ll- MICHIGAN STATE UNI IVERS II I III I III III IIIIIIIIII IIIIIIIIII 3‘129M(XN3‘|8363 II This is to certify that the dissertation entitled AGRO-INDUSTRY STRUCTURE AND ITS CONTRIBUTIONS TO REGIONAL INCOME AND EMPLOYMENT IN INDONESIA presented by Adhi Santika has been accepted towards fulfillment of the requirements for DOCTOR OF PHILOSOPHY degmin RESOURCE DEVELOPMENT I Major prdzflér Date September 24, 1990 MS U is an Affirmative Actt'on/Eq ual Opportunity Institution 0- 12771 r - x LIBRARY I "131“!“ State I University PLACE IN RETURN BOX to remove this checkout from your record. TO AVOID FINES return on or before date due. DATE DUE DATE DUE DATE DUE "7:375 0 5,751: —7I==I MSU Is An Affirmative Action/Equal Opportunity Institution omens-9.1 ABRO-INDUSTRY STRUCTURE AND ITS CONTRIBUTIONS TO REGIONAL INCOME AND EMPLOYMENT IN INDONESIA By Adhi Santika A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Resource Development 1990 .£flBE§ITR£ISHP AGRO-INDUSTRY STRUCTURE AND ITS CONTRIBUTIONS T0 REGIONAL INCOME AND ENPLOYNENT IN INDONESIA By Adhi Santika Agro-industry has been important in fueling economic growth in Indonesia. In addition to providing employment opportunities for an Indonesian population that still depends largely on agriculture and agro-industry fer a livelihood, agro-industry contributes to the economy by adding value in processing agricultural commodities. Of course, the increasing quantity of raw material from agriculture has permitted an expansion of agro-industry activities which implies a need for more labor, given that markets exist for the products. The performance of Indonesian agro-industry sectors is evaluated in this study by two techniques of economic analysis to determine the appropriateness of expansion of an agro-industry sector for the Indonesian economy. First, the theory of backward and forward linkages is used as the underlying I foundation to measure agro-industrial interdependence. Second, total value added and labor requirements to satisfy a unit increase in sectoral final demand are examined. This study uses an input-output Adhi Santika. technique as the main framework for the analysis of appropriateness for changing the Indonesian agro-industry structure. Using input-output tables for 1971, 1975, and 1980, the study delineates 32 agro-industry sectors out of 66 sectors included in the transactions table representing the Indonesian economy. The study finds that certain agro-industries are relatively more appropriate than others in terms of backward and forward linkages and value added - labor requirements. These are the spinning industries sector, the wheat flour and products sector, the rubber products sector, the sugar cane and brown sugar sector, the rice milling, cleaning, and polishing sector, the tobacco leaves and processing sector, and the beverages industries sector. A major problem in evaluating Indonesian agro-industry and the development opportunities in targeting an agro-industry sector for expansion is that labor supply by occupation and skill level is not included in the Indonesian input-output table. Therefore, it is essential that further research focus on labor supply in order to produce a comprehensive analysis. copyright by ADHI SANTIKA 1990 lNCflflliCNHflLIEEISEIEHSUCES Many individuals and organizations have made it possible for me to complete this dissertation. It is impossible to specify all of them. The Agency for Agricultural Research and Development (AARD) of the Republic of Indonesia, Ninrock International, and the International Food Policy Research Institute provided funding for completing coursework and conducting fieldwork. I am deeply grateful to all of these organizations and their related officials. The gratitude I owe to Dr. Daniel E. Chappelle, Professor, Department of Resource Development, Michigan State University, is beyond my power of expression in any language. He served as my dissertation director, guide and as my major professor during course work. I would also like to thank Dr. Milton H. Steinmueller and Dr. Paul E. Nickel, Department of Resource Development, Michigan State University, and Dr. Roy J. Black, Department of Agricultural Economics, Michigan State University, for serving on my committee and for their extremely valuable comments on this study. In addition, Dr. Mark H. Rosegrant, Research Fellow of the International Food Policy Research Institute, Washington D.C., was instrumental in getting this iv research initiated. Without his support, this degree would have been an unfulfilled dream. Thanks are also due all the Indonesian government officials contacted during the fieldwork. Without help in one way or another from Kusmadi Saleh, M.A., of the Central Bureau of Statistics, Republic of Indonesia, the dissertation research could not have been undertaken or completed. Deep appreciation also goes to the Editorial Board of the State News, Michigan State University and Patricia Whittier, who spent valuable time in helping me edit the draft of the dissertation. Finally, I could not have complete my graduate work without the enduring patience of my wife, Mimy, and my son, Prasiddha. In addition, my wife typed all my class papers and worked to help support the family while we lived in Michigan. She helped tabulate the survey data. Her understanding and affection has been extremely valuable for me. I thank her for all this, for her love. URAHBJJEI (3E? (SKIEEITEEPIES CHAPTER ONE . . . INTRODUCTION . . . . . Problem Statement . Research Objectives . . Organization of the Dissertation CHAPTER THO . . . AGRO- INDUSTRY IN INDONESIA . . . . . Labor Force . . . . Trends in Agro- Industry Production CHAPTER THREE . THE ANALYTICAL FRAMEWORK AND THE RESEARCH METHODS. OF STUDY . . Inter-Industrial Linkage Analysis . . Employment and Value Added Requirements . The Concept of Appropriate Technology . Variable Specification and Data . CHAPTER FOUR . . . INTERDEPENDENCE 0F AGRO- INDUSTRY AND OTHER SECTORS . . Backward Linkage Analysis . Forward Linkage Analysis . . Analysis of Appropriate Agro— Industry . Structural Changes in Employment CHAPTER FIVE . FUTURE DEVELOPMENT OF AGRO- INDUSTRY