed to address the income distribution issue are often the first to be dropped when resources are
limited. '

58

take into account the time value of money and, thus, to reflect present values. Second,
market prices used in financial analysis are adjusted to reflect social accounting or their
shadow prices to eliminate the effect of existing distortions in national economy. In addition,
economic analysis attempts to account for extemalities and indirect effects, both of which are
ignored in financial analysis. On the other hand, taxes, subsidies, and other transfer

payments are included in financial, but not in economic analysis.

3. 1. 1.2.2 Shadow Pricing

There is a wide debate in the literature about shadow pricing. Some authors argue
against shadow pricing for it requires a lot of effort that is sometimes not proportional to its
contribution to the evaluation results. Gittinger (1982) suggests starting with market prices,
generally at the point of first sale, unless it is proven that they do not accurately reflect
economic values. Thus, adjustments are only required if there are significant distortions
arising from direct transfers or policy induced distortions (such as taxes, subsidies, tariff,
etc), supply restrictions, existence of monopoly power, and excess capacity. Adjustments are
generally done in three successive steps: (1) adjustments for direct transfers, (2) adjustments
for price distortions in traded items, and (3) adjustments for price distortions in non-traded
items (Gittinger, 1982).

Adjusting market prices for policy-induced distortion implies treating taxes, subsidies,
loans, and loan services as direct transfer payments, either from the government to farmers or
vice versa, because they do not reflect changes in national income. Taxes such as sale taxes
are part of the benefit stream, as opposed to being part of the cost stream, as it is normally
the case in financial analysis. Subsidies on fertilizer or seeds sale would be ignored and the

full amount of the prices used.

59

For non-traded items, the valuation procedure starts with determining the domestic
market prices. For traded items, the valuation procedure starts with estimating border prices
which are equal to the CIF prices for imported items and FOB for exported items. These
prices are then adjusted for domestic transport and marketing costs between the point of
import (export) and the project site. The rationale behind this approach is that if, for
example, the project produces an import substitute, the value of this good to the nation as a
whole is equal to the value of the foreign exchange saved that would have otherwise been
used to import the good (Gittinger, 1982). In the case of diverted exports, the cost to society
is the foreign exchange loss that would have been gained had the good been exported. These
adjustments are necessary because in many countries peeple may be paying a premium on
traded goods as a result of currency over valuation, over what they pay on non-traded goods.
This distortion is not taken into account when the prices of traded goods are converted to the
domestic currency equivalent at the official exchange rate (OER).

Two equivalent ways are often used in the literature to incorporate a premium on
foreign exchange during the price adjustment process. One of these is the shadow exchange
rate (SER) approach advocated by the World Bank and UNIDO. This approach converts the
foreign exchange into domestic currency by making the traded goods relatively more
expensive in domestic currency by an amount equal to the premium (FEP). The other method
is the standard conversion factor (SCF) approach, which is advocated by OECD. This
approach consists in (l) converting foreign exchange prices to their domestic currency
equivalent by using the official exchange rate, and (2) reducing all prices of non-traded goods

by multiplying them by an appropriate SCF.

60

SER = OER(1+FEP) (3.1)
SCF = ——l—— (3.2)
(1+FEP)

More comprehensive valuation methods, which focus on the accuracy of the valuation,
have been developed by the World Bank, OECD, UNIDO and environmental economists.
These methods include in the valuation various social weighting schemes, but they have not
been widely used because of their complexity and the controversial feature of some of their

aspects (Little and Mirrlees, 1990; Squire, 1990).

3.1.1.3 mama
3.1.1.3.1 Efligiengy flenefigggst Analysis

Ideally, the most desirable state of any society is maximum social well-being. The
determination of the maximum social well-being point requires the existence of a social well-
being function emerging implicitly from a unanimous agreement among members of the
society. The problem is that, as established by Arrow’s impossibility theorem, the social
well-being function is impossible to find or, if determined, it can only be dictatorial. In the
absence of an identifiable social well-being function, economists have proposed a number of
criteria by which the social desirability of a project could be measured.

Efficiency benefit/cost analysis is viewed as a specific application of modern welfare
economic analysis, which emerged out of pOsitivism as a behavioral norm for scientific A
objectivity. It is a particular approach to benefit/cost analysis which focuses on net
contribution to the national income and uses the potential Pareto improvement criterion. This
principle states that an investment is considered welfare improving if and only if those who

gain can potentially afford to compensate those who lose and still be better off, provided that

61

there is a random sorting of losers and gainers over an unending sequence of actions. It
therefore considers aggregate benefits and costs expressed in terms of national income,
without regard to the distributional effects, and implicitly assumes a social welfare function
(utilitarian welfare function) with a unitary weight for all individuals. In order words, it
assumes a society in which all individuals have identical preferences.

Various measures have been used to quantify individual welfare change.
Conventionally, the equivalent variation (EV)28 and compensating variation (CV) are used in
applied welfare analysis as exact measure of welfare change. One of the problems that the
use of CV and EV poses is the fact that a straightforward, manageable procedure of
expressing them, in terms of elementary mathematical functions, has not yet been derived
(McKenzie, 1983). As a result, information require to obtain them is very demanding. This
is so because they are based on the Hicksian demand curve which is not directly observable.
It is therefore common to resort to empirical approximation in applied work. The theory of
consumer behavior indicates that, in principle, there is a link between the ordinal structure of
consumer preferences and the structure of consumer demand functions. The greater the
income effects, the greater is the difference between the CV, the EV, and consumer surplus.
Willig (1979) argues that, in most cases, consumer surplus is a ”close” approximation of CV
and EV. Furthermore, he established that for a single price change, provided individual’s
expenditure on the good and the variation are not very large, the error involved in using

consumer surplus as an estimate of the CV or EV is less than five percent.

 

as The EV and CV are expressed in term of the difference in expenditure functions between the initial
and terminal price, plus the change in individual’s money income. The EV represents the amount of
money which if added to the individual’s initial income, would have an effect on his utility equivalent to
that of the policy change ifhe was to face the original set of prices. By contrast, the CV measures the
change in money income that would just compensate the individual for a policy change in order to keep
him at the initial level of utility. Unlike the EV, the CV is not a utility indicator, and it is ambiguously
defined. In addition, both have different property rights implications.

62

In this study, even though the conditions referred to by Willig were not empirically
validated, they are assumed to be satisfied, on the grounds that the maize technology is
relatively new in the studied area and MAISCAM is the major buyer. Consumer surplus is
therefore used to measure welfare change. The welfare or utility that consumers are expected
to derive from consuming a good is reflected by economic prices which in turn are assumed

to accurately reflect consumer willingness to pay.

3.1.1.3.2 cial u lu d Technl ical h
Figure 3.1 represents a partial equilibrium model of the total demand and supply for a
good under perfect competition. The equilibrium condition is achieved at price Po and

quantity Qo where quantity demanded equals quantity purchased.

Pn'oe

 

0'0

0
0. Quantity

 

 

 

W: Graphical Representation of Individual’s Welfare.

63

The total welfare derived from the quantityQ0 could be approximated by the area
under the demand curve. For all units up to Q0, the price the consumer is willing to pay
exceeds the cost (price) of producing a unit of the good. Therefore, there exists an excess of
welfare or utility over cost. However, on the last unit, the price just equals the cost of
producing it. Traditionally, consumer surplus is the area under the demand curve (D) and
above the equilibrium price (Po). It is used to approximate the excess of what consumers
would be willing to pay over what they actually do pay. Producer surplus is the area above
the supply curve (S) and below the equilibrium price.

With changes in technologies, output for a given unit cost increases, or the price for
producing a given unit of output falls. This is represented graphically in Figure 3.2 by an
outward shift of the supply curve. Therefore, the change in the welfare surplus resulting
from technological changes is the total area PoabP, between the demand and supply curves

before and after adoption of a technology.

 

"D
as

-‘
e

 

a
GP. at W

 

 

 

 

W: Welfare Effect of a
Single Price Change.

64

In this study, simplifying assumptions of a perfectly elastic demand curve and
perfectly inelastic supply curve are made in order to measure economic welfare, strictly as a

function of the value of additional products generated, as indicated by Figure 3.3.

Price

 

 

 

 

 

 

0. 0' W

F igure 3.3: Welfare Effect of a Single Price Change under Simplified Assumptions.

Even though the supply and demand elasticity assumptions were not empirically
validated, they are assumed to be justified. Social surplus is therefore used to measure
welfare change asa net contribution to the national income. The main advantage of the
assumptions on demand and supply elasticities is that they preclude analysis of distributional
effects, and make it unnecessary to undertake the difficult task of estimating the Hicksian
demand curve. Thus, no information needs to be generated about the characteristics of supply
and demand in order to analyze welfare changes. While there are methods to incorporate
non-efficiency objectives, all require using some type of arbitrary weighting scheme, which

requires a priori agreement regarding the social welfare function. Moreover, as Contant and

65

Bottomley (1988) point out, distributional objectives can always be taken into account when

setting priorities, and when interpreting the results of efficiency benefit/cost analysis.

3.1.1.3.3 The M ur of Pr 'ect W : The Int rn R te of Return

After benefits and costs are identified and valued, the next step in benefit/cost analysis
is to select and compute success criteria. There are basically three distinct quantitative
measures of project worth suitable for application to impact studies in agriculture. The
measures most often used are the benefit/cost ratio (BIC)”, net present Value (NPV), and
internal rate of return (IRR).

The internal rate of return corresponds to the discount rate i that makes the NPV
equal to zero. The net present value is a straightforward discounted measure of project

worth, computed as the present value of the incremental net benefit stream.

 

NPV = E BFC‘ (3.5)
i (1+i)‘
where, B, = benefit in year t

C. = cost in year t
i = discount rate

The NPV can also be calculated by subtracting the present value of the cost stream

from the present value of the benefit stream:

 

an Historically, the benefit/cost ratio criterion was the first widely used discounted measure of project
worth, but it is not commonly used in developing countries. Gittinger (1982) argues that this is so because
by the time measures of project worth began to be applied in developing countries, the NPV and IRR were
widely known and used.

 

 

n B n C
NPV = ' - ‘ (3.6)
g (1 fl)‘ ; (1+i)‘

Two simplifying assumptions are implicit in the formulation of the NPV criterion: the
reinvestment rate is equal to the discount rate, and both are assumed to be constant over
time”. The first assumption is only valid if the capital market is perfect and the opportunity
cost of capital (discount rate) does not depend on the size, the length or other characteristics
of the investment.

The formular of the IRR is therefore as follow:

NPV = . ii = o (3.7)
21: (1+i)‘

When used in economic analysis, the IRR is sometimes referred to as the economic
rate of return, as opposed to the financial rate of return terminology used in financial analysis.

It is the World Bank’s preferred measure of project worth.

 

3°Assumingnetreturnsateachperiodarereinvestedattheraterandadiscountratei,assumingboth
rand i areconstant over time:

(s,-c,)(1+r)'-l+(B,-c,)(1+r)~-1+....+(s,-c_)
(1 +0“

NPV-

 

If the reinvestment rate and the discount are equal:

(s,-c,)(1+t)'-l+(s,-c,)(1+t)~'2+....+(s,-c,)
(1 +0“

win-cognac), git-C.)

(1+o‘ (1+02 (1 +0“
which is the expanded version of equation (3.5).

NPV-

 

 

NP

67

Numerous problems are encountered in the application of the IRR. First, if compared
with the NPV, it could result to a different ordering when ranking different investment
alternatives. Secondly, there exists no simple formula for finding it. Thirdly, it could be
negative, non-existent or have more than one value, depending on the number of sign changes
in the cash flow stream - which makes the IRR sometimes difficult to interpret.

Concerning the ranking issue, Robinson et_al (Forthcoming) showed that this occurs if
the homogeneity of measurement principle and consistency in timing principle are violated
when the model is constructed in an inconsistent manner. Robinson M (Forthcoming)
identified six consistency principles31 that should be taken into account in any IRR model,
which implies some adjustments. The adjustments do not change the NPV value and its
ranking, but do change the value of the IRR so that its ranking becomes identical‘to the NPV
ranking. As a result, these adjustments are not necessary when the NPV is used as evaluation
criterion.

In practice, the IRR is determined by a trial and error procedure, based on some key
facts: (1) it requires at least one negative value in the not benefit stream, and (2) the

relationship between the NPV and the discount rate depends on the pattern of cash flows.

 

3‘ These principles are:
1) The cash flow principle which requires that physical units of inputs and outputs be converted to
their cash equivalent and be measured in a consistent unit (mostly discounting).

2) The consistency in timing principle which requires that returns and costs be entered in the formula
in the period they are received or paid for;
3) The homogeneity of measurement principle which requires that the investment under analysis and

the rate of return on the alternative to which it is compared be measured in a consistent units,
namely with respect to inflation, taxes, size etc.

4) The life of asset principle which requires that the proper length of time for measuring all costs and
returns associated with the investment be considered, and,

5) The total costs and returns principle which requires that all costs and returns associated with the
investment be considered.
6) The geometric mean principle which states that investments be compared using geometric means

(not arithmetic means).

68

Usually, the IR is negatively related to the NPV, when an initial negative outlay is followed
by positive cash flows in the later periods. But when the initial positive outlay is followed by
negative cash flows in the later periods, the NPV and the discount rate are positively related.
This is for example the case when loans are evaluated from a borrower’s perspective.

One of the common practical way used to determine the IR is to find, by trial and
error, two discountrates that are positive and negative, respectively, and make an
interpolation between them to identify the rate at which the NPV is equal to zero. Gittinger
(1982) advises never to interpolate between discount rates that are more than five percent

points apart.

3.1.1.4 W

The theoretical justification of efficiency benefit/cost analysis has been criticized by
various authors. They all recognize the importance of efficiency (which dominates
benefit/cost analysis) and they all identify efficiency as one necessary condition in determining
the social desirability of a project. Yet, they argue that the society may have other legitimate
goals. Some authors require that a movement toward efficiency be achieved for any
improvement to be considered as having taken place. When applied alone, most of the
criteria used are vulnerable on ethical, philosophical and pragmatic grounds. The debate
hinges on whether or not the improvement injures someone in the economy and how
legitimate that could be (Randall, 1987).

One major criticism is targeted at the traditional assumptions that it does not matter
whether benefits generated by the investment accrue in consumption or in investment, or
whether these benefits accrue to the poor ‘or the rich, as long as the compensation principle

applies. This criticism can be summarized by the claim that, in a competitive market setting,

69

it is a tradition to assume that everybody places the same private (relative) value to a product
which is reflected by its price, but this does not mean that one additional unit of that good is
socially valued in the same way by the poor and the rich. Squire and Van Der Tak (1972)
argue that the distribution of benefits among consumer groups (poor and rich) affects social
output due to differences in consumption and investment propensities. Furthermore, in a
situation where the nation’s level of investment is not enough to sustain a desired growth,
investment would be preferred to consumption.

Additional criticisms against efficiency benefit/cost analysis as stated by Baram (1980)
include (i) the tendency to omit intangible effects of improvements or their arbitrary
valuation, and (ii) the theoretical fact that consumer surplus does not have any willingness to
pay or to accept compensation interpretation, especially under large price changes. It is only
under no income effect (i.e., under constant marginal utility of money) and relatively small
changes that it could approximate consumer willingness to pay. Furthermore, its value is path
dependent under a multiple price change situation (Boadway and Bruce, 1991).