IN INDONESIA . . . . CHAPTER SIX . . - SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS Summary . . Conclusions . Recommendations . REFERENCES APPENDICES vi Page (005030) 01¢wa ILLIEE]? (3E? TIUAEIIJEES Some Indicators for Manufacturing Sector in Indonesia 1974/1975, 1979 and 1986 . Labor Force Participation Rates by Sex and Educational Attaintment in Indonesia, 1977 Agro- Industry Sectors with Backward Linkage Coefficient above 0.5 for 1971,1975, and 1980 in Indonesia . . . . . . . . . . . . . Agro- Industry Sectors with Forward Linkage Coefficient above 0.5 for 1971,1975 and 1980 in Indonesia . . . . . . . . . . . . . Value-Added - Labor Ratios (Total and Direct Requirements) for Final Demand by Thirty Two Agro-Industry Sectors, 1971 . . . . . Value-Added - Labor Ratios (Total and Direct Requirements) for Final Demand by Thirty Two Agro-Industry Sectors, 1975 . . . . . . Value-Added - Labor Ratios (Total and Direct Requirements) for Final Demand by Thirty Two Agra-Industry Sectors, 1980 . . . . Total Persons Employed in Seven Agro-Industry Sectors in 1971, 1975, and 1980. . . vii Page 13 35 49 62 7O 73 75 83 3 4 4. .l .2 .2 3 Total K—L Selecting Total V-L Selecting Total V-L Selecting Total V—L Selecting Total V-L Selecting LIST ‘ OF FIGURES Ratios and Direct K-L Ratios for Appropriate Industries in Bangladesh . Ratios and Direct V-L Ratios for Appropriate Industries in Indonesia Ratios and Direct V-L Ratios for Appropriate Agra-Industries in 1971 Ratios and Direct V-L Ratios for Appropriate Agro-Industries in 1975 Ratios and Direct V-L Ratios for Appropriate Agra-Industries in 1980 viii Page 38 41 71 74 78 (ZIIIXEPUPIEIR (31313 INTRODUCTION PROBLEM STATEMENT Given that most Indonesians still depend on agriculture and agro-industry for their livelihoods, these are two particularly important sectors of the Indonesian economy. The importance of these two sectors can be seen in the principal needs for Indonesia which are shown in! the national guidelines of state policy. One of the national guidelines states that the general pattern of national development should emphasize the agricultural sector and encourage industries converting agricultural raw materials into industrial raw materials and finished goods. It is important to stress here that both agriculture and agro— industry sectors are considered to be sectors that can raise national income while at the time promoting employment opportunities. It is important that both the agriculture and agro-industry sectors selected for basic national development are those in which the nation has a real comparative advantage. That is, the government should not provide incentives for expansion in those sectors for which evident comparative advantage does not exist. In order to examine comparative advantage and employment opportunity in both agriculture and agro-industry sectors, therefore, it is necessary to consider the basic attributes of these sectors as well as their current development. According to Pelzer (1971), the development of a plantation economy brought about the division of Indo- nesian agriculture into two major sectors: a highly scientific estate use of labor and capital; and a peasant agriculture, tradition-bound and, at least in Java, highly labor intensive. The plantations, because they were able to finance the construction and operation of factories, took over the cultivation of crops requiring complicated and costly processing, while the peasants concentrated on the production of domestic food crops and the export crops that demanded little processing. Agriculture still provides well over half of all em- ployment in Indonesia; therefore, trends in the size of the agricultural work-force of great importance, despite the somewhat misguided interpretation often placed on a decline in agriculture's share of total employment as evidence of success in industrialization. To draw any clear interpretation of the trends in agricultural employment, two items of information are needed and these are not available in Indonesia, at least not in any reliable form. The first is a comparison of labor productivity in agriculture and labor productivity in other sectors to which the agricultural labor force migrates. For evaluating the 3 success of economic policy. at least in so far as it influences economic structure and employment, there has been great interest in Indonesia in measuring the growth of labor force and, more specifically, employment in different, sectors. The second is a measure of agricultural employment refined enough to give trends in total hours worked in the agricultural sector, not just trends in the very questionable measure of the total number of persons who reported agriculture as their main activity in response to questions in various censuses and surveys. Nithin the agro-industry sector, there have been a number of important changes in recent years that would be expected to affect the level and pattern of demand for labor. According to Austin (1981), agro-industry is an enterprise that processes agricultural raw materials, including ground and tree crops as well as livestock. Agro- industrial growth permits diversification of exports required for a viable improvement of long-run balance of payments. To gain perspective on the problem and prospects of agro-industry in Indonesia, it is worth examining the main features and structural relationships underlying Indonesia's agro-industry sector. In terms of production activity, the agro-industry sector utilizes processing technologies that do not require as much labor as the agricultural sector. The labor force in the agro-industry sector must have additional skills that are needed in processing agricultural products. Additional 4 labor skills mean that labor productivity tends to be higher than in the agricultural sector. Besides that, increasing value added can be earned by agro—industry activity where raw materials from agricultural sector are processed to supply consumer products. Therefore, it is the agro- industrial sector that could offer the best chances of raising labor productivity and increasing value added. The expansion of this sector together with the construction and services sectors, will increase the availability of non-farm employment opportunities. The growing importance of agro- industry employment alternatives for the rural population strengthens the conclusion that agricultural development policies cannot be formulated in isolation from policies concerned with the growth of labor demand in agro-industry sectors. RESEARCH OBJECTIVES This research attempts to explain problems faced by the Indonesia's agro-industry sectors by achieving the following objectives: a. To analyze the linkage among sectors of the economy, especially the agro-industry sector and the agricultural sector, including the relative importance of both sectors in terms of their impacts on each other and the economy as a whole. b. To measure both total labor requirements of and total value added by the agro—industry sector. 