Smith (1986) argues that the criticism about the tendency to omit intangible effects of
investments is incorrect, as omissions simply result from error in specific benefit/cost
analysis, and are not the fault of the methodology. A significant amount of research has been
directed toward non-market valuation techniques such as the contingent valuation approach to
value the intangible effects.

Despite these criticisms, efficiency benefit/cost analysis based on consumer surplus
concept continues to be the most frequent used approach. This is so mainly because it is the
easiest approach to apply and understand. In addition, the United States’ Flood Control Act
of 1936 provided a legal sanction to its fundamental principle (potential compensation) in the

United States. Also, the development in the 19503 in the United States of programs where the

70

government set targeted benefits made cost effectiveness a desirable objective. Another
reason is the fact that various second order efficiency effects identified by Squire and Van Der
Tak and various authors have proven, in actual application, to have relatively small impact on
the configuration of relative prices and measurements, and on other errors inevitable in
benefit/cost analysis. Citing the World Bank’s project planning experience, Little and
Mirrlees, Krutilla (1981) argue that this is particularly true in the somewhat special

circumstances in developing countries.

3.1.1.5 Sensitivity Anflysis
The reliability and validity of all measures of project worth depend on the quality of

the data collected, and on the assumptions made. Typically, the data and assumptions used
are imperfect. Some benefits (costs) are diffith to measure and there is always some degree
of uncertainty associated with the projections that are made. Consequently, it is advisable to
use conservative values or best estimate values in the estimation process. Unfortunately, as
Pouliquen (1970) argues, the use of conservative values implies looking at a project with
conservative eyes. Therefore, the final result is likely to be conservative. In practice, a
straightforward way to handle data quality, uncertainty and conservative estimation problems
ls through sensitivity analysis. This technique measures how sensitive the measures of project
worth used are to reasonable changes in the assumptions made. It is performed by relaxing
the assumptions made. If the measure of project worth does not change significantly, one can
therefore feel reasonably confident about the accuracy of the project worth measures. Also,
by introducing alternative values, one could determine which variables are critical to the

overall performance of the project.

lIEC

SOUI

p036

lllll:

lat

71

Unfortunately, although sensitivity analysis does permit one to identify variables that
are critical to the project’s performance, it does not by itself provides information about the
sources of uncertainty, nor does it completely take into account risk and uncertainty. Also, it
poses serious problem when variables are related, since one typically vary one variable at a
time.

'Various other alternative approaches for assessing the sensitivity of assumptions and
data values are found in the literature. For example, the simplest method is to use the
switching value technique. The switching value of a variable corresponds to a value of that
variable at which the NPV becomes zero or the IRR equals to the economic opportunity cost

of capital. More sophisticated tool of risk analysis include the use of probability theory.

3.1.2 Institutional Analysis

This section builds on the subsector analysis approach. The subsector concept refers
to a "vertical set of activities in the production and distribution of a closely related set of
commodities” (Shaffer, 1968). Marion 1;], (1986) defines it as " an interdependent array of
organizations, resources, laws, and institutions involved in producing, processing and
distributing and agricultural commodity”. These definitions emphasize the vertical orientation
of subsector analysis, the institutional framework, and how its affects the various stages.

Two key aspects are recognized in the subsector concept: (1) there is a chain of
dynamic relationships among the different steps which require some kind of coordination for
the subsector to perform efficiently, and (2) because these steps mutually affect each other,
any analysis at any given level of the various activities is insufficient. What is needed is a

global assessment to identify the weaknesses and strengths of the subsector. In this respect,

72

this approach follow a kind of system approach. More so, it "iteratively combines a global,

systematic approach with an analytical one" (Bino and Duncan, 1992).

3.2 Review ROR Studie in A ri
3.2.1 Geographical Distribution of ROR Studies

There is a substantial literature on ex-post impact assessment of agricultural research
investments throughout the world, but most of this literature assess investments made in
developed countries, Latin America, and Asia. Oehmke an, (1992) reports that up to 1992,
less than a dozen of rate of return studies were conducted in Africa (Table A.4), compared to

79 in developed countries, 66 in Latin America, and 25 Asia.

3.2.2 Nature of ROR Studies

Schultz made the first attempt to quantify the returns to agricultural research
investments in 1953 (Norton and Davis, 1981). Basically, using a consumer surplus
approach, he assumed that research benefits could be estimated by the value of the input
saved. He compared the costs of 1950 output, using 1910 techniques, with the actual costs of
producing 1950 output. A review of the research impact evaluation literature reveals that the
methods used have been steadily improVed over the last three decades. Norton and Davis
(1981) report that over this period, two basic methodologies have been dominant: the index
number and the production function approaches. The key distinguishing feature of the index
number approach is that it generates an average rate of return which allows for assessing the
entire research investment, as opposed to the production function approach which estimates a

marginal rate of return.

73

In addition, numerous non-rate of return or descriptive approaches to assess research
impact have often been used, particularly in Africa. Most of these studies were carried out as
part of a project assessment activity, either in a national research institute or in an
international institution. Typically, the assessment criterion used is the adoption rates, both in
terms of number of farmers and total land under cultivation. For example, in 1984, 75
percent of the total irrigated rice area of 15,000 hectares in Tanzania were planted to two
IRRI varieties, while 60,000 hectares in Nigeria in the same year and 70,000 hectares in
Senegal in 1983 were planted to improved varieties (Daniels _et_a_l., 1990 citing Anderson,
Herdt, and Scobie, 1988). This literature reveals a wide array of collaborative germplasm
and varieties exchange efforts between IRRI, ISNAR, CIMMYT, IITA and various national
research institutes.

Two studies evaluated USAID experience in agricultural research. In 1982 Dai
(1982) examined 131 evaluationsof 48 agricultural research and in 1983 Murphy (1983)
analyzed numerous project evaluation studies. Dai highlighted the problems of national
research limited technical capacity, procurement delay, and unavailability of good data to
facilitate project performance comparisons. Also, this study revealed that while 21 of the
projects were explicitly focused on small farmers, only 8 attempted to analyze farmers’

constraints.

3. 2.3 Magnitude of ROR Values

Most non-African studies indicate high rates of returns in excess of 30 percent as
could be seen in Table A.4. Theses results indicates that agricultural research has generally
performed well, and justifies investment in this sector. However, some authors argue that

this literature presents a biased picture of research investment impact because research failures

74

are rarely included in the evaluation portfolio. Daniels etal, (1990) argue that nonetheless, if
this argument is true for some specific commodity research, " many aggregate studies from
Asia and Latin America measuring the impact of a country’s total level of investment in
agricultural research....indicates high returns".

As in developed countries, Latin America, and Asia, agricultural research evaluations
in Africa indicate high rates of return. A World Bank study (World Bank, 1988) estimated
the returns to cotton development projects in Burkina-fasso, COte—d’lvoire, and Togo to be 31,
37, 11 and 41 percent, respectively. Yet, Evenson (1985) argues that, generally, the impact
of national agricultural research efforts is lower in West African countries than in developed

countries.

3.2.4 Key Determinants of the ROR Values

Griliches (1958), Bredahl and Peterson (1976) indicate that a key determinant of
research benefits is the total value of the crop. However, this does not mean that ”low value"
commodities do not yield high returns. Also, in almost all of the studies, the importance of
the institutional support emerges. Ayer and Schuh (1972), Evenson and Jha (1973), Akino
and Hayami (1975), and Flores-Moya gal, (1978) indicated that the structure of research
institutions was critical to the success of research programs in Brazil, India, Japan, and the
Philippines. Also, Evenson and Jha attribute high returns to agricultural research in the USA
to the linkage between research, extension, and farmers, while Hertford fl (1977) attribute
the negligible returns to cotton research in Columbia to the poor organization of the research
efforts. A

An equally important determinant of research success is the infrastructural support.

Daniels 131, (1990) report that the contribution of research in Asia, Latin America, and

Non

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75

North America was substantially increased because it was complemented by efforts to develop
irrigation, drainage and other physical infrastructures".

The high returns on cotton in the World Bank study in Burkina-lasso, COte-d’lvoire,
and Togowere were attributed to a cotton package which included new technology, a strong
input supply networks, timely cash payment to farmers, and support from autonomous
institutions. Daniels et_a_L (1990) citing Lele gal; (1989) report that institutional factors such
as extension, input availability, marketing, processing and capitalization of cotton sector were
fundamental in explaining the sustainable development of cotton in African French-speaking
countries.

Research design and implementation were cited as a problem in 15 of 39 projects by
Dai (1982) from an examination of 131 evaluations of 48 USAID-sponsored agricultural
research projects. Murphy’s (1983) study documented USAID’s success in training
researchers and establishing or expanding research facilities. She also stated that the
effectiveness of USAID assistance was hindered by managerial weaknesses, unfavorable
government policies, and inadequate awareness of household farming circumstances.

' In 1985, an evaluation of the 128 World Bank-supported projects in 10 countries
highlighted the Bank’s lack of consideration for the sustainability of research beyond the
inVestment period, the need to improve research management, and inadequacy of the
institutional structures. In 1988, an impact assessment of 13 CGIAR centers found that high-
yielding wheat varieties, mostly from CIMMYT and its predecessors, were being widely
grown in developing countries in 1982-83, including Zimbabwe, Ethiopia and Kenya. Also,
Zimbabwe, Kenya, Malawi and Tanzania, using germplasm from CGIAR Centers in their
variety development program. IITA has released two maize varieties with a good resistance

to tropical rust, and lowland blight.

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76
3.2.5 ROR Studies in Cameroon

In Cameroon, even though agricultural research has been conducted for more than
three decades now, only two non-published pilot ROR impact studies have been conducted
within the national Institute of Agricultural Research (IRA). In 1989, Pham _eLaL applied the
ISNAR approach to agricultural research impact assessment, developed by Contant and
Bottomley, in a priority setting exercise for the Fruits and Pineapples, as well as Cereals
programs. Two year later, Ngo Nlend (1991) applied the same methodology to assess the
impact of the Nkolbisson TLU recommendation for three maize and three cassava varieties, as
well as a maize fertilizer recommendations in the Center Province. Her study indicated high
internal rate of returns to the investment made, ranging from 60 to 108 percent. She also
reports that these rates were not sensitive to reasonable variations of adoption factors, unless

these factors are reduced by 90 percent.

3. 2.6 Conclusion

The consistently high returns to research in Latin America, Asia, and in the few
African countries’ studies suggest a bright future for African agricultural research. However,
Africa differs from developed countries, Latin America, and Asia in many ways, including
more complex environmental constraints, weak physical infrastructural, and the lack of a long
research tradition (Oehmke 331,, 1992). Furthermore, many environmentally sensitive area
of Africa have experienced a loss in their productive capacity to a point where, in some cases,
maintaining the current level of productivity is crucial.

Daniels 13L (1990) argue that while it is too early to expect a rapid and large-scale
transformation of African agricultural research, this does not mean that research projects with

low RORs should be considered acceptable in Africa, merely because they are from Africa.

77

It simply means that research impact assessment in Africa should be based on a realistic
perspective that takes into account its ecological and socioeconomic environments. In
addition, impact analysis must pay particular attention to providing insights as to the key
factors that have contributed to the success or failure of prior investments. Only with this

information will it be possible to increase the impact of agricultural research in Africa.

CHAPTER 4 ANALYSIS and RESULTS

4.1 Research Activities
Data needed to carry out the ROR analysis were collected in Cameroon from June 8
to August 31, 1991. Data collection proceeded in three phases. This section briefly presents

research activities during these phases.

4.1.1 Identification of Research Focus

From June 8 to June 15, the researcher met with IRA, NCRE, and USAID
administrators in Yaounde, as well as with other key informants in Maroua and Garoua, to
identify potential cr0ps and location for the research evaluation study. Two concerns were
emphasized during these discussions: data availability, interests and the needs of primary
users of the results. By the end of this period, it was’agreed that the study should focus on

maize in the North Province.

4.1.2 Preliminary Data Collection

From June 16 to July 14, the researcher undertook the first round of data collection.
This effort concentrated on (a) identifying the institutions that have been involved in maize
research and extension in the North Province, (b) determining specific data to be obtained
from the identified institutions, and (c) contacting key informants within each of the
institutions. During this phase, the researcher met with key informants at IRA-Maroua, IRA-

Garoua, SODECOTON, MINAGRI, NCSM, and “Office Cerealier" and reviewed available

reports.

78

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Chg

ath.

79
4.1.3 Supplemental Data Collection

5 From July 20 to August 31, after reviewing the documents obtained to identify
additional data needs and their possible sources, the researcher conducted a second round of
data collection, concomitantly with visiting with farmers in various villages. During this
period, the researcher interviewed several new and previously contacted key informants,
reviewed more documents, and visited farmers and extension agents. The goal of these visits
was to visually assess the impact of maize research and extension, as well as to check the
validity of some assertions made by key informants. In addition, the researcher attempted to
design and implement a complementary formal survey, but this effort was abandoned due to
the relatively high fee requested by the Ministry of Agriculture’s Division of Statistics to
implement the survey.

During data collection, the researcher interviewed a total of forty-nine key informants,
some two or three times, collected numerous reports, and held four group meetings with
farmers and extension agents. Key informants interviewed included 15 IRA and N CRB
researchers, 8 SODECOTON staff members, 2 NCSM staff members, and 20 others from
various institutions such as World Bank, USAID, MINAGRI, ”Office Céréalier",

MAISCAM, Pioneer Seed, NEB, and EEC.

4.2 W

In general, a new agricultural technology generated through research and extension
has a long gestation period. During the deveIOpment phase, net benefits are negative, but
become positive once the new technology is widely adOpted by farmers. Thus, an appropriate
choice of the time period over which costs and benefits are to be included is critical to

achieving an unbiased ROR result.

80

This study includes costs incurred and benefits generated over the period 1979 to
2000. While research on maize in the North Province began 1976 with SAFGRAD Project
#26, no information is available on research activities and costs prior to 1979. The year 2000
was selected as the ending year, based on the assumption that the varieties released up to 1990
will still be used by farmers for the next ten years, given Cameroon’s financial crisis which

has led to a substantial reduction in research funding.

4.3 W

The costs attributed to research, extension and adoption of maize in the North
Province are partitioned into two main categories: research costs and extension-adOption costs.
The procedure used to estimate the various costs was mainly determined by data availability.
For example, seed multiplication costs were not directly included because data were not
available, but are accounted for indirectly by including the cost of seeds to the farmers. The
implicit assumption here is that seed prices reflects actual production costs. In addition,
numerous simplifying assumptions were made because the data collected were not organized
to serve a ROR study. For example, long-term training costs were excluded due to the long-
run nature of the associated benefits and the difficulty in estimating the share of these costs
that should have to be attributed to a single crop. These assumptions are then relaxed in the
sensitivity analysis section to assess their impact on the ROR estimates.

For the years 1979 to 1990, research and extension costs as well as benefit estimates
are based on actual data collected during field work. For the period 1991-2000, only

extension costs and benefits are considered”. To estimate these costs and benefits through

 

3’ Although under ordinary circumstances some maintenance research costs should have been included,
no provision is made for it in this study because of the financial crisis IRA faces.

81

the year 2000, the study introduces two scenarios. First, the base run analysis incorporates
constant costs and production levels (equivalent to the 1990 levels), based on the assumption
that given the financial crisis, there is no reason to expect any increase in extension
expenditures or maize production in the North Province. Then, a more realistic scenario,
which assumes a minimum 50 percent decline in expenses and production over the same

period, is introduced.

4. 3. 1 Research Costs

Research costs include breeding, on—station agronomy, and on-farm research costs
incurred by all research units (mainly NCRE and SAFGRAD’s Projects) involved in maize
research in the North Province. These expenditures are subdivided into four costs categories:
equipment and supplies, salaries and benefits, direct research expenses, and administrative and
short-term training costs. See Table A5 for the specific components in each of these costs

categories.

4.3.1.1 NE W (ATgflj

NCRE provides financial support to maize breeding and agronomy activities. Maize
breeding in the North Province is conducted by a research team of three researchers based at
Nkolbisson (Dr. C. The, J .B. Zangue, and C. Zonkeng) and at Garoua (B. Mongmong). The
breeding unit’s mandated area covers the lowland altitude zone of Cameroon, which
encompasses the North Province, as well as the South, the Center, the East and the South-
West provinces. However, the maize breeding unit has focused its research in all these

provinces with the exception of the South Province. Most of the maize varieties developed by .

82

this unit are tested in its mandated area. The agronomy unit is based at Garoua and works on

a variety of crops including maize, sorghum, millet, groundnut, and cowpea.

Breeding and Agrgnomy @sts

Since actual expenditures for these two research units were not directly available for
the historic period 1981-1990, yearly summaries of total NCRE actual expenditures (Table
A5) are used to estimate each unit’s costs, based on the following procedure. First, as the
data obtained from NCRE administration did not include salaries and benefits for national
researchers (Table A5), these costs were estimated by first determining each scientist’s
current civil servant status (class, and echelon) and then using the public service salary
schedule to estimate his salary, including research allowances.

Second, since data are not available to estimate trial costs for each year, actual work
plan budgets for the years available (i.e.; 1987-91) were used to estimate the proportion of
NCRE’s total expenditures that supported these units; and then this proportion was used to
compute the annual costs for the trials implemented by each» research unit as summarized by

following formula:

 

Mass . ATE,” 41

Breed: ATE, = ppm *OER wrth ab = ( - )
AIC'“
MC"

48”.: 47C. = ugm’mrosa with p. = ——‘.'— “-2)
AK?”

where:

ATC, = Estimated annual total trial costs for the maize breeding unit.

ATC, = Estimated annual total trial costs for the cereal agronomy unit.

p. = Proportion of TC“ attributed to the Nkolbisson maize breeding unit.
a, = Proportion of TC“ attributed to the Garoua cereal agronomy unit.
TC“ = NCRE’s actual annual expenditures.

83

ATC,” = Annual budget estimates for the breeding unit.
ATC,” = Annual budget estimates for the cereal agronomy unit.
ATCB, = NCRE’s annual budget estimates.

OER = Official Exchange rate (US dollars into F. cfa).

As mentioned above, the coefficients of proportionality u, and pt. are computed from
the available five years (1987-1991) of work plan budget estimates (Table A6). NCRE’s
work plans provide rough budget estimates of trial costs (less salaries and benefits) for each
research unit. Budget estimates represent a reliable source of data for partitioning total
project costs because NCRE uses an incremental budget approach which does not allow a
research unit to spend more than 10 percent in excess of its budget estimates. Even though
key informants observed that these two units regularly overspent their budgets, NCRE
administrators argued that the pattern of spending was somewhat similar over the years. The
values of p, and It. estimated to be 1.15 and 1.11 percent, respectively (Table A6), are
therefore assumed to closely reflect the proportion of the each unit’s actual share of NCRE’s

total expenditures.

N Pr v'n ’ M ' e Br ' r t

Because only part of the breeding unit’s costs are spent on research in the North
Province, it was necessary to estimate the share of this unit’s total expenditures to be assigned
to maize research. Also, because the agronomy unit works on several crops, it was necessary
to estimate the share of this unit’s total expenditures to be assigned to maize. The procedure
used to estimate the breeding unit’s expenses attributed to the North Province assumes that the
team expenses in each province within its mandated area are directly proportional to relative
maize area in that province. For the North Province, the coefficient of proportionality is
estimated to be 28.37 percent (Table A.7). Similarly, for the agronomy unit, the unit’s

expenses attributed to maize research in the North Province are assumed to be directly

84

proportional to this unit’s annual ”research effortsm on maize. The following equations

summarize these assumptions:

AREA "°"" '
arc," = Apart, with A, = ——‘-’—— (4.3)
AREAbTM
ATC“ = AgATCa with To = 0.70 (4.4)
where: -
ATC,. = Estimated annual total costs for maize breeding in the North Province.
ATC, = Estimated annual total costs for maize agronomy in the North Province.

AREA,” = Maize area in the North Province.

AREA,“ = Total maize area from Provinces covered by the breeding unit.

)s, = Proportion of the North Province maize area in ARE/LT“.

A, = Proportion of estimated annual costs for agronomy attributed to maize.

The estimation procedures for the share of each research unit’s total expenses
attributed to maize in the North Province are different because of data problems. The
preferred estimation approach for this study is the use of ”research effort" data which are
assumed to better reflect the actual share value. The value 0.70 (estimate of M was obtained
from direct interviews with the research team, and from NCRE annual reports and work
plans. The pr0portion of the North Province maize area from the total maize area in the
breeding unit’s mandated zone is used as a second best proxy because the unit’s "research
effort” data by province was not available. On the basis of the equations (4.3) and (4.4),

Table 4.1 and Table 4.2 below summarizes NCRE’s maize breeding and agronomy costs in

the North Province.

 

’3 The concept “research effort“ refers to the proportion of the research unit’s time allocated to a
particular operation or trial. This concept is used by the N CRE project under the assumption that
researchers’ time allocation is directly proportional to the relative financial cost of the operation or trial
under consideration within the team’s research program.

85

Table 4.1: Estimated NCRE Maize Breeding Expenses (Nominal F.cfa). North Province, Cameroon, 1981-90.

 

 

 

Year Equipments Salaries & Benefits Direct Adminis. Total

and Research Conference Annual

Supplies EKP‘W‘“ Nationals Costs & Training Costs
1981 96,870 223,561 673,120 17.044 76.126 1,086,721
1982 183,789 792,872 2,799,790 45 .068 150.163 3 .971 ,682
1983 112,330 868,402 3,011,180 136,473 200,897 4,329,282
1984 179,633 1,040,651 3,298,492 172,835 235 .166 4,926,777
1985 107,792 1,143 .273 3,344,695 182,755 21 1,765 4,990,280
1986 142,666 1,234,270 4,090,509 127, 156 193 .891 5 .788 ,492
1987 360,272 1,328,063 4,229,789 239,337 286.308 6.443 .769
1988 95,188 1,352,526 4,393,819 226,333 315,441 6,383,307
1989 237,501 1,659,685 4,545 ,272 271,916 227,279 6,941 ,653
1990 220,077 1,852,407 4,787,155 433,903 533,454 7,826,996
Total 1,736,118 11,495,710 35,173,821 1,852,820 2,430,490 52,688,959

 

Table 4.2: Estimated NCRE Maize Agronomy Expenses (Nominal F .cfa), North Province, Cameroon, 1981-90.

 

 

 

 

Year Equipments Salaries a Benefits Direct Administration Total
and Research Conferences 8t Costs
5999,13“ Expatriates Nationals Costs Training
1981 230,702 532,426 0 40,592 181,306 985 .026
1982 437,729 1,888,281 34,274 107,332 357,625 2,825 .241
1983 267,522 2,068,163 115.873 325,021 478,450 3 .255 .029
1984 427,808 2,478,385 134,662 41 1.618 560,066 4,012,539
1985 256,715 2,722,787 610,109 435,245 504,333 4,529,189
1986 339,769 2,939,503 2,231,756 302,831 461 .765 6,275 .624
1987 858.014 3 .162,880 2,525,520 569 .999 681.863 7.798.276
1988 226,698 3,221,140 2,504,030 539.029 751,247 7,242,144
1989 565 .626 3 .952,661 2,760,997 647.5 87 541,281 8,468,152
1990 524,129 4.41 1.643 3 .048.685 1.033 .372 1 .270.459 10,288,288
Total 4,134,712 27,377,869 13,9653“ 4,412,626 5,788,395 55 ,679.508

 

86

One major observation that can be made from these two tables is that over the historic
period, salaries and benefits averaged 88.6 and 74.3 percent of the NCRE maize breeding and
agronomy units’ expenses, respectively. By contrast, direct research expenses accounted for
only an average of 3.5 and 7.9 percent of the breeding and agronomy units’ expenses,

respectively.

4.3.1.2 SAFQRAD Prgiggs’ Cam

SAFGRAD’s costs included in this study are those incurred by SAFGRAD JP #31 and

the SAFGRAD/FSR“. Therefore, total SAFGRAD costs on maize research are equal to:

ATCW = Art” + ATCFSR (4.5)

where:

ATC‘“ = Estimated annual SAFGRAD projects’ costs attributed to maize.

ATC” = Estimated annual costs for SAFGRAD JP #31 attributed to maize.

ATC‘“ = Estimated annual costs for SAFGRAD/FSR attributed to maize.

Unfortunately, available SAFGRAD data provides only estimates of these costs
aggregated for all research activities. But, given the multiple crop involvement of these
projects (i.e., maize, groundnut, cowpea, and sorghum), only a portion of their costs should '

be charged against the maize research program. The assumptions used to determine these

shares are discussed below.

AF RAD P
SAFGRAD JP #31 cost data were obtained from two different sources (Table A.8).

For the first five years (1979-1983). data on total costs by main expenditure categories (i.e.,

 

3‘ Another SAFGRAD project (SAFGRAD JP #26) operated in the North Province from 1977 to 1979.
but it is not considered in the analysis because virtually no written documents are available.

87

travel and per diem, shipping and storage, housing, other direct costs, equipment-supplies-
materials, salaries and benefits) were obtained from a final report submitted by Owen
Gwathmey, the first of the two expatriate researchers assigned to the project. During a phone
call, he also provided the assumptions that made it possible to break down each category total
into annual expenditures. First, for travel and per diem, shipping and storage, he reported
that the first and the last years accounted for 35% of the total costs for each category, while
each of the middle years accounted for 10%, respectively. Second, for housing and other
direct costs, he proposed using an annual 4% " institutionalized" increase assumption. Finally,
annual shares for equipment, supplies and materials are assumed to equal 35%, 30%, 15%,
15%, and 5%, respectively for the years 1979 to 1983.

For the remaining years (1984-1987), the second expatriate, Jerry Johnson, provided
(via phone interview) estimates of annual project costs broken down into salaries and benefits
and non-salary expenses, based on his personal files (past contracts and canceled voucher
reports). Because no reasonable assumption was provided to breakdown this second set of
data into expenditure categories, it was is not further partitioned.

In addition, these scientists estimate that maize accounted for 35% (for 1980-1984)
and 7% (for 1986) of annual Project expenditures. These estimates were then used to
estimate Project costs attributed to maize research under SAFGRAD JP #31, as summarized

in Table 4.3 below.

88

Table 4.3: SAFGRAD JP #31 Expenses (Nominal F.cfa) on Maize, North Province, Cameroon. 1979-1987.

 

 

 

Year Travel & Shipping Housing Other Equipment Subtotal Salaries Total

Per Diem & Storage Direct s Non-Salary and Expenses

Expenses Supplies 8r. Expenses Benefits'
Materials

1979‘ 0 0 0 0 0 0 0 0
1980 202.873 47.657 862.416 39.012 1,542,405 2,694,363 2,422,174 5,116,537
1981 260.865 61.279 1,164,384 52,671 991,651 2,530,850 3,244,641 5,775 .491
1982 315.495 74.112 1,478,644 66.887 1,199,324 3,134,462 4,081,015 7,215,478
1983 1,280,656 300,837 1,800,629 81,452 463 .646 3 ,927,220 4,914,970 8,842,190
1984 na na na na na 6,214,053 15,148,168 21,362,221
1985‘ 0 0 0 0 O 0 0 0
1986 na na na na as 656,543 2,508,168 3,164,711
1987‘ 0 0 0 0 0 0 0 0
Total 2.059.889 483.885 5 .306.073 240,022 4,197,026 19,157,491 32,319,136 51,476,628

 

'na' stands for data “not available“ by expenditure category.

" Includes both nationals and expatriates salaries.

" The value zeros indicate that no maize trials were implemented in that year.

These results indicate that, as with NCRE data, salaries and benefits were the

dominant costs component (62.8 percent) of SAFGRAD JP #31’s total expenditures attributed

to maize. Also, it appears that the total expenditures in support of maize research were very

high. This suggests that either the weights used to partition total project costs are not realistic

or that the project was a high cost investment. In the sensitivity analysis, these weights are

adjusted to check the importance of the likely estimation error on the ROR.

W

Total SAFGRAD/FSR annual costs (1986-1988), excluding researchers’ salaries and

benefits. broken down into specific categories. were available from the documents collected

(Table A.9).

A further search traced the salaries and benefits for the national (G. Ngono)

89

and expatriates (D. S. Ngambeki and L. Singh). To estimate the share attributed to maize,
these costs are partitioned between the various crops dealt with by the research team, based
on the assumption that 55%, 79%, and 62% of the team’s effort was directed at maize in
1986, 1987, and 1988, respectively”. The estimated costs incurred for maize research

under SAFGRAD/FSR are summarized in Table 4.4.

Table 4.4: Estimated SAFGRAD/FSR Expenses (Nominal F.cfa) on Maize, North Province, Cameroon, 1986-1988.

 

COST ITEMS 1986 1987 1988 Total

 

Total Equipment and Supplies 7,075,215 10,003,135 202,215 17,280,565
Total Salaries and Benefits for Expatriates 10,757,578 29,126,445 24,488,071 64,372,094
Total Salaries and Benefits for Nationals 4,009,068 19,516,849 13,205,599 36,731,516

Total Direct Research Expenses 2,424,185 2,548,867 1,588,442 6,561,494
Admin. Conf. & Short-Term Training 828,430 4,094,610 1,226,337 6,149,377
Total Expenses 25,094,476 65,289,906 40,710,664 131,095,046

 

4.3.2 Extension and Production Costs
W

Extension costs include costs incurred primarily by SODECOTON. The Ministry of
Agriculture’s extension service and other "minor" projects’ costs were excluded in this study
because their maize activities are marginal and, most importantly, these data are either
unreliable or simply non-existent. SODECOTON extension costs (EXC’°°) attributed to maize

include only salaries and benefits since the primary focus of SODECOTON is cotton.

 

3’ These estimates. computed using SAFGRAD/FSR’s annual reports data. were calculated by dividing
the trial area under maize by the total area for all trials the research project implemented in each of the

corresponding years.