5 c. To make recommendations to improve performance of the agro-industry sector in Indonesia. ORGANIZATION OF THE DISSERTATION Chapter Two describes various aspects of Indonesian agro-industry with emphases on current government policies as well as current problems. The third chapter deals with the analytical framework and research methods and describes the model, variable specification, and data. Chapter Four is devoted to the presentation of data generated by the study. This chapter covers the descriptive analysis of interdependence of agro-industry and other sectors, especially the agricultural sector. Chapter Five deals with the future development of agro-industry in Indonesia. The last chapter summarizes the findings, draws conclusions, and makes recommendations for agro-industry policies and for future research. (ZIIAAIPUCISIR UFUUCJ AGED—INDUSTRY IN INDONESIA LABOR FORCE Indonesia's population increased from 131 million in 1966 to 138 million in 1978 and 165 million in 1985. Average annual population growth was 1.8 percent from 1970 to 1978 and 2.21 percent for the period 1980 to 1985 (Central Bureau of Statistics, 1985). According to a Horld Bank Report (1985) that contains comprehensive aggregate data on the- growth of the Indonesian economy over the periods 1961 - 1971 and 1971 - 1980, employment (measured by the number of employed persons) grew at an estimated rate of 2.9 percent per annum during 1971 - 1980, up from 2.4 percent during the '60s. These rates fall within the lower end of plausible employment growth rates given in a previous World Bank report. The acceleration in employment (and labor force) growth during the 1970s is associated with an increase in the proportion of the working age pepulation rather than with an increase in labor force participation rates. With the increase in the total labor force, the nation is confronted with the problem of how to provide jobs. 7 Since average productivity in manufacturing industries will probably increase, with the consequence that workers must be diverted to occupations elsewhere. The agricultural sector might continue to provide the bulk of employment, but it might not be able to absorb productively the remaining increase in labor force. The ratio of labor force to population did not change during the period from 1961 to 1982. But there has been a substantial reduction of the proportion of the labor force engaged in agriculture, from 73.4 percent of the total labor force in 1961 to 65.9 percent in 1971 and 54.66 percent in 1982. This reduction is significant and implies a shift to the other sectors and a major expansion in non-agricultural employment. During this same period there was, however, an increase in absolute numbers of laborers in the agricultural sector due to population growth. During the last decade and in terms of absolute numbers, agriculture, in particular food agriculture, has remained by the far the largest single source of additional employment, accounting for more than 40 percent of incremental employment. Uithin the sub-sector of food agriculture, rice is the most labor intensive food crop, in terms of both man-day inputs per hectare and per ton produced. However, labor productivity in agriculture did not increase during the decade. It is furthermore expected that the rate of labor absorption in food production will decrease. Hence the accelerated expansion of non—farm activities, especially labor-intensive 8 manufacturing and its regional distribution, have become critically important and will determine the rate and quality of future employment growth. According to Hugo et al. (1987), knowledge about the industrial work-force distribution and trends in industrial composition over time can provide a basis not only for evaluating the success of government policies, but also for forecasting labor absorption in other sectors. However, extreme care must be taken in the use of census data for this kind of analysis in a country at Indonesia's stage of development. This is because seasonal change in the participation rate of agricultural employment might be taken to indicate labor force responsiveness in labor market. In the case of agricultural sector, there is labor force responsiveness due to the fluctuation of demand and supply of labor especially at the peak season, e.g., harvesting season in the rice field. The presumed trade-off between industrial growth and efficiency on the one hand and employment creation on the other might be far less sharp than believed in some quarters (Stewart and Streeten, 1971). The conflict may be un- avoidable when use of relatively labor intensive technologies means the combination of employment and outdated machinery and equipment. But if new techniques that are adapted to the country's factor endowment are implemented, if double or triple shifts of workers are used, and if the machines are run at faster speeds, the situation 9 may be different. There is no reason to believe that the more labor-intensive activities necessarily involve higher capital-output ratios than the relatively small scale production that may be typical for a country such as Indonesia. The International Labor Office, in its study “Employment Aspects of Industrialization" with special reference to Asia and the Far East, has shown that those industries with relatively lower capital-labor ratios tend to have relatively higher levels of output per unit of capital invested (ILO, 197D). TRENDS IN AGRO—INDUSTRY PRODUCTION In the first phase of its industrialization, Indonesia was probably correct in directing industrial investment and growth primarily to meeting demand of the domestic market. There was an obvious market for imported products, so that import substitution could be expected to attract investments. And, although the low purchasing power of the Indonesian population called for low output volumes, the loss of efficiency in terms of higher costs was not large because economies of scale are not very significant in production of light consumer goods. 