90
Total staff costs were available from SODECOTON, by personnel category (Table

A. 10). To estimate maize’s share of total extension costs, the study relied on
SODECOTON’s Director of the Production Division’s rough estimate (personal interview)
that one-twelfth of all extension time is spend on food crops. This estimate was validated
through a rapid field interviews with several extension agents. This study assumes this
pr0portion has varied over time, given that the crop area serviced by SODECOTON and the
relative importance of food cr0p versus cotton has changed over the study period. An analysis
of SODECOTON food cr0p and cotton areas (Table 2.3) identifies three distinct periods.
Prior to 1982, SODECOTON focused on cotton, but in the second (1982 to 1984) and third
(1985 to 1990) periods, it expanded its support to food crop production. Therefore, the study
assumes that, based on each period’s relative average area, 0.5 percent, 5.0 percent, and 8.0
percent (i.e., one-twelfth) of extension time was spent on food crops during the periods 1979-
1981, 1982-1984, 1985-1990, respectively. Total salaries and benefits attributed to maize are
then computed by assuming that maize extension costs are proportional to maize’s share of the

food crops area. These two assumptions are reflected in the following equation.

Area ‘
exam = (armor—"£2 (4.6)
Area,“
Where: -
a = Proportion of extension time spend on food crops extension activities.

TPC = Total SODECOTON’s Extension Personnel Benefits and Salaries.
Aream= SODECOTON extension area under maize in each year.

Area...“ = Total SODECOTON extension area in each year.

As stated earlier, this equation is used to estimate salaries and benefits over the

historic period 1979-90 (Table 4.5a-c). For the period 1991 to 2000, it is assumed extension

costs allocation to food cr0p will remain unchanged and equivalent to the 1990 level. This

91

rather optimistic assumption, given the ongoing financial crisis, is relaxed in the sensitivity

analysis.

Pr duction t

This cost category refers to expenses incurred by farmers. Maize in the North
Province is cultivated under two distinct production systems, the low input system and the
high input system. Because farmers following each system apply different inputs, the costs
associated with each system are different. Thus, to estimate the total annual costs to farmers
adopting the maize package, it is necessary to first estimate the unit costs (per hectare)
associated with each system and then multiply these costs times the area planted in each of
these systems. Annual production system costs (APC), defined as the costs associated with

both systems, are computed as:

APC = APCM + are

W with arc, = zit/mam, (4.7)

Where:

APC, = Estimated annual costs for system i, i=traditional or intensive system.

APCM = Estimated annual costs for the traditional system.

AFC... = Estimated annual costs for the intensive system.

INPi = Estimated annual unit input costs per hectare in system i.

AREAi = Estimated area cultivated each year under system i.

The low input system is implemented by both SODECOTON and non-SODECOTON
farmers; but the high input system is only followed by SODECOTON farmers, who plant

either monocrop maize or intercrOp maize with sorghum.

T 1 E . 1 E 1 . g
Using equations (4.6) and (4.7), the base run estimates of annual maize extension and

production costs in the North Province were computed. as summarized in Table 4.5 below.

92

Table 4.5(a): Estimated Maize Extension and Production Costs (Nominal F.cfa), North Province, Cameroon, 1979-2000.

 

 

COST ITEMS fl 1979 _ 1980 1981 1982
I. EXTENSION COSTS
Salaries and Benefits: - Senior Stafi' 133,691,888 274,664,066 351,161,203 392,209,511
- Others 212,351,618 265,318,256 342,440,879 416,619,197
Ratio Area Maize vs Other Crops (weights) 0.69 0.83 0.76 0.08
Total Extension Costs for Maize 955,080 1,792,741 2,108,550 3,235,315
11. PRODUCTION SYSTEM COSTS
- Low Input System
Land Clearing area (ha) 4,500 4,500 4,500 4,500
Land Clear. Costs (8 days-hour/ha at 4,400 fcfa) 19,800,000 19,800,000 19,800,000 19,800,000
Land Prep. (21 days-hour/ha at 11.550 fcfa) 51,975,000 51,975,000 51,975,000 51,975,000
Total Seed Cost 4,500,000 4,500,000 5,062,500 6,187,500
Planting Cost (15 days-hour/ha at 8,250 fcfa) 37,125,000 37,125,000 37,125,000 37,125,000
Weeding Cost (49 days-hour/ha at 26.950 fcfa) 121,275,000 121,275,000 121,275,000 121,275,000
Total Costs for the Low lam 8mm 234,675,000 234,675,000 235,237,500 236,362,500
- High Input System
Land Clearing Area (ha) - pure maize 1.660 1.652 2,191 2,370
Land Clearing Area (ha) - mixed 0 0 . 0 0
Land Clear. Cost (8 days-hourlha at 4.400 fcfa) 7,304,000 7,268,800 9,640,400 10,428,000
Land Prep. Cost (21 days-hourlha at 11,550 fcfa) 19,173,000 19,080,600 25,306,050 27,373,500
Total Seed Cost (30 kg/ha) 3,304,000 3,304,000 4,382,000 4,740,000
Planting Cost (6 daySohour/ha I 3,300 fcfa) 5,478,000 5,451,600 7,230,300 7,821,000
Weeding:
Area (ha): Pie-emergence (hernicals 1,632 1.632 1.632 1,671
Contact Gunicals 0 0 0 0
Manual Wading 28 20 559 699
Market Price of Cliernical (Fcfalha) 2.000 2,000 2.000 2.000
Cost/Chemical (2 days-hourlha ‘ 1,100 fcfa) 5,059,200 5,059,200 5,059,200 5,180,100
Cost/Manual (49 days-hourlha 1 26.950 fcfa) 754.600 539,000 15,065,050 18,838,050
Fertilizer (N-P-K):
Area (ha): 0-50-0 0 0 0 0
200-50-0 1.660 1.652 2,153 2,350
150-50-50 0 0 0 0
150-50-100 0 0 0 0
100-50-50 0 0 0 0
100-50-100 0 0 0 0
NPKSB Market Price (50 kg bag) 5.000 5.000 5,000 5,000
Urea Market Price (50 kg bag) 2,000 2,000 2.000 2,000
Cost or Fertilizer ' 36,520,000 36,344,000 47,366,000 51,700,000
Cost of Fertil. Applicdion (2 hrs/ha I 300 Fcfa) 498.000 495.600 645,900 705,000
Total Cm for the lilgh lam m 78,090,800 77,542,800 114,694,900 126,785,650
_, “NW k" Cm _ _ __'26°°v7 __ 349932400 _ W43-

     

93

Table 45(13): Estimated Maize Extension and Production Costs (Nominal F.cfa). North Province, Cameroon. 1979-2000 (Cont'ed).

_7

J

 

COST ITEMS

1. EXTENSION COSTS
Salaries and Benefits: - Senior Staff
- Others
Ratio Area Maize vs Other Crops (weights)
Total Extension Costs for Maize

II. PRODUCTION SYSTEM COSTS
0 Low Inptn System

Area Cleared (ha)

Land Clear. Costs (8 days-hourlha at 4,400 fcfa)

Land Prep. (21 days-hour/ha & 11.550 fefa)

Total Seed Cost

Planting Cost (15 days-hourlha at 8,250 feta)

Weeding Cost (49 days-hour/ha at 26.950 fcfa)
Total Costs for the Traditional

0 Intensive System

Land Clearing Area (ha) - pure maize

Land Clearing Area (ha) - mixed

Land Clear. Cost (8 days-hourlha at 4,400 fefa)
Land Prep. (21 days-hour/ha at 11,550 feta)
Total Seed Cost (30 kg/ha)

Planting Costs (6 days-hour/ha at 3.300 fcfa)

Wading: _
Area (ha): Pre-emergenee Chemicals

Contact Chemicals

Manual Weeding
Market Price of Chemical (Feta/ha)
Cost/Chemical (2 days-1101117111 a 1.100 feta)
Cost/Manual (49 days-hourlha at 26,950 fcfa)

Fertilizer (N -P-I():
Area (ha): 0-50-0

2%-50-0
150-50-50
150-50-100
100-50—50
100-50-100
NPKSB Market Price (50 kg bag)
Urea Market Price (50 kg hag)
Cost of Fertilizer
Cost Fert. Applie. (2 hrs/ha at 300 Feta)

 

1983 1984 1985 1986
137,892,322 249,427,626 255,245,710 210,392,283
563,019,678 562,475,392 885,918,576 657,819,779

0.10 0.11 0.14 0.12
3,504,560 4,465,467 13,313,583 8,682,121

5,150 5.857 7.760 9,350
22,660,000 25,770,800 34.144,%0 41 ,140,%0
59,482,5% 67,648,350 89,628,000 107,992,500

7,081,250 8,419,438 1 1,640,000 14,025,000
42,487,5% 48,320,250 64,020,0% 77.137,5%
138,792,5% 157,846,150 209,132,000 251,982,500
270,503,750 308,004,988 408,564,0% 492,277,500
2,379 3,296 5,544 5,303

92 168 573 932
10,872,400 15,241,6% 26,914.8% 27,464,8%
28,540,050 40,009,200 70,651,350 72,095,100
6,120.0% 8,555,000 21 .505,5% 24,029,000
8,154,3% 11.431,2% 20,186,1% 20,598,600
1,977 2,624 3,860 3,221

0 0 0 0

494 840 2,257 3,021

2.0% 2.0% 3.0% 5.0%
6,128,700 8,134.4% 15,826,0% 19,648,1%
13,313,3% 22,638,0% 60,826,150 81,415,950
92 167 573 939

0 0 0 0

803 1.146 0 0

1.553 2,150 0 0

0 0 2,104 2,162

0 0 3,440 3.141

5.5% 6.1!” 6.5% 8.5%
3M!) 41!” 4.1!!) 5.0%
57,945.11!) 94.96411!) 132,476,” 163,581,“
1,4413% 2,027,7% 3,498,3% 3,463,5%
132,514,950 203.%1,1% 351,884,2% 412,296,050

We- __ __

- W

 

94

Table 4.5(c): Estimated Maize Extension and Production Costs (Nominal F.cfa), North Province. Cameroon. 1979-2000 (Cont'ed).

 

 

 

COST ITEMS 1987 1988 1989 1990
I. EXTENSION COSTS
Salaries and Benefits: - Senior Staff 139,089,000 112,271,120 103,504,697 98,316,000
- Others 646,606,000 557,322,988 532,705,465 494,999,000
Ratio Area Maize vs Other Crops 0.08 0.12 0.13 0.11
Total Extension Costs for Maize 5 .237.967 6.695 .941 6,892,277 5,438,721
II. PRODUCTION SYSTEM COSTS
0 Low Input System
Land Clearing Area (ha) 8,750 12,736 20,030 19,990
Land Clear. Cost (8 days-hour/ha at 4.4% feta) 38,5%.%0 56,038.4% 88.132,0% 87,956,000
Land Prep. Cost (21 days-hour/ha at 11.550 fcfa) 101,062,500 147,100,8% 231.346,5% 230,884,500
Total Seed Cost 11,484,375 16,716,%0 22,533,750 22,488,750
Planting Cost (15 days-hourlha at 8.250 feta) 72.187,5% 105,072.0% l65.247,5% 164,917,500
Weeding Cost (49 days-hour/ha at 26,950 fcfa) 235,812,500 343,235.2% 539.808,5% 538,730,500
Total Costs for the Low lug m 459,046,875 668,162,4% 1,047,068,250 1,044,977,250
' Hish Input System
Land Clearing Area (ha) - pure unize 3.833 5,444 6,420 4,746
Land Clearing Area (ha) - mixed 706 477 782 249
Land Clear. Cost (8 days-hour/ha at 4.4% feta) 19.971,6% 26,052,4% 31,688,800 21,978.%0
Land Prep. (21 days-hour/ha at 11,550 feta) 52,425,450 68,387,550 83,183.1% 57,692,250
Total Seed Cost (30 kg/ha) 17,450,0% 23,207,0% 29,427,3% 20,717,550
Planting Cost (6 days-hourlha at 3.3% feta) 14,978,7% 19,539,3% 23,766,6% 16,483,500
Weeding:
Area (ha): Pie-emergence Chemicals 2,971 3,144 2,501 1.782
Conuct Chemicals 805 1,890 2,950 1,436
Mama! Weeding 763 887 1.751 1.777
Market Price of Chemical (Feta/ha) 8,%0 10.0% 10.%0 10.0%
Cost/Chemical (2 days-hourlln at 1.1% feta) 27,921,600 36,977,4% 31,%6,1% 21,359,800
Cost/Mama! (49 days—hourlha at 26,950 feta) 20,562,850 23,904,650 47,189,450 47,890,150
Fertilizer (N-P-K):
Area (ha): 0-504) 565 477 782 249
200-50-0 0 0 0 0
150-50-50 0 0 0 ' 0
150-50-1% 0 0 0 0
100-50-50 642 950 2,1 17 1,202
1%-50-1% 3,188 4,494 4,269 3.528
NPKSB Market Price (50 kg hag) 8.5% 8.5% 6.0% 6.0%
Urea Market Price (50 is hit) 5,%0 _ 5.2% , 5.5% 5.5%
Cost of Fertilizer 122.175.%0 175,014,8% 174.658,5% 129,563,5%
Cost Bert. Application (2 hrs/ha at 3% Peta) 2.467.500 3.409,5% 4.066,2% 2,912.7%
W 277,952,7% 376,492,600 424,986,050 318,597,450

_7365999.571,044,655,0% 1,472,054.3% 1,363,74.7%

   

95

To estimate production costs reported in Table 4.53 to Table 4.5c, the following data
and assumptions were used. The labor requirement (mandays) and labor opportunity costs36
for cultural practices were obtained from research data collected under farmers’ conditions.
Estimates of input consumption (area, type and application rate) and their unit costs are based
on data reported by SODECOTON. However, to value seed used in the low input production
system, the market purchase price of maize grain is used, under the assumption that farmers
following this, system get their seeds from either the previous year’s crop or from the market.
In contrast, farmers following the high input production system use treated seeds obtained
from SODECOTON. The area under each production system was obtained from
SODECOTON’s annual reports.

Although land is actually prepared manually, with animal traction, or with tractors,
this study assumes all land was prepared manually. This simplification was necessary since
no data are available to estimate animal traction and tractor use costs. This introduces
minimal bias since SODECOTON reports indicate that about 90 percent of the total maize
area is cultivated manually. In addition, this analysis assumes only one weeding, which
reflects the usual practice. The costs of tools and harvesting are not included because data
were not available. Finally, social costs such as those related to infrastructure deve10pment
and literacy program, as well as numerous administrative costs are not included in this study
because they are primarily incurred for cotton production. .

One general comment that Table 4.5a-c highlights is that, over the historic period, the
low input production system averaged 66 percent of the total production costs. The most

important cost component in this production system is weeding cost which represents about 50

 

3" Since an estimate of the opportunity costs of labor was only available for 1990, this is used to value
labor costs throughout the estimation period. This opportunity cost was obtained from the Maroua TLU
(TLU Maroua, 1991).

96

percent of the system’s total costs. The most important cost component in the high input

production system is fertilizer cost.

4.2.3 Benefits Determination

The estimation of benefits associated with maize research and extension in the North
Province is based on two key assumptions. First, many key informants interviewed during
the field work claimed that all of the maize varieties grown in the North Province are
improved varieties. However, the North Province is contiguous to the Adamaoua Province,
which has a long tradition of maize production. Thus, some farmers following the low input
production system in the area adjacent to the Adamaoua plateau, could be growing traditional
varieties. In fact, the 1978-79 SODECOTON annual report (p.15) notes that ”local traditional
varieties” are being replaced by improved varieties in these areas”. Consequently, although
some traditional maize could have been introduced from the Adamaoua Province, the base run
analysis assumes all of the Province’s maize area has been planted to improved varieties.

Second, key informants and various reports reviewed suggested that some of the
maize area replaced land previously planted to sorghum. Unfortunately, data on the maize
area previously (or intended to be) cropped to sorghum were not available. Therefore, in the
base run analysis, it is assumed that all of the maize area has been planted in newly opened
fields, but subsequent scenarios relax this assumption in the sensitivity analysis.

The annual benefit stream is computed as the value of the Province’s total maize
production netted out by the foregone sorghum net revenues (SNR) or Opportunity cost (OPC)

of maize production as summarized in the following general equation:

 

’7 One objective of the survey that the researcher unsuccessfully attempted to carry out was to resolve
this issue.

97

BENEFIT = [YLD *(AREA *ADOP)] *PRI - OPC (43)

with OPC = [(AREA *ADOP) *AAF] *SNR (4.9)

Where:

YLD = Maize yield.

AREA = Maize area in the North Province

ADOP = Adoption rate.

PR1 = Unit price of Maize.

AAF = Area adjustment factor i.e., maize area previously planted with sorghum.
This equation is used to compute the base run net revenue estimates, as summarized in

the Table 4.6.

Table 4.6: Estimated Maize Revenues (Nominal F.cfa), North Province, Cameroon, 1979-2%0.

 

Year Improved High Input Low Input High Input Maize Sorghum Gross
Sorghum System System System Grain Weighted Revenues“

Adoption Maize Maize Maize Market Average

Rate Area Area Yield Price Net Revenues

(5) (bl) (h!) (Uh!) (Eda/k8) (F-cfl/ht)
1979 0 1,660 0 2.% 40 83,350 132,8%,%0
1980 0 1,652 0 2.% ' 40 83,350 132,160,%0
1981 0 2,191 0 2.% 45 83.350 197,190,%0
1982 0 2,370 4.5% 2.% 55 83,350 592,350,0%
1983 0 2,471 5,150 2.50 55 83,350 814,206,250
1984 0.%4 . 3,464 5.857 2.50 58 83,351 1,062,052,313
1985 0.012 6,117 7,760 2.30 60 83,352 l,379,586,%0
1986 1 .030 6,242 9,350 3 .% 60 83,546 2,251.170,0%
1987 1.849 4,541 8,750 2.10 53 ‘ 83,701 1,146,985,875
1988 2.613 5,921 12,736 2.30 53 83.846 1,745,334,990
1989 3.081 7.202 20,030 2.% 45 83,935 1,549,530,%0
1990 3.299 4,995 19,990 2.35 45 83,977 1,944,562,725

 

 

“Comtedundertheamnptionthatmaizedidnotrephceaorghumfi.e.,withzeroopportunitycost).

98
Maize area and yield data in the historical period were obtained from SODECOTON

annual reports. Even though the area under SODECOTON supervision includes only about
70 to 80 percent of the Province’s farming population, using SODECOTON data does not
seem to create a major problem for estimating the maize area since these data are fairly
similar to the Province 1984-89 data from the national agricultural census. However,
SODECOTON reports provide separate yield estimates neither for sole versus intercropping,
nor for low versus high input production systems, partly because of the extreme variability in
plant density across farms. To address this issue, the study assumes that the maize yield in
low input production system is two-thirds the yield in the high input production system. The
margin of error associated with this assumption is likely to be fairly small.

Similarly, to estimate the opportunity cost of the sorghum area replaced by maize, the
net revenue per hectare of sorghum should be computed for each system under which
sorghum is produced. However, since the necessary time series data were not available, to
estimate this value, the study uses a one year (1990) estimate of net revenues for the low and
the high input sorghum production systems that were calculated by the Maroua TLU (1991).
These two values are weighted by the sorghum annual adoption rate «time series estimated by
Sterns (l993)- to compute annual weighted average net revenues.

Finally, the value of total production (maize and sorghum) is estimated using market
prices reported by the Provincial Delegation of Agriculture in the North. Assuming that
maize is a new crop in the Province, the benefits generated by maize research and extension
in the North Province are estimated using maize area, yield and market prices, as well as the
opportunity cost associated with maize production (i.e., the value of the foregone sorghum

production, which is initially assumed to be zero).

99
4. 5 Benefig/Cost Analysis

The ROR analysis was carried out in three stages. First, in the base run the financial
rate of return (FROR) is computed using equation (3.6). This result incorporates the initial
assumptions that reflect the best estimates for all the costs and benefits items, as described
above. Due to the non-availability of data necessary to determine the economic values of the
costs and benefits identified, only financial analysis is carried out. Hence, no adjustment is
made for inflation, the real exchange rate, or shadow prices. Most importantly, the use of a
financial maize price is justified by the fact that maize grown in the North Province is
produced mostly for local consumption; and while some maize is being imported (especially
by MAISCAM and for livestock), the amount imported is minimal.

Second, to assess the sensitivity of the base run results, these initial assumptions are
progressively relaxed using alternative values within reasonable bounds. Fifteen variables are
considered in this sensitivity analysis: North Cameroon’s maize share in the NCRE’s breeding
and agronomy expenses, maize’s share in SAFGRAD JP #31’s and SAFGRAD/FSR’s total
expenses, maize extension/adoption expenses. seed costs, low and high input systems" costs,
maize area and maize yield in the historic period, the area adjustment factor for foregone
sorghum production; and projected extension expenses; and projected maize area. Based on
these varying assumptions, ranges of FRORs are computed to determine the sensitivity of this
investment evaluation criterion to changes in the value of these variables. Finally, critical
variables are identified and their values'are changed individually and in combinations. During
this sensitivity analysis, the assumption regarding the percent of the maize area planted in
newly opened field is relaxed by assuming successively that 10 to 1% percent of the maize

area was previously planted to sorghum.

100

Finally, the third section discusses of the institutional factors that explain the NPV and

FROR values computed.

4. 5.1 Base Run Analysis

In this analysis, the annual total costs (TC) stream is computed as the sum of NCRE
(ATCNCRE), SAFGRAD (ATCS‘F),nd extension costs (EXCSOD), and production costs (APC).
Using the cost and benefit values presented earlier, annual net revenues from maize research

and extension in the North Province are computed, as summarized in Table 4.7 below.

.2682. o... 8.858....— ofi 5 33:52
88.. .2. E 826898 2. 8.86... 23 on... .8... 2. ES 8.. 2.. .88.... o... 8:82. 838.....3 82.. .8 88:. .2...

 

 

101

«8.338 8888.43... 848.088.. 8.....8...: 888888.. .8898 o 2. a o 88-8...
8.5.5.8...“ 888883.. 588.88.. 83.88: 888888.. 5.8...“ 388...... a. 3 38.2.8. 8...
8982.8 .8833. 233.82.. 8868.84 8388...... 2.888.... 48.848. 2 a. 48.84.: 8...
888888 83888.. 30.9.8.8; 8888.88 8482.88 .3886 2.88.: 2 «8.8.8.2. 89.808. 88.
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102

One general comment that this table highlights is that, over the historic period,
research costs averaged 82 percent of the total cost of maize research and extension in the
North Province. The relative contribution of each of the three research projects involved are
45 percent from SAFGRAD/FSR, 37 percent from NCRE, and 18 percent from SAFGRAD
JP #31, the bulk of which is made up of salaries and benefits. If one considers total research,
extension and production costs, over the historical period, research costs account only for
about three percent while extension costs represent less than one percent.

For the period 1979-2000, maize research and extension generated an internal rate of
return of 11.7 percent, computed using the net revenues data stream in Table 4.7. This ROR
represents a conservative estimate of impact since it only includes the direct and quantifiable
impact of the maize research and extension program. For example, an additional benefit not
accounted for in the base run data analysis includes the contribution of these research projects
to institutional building at IRA. Although impossible to estimate, these projects made a major
contribution to the development of more productive human capital, some of whom are now or
are likely to be in positions which give them the opportunity to continue to contribute to
agricultural and rural development.

Before assessing the significance to this ROR value, one has to keep in mind two key
assumptions upon which this value is based. First, that virtually all of the maize area in the
Province is planted to improved varieties from research and extension and, second, that all
area planted to maize is grown on newly opened fields. Also, as discussed in the theoretical
section, the computational procedure used assumes that all farmers trade cash flows between
time periods at the same price or discount rate. The significance of these underlying

assumptions are discussed in the sensitivity analysis section.

103

Given these assumptions, the estimated rate of return is close to the market rate of
capital borrowed at the bank, which this study assumes is the approximate opportunity cost of
capital (the market interest rate varies between 12 and 15 percent). While there exists an
informal credit market, very little information is available on its importance and the discount
rates that apply. In addition, these rates vary from one location to another, as well as from
one time period to another. A major weakness of this opportunity cost assumption is that it
implicitly assumes unlimited savings and borrowing opportunities at the same interest rate.
This is not likely to be true because farmers have limited and different credit or borrowing
capacity”, and some farmers tend to use the informal market. Consequently, using the bank
interest rate as the defendant underestimates the true opportunity cost of borrowing.

Three of the factors that explain the successful expansion of maize in the North
Province are the inherent characteristics of maize production, the characteristics of the
physical environment, and the food demand status of the Province. As mentioned in the
background section, the North Province benefits from relatively favorable climatic conditions
for maize production with annual rainfall ranging from 700 millimeters to 1,100 millimeters,
which in addition to favorable temperatures, provides sufficient moisture for plant germination
and growth and leads to less post-harvest fungic infestation and damages from weevils. As
one moves to the north where there is less rainfall, maize production progressively becomes
marginal, while further south, in the Adamaoua Province where the climatic condition are
more favorable, maize production is more developed.

In addition, sorghum, which is the Province’s major traditional food crop, is less

productive than improved maize. As a result, farmers are increasingly relying on maize as an

 

3' The borrowing capacity represents each farmers’ reserve available for credit use. When a farmers
borrows, he reduces his reserve. The cost of the loan is therefore the interest rate to be paid plus the value
of the credit reserve that is sacrificed.

104

important source of family food, especially in the hunger period before sorghum is harvested.
Many key informants believe that, as with sorghum, the compatibility of maize with the
existing farming system and the ease of the cultural practices involved in maize production
(relative to cotton production) are some key reasons that explain why farmers have adOpted
the maize technology. In fact, it is a common view that both of these circumstances and a
strong market demand are the driving forces of maize research and extension in the North
Province. Other factors that have contributed to success of maize research and extension are

discussed in the institutional analysis section.

4.5.2 Sensitivity Analysis

This section tests the responsiveness of the estimated base run IRR to reasonable
changes in selected assumptions and/or variables’ level used in the initial analysis. The
choice of variables/levels to modify in the sensitivity analysis is based on educated assessment
of critical variables and assumptions believed to potentially affect the ultimate result. More

than 50 runs were made, but only the most interesting ones are reported in Table 4.8 below.

105

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108
Rugs 1-4; Research Expemej

The IRR was recalculated using as much as a 25 percent increase in NCRE,
SAFGRAD JP #31, and SAFGRAD/FSR expenses attributed to maize research in the North
Province (Table 4.8). These adjustments were run separately (runs 1-3) and simultaneously
(run 4). The results obtained show an IRR not less than 11.6 percent, which indicates that as
much as a 25 percent error in the estimation of research costs has almost no impact on the
ROR. Consequently, the estimated IRR value is close to its true value, if these cost items

accounted for the only estimation error in the computation process.

R -7' DE N Ex e

Three scenarios are considered in an attempt to account for possible underestimation
of extension/production expenses. In one case (run 5), both estimated extension and
production expenses were adjusted upward by up to 25 percent, and this yielded an IR of
11.56 percent. In the second case (run 6), it was assumed that the only estimation error is the
costs of seeds. This scenario was run to test the impact of the assertion made by many key
informants that maize seed price was subsidized by the government at about 60 percent.
Adjusting the seed price upward to account for the subsidy reduced the IRR to 10.9 percent.
In a third scenario (run 7), both the estimated seed costs and SODECOTON’s
extension/adoption expenses were increased by 150 (i.e. 60 percent subsidy) and 25 percent,
respectively, which yielded a 11.0 percent IRR. Thus, if one considers only potential errors
in estimating these extension/production expenses, an upward adjustment of up to 25 percent

still gives an IRR of no less than these 11.0 percent.

109
Runs 8-11: Research, Extension and Production Costo

After having adjusted research and extension/production expenses separately, these
three cost items were then increased simultaneously by 5-10 (runs 8-9) and 15-25 .(runs 10-11)
percents. The results indicate an IR in the range 10.72-9.79 and 8.88-7.03 percents,
respectively. These results show that a 10 percent estimation error on total research,
extension and production costs would have a significant negative impact on the IRR.
Realistically, given that these costs estimates are based on actual data, estimation errors of this

magnitude are highly unlikely.

Run 12: Maize Area over the Eistorio Eerioo

The base run IRR was computed using SODECOTON data which do not include the
entire Province’s maize production area, since key informants and available statistics indicated
the maize area outside the SODECOTON zone is relatively insignificant. However, this
assumption was relaxed upward by 25 percent, ceteris paribus. The run generated an IR of

13.5 percent, representing a 1.8 percentage points increase over the base run IRR.

- 2' ' i

In the base run, gross revenues from maize production in the North Province was
computed using estimates of the high input system’s yield and assuming that the yield in the
low input system is two-thirds the yield in the high input system. In runs 13-14, when these
yield estimates were increased to up to 10 percent, the IRR increased by as much as 1.7
percentage points over the base run value. To further test the effect of yield on the IRR, in
runs 15-17, maize yield was adjusted upward to as much as 50 percent, which gave an IRR of

21.5 percent. Even when yields are increased by 50 percent simultaneously with 20—40

110

percent higher input costs (run 18-20), the IR is still greater than the base run. Finally,
when maize yields are increased by 100 percent and input costs by 20-40 percent, the IRR

exceeds 20 percent.

Runs 23-25: Maiz Ar Pr vi u l r t Sor hum

A major assumption in the base run analysis is that maize did not replace sorghum,
but rather all maize was planted on newly opened land. However, common sense and
SODECOTON report suggest the contrary; Run 23, in which it was assumed that only 9
percent of the maize area replaced sorghum, generated a ROR of 10.0 percent. Increasing this
percentage to 28 percent further reduces the ROR to -4.3 percent, which shows that the
assumption about the proportion of sorghum area replaced by maize is extremely critical.

Overall, these results raise some concerns about the profitability of this investment.