0n the other hand, the structural characteristics of Indonesia did not favor a vigorous expansion of manufactured exports. Industries producing goods based on domestic raw materials are those in which Indonesia, in principle, has developed, or may reasonably be expected to develop, a 10 comparative advantage. While the material inputs and the labor component in processing costs are substantial, costs can be kept comparatively low because wages in Indonesia are among the lowest in the world. Labor productivity can be raised and domestic raw materials are, or could be, available at relatively favorable prices. Provided Indonesia's comparative advantage is not curtailed by adverse world market conditions, the promotion of resource- based industries should result in an improvement of the export position. From the national point of view, industrial development should take place in selected lines rather than across. the board. There is substantial evidence within the deve10ping world that wide scale industrialization is bound to become inefficient and that it will slow down economic progress in the long run. Indonesia, as a late-comer among the industrializing countries, should avoid costly mistakes made elsewhere and should try to establish, from the very beginning, a pattern of industrial development that relies on efficient lines of production and promises of substantial social returns. This strategy calls for manufacturing specialization according to the classical concept of comparative advantage (Donges et al., 1974). Although this concept is in principle a theoretical one, it can be easily adjusted to become operational under the conditions prevailing in Indonesia. Comparative advantage alone 11 provides a criterion for guiding industrialization with a view to obtaining the highest benefits. According to Donges et al. (1974), three groups of relatively labor-intensive industries can be distinguished: The first group consists of the most labor-intensive industries in which total value added per employee, as well as both components of value added, rank below the industrial average. The industries that most consistently belong to this group are canned foods, textiles, shoes, leather manufactures, wood products, paper products, and miscellaneous manufactures. In the second group are the labor-intensive industries using relatively more skilled labor. Examples are various non-metallic mineral manufactures, a number of non-electrical machines, some electrical appliances and some steel products. The third group consists of a few labor-intensive industries using relatively more physical capital than those industries cited above; examples are beverages and plastic articles. Arranging the industries according to the two-digit International Standard Industrial Classification, the following can be classified as relatively labor-intensive industries: food processing (ISIC 20); tobacco manufactures (22); textiles (23); clothing and footwear (24); wood processing (25); furniture (28); paper and paper products (27); printed matter (28); leather and leather manufactures (29); rubber products (30); electrical machinery (37); and miscellaneous manufactures (39). 12 In Indonesia, with abundant labor but scarce capital, growth of labor productivity is not the most meaningful criterion.for assessing overall efficiency (Papanek, 1980). It reveals only the productivity of those workers who were effectively employed. It would be more useful to know the output, or value added, per unit of such scarce inputs as capital. At least in the case of agro-industry sector there are economic accounting systems that incorporate an analysis of both total output and value added requirements. Therefore, when one is concerned with the efficiency of agreeindustry sector, it is necessary to consider the links between output and value added which will generally be based on the availability of inputs. Indeed, input availability is a reflection of the supply of resources. If labor productivity were seen as the result of having spread a given capital stock over a large number of previously unemployed workers, per capita income of the whole labor force would increase. Labor productivity is an important factor of agro- industrial development in Indonesia. Rapid agro- industrialization can significantly improve the efficiency of Indonesia's agriculture through the supply of inputs and the processing of the sector's output. According to the Table 2.1, the manufacturing sectors in Indonesia generated value added at increasing rates for the period 1974/1975 - 1986. The value added growth of sector 31 was 200.14 percent during 1974/1975 — 1979 and 13 284.39 percent for the period 1979 — 1986; the value added growth of sector 32 was 198.34 percent during 1974/1975 - 1979 and 515.76 percent for the period 1979 ~ 1988; and the value added growth of sector 33 was 281.62 percent 1974/1975 — 1979 and 762.24 percent for the period 1979 — 1986. Thus, Table 2.1 Some Indicators for Manufacturing Sector in Indonesia 1974/1975, 1979 and 1986 Industry Code Year Value Added*> VA/L**> 31 1974/1975 289,891 159.1 1979 889,770 431.8 1986 3,420,233 1,925.2 32 1974/1975 85,609 128.8 1979 255,411 417.1 1986 1,572,723 2,067.3 33 1974/1975 41,475 24.3 1979 149,982 167.0 1986 1,297,708 1,187.4 *> = in million Rupiah **> = Value Added/Labor ; Labor = persons engaged 31 = manufacture food, beverages, and tobacco 32 = manufacture of textile, wearing apparel, and leather 33 : manufacture of wood and wood products Source : Central Bureau of Statistics. Statistical law. 1988. the trend during 1974 to 1986 was that the value added — labor ratios of manufacturing sectors consistently increased in positive terms. The point, of course, is that the problem of employment growth at the national level can be solved by considering the entire structure of the manufacturing sectors. It seems apparent that the 14 development of the agro-industry sector as one of the manufacturing ‘sectors provides great opportunities to increase employment potential for the growing labor force. In addition, a processing plant can open new crop opportunities to farmers and create additional farm revenues In this study, the major theme is the economic development of agro-industry sector in comparison to other sectors of the national economy. The major contrast that is highlighted in this study is that between those sub-sectors of the agro-industry sector that satisfy both value added and labor requirements and those that do not. CZEIIKE?1PIEIR HPIIIRIEIE THE ANALYTICAL FRAMEWORK AND THE RESEARCH METHODS OF THE STUDY THE INPUT-OUTPUT MODEL An input-output model allows the quantification of regional economic interdependencies when data are organized into sectors representing the important economic sectors of the region (Diamond and Chappelle, 1981). Inputeoutput analysis is concerned with interdependence of producing and consuming units in a modern economy and with showing interrelations among different sectors that purchase goods and services from other sectors and, in turn, produce goods and services that are sold to other sectors (O'Connor and Henry, 1975). More specifically, Pedersen and Chappelle (1989) describe input-output analysis as the study of interdependence among sectors (industries) in a.region that can be used to measure the effects felt throughout an economy when demand or supply changes in one or more sectors. In regional planning, Williamson and Tait (1988) explain that input-output techniques have been applied in a number of planning efforts that use such criteria as output, employment, and income. According to Chenery and Clark (1962) and Heesterman (1970), input~output analysis is 15 16 probably only the first of several quantitative methods for handling inter-industry economics. In terms of economic transactions, Hewings (1985) shows that in inputeoutput analysis, profits are contained within the value-added entry, and hence, the system represents a relatively complete picture of the transactions in economic system. The input-output model is based on the Leontief input- output system which is, in turn, based on two sets of basic conditions (Leontief, 1953). First, there are balance requirements, i.e., the combined inputs of each commodity or service must equal its total product. Second, there is a definite relationship between quantities of all the inputs absorbed by one particular industry and the level of its total output. According to Richardson (1972), the input- output model has two characteristics: 1) it provides a descriptive framework for showing the relationships among industries and between inputs and outputs; and 2) it makes certain economic assumptions about the nature of production functions. It is an analytical tool for measuring the impact of autonomous disturbances on the economy's output and income. The static input—output system in its simplest form is founded on three assumptions (McGilvray, 1964; Fedorenko, et a1, 1972; Skolka, 1988): 1. Each sector produces a single output with a single input structure and there is no substitution among the outputs of different sectors. 2. The inputs into each sector are simple proportions only 17 of the level output of that sector, i.e., the amount of each kind of input absorbed by any particular sector goes up or down in direct proportion to the increase or decrease in that sector's total output. 3. The total effect of carrying out production in several sectors is the sum of the separate effects. In terms of availabilities of resources, according to Miller and Blair (1985), there is a fundamental assumption that the inter-industry flows from sector i to sector j depend entirely and exclusively on the total output of sector j for that same time period. The input—output format is useful for thinking about and probing into the problem of unemployment in a city or region, and in particular, the problem of providing new jobs for an unskilled population. One of the major advantages of an input-output approach is that it allows us to set up a classification of sectors, commodities and services that is useful and appropriate for addressing the problem at hand. According to Nickel et al. (1978), input-output models have been developed to specify impacts at the national, regional, and specific industry levels. According to O'Connor and Henry (1975), when doing an input-output study it is necessary to produce three main tables: 1. Transactions Table. The basic table of an input-output system is known as the transactions table in which are entered in value 18 terms the various economic flows within the economy during some particular base year usually at producer prices in nominal terms. To prepare this table, the economy is divided into a number of sectors usually based on national census of production and other national statistical data. Table of Technical Coefficients. Technical coefficients are calculated from a transactions table. These coefficients are calculated by dividing every item in quadrant I and III of a transaction table by the sum of the column in which the item is recorded. Table of Interdependency Coefficients. Because of the inter-relationships between different sectors of an economy, a change in the final demand for the products of one sector causes ramifications throughout the system; the change affects not only the outputs of the sector concerned but also those of most, or perhaps all, of the other sectors of the economy. One of the main aims of input~output analysis is to study these changes, but unfortunately, the technical coefficients cannot be used directly for this purpose as they show only what are known as the direct or first order effects of changes in final demand. To study second and high-order effects, other operators known as total or interdependence coefficients are required. These coefficients are obtained by inverting the (I-A) 19 matrix of coefficients. The key to Leontief's input-output system is the construction of the input-output (or transactions) table. The transactions table shows the flow of commodities from each of the producing sectors to all other consuming sectors, both intermediate and final. In an n sector model, the flow of commodities from the i—th sector can be expressed as: (1) X1-;Xu+(C1+Ii+GI+Ei) where X1 2 gross output of the i-sector, X13 2 the amount of output of i-th sector purchased by the j-th sector as intermediate input, and C1, Ii, 61, and E1 are private household consumption demand, private business investment demand, government expenditure, and export demand respectively, comprising the final demand for output of the i-th sector. Since the sector is a producing sector, it also requires inputs from various sectors in the following relationship: where L3 = wage payment, V; = other value added and M3 = imports of commodity j from abroad. The crucial assumptions underlying equations (1) and (2) are: 1) each sector produces only one homogenous commodity (no joint products); and 2) the value of goods and services delivered by the i-th 20 industry to the other producing sectors is a linear and homogenous function of the level of output of the purchasing sectors, j. The latter implies constant returns to scale, fixed proportion and no substitution among inputs, which rules out external economies and diseconomies. The system also assumes equilibrium at given prices, and in static versions there are no capacity constraints so that supply of each commodity is perfectly elastic (Richardson, 1972). The input-output structure of any particular industry is presented by a set of technical coefficients, 813. each of which states the amount of a particular input absorbed by that industry per unit of its own output, <3) Xx: " ‘1ij x . . .21 where 813 = direct coefficient that quantifies input requirements to be purchased from sector i by sector j and [A] 2 matrix of 3138 which may be considered a quantification of technical production relationships. INTER-INDUSTRIAL LINKAGE ANALYSIS Agro-industry's performance in the national economy and its impact is more complex to analyze than most other sectors. This is because agro-industry is an intermediate sector that is characterized by both backward and forward linkages to other sectors. These two types of linkage must 21 be considered to estimate the total economic impact of each agro-industry. Such estimation is especially useful in identifying key national economic sectors. Backward linkage means that mutual attraction is important mainly to the supply activity (Hoover and Giarratani, 1984). In other words, a market-oriented activity is attracted by the presence of an activity to which it can sell. While forward linkage means that an impact of change is transmitted to an activity further along in the sequence of operations. According to Nickel et al. (1978) and Miller and Blair (1985), the term "backward linkage" is used to indicate the economic interconnections of a particular sector to those sectors from which it purchases inputs. In contrast, the term "forward linkage" is used to indicate the economic interconnections of particular sector to those sectors to which it sells its output. For example, the paddy sector in Indonesia has both backward and forward linkages. The paddy sector is the main agricultural sector on most islands of Indonesia and produces the staple food for most of the population. The backward linkage can be seen in the paddy sector activity'on any island of Indonesia. The usual orientation in rice porduction is to focus on the availability of physical inputs that are needed in the paddy field, e.g. seeds, fertilizers, 'pesticides, and mechanical technology. The paddy sector activities are likely to be stimulated by any changes in aggregate supply of seeds, fertilizers, 22 pesticides, and mechanical technology, and thus, are the sources of production input from which paddy sector purchases physical inputs. 0n the other hand, the paddy sector has impacts on one or more activities further along in the sequence of operations. The supply of the paddy sector is an inducement to establish a considerable range of activities from handpounding of rice, rice milling, and cleaning~ and polishing of rice, to processing and preserving of rice and trade activities. These further activities are categorized as forward linkages in economic analysis. Schultz (1976) emphasizes that backward linkages indicate to what extent the economic branches have been specializing. 0n the other hand, forward linkages give an indication of the direction of supply. The intersectoral linkages can be analyzed by using the input-output technique (Czamanski, 1973; Diamond and Chappelle, 1981). Further explanations about the input-output framework as the underlying bases of linkage analysis are given by Chenery and Watanabe (1958), Hudahar (1982), Miller and Blair (1985), and Haji (1987). Chenery and Hatanabe (1958) have developed two linkage indexes: (5) LDj'-§X1j/xj-§au In; 2 direct backward linkage index the number of units of commodity i used in X1.) production of X3 units of commodity j 23 813 = the number of units of commodity i used in production of one unit of commodity j (6) LD,’ " 21x15 / Z, me = direct forward linkage index Xi: = the number of units of commodity i used in production of X units of commodity j Zi = total demand which is the sum of intermediate demand (21311) and final demand (Y1) for output from ith sector. One of the major themes of this study is to evaluate economic linkages of the agro-industry sector at. the national level for the years 1971, 1975, and 1980. This effort relates to that part of the Indonesian development targeting program