R 22°Ext in dMizer v eFrec tPerid

Given the reduction in government budget allocated to develOpment agencies due to
the economic crisis Cameroon is facing, it is realistic to expect a substantial reduction in the
level of support SODECOTON is able to provide to farmers in the future. The base run
analysis assumed a constant level of investment to the year 2000 equal to the magnitude of the
1990 investment. While there is no way to predict what this level could be, runs 26-27
attempt to take into account a more than likely reduction of extension effort by reducing
SODECOTON’s expenditures on benefits and salaries for its personnel by 50 to 100 percent.
Interestingly, the results indicate that a substantial decline in SODECO’I‘ON’s support with
no reduction in maize area planted reduces the base run rate of return by no more that 0.3

percentage points. This implies that regardless of what would happen from the year 1991 to

111

2000 in terms of public support to maize extension, the base run rate of return will remain
unchanged, ceteris paribus.

Yet, to assume that reduced maize extension expenditures would have no effect on
maize area is somewhat unrealistic. Thus, to take into account the link between maize
extension effort and maize area, both variables were adjusted simultaneously in runs 28-29,
by reducing maize extension costs by 50 percent and maize area by 25 to 75 percent.
Unexpectedly, the results obtained show that the IRR ranges between 11.6 to 11.8 percent,

which is not significantly different from the base run result.

Summary

The sensitivity analysis revealed that the most important determinant of the ROR
obtained were the assumption about the maize area previously cr0pped to sorghum. These
results also showed the significant impact of maize yield on investment profitability,
supporting the hypothesis that the IRR would have been even more attractive had the varieties
extended been hybrids, ceteris paribus.

In contrast, adjusting historic research and extension/adoption expenses upward by as
much as 10 percent did not prove to have a major impact on the rate of return. But beyond
this range, the IRR is reduced by at least 20 percent, if all cost estimates are adjusted
simultaneously.

Finally, the sensitivity analysis showed that, regardless of what would happen from
the year 1991 to 2000, in terms of the level of maize extension support and maize area, the
base nm rate of return remains unchanged, ceteris paribus. This is explained by the fact that
these costs are small (relative to the one of the early periods) and the distant time periods

during which they are incurred lead to corresponding present values with only marginal

[12

effects on the IRR. The major drawback in this sensitivity analysis is that fact that in most

cases, adjustment are considered separately.

4.6 Institutiogg! Analysis"

The previous sections of this chapter present the quantitative part of this ROR study.
In general, ROR studies show that there exists considerable variability across locations within
a country and between countries with respect to the magnitude of the ROR for the same
technology. A major reason for this variability is the difference in the physical and
institutional contexts within which the technology is developed and used. These institutional
and physical factors establish constraints and opportunities for economic agents, through their
effects on the incentive structure, which in turn generate outcomes or payoffs. Consequently,
within the same physical environment, alternative institutional arrangements generate differing
patterns of interactions and thus differing payoffs. It is only when the quantitative analysis is
integrated with an analysis of the institutional setting that one begins to understand factors
underlying the performance of a new technology.

While this section incorporates the institutional dimension, it does not anempt to
provide a comprehensive analysis of the institutional setting of maize research and extension
in the North Province. Rather, it is based on the author’s personal experiences, interviews
with key informants, and a review of appropriate literature. The analysis proposes key
factors that have contributed to the estimated ROR to research and extension, in addition to
the characteristics of the physical environment and the technology discussed earlier. It also

highlights potential constraints to future expansion of maize production in the North Province.

I I 3
4. 6. I Research and Extension

Maize expansion in the North Province is partially due to both the unique and long
standing complementary organization of research, extension, and seed supply, and the strength
of these institutions. In most parts of Cameroon, a large number of institutions, mostly
governmental, support the agricultural sector. Their mandates are broad and, in many cases,
overlap. For example, in the Center Province, extension activities were undertaken by
SODECAO, NETP, MINAGRI, SOCOOPED, MIDEVIV, NGOs, and to some extent by the
TLU. Coordination and c00peration between these institutions has been a major issue of
concern in the policy debate, and has often been cited as one of the reasons why the
implementation of development policies has fallen short of government’s expectation.

In contrast, agricultural institutions in the North Province are much better organized.
While IRA is responsible for all agricultural research, as is the case in the rest of the country,
agricultural extension is dominated by SODECOTON with the support from NCSM for seeds
provision prior to its privatization. Although numerous other institutions are also present in
the Province, their activities are either marginal (e.g., SODEBLE, MINAGRI and Project
Céréalier) or very specific (e. g., SEMRY for irrigated rice and MAISCAM for maize
processing). This set up is unique in the country in the sense that fewer different institutions
are involved in agricultural research and extension, which facilitates better coordination. For
example, SODECOTON deals with both food crops and cash crops, provides inputs to and
buy production surpluses from farmers. In addition, SODECOTON follows a modified
Training and Visit extension system, which not only seeks to increase production but also to
promote commercialization, farmer organization, and education. Specific efforts to support
these goals include programs to diffuse improved varieties and production techniques (e. g.,

mechanization), supply necessary inputs, empower farmers through self-managed

114

cooperatives, market production surpluses, expand the development of infrastructure (e. g.,
roads), and promote farmers’ literacy. Thus, the success of the maize research and extension
in the North Province is partially due to SODECOTON’s broad mandate.

Furthermore, the significant impact of IRA and SODECOTON on maize production in
the North is partly due to the unique approach to research and extension that they have
ad0pted. In contrast to the classic situation, where research and extension have generated
numerous scientific reports and findings with little applicability to small farmers’ conditions,
these institutions rely on joint annual planning meetings, on-farm testing, field demonstration,
joint monitoring and evaluation, and prototype extension bulletins to ensure that the new
technology generated is appropriate to farmers’ needs and is extended to them.

These joint planning meetings have reinforced the holistic and interdisciplinary
characteristics of the farming system methodology, and contributed to building and
strengthening proactive and mutually beneficial relationships between research, extension and
farmers. This collaboration has resulted in significant management innovations that have (a)
improved the identification of farmers’ problems, (b) improved research implementation
which has produced higher quality research results, (c) provided greater incentives to
researchers and extension staff, ((1) improved the coordination and use of scarce resources,
and (e) generated a greater flow of information that is useful to farmers. As a result, farmers
benefit from greater access to high-yielding varieties and cultural practices adapted to their
circumstances, and lower transaction costs, all of which translate into more farm income. In
addition, fa'rmers’ active participation in the identification of research issues and the
evaluation of results has increased their interest in new technologies. Finally, a major

incentive to researchers is provided by the guarantee that if they develop appropriate

115

technologies, an effective extension system is in place which has proven its ability to widely
diffuse new technologies.

Unfortunately, the close proactive link between research and SODECOTON has been
informal, in the sense that there exits no formal institutional arrangements to insure continued
cooperation between researchers and extension agents. This deficiency raises some doubts
about the sustainability” of the system. Also related to the sustainability issue is the high
level of donor funding that has been required to support the joint research program (NCRE
and SAFGRADs) and the extension system. It is doubtful that the government will be able to
maintain a reasonable level of investment after the mid-1994 when the NCRE Project is to be
terminated. Already, the current economic crisis has drastically reduced the government
capacity to provide recurrent costs for research, credit, input supply, marketing, and
processing. Unless the economic crisis is resolved, further reductions are likely in the future.

In an effort to adjust their budgets to the country’s reduced finances starting from
1990, SODECOTON and IRA signed performance contracts with the government. To
comply with its contract, SODECOTON attempted to reduce its expenses for social programs
and narrow its focus to a limited number of operations by, for example, decreasing subsidies
(e.g., cotton since 1989) and reducing or stopping its purchase of food crops such as maize.
While these reforms will reduce operating costs, SODECOTON (1979-80, p.2; 1985-86, p.3)
fears that if it no longer buys food crops (which. are rotated with cotton), farmers will I
dramatically reduce their cotton area.

On the other hand, an expansion of the food crop area could also threaten cotton
production which is SODECOTON’s primary focus. For example, in 1979 when world price

of cotton dropped and SODECOTON’s groundnut oil (Diamaor) faced increased competition

 

3’ The concept sustainability is used here to mean sustained institutional performance.

116

with less expensive imported oil, SODECOTON reduced its guaranteed price for cotton. This
prompted many farmers to look for better alternatives, such as maize for which a market was
guaranteed by MAISCAM. In addition, after SODECOTON signed its performance contract,
it started charging IRA for implementing research trials. Because IRA also faced a financial
crisis, it immediately decreased the number of on-farm trials it contracted out to
SODECOTON.

These policy changes are indicative of the new environment under which both
research and extension have to be conducted in the future. Clearly, SODECOTON can no
longer afford to ignore the high costs of its activities, given its need to improve its financial

performance.

4. 6.2 Inputs Availability and Delivety

As indicated by the sensitivity analysis, returns to research and extension are highly
sensitive to maize yield. Among various determinants of yield, two are critical; the maize
type and cultural practices”. While Cameroon has benefited from the existence of a reliable
source of open-pollinated maize seeds, little effort has been directed at developing hybrids

with greater yield potential.

4. 6. 2. 1 W
A major determinant of maize expansion in the North Province has been the existence
of a reliable support system for producing and distributing quality seed. Anecdotal evidence

supported by SODECOTON reports (SODECOTON, 1985-86 p.61) suggest farmers are

 

‘° As discussed previously, collaborative applied research carried out by IRA and SODECOTON has
successfully identified cultural practices that have been widely adapted by maize farmers.

11 7
reluctant to keep seeds from the previous production (SODECOTON, 1985-86 p.61);

Therefore, they either purchased seeds on local markets or through SODECOTON.
Historically, SODECOTON’s main source of seeds has been the NCSM although IRA has
provided limited amounts of seeds. But, due to poor financial performance, NCSM was
privatized in 1991 and (symbolically) bought by Pioneer.

While Pioneer’s involvement in seed production initially raised hopes for a brighter
future for maize production in the country as a whole and in the North Province in particular,
these hopes were shattered when Pioneer pulled out in July 1993. This set back constitutes a

serious handicap to the expansion of maize in the North Province.

4622 WWW

With regard to the inherent yield potential, research results indicate that the yield for
most improved varieties extended in the North Province are quite encouraging. In the North,
under farmers’ conditions, the available improved varieties yield two to three times as much
as traditional varieties.

To date, maize breeding and extension in North Cameroon in particular, and in the
country in general, has been focused exclusively on identifying and developing open-
pollinated varieties, despite evidence of some yield advantage obtained by the lowland
breeding unit. For example, available research results indicate that hybrids outyielded Open-
pollinated varieties by 50 to 100 percent, under good management and adequate rainfall (1990
NCRE lowland breeding unit results). But, as Cameroon’s economy restructures to overcome
the current financial crisis, the traditional debate of hybrid/open pollinated maize types takes
greater significance. The study’s sensitivity analysis showed that a 50 percent increase in .

maize yield increases the base run returns to research and extension by 3.08 to 4.86 percent,

118

assuming a 20 to 30 percent increase in adoption costs. Similarly, the IRR increases by 10.8
to 13.8 percentage points under a 100 percent increase in yield and a 20 to 30 percent
increase in adoption costs.

Key informants reported that IRA’s focus on open-pollinated varieties has often been
justified by the claims that (a) farmers cannot profitably adopt hybrids under risky and low
input conditions“, (b) small farmers will not be willing or cannot afford to replace their
seeds each season, as required with hybrids, and (c) that success in hybrid maize production
requires the existence of a well—established hybrid seeds industry which does not exist in
Cameroon.

Recent evidence from other developing countries suggests that these claims (a and b)
are not based on facts. Byerlee M (1993) report that hybrids have been successfully
adopted and were profitable under low input conditions in India and El Salvador, as well as
Eastern and Southern Africa (Malawi, Zimbabwe, Kenya, Swaziland, Lesotho, Zambia, and
South Africa ‘2. Although these results were obtained from studies that compared hybrids to

an unimproved local open-pollinated variety, and where a well-established hybrid seed

 

“ It is often argued that hybrid’s higher production potential can only be achieved under favorable
climatic conditions when a complementary package of inputs such as fertilizer are applied.

‘2 Byerlee out! (1993) reports that:

a) In Swaziland, hybrid maize varieties are extensively adopted by small-scale farmers. Around the
late 19808, hybrid seeds were planted on about 80 to 90 percent of the maize area.

b) In Kenya, there has been a rapid and widespread adoption of hybrid varieties and a complementary
package of improved practices even though this seem to have occurred mainly in the commercial

maize producing areas. Maize area with hybrids row from 35 percent in 1970-74 to 64 percent

in 1986-88, much of which occurred in areas dominated by very small farmers. This expansion

in hybrid maize production has been accompanied by a very low fertilizer use on hybrid.

c) In Malawi, an analysis of the zerofenilizcr plot of data from 212 on-farm demonstrations (hybrid
versus local maize with and without fertilizer) conducted over the past three years (1990-92) in

the Lilingwe area shows that hybrids outyielded local varieties by 56 percent (380 kg) over all

three years including 1992, one of the driest year in Malawi’s history. Simple economic budgets
indicated a marginal return to farmers above 100 percent even under no subsidy alternative.

(1) In Zimbabwe, the performance of hybrid varieties under the low input conditions has been similar
to the results at obtained in Malawi.

119

industry existed, the results question the conventional wisdom that has guided maize
development in Cameroon. Thus, there is a need for Cameroon researchers to reevaluate the

potential benefits of expanding research to hybrid maize.

4. 6.2.3 Improvod Mag e goods Rolooog

Seed releasepolicies play an important role in insuring that new varieties are available
to farmers. Currently, the procedures for seed production and release are determined
informally by breeders with the assistance of agronomists and parastatals. As a result, there
exists no informed criteria for releasing new varieties. Thus, there is a need to develOp a
uniform policy that defines the characteristics (yield advantage threshold, stability, color,
endosperm type. etc...) to ensure the timely release of high quality seeds.

An attempt to address this issue has already been made with the extension of IRA’s
mandate to "ensuring an adequate supply of seed and other planting materials through seed
multiplication and certification, and provision of foundation seeds to developmental agencies
and private sector organization" (IRA, 1989). While IRA now has a mandate for seed
production, it is important to ask the question how effective will the research system be in

producing and supplying quality seeds, at reasonable costs and in a timely manner?

4.6-2.4 Wit!!!

Because maize is highly responsive to fertilizer, greater use of fertilizer in maize
production could potentially increased yields. Yet, on the average, between 1979 and 1990,
farmers applied chemical fertilizer on only 31.5 percent of maize area in the North Province

(ranging between 15 and 44 percent), the bulk of which was imported.

120

Prior to 1987, fertilizer importation was coordinated by government through
administrative processes that imposed legal constraints on private transactions (i.e., import
authorization and license, special clearance to use ships other than Cameroon Shipping lines
Company (the national shipping company), and custom inspections. On the other hand, the
private sector agents related directly to government agencies and they only indirectly related
to one another.

Fertilizer was imported through a joint operation between the MINAGRI and
FONADER. An interministerial tender board had authority to accept bids from fertilizer
importers and award contracts, with funds provided by FONADER and the Ministry of
Finance. Imported fertilizers was then allocated to provincial cooperatives or Delegations of
Agriculture on the basis of their needs as determined by MINAGRI - SODECO’I‘ON was the
largest consumer of the imported fertilizer. A uniform pricing policy has been applied,
regardless of the type of fertilizer and the location. This has corresponded to a government
price support to farmers amounting to about 65 percent on the average (Oakerson and Truong,
1990).

The public monopoly on the importation and distribution of subsidized fertilizer
created opportunities for rent-seeking behavior and corruption through selective use of
discriminatory power entrusted to bureaucrats. This behavior has translated into the offering
of large number of small contracts with high freight costs, and failed to generate sufficient
information to ensure timely distribution, at low costs. As a result of the institutional setting
and the fertilizer subsector’s poor performance, an unspecified but seemingly important

amount of fertilizer is smuggled from Nigeria”.

 

‘3 Up to the late 19703 maize import was marginal, but since 1980, the amount imported has become
significant because of: the uncertainty associated with seasonal price fluctuations, security inventory keeping
as a strategy to guarantee the supply to potential buyers, the credit structure which makes it easier to get

121

Triggered by the financial crisis prevailing in the country, in 1988 the government
initiated a fertilizer subsector reform program with the support from USAID. This program
was aimed at liberalizing and privatizing fertilizer procurement, introducing free market
pricing, and reducing fertilizer subsidy to zero by 1991 (Oakerson and Truong, 1990). If
successful, these reforms will solve many of the problems plaguing the subsector. Yet, the
effectiveness of this major'restructuring effort will depend on the sustained commitment of
government bureaucrats to liberalization, the entrepreneurial and innovative initiatives of
private economic agents, the market structures, their competitiveness and profitability, as well
as the introduction of new institutional arrangements relating to issues such as property rights
and dispute settlement.

An equally important constraint to increasing the performance of the subsector is
related to the intrinsic nature of the fertilizers themselves: chemical fertilizers are bulky
products that can be damaged by exposure to water, import and distribution require large
amounts of dry storage space, and the chemical compounds in fertilizer decompose and can be
depleted over a period of two years under poor storage conditions. Consequently, the actual
nutrient content of the fertilizer may not be consistent with its labelling, given delays in
transportation, distribution and the seasonality of its use. Until recently, SODECOTON
carried out all the necessary functions. Yet, SODECOTON only sells fertilizer to cotton
farmers and if mandated again to distribute fertilizer, SODECOTON alone could not possibly

satisfy the fertilizer demand of an expanding maize subsector.

 

a loan for maize importation than for buying local maize (Conte et al, 1993).

122

4. 6.3 Rural Financing

Another major contributor to the success of maize production and extension in the
North Province has been the input credit program sets up by SODECOTON. To some extent,
this program contributed to relaxing the capital constraint that farmers faced. Although maize
production in the North Province is not capital intensive, farmers need access to working
capital, at least to purchase fertilizer. However, as this subsector expends, the demand for
capital will grow beyond SODECOTON capability to provide it. Yet, although the country’s
rural financial sector has expanded rapidly in recent years, its performance has not been
encouraging.

In the North Province, a parastatal organization with a national mandate, FONADER,
was established principally to distribute credit for rural development. Unfortunately, its
organizational phiIOSOphy failed to consider the socioeconomic characteristics of the
environment in which it operated. For example, farmers were required to provide collateral
and go through a lengthy administrative process (negotiation time) in order to be eligible for a
loan. In addition, high transaction costs (costs of maintaining and collecting loans), low loan
recovery problems, and the scale bias of the loan program against small farmers made it
impossible for FONADER to be successful. While the informal sector has limited access to
capital,it is more flexible, scale neutral, and sensitive to farmers’ circumstances. The
challenge for decision makers is to redesign existing credit institutions so they can better
support sustained growth and development for the maize subsector in particular and

agriculture in general.

123

4. 6. 4 Marketing Potential and Post-Harvest Opportunities

Although the area under intensive commercial maize production in the North Province
is significant, much of the area is under low input subsistence farming. However, in the last
decade, subsistence farming has been gradually transformed into a higher value commercial
production system as more and more farmers look at maize as a major source of income.

This attitude has been driven by not only the inherent characteristics of the technology itself
(relative to cotton), the existence of strong research and extension support institutions, and
occasional drops in cotton prices, but also by a stable and attractive guaranteed market
provided by MAISCAM.

Because MAISCAM is still operating below capacity, there is still some additional
marketing potential to be exploited. However, if maize production in the region expands
greatly, MAISCAM alone will not be able to absorb the Province’s total production. Thus, in
the long-run, an efficient market structure will have to be developed and alternative uses for
maize (including the feed industry) will have to be promoted to sustain the growth of the
maize subsector over time. In addition, although this study did not include an extensive
market analysis, discussions with various key informants indicated that seasonal market price
variability is a major constraint to the expansion of maize production in the North Province.
For example, these informants cited maize price variability as a major factor for increased
importation of maize. A better understanding of the marketing aspect of the maize subsector

may therefore be necessary to identify the problem and suggest possible solutions.

4. 6.5 Information System and Coordinations
A major constraint to the expansion of maize production in the North Province is the

lack of timely and accurate production and market information, which is needed by both the

124

public sector as well as the private sector. The collection of basic information on agriculture
is intrusted to DEP (farm level data on crop planting, production, marketing, prices and input
use) and the Direction of Statistics and National Accounts in the Ministry of Plan and
Regional Development (for wholesale and food retail prices, population statistics, and imports
and exports). Both institutions have historically had problems collecting and disseminating
data or information on a timely basis.

With the economic crisis, their performance has worsened. In 1989, the AMP and
CAP projects, sponsored by USAID, were established in an attempt to improve data collection
and information provision. However, these data are still not available at the intermediate
farm and village market levels, except for the West Province. The need for appropriate and
timely data has become increasingly critical as the country attempts to restructure its economy
to support the private sector, and to detect and adjust to emergencies. Moreover, access to

these data is extremely important for the expansion of maize research in the North Province.

CHAPTER 5 SUMMARY and CONCLUSIONS

5.1 Summaa
5.1.1 Institutional Setting

The agricultural sector has always been the main contributor to GDP, foreign
exchange, and employment in Cameroon’s economy. In 1990, it employed 75 percent of the
working population, accounted for 47 percent of export earnings, and contributed 24.8
percent of the value of the country’s total production (World Bank, 1990).

Facing declining output per capita, the Cameroon government invested heavily in
agricultural research in order to increase productivity and thereby meet the expanding demand
for food, based on p0pulation growth. Agricultural research in northern Cameroon began in
the colonial period (1948) with the establishment of a research station at Guetale, which
focused on export crops - mainly cotton. Cotton production rapidly became a way of life for
two generations of farmers (Stems, 1993), as the cotton-based agricultural system, driven by
a massive government intervention, literally transformed the agricultural sector in the
Province. In the mid to late-1970s, IRA initiated research on food crops, but it was not until
1984 that farming systems research became a full-fledged program. Over the last two decades,
the food crop research budget and related activities increased in importance as a result of
donors’ support to NCRE and two SAFGRAD projects (J.P. # 31 and FSR).

In contrast to the institutional setting of agricultural extension in the southern part of
the country, extension activities in the north are dominated by SODECOTON, a parastatal
organization created in 1974 to take over from the French cotton company, CFDT. Co-
founded by the Cameroon government and France, supervised by the Ministry of Commerce,
and collaborating with the Ministry of Agriculture’s extension service, SODECOTON covers

125

126

both the Extreme-North and North provinces. SODECOTON’s extension service, which
follows a modified Training and Visit extension system approach, became involved in food
crop extension in 1974-75 with rainfed rice, and, then maize a year later. The objective of
these food crop extension activities was to encourage farmers to replace sorghum
progressively with more productive crops, so farmers could devote more of their time and

larger portions of their land to cotton production (SODECOTON, 1976-77; p.20).

5.1.2 Maize Production

The main traditional food crops in the North Province are cereals (sorghum and
millet) and legumes (groundnut and cowpea). The relative importance of these crops varies
across the Province, with maize being grown mostly in the south-east region. Although maize
was introduced in coastal Cameroon some 400 years ago by the Portuguese (Ayuk-Takem,
1991), is cultivated extensively in all ten provinces, and is an important part of the
population’s diet, key informants argue that it was not until the early 19703 that maize
production was introduced in the North Province. But, over the last decades, the maize area
in the northern part of Cameroon has expanded tremendously. During the period 1976 to
1990, seven new maize varieties were extended in the North Province, two of which were
introductions from Nigeria. These varieties have performed quite well, with the yield under
the high input production system in farmers’ fields averaging 2.3 metric tons per hectare,
ranging from 2.0 to 3.0 mt/ha.

In the North Province, maize is extended under low input and high input production
systems. These two systems differ not only in terms of the input use, but also in terms of the
level of SODECOT ON monitoring. Farmers participating in the high input production system

are supervised by SODECOTON field agents, and must grow crops using mechanical land

127

preparation (oxen and tractor), seed treatment, herbicide and fertilizer, and a specific plant
density (0.80 x 0.25 m, one plant per hill). Farmers participating in the intensive system
have little choice but to follow SODECOTON’s guidelines. In contrast, most non-
SODECOTON farmers grow crops with minimal input (low input production system).
SODECOTON food crops efforts have been supported by the existence of a public seed
company (NCSM) from 1975 to 1990 and, since 1984, MAISCAM has provided a major

private market outlet.

5.1.3 Profitability and Success Factors

The base run analysis of estimated benefits and costs yielded an 11.7 percent internal
rate of return, which is close to the bank interest rate, considered as the defending alternative.
Over the historic period (1979-1990), research expenses accounted for 82 percent of total
research and extension costs, the bulk of which was made up of salaries and benefits. In
contrast, research and extension represents respectively only about three and less than one
percent of total costs including production costs. Over this same period, about 66 percent of
total production costs were incurred in the low input production system, the main cost
component being weeding cost. The interpretation of this result has to be made within the
context of two key assumptions upon which the IRR is based: first, that virtually all of the
maize area in the Province is planted to improved varieties from research and extension and,
second, that all area planted to maize is grown on newly opened fields. This last assumption
turned out to be very critical in the sensitivity analysis for the value of the IRR obtained.
When the maize area previously under sorghum is assumed to be 28 percent, the IRR
becomes negative. This result raises some legitimate concerns about the profitability of maize

research and extension in the North Province. In addition, the sensitivity analysis on the base

128

run data set indicated that (a) upward adjustments of research, extension and adoption

expenses within a reasonable range (i.e., as much as 10 percent) have limited impact on the

IRR value, while (b) both maize area and maize yield adjustments significantly impact the

IRR value. The importance of the latter variable to the profitability of maize research and

extension in the North Province, suggests the need to develop and promote hybrids as part of

the strategy to increase productivity.
The study indicates that the following key factors have contributed to the expansion of
maize in the North Province:

a) Relatively favorable climatic conditions for maize production, coupled with the need
for more productive technologies to reduce food insecurity, especially during annual
hunger periods.

b) The simplicity of maize production management relative to management requirements
for other cr0ps (such as cotton) and the compatibility of maize with the existing
farming systems and consumption pattern.

c) The early maturity of maize, relative to other traditional cereals, which enabled
farmers to harvest the crop during the hunger period and earn an early income.

(1) A unique institutional set-up under SODECOTON, whose mandate extends over a
wide range of complementary activities including food and cash crop extension,
providing inputs to and buying production surpluses from farmers, contributing to the
development of infrastructure, and promoting farmers’ literacy.

e) The existence of apprOpriate research results that were generated through scientific
exchanges and collaborative linkages (genes, technical knowhow, institutional build-

up, and training) within national programs and between IRA and IARS.

129

t) The high quality of human capital both in research and extension, which developed
effective research and extension methodologies and recommendations consistent with
farmers’ problems“. For example, SODECOTON has a corps of 1,000 relatively
well-trained and closely supervised monitors (agents) for about 170,000 farmers
(IBRD, 1989; World Bank, 1990).

g) Strong institutional linkages between research and extension, which took advantage of
the institutions’ complementarities and were effective in identifying and taking into
account farmers’ constraints and setting research agenda. Furthermore, these
linkages provided incentives for both project researchers and extension agents.

h) The emergence in the mid-19803 of a major input supply source (SODECOTON) and
a major market outlet (MAISCAM) for farmers’ maize production surpluses, almost
concurrently with the introduction of maize, that guaranteed access to inputs through
the extension service and access to a private sector market for maize.

i) The decline in the cotton price, which gave maize a market price advantage over

COIIOII.

5.2 W

The study revealed a positive impact of investment on maize research and extension in
the North Province. Field visits and SODECOTON reports indicate a rapid expansion of
maize in this Province. But, for maize production in North Cameroon to further expand and
be sustainable, there is a need to find ways to develop the marketing and processing side now

that the production potential has been developed.

‘

“Although the quality of human capital both tn IRA and SODECOTON was not explicitly discussed
"1 the malts section, it was often cited by key informants as a major contributor to the expansion of maize
rescarch and extension in the North Province.

130

This study has clearly indicated that research, extension and marketing are
complementary. For example, research will have limited impact unless the results obtained
are adapted to the target environment and are extended to farmers, and farmers cannot
increase their production unless there market opportunities for the surpluses. As a result,
none of these functions can, by itself, be effective in achieving its objective; A minimal level
of investment in research, extension, and marketing is therefore necessary to achieve an
acceptable return on the investments made in the agricultural sector.

On the research side, in order to adjust to the new environment, IRA needs to expand
its program of economic analysis, which has been limited to simple partial budgeting. For
example, high priority must be given to conducting studies on the economics of production,
returns to research, and resource allocation, as well as subsector analysis, if IRA is to play a
more effective role in the national policy'deliberation. This will require both the systematic
collection of research results and related data and the presentation of these data in an
appropriate format.

The demonstrated importance of maize yield on the IRR, as well as evidence from
various other countries, suggest the need to reevaluate the role of hybrid corn in Cameroon
maize future. The conventional wisdom that hybrids must be promoted as part of a rigid
package and as a separate and distinct crop with special requirements needs to be reevaluated
with the objective of coming up with the best strategy for the farmers. While the agronomic
risk seems to be small, the timeliness in the availability of cash, quality seeds and fertilizer,
and the timely anticipation of institutional problems related to seed production will be critical

for successful adoption of hybrid varieties in Cameroon. The end of direct government
involvement in seed production and the emergence of a private sector requires that issues such

as Ilite] lectual property rights on germplasm (public good by nature) and the associated ethical

131

problems, as well as potential monopoly profit be regulated to insure that farmers are not
exploited. Historically, the role of the public sector in research and development and in
extension has been essential and will remain important in the future.

Success stories in hybrid development and adoption in developing countries have
depended on strong public sector research and extension. Byerlee M (1993) notes that in
Africa, research and extension on hybrid maize has been stagnating. Most of the varieties
are about 40 years old, while in countries like Brazil the turnover rate is about 3 to 4 years.
Therefore, active support of public sector research and extension is needed, in addition to
incentive provision, training, seed release policy, and for developing and organizing markets.
It is interesting to note that, in most of the deve10ping countries that have promoted the
adoption of hybrids, all maize breeders are from the public sector, and the seed industry has
often been monopolized by multinationals who did not develop the market, but took advantage
of an existing market (Byerlee _e_t_ol_, 1993).