that emphasizes the agricultural sector and encourages industries converting agricultural raw materials into both industrial raw materials and finished goods. It is possible to use the approaches to linkage developed by Chenery and Watanabe (1958) in economic impact analysis at national level. Of course, it is essential that evaluation of economic impacts be based on both the correct sectors and periods required by the objectives of the study. The 32 agro-industry sectors employed here, which come from a 66 x 66 national input-output matrix, are all significant in examining agricultural development. A simple way to examine the importance of each agro-industry sector during a 24 period of time is to compare its contribution with those of other sectors of the national economy. For comparison, it is necessary to determine that the sector classification is the same for each year of analysis. Fortunately, the sector classification of the Indonesian economy for the years analyzed (1971, 1975, and 1980) does employ the same framework and definition. To determine optimal development strategies, therefore, the orientation of linkage analysis can be focused on a sectoral comparison of each agro- industry sector for the years 1971, 1975, and 1980. Although these comparisons are essential they do not constitute a complete evaluation of agro-industry sectors in the national economy. In terms of development strategy, the highest priority should be given to those sectors that have high forward and backward linkages and the lowest priority to sectors that have low forward and backward linkages (Hirschman, 1958). This is because any sector with either a high backward or a high forward linkage index is likely to induce more investment and to stimulate new activities through multiplier effects. EMPLOYMENT AND VALUE ADDED REQUIREMENTS According to Chappelle et al. (1986), the inverted Leontief matrix (i.e., [I - AJ‘l) is a multiplier matrix itself in that it provides information on the amount of sales generated by each sector of the regional economy when its final demand is increased by one dollar. This assertion 25 will be used in estimating the output level of the Indonesian economy for 1971, 1975, and 1980 with a modification on the inverted Leontief matrix by inserting an import coefficient matrix (Kb. Imports are a part of supply for goods and services in a given country. Imported goods and services are often used in the production process and final consumption. The import data collected by the Indonesian Central Bureau of Statistics were recorded at ”cost, insurance, freight" (c.i.f.) price by individual code number. According to Kreinen (1983), c.i.f. covers the cost of the Commodity up to the port of entry. Essentially, it includes ocean freight and other intercountry transportation costs, which the f.o.b. (free on board) price excludes. Therefore, every import commodity must first be grouped according to I-O classification. By summing the import value of individual commodities in an I—O table, one arrives at import value for that item. Import at producer's prices consists of c.i.f. value, import duty and sales tax on import goods. Finally, imported goods and services are separated from domestic production to form a non-competitive type import. Non- competitive imports are imports of commoditieSathat are not domestically produced (Miller and Blair, 1985). Input-output accounts provide a quantitative approach to output level (X) calculation. That is, in the first step of its calculation the total import and final demand should be separated. The rationale of division between final 26 demand (F) and total import (M) is that if(I=A)¥F calculation is based only on F rather than (F ~ M), X represents an output level that comes from the assumption goods and services are domestically produced. (7) AX+F~X+M where F1 is final demand for sector i and M1 is import in sector i. (8) (I-A)X-F-M (9) x- (I - A)"(F - m The second step of X calculation is that imports of commodities should be considered in terms of the place where they were produced. The reason for this is that commodities imported are not coming solely from abroad but are also domestically produced (competitive imports) and imports are endogenous variables. Up to this point, according to the Central Bureau of Statistics (1976), it is assumed that imports are proportional to domestic consumption. 1118 an import coefficient with respect to domestic consumption. Given the above considerations, the Central Bureau of Statistics (1976) developed a mathematical model for the import coefficient, }L Import (10) p. = Intermediate demand + Final demand - Export where Intermediate demand + Final demand = Total output. Hith simplification of F0 = final demand - export 27 F0 F ~ E therefore, (11) u, - MN?“ + F!) solving for M1 (12) ”1' 91(§Xu+Ff) and equation (7) can be restated (13) ){-.AX-r17-.M and substituting simplification of F. in equation (10) and substituting equation (12) (14) X-AX+F'+E-!?(AX+F') if equation (14) is stated in a matrix form, then: B = .. = export A? 2 import coefficient matrix 28 (15) XIAX+F’_+E-Am?+F'13 (16) X=(Ax—AXM)+(F°+F'13)+E (17) x,-u- . V- vlr- (I—DDAI" where 0 is the diagonalized matrix .of value added coefficients. Then V measures total (direct and indirect) value added required to sustain a unit increase in the final demand for output of sector j. Both analysis for total (direct and indirect) labor and value added requirements should be followed by further analysis in terms of direct requirements. According to Alauddin and Tisdell (1988), the direct labor requirement (say, “1) of a unit increase in final demand is given by: (25) “1 ' (1: * {311311) where 13 is a vector of employment and 11 a1: is the direct production requirements from each sector multiplied by labor output ratios (coefficients) for each sector. To estimate direct value added requirements (say, 91) stemming from the final demand for a sector's production, 32 the direct production requirements from each industry must be multiplied by the value added output ratios (coefficients) for each sector: (26) 3: ' (V: + {New where v is a