A key factor contributing to higher maize yield is fertilizer application. Given the
performance of previous public agencies on the importation and distribution of fertilizer, as
well as the amount of fertilizer that would be needed to support a major increase in maize
production, greater private sector involvement and a reduction of public investment are
imperative. This calls for a rationalization of the public investment portfolio to create an
attractive environment for the private sector. Already, the reform of fertilizer subsector is
underway in an effort to liberalize the economy and expand the private sector. The success
of this reform depends on sound microeconomic incentives and reduced administrative
control. For example, potential incentives could include policies that would make it possible
for entrepreneurs to take advantage of the significant economies of scale in shipping. This

would ultimately contribute to reducing fertilizer costs to farmers. Fortunately for the

132

country, the main port of entrance (Douala) has an excess capacity that could accommodate
larger amounts of imports (Oakerson and Truong, 1990), but the reliability of suppliers and
transporters, and the availability of dry storage facilities remain a major concern.

Finally, a major constraint to maize expansion in the North Province is the inadequacy
of the region’s financial support systems. This has been the missingpiece in the agricultural
development institutional setting’s puzzle which SODECOTON was able to partially fill.

Yet, SODECOTON’s ability to provide financial support to farmers is far too limited to meet
public expectations that maize expansion should be a vehicle for poverty alleviation. Thus,
there is a need to create new financial support systems which better fit farmers’ conditions
and development expectations. For example, consideration should be given to developing or
strengthening financial intermediaries, as informal financial lenders provide some financial
services more efficiently than the formal credit service. In any event, the government needs
to realize that the performance of a financial market depends on the economic vitality of the
clients it serves. If these clients are poor or financially unstable, their ability to use the
financial market is diminished and they will be less willing to borrow and less able to repay
the loans. A major implication of this is that maize expansion should be viewed in the more
global context of rural poverty alleviation and economic development. This perspective is
needed in order to develop rural micro enterprises and production and consumption linkages

necessary for an expansion beyond the subsistence level.

5 .3 M915:
The quality of this research is constrained by numerous factors, the most important of
which is the availability and quality of data. In Cameroon, inadequate attention has been

given to data requirements for this type of analysis. As a result, this constraint required

 

133

numerous assumptions, some of which are almost arbitrary, and which turned out to be the

basis for most of the difficulties encountered including:

a.

inability to compute economic values for the benefits and costs items identified,
whenever necessary;

inability to estimate research and extension extemalities generated by maize
production. For example, this is the case for maize research and extension’s
contribution to household food security and institution building;

Maize yield by production system and proportion of maize area previously cropped to
sorghum;

Inability to account for changes in production that would have occurred without the
project;

inability to be more specific in predicting future policy, institutional and financial
environments under which crop research, extension and adoption will be performed;
inability to estimate more realistic supply and demand parameters which made it
impossible to do distributional analysis;

minimal treatment of risk and uncertainty. This was done using conservative values,
best estimates available, and sensitivity analysis. Unfortunately, sensitivity analysis
does not constitute a comprehensive analysis of risk. A combination of sources of
uncertainty would have been more realistic, but yet difficult to interpret. However,
sensitivity analysis is simple and requires less data than more sOphisticated methods of
risk analysis.

Though attempts made to minimize these weaknesses, were not entirely successful, the

assumptions that are made are reasonable and, as shown by the sensitivity analysis many of

these weaknesses are likely to have little significant impact on the IRR estimate.

134

5 .4 We Research Neefi

Despite the limitations imposed by data availability, reasonable ROR studies can still
be done. The methodology that would have to be used may be different from one study to
another as specific assumptions are made to accommodate the data available. The importance
of an ROR studies for any research institute in general and for IRA in particular stems from
the fact that it provides a quantified and documented basis for allocating the constrained
research budget. In addition, the inclusion of an institutional analysis highlights the strengths
and weaknesses (constraints) in the research and development process. Success stories would
be powerful leverages upon which the administration can rely in stressing the importance of
research for the national economy and in the negotiation for public support to research.

Yet, as much as ROR studies need to be encouraged, additional effort is required to
improve data collection and record keeping in a cost efficient way. The basic data needed for
ROR includes yields, area in production, adoption rate, input consumption, input and output
prices with information on taxes or subsidy level, salaries and benefits for research staff as
well as their time allocation to various crops they work on. InstitutiOnal analysis should
extend to input and output market studies and to the exploration of forward and backward
linkages and coordination processes between various interrelated stages of a particular
subsector. Such studies will not only increase the effectiveness of research but also will

constitute a major contribution to the national policy deliberation process.

APPENDICES

135

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136

Table A.2: Varieties Developed and Released by NCRE Project, Cameroon, 1981-90.

 

 

Variety Year Ecology Description (Cycle,
Released COIOF, Type"’)
Lowland Maize
CMS 8501 1985 North, South East Medium, White, OP
CMS 85-3 1985 Center & North Medium, White, OP
CMS 8602 1986 North Early, Yellow, OP
CMS 8704 1987 Center & North Medium, Yellow, OP
DMR-ESR—Y 1988 Center Early, Yellow, OP
CMS 8710 North Late, White, OP
Ndock 8701 Center Late, White, OP
Highland Maize
Shaba 1986 Adamaoua Late, White, OP
Kasai 1985 West & North West Short, White, OP
Coca SR md West & North West Late, White, OP
Bacoa SR md West & North West Early, Yellow, OP
Rig
IR 71 67 1986 Ndop Plain Irrigated
Cica 8 1984 Mbo Plain Irrigated
BKN 3033 1987 Agrilagdo Irrigated
ITA 222 md Agrilagdo Irrigated
mm
835 1985 Extreme North Early, White
C854 1988 Extreme North Early, White
C895 1988 North Medium, White
CS6] 1988 North Medium, White
834 1986 North Medium, White

 

“’"OP" stands for ”Open pollinated“.
”md" stands for missing data.
Some: Adapted from NCRE Annual Reports, 1992-90.

 

137

Table A3: National NCRE Scientists Trained/in Training") from 1982 to 1994, IRA-Cameroon.

 

 

 

 

 

Degree
Disciplines MSG PhD
Trained On Training Trained In Training

Agronomy 0 4 0 1
Soil Science ‘ l 0 1 0
Rice Agronomy 1 l 0 0
Rice Breeding 1 0 O O
Maize Breeding 3 0 1 1
Maize Pathology 1 0 0 0
Cereal Pathology 0 0 1 0
Extension Agronomy 2 1 2 l
Education/Extension 0 0 0 1
Agricultural Economics 1 2 1 l
Sorghum/Millet Breeding 3 1 0 1
Grain Storage Entomology l 0 0 0

 

“" Only the highest diploma acquired is included.
Source: Adapted from various NCRE Documents.

138

Table A.4: Summary of Published ROR to Agricultural Research Studies for Africa up to 1992.

 

 

Author(s) Year Country Crop Period Rate of
studied Return
(96)
Abidogun 1982 Nigeria Cocoa - 42
Evenson 1987 Africa Maize & Staple CrOps 1962-1980 30-40
Norgaard 1988 Africa Cassava 1977-2003 149: 1"”
Schwartz M 1989 Senegal CowPea 1981-2015 63
Karanja 1990 Kenya Maize 1955-1988 40450
Mazzucato 1991 Kenya Maize ' 58-60
Mazzucato & Ly 1992 Niger CowPea & 1975-1991 <0
Millet/Sorghum 1975-2006 2-21
Boughton & Henry de 1992 Mali Maize 1969-1991 135
Frahan 1962-1991 54
Schwartz, Sterns & Oehmke 1992 Senegal Cowpeas 1981-1986 31-92
Sterns & Bernsten 1992 Cameroon Cowpea 1979-1992 3
1979-1998 15
Sorghum 1979-1998 1
Harward et_al 1993 Zambia Maize 1978-1991 <0
1978-1991 90-103
1978-2001 96-106
Laker-Ojok I993 Uganda Sunflower 1985—1996 31
1985-2006 38
Maize 1985-1996 , <0
1985-2006 33
Soybean 1985-1996 <0
1985-2006 6
Makau Kenya Wheat 1928-1982 30-40
Mcmillan M Zimbabwe Maize
Ahmed & Sanders Sudan Sorghum 1983-2005 22-39

 

‘" Benefit/Cost ratio of the casaava mealybug control at IITA.

 

 

 

Source: Adapted from Crawford (1993), Oehmke gt_a_11 (1992), and Salinger and Stryker (1991).

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.:o_.8.u_:_Ee< mduz "roamed

 

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8. .3. 88.8. 8488 88.88 5.8. 8.8: 88.8. 3.8.x. :88: 8a.... 3.8 8.22.. .358
mom. . m mend. 30.8 31% Sad. 22... NR... .2... 0. nd 08... £833. 8.8-5.6
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.83 8. n. o 88... 8 o 2...... a c 8.. .28 8.5.... 8.38-...
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83... 28.8. 88.2 .88 83a :18 8.8 28.8 .8... an; 3:83 5.83..
«8.8. 83.; 8.8 :28 8...: .8.“ 8...... 28.2 o 83 .23 .380
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83...... .888: 88.8... 8.68.. 83; . .888 83% 88.8.. 88.8. 8a."... 3.2.39... a. 3.3.2..
“8.3 82.8 ~88 248m 88...: “8.2 88.2. 32... 8...: 88.8. ..
3.8 .8. a. .88 «8.8 8...: 8.8. n. ..: 82.. 83 «8.: 8:88.825... .228
3....“ 8....“ o $3.9 33.8 3.8 .3...” 5.... 28.8 8...“ <.:. 3 8.2.2.... .5838
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32-32 6888.6 .83 1.5882

. .35.... 9.02 3.; 83.3

140

Table A.6: NCRE Work Plans' Budget AllocatiOn (in Nominal value), Cameroon, 1987-1990.

 

 

Year Breeding Agronomy NCRE Official Ratio Ratio
Unit Unit Project Exchange Breeding Agronomy

(F .cfa) (F .cfa) ($US) Rate Unit (%)a Unit (%)"

(F .cfa/SUS)

1987 7,650,000 8,870,000 2,078,157 300.5 0.0123 0.0142
1988 7,400,000 6,900,000 2,442,582 297.8 0.0102 0.0095
1989 9,500,000 11,300,000 2,434,819 319.0 0.0122 0.0145
1990 14,000,000 7,300,000 4,490,334 272.3 0.0114 0.0060
Average 0.0115 0.0111

 

" Computed as: breeding research unit cost/(NCRE cost * official exchange rate).
" Computed as: agronomy research unit cost/(NCRE cost * official exchange rate).

Source: NCRE Work Plans 1987-1990 and

Table A.7: Maize Area (hectares) in the NCRE Lowland Breeding Unit's Mandated Zone, Cameroon, 1984-1987.

Year South

Province
1984 8,204
1985 8,480
1986 6,873
1987 6,760
1988 6,535
1989 5,803
Average

Cemer
Province

12,391
13,037
21,275
20,013
15,731
11,951

Adamaoua
Province

25,174
18,988
15 .815
19,608
20,310
22,326

North
Province
10,700
24,044
15,849
12,554
17,585
23.553

Ratio
(%)'
0.1895
0.3725
0.2650
0.2130
0.2923
0.3701
0.2837

.

‘ Conputed as: North Province area divided by the aunt of the area in all three provinces.

Source: National Agricultural Cenaua.

141

Table A.82 SAFGRAD JP #31 Total Expenditures (in Nominal SUS), North Province, Cameroon. 1979-1988‘”.

 

COST ITEM 1979 to 4/4/l984 to 7/l/l986 to 7/l/l988 to
1983‘“ 6/30/1986“’ SID/1988‘“ 8/15/1988“

27,433

Travel and Per Diem

Shipping and Storage 6,444

Housing 61,308

Other Direct Costs 2,770

Equipment, Supplies and Materials 69,518

Subtotal Non-Salary Expenses 121,881 229,280

Salaries and Benefits 170,593 222,835 4,099

Office Supplies 3,771

Research Equipment 8,460

Research Supplies 9,137

Vehicle Maintenance/Repairs 3,987

Fuel 14,073

Vehicle Insurance 1,444

Temporary Labor 27,686

Temporary Driver/Secretary 6,873

Training by TLU 1,918

 

mAny blank in the table simply mearu the data was not provided under that particular form by the source.

“'"Other Direct Costs“ includes health insurance, passport, visas, professional journals, communications, vaccines, bank charges.

M"l-unipment, Supplies and Materials' includes office supplies, equipment repairs, laboratory equipments, field trials, supplies,
labor, secretary, translation, training workfiops.

“’Paid for by SAFGRAD JP '31.

"’Paid for by NCRE Project.

Source: SAFGRAD LP. I3! (1984) for 1979 to 1983, and phone interview with Jerry Johnson for 1984-1988.

142

Table A.9: SAFGRAD/FSR Expenses (Nominal F.cfa), North Province, Cameroon, 1986-1988.

 

 

 

COST ITEMS 1986 1987 1988
Office Maintenance 0 0 31,471
Typing Table 0 422,910 0
Photocopy Machine 0 1,875,193 0
Office supplies 1,426,565 0 0
Office Stationaries 2,813,462 877,817 294,682
Calculator 10,000 6,000 0
Vehicle 8,614,000 6,320,276 0
Motocycle 0 3 , 160,000 0
1. Total Eguipment and Supplies 12,864,027 12,662,196 326,153
Rent and Furniture 8,536,483 4,800,000 9,094,589
Local Transport 1,422,750 3,268,918 1,602,300
2. Total Salaries and Benefits Expatriates 9,959,233 8,068,918 10,696,889
Local Personel Salaries 4,511,724 19,207,876 17,585,344
Overtime 0 10,000 0
Per Diem 702,700 896,910 229,000
Transport 832,785 1,605,275 245,920
Medical Care 0 4,000 0
3. Total Salaries and Benefits Nationals 6,047,209 21,724,061 18,060,264
Experimental Materials 1,215,995 202,965 0
Laboratory Chemicals 191,232 160,600 114,167
Sample Analysis 11,400 0 0
Meetings & Field Days 117,240 49,904 0
Vehicle Maintenance 2,167,697 1,607,125 762,201
Fuel 704,045 1,143,620 1,674,235
Sign Printing 0 62,200 0
4. Total Direct Research Elm 4,407,609 3,226,414 2,550,603
Insurance, Licence 733,322 3,716,822 992,475
Water, Gaz, & Electricity 108,787 190,345 0
Mail, Cables, Telex 439,569 742,939 521,191
Bank Charges 18,743 60,499 50,657
Documentation 5 1,558 72,705 0
Miscellaneous 154,258 399,740 413,640
5. W 1,506,237 5,183,050 1,977,963
E E _—

 

Spurgg: IRA Maroua

 

 

Table A.10: SODECOTON Personel Costs (in Nominal F .cfa), Cameroon, 1979-1990.

143

 

 

Year Senior Staff Others
1979 133,691,888 212,351,618
1980 274,664,066 265,318,256
1981 351,161,203 342,440,879
1982 392,209,511 416,619,197
1983 137,892,322 563,019,678
1984 249,427,626 562,475,392
1985 255,245,710 885,918,576
1986 210,392,283 657,819,779
1987 139,089,000 646,606,000
1988 112,271,120 557,322,988
1989 - 103,504,697 532,705,465
1990 98,316,000 494,999,000 '

 

Source: SODECOTON

 

'5...

144

 

M: SODECOTON Geographical Coverage

BIBLIOGRAPHY

145
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