vector of value added. THE CONCEPT OF APPROPRIATE TECHNOLOGY It is widely recognized that appropriate technology is a problem for developing countries. Indonesia must keep in mind its means and its development objectives. Indeed, Indonesia must evolve an approach to industrialization that combines the use of advanced technologies with the use. of inexpensive alternative technologies that would encourage employment and production in rural areas and small scale industries. Appropriate technology may be defined as the set of techniques that makes Optimum use of available resources in a given environment. In contrast, most groups working with appropriate technology associate it with a specific set of characteristics rather than with social maximization in abstract. Characteristics of appropriate technology include: more 'labor use in comparison with a less appropriate technology (higher L/O); less capital use (lower K/L); less skill use; more use of local materials and resources; smaller scale; and production of products needed by consumers. According to Jequier and Blanc (1983), 33 appropriate technologies are characterized by high potential for employment. In terms of human resources, Congdon (1977) emphasizes that appropriate technology must create jobs for all people in society, and in this way, make maximum use of human resources. Choi and Lee (1983) describe appropriate technologies as small—scale and labor-intensive technologies requiring a small amount of capital investment and having high employment generation effects. An appropriate technology should be an efficient technology and, at the same time, one that fully reflects the abundance or scarcity of particular resources in the ’composition of the necessary inputs. It should substitute, for example, more direct labor for capital within a given total of cost in an economy in which labor is plentiful and capital is scarce (Robinson, 1979). In view of both the abundance of domestic labor and the scarcity of domestic capital, it is important that the Indonesian government accept foreign investment programs. The accomplishment of direct foreign investment in Indonesia is done by multinational corporations (MNCs). According to Gillis et al. (1983), perhaps the most common host country objectives are those of job creation, transfer of usable technology and skills, and saving or earning foreign exchange. For example, Indonesia typically requires MNCs in natural resources to fill all unskilled jobs with Indonesians after three years, but only 75 percent of skilled and supervisory jobs and 50 percent of technical and managerial positions 34 must be held by Indonesians. In 1980, capital in the amount of $467,000 was required for creating one job in pulp and paper. Yet in textiles, a job could be created for only $10,000 of investment. The introduction of advanced technologies into industrial structures brings about well—known consequences, especially in a country where development programs are at the early stage. In particular, the adoption of production processes characterized by high capital intensity accentuates the imbalance of factors in underdeveloped economies. Particularly in the industrial sector, reduction of manpower per unit of output is the main purpose of technical advance, and use of such new technologies tend to limit employment possibilities (Rad-Serecht, 1979). The diminishing use of labor in production leads in turn to an increased concentration of incomes that is detrimental to the wage-earners. This, in turn, tends to reduce the size of the home market and encourages an industrial development in which capital-intensive industry is more desirable than labor-intensive industry. One explanation for the diminishing use of labor is that the quality of human resources is improved which leads to more productive workers. Labor quality can be enhanced by education of both children and adults. According to Gillis et al. (1983), education can be defined broadly as all forms of human learning, or more narrowly as the process that takes place in specialized institutions called schools. 35 In any economy there is a strong tendency for people with certain levels of education to hold certain types of jobs. jobs at a period of time The proportion of people who hold in a given place is the labor force participation rate. For example in Indonesia, as Table 3.1 shows, there is a positive correlation between education level and labor force participation rates both in urban area and rural area. Many theories of technological development for developing countries consider the selection and development of appropriate technologies based on the above perspectives. Since the agro—industry sector is often characterized by new processing technologies, using fewer human resources and at Table 3.1 Labor Force Participation Rates by Sex and Educational Attaintment in Indone- sia, 1977. Elementary High School Academy & Sex No School Inc. Com. J S University M urban 74.41 48.07 67.23 59.11 77.62 86.51 rural 88.13 65.87 81.67 60.82 81.76 83.21 F urban 33.32 20.18 19.50 20.01 40.48 49.04 rural 47.06 33.12 31.81 20.21 61.50 83.71 Inc. 2 Incomplete Com. = Complete J = Junior S = Senior M : Male F : Female Source: SAKERNAS, 1977 38 relatively higher cost than the agricultural sector, it is necessary to evaluate the agro~industry sector as including one type of technology that could be appropriate for the development of developing countries. In evaluating the agro-industry sector in terms of 40w cost of final product and high potential for employment, Alauddin and Tisdell (1988) determine an appropriate technology for each sector of the economy, total capital- labor ratio and direct capital-labor ratio. In Figure 3.1, they identify 47 Bangladesh industries in some of which are appropriate technologies in terms of total as well as direct capital ratios, i.e., total K/L versus direct K/L. ‘ To pursue the point of identifying appropriate technologies in terms of total as well as direct capital ratios, Alauddin Total K—L ratio * * )k * *** Jk * * * x M B * x x *x a x x a x a a ** 0 A Direct K-L ratio Figure 3.1 Total K-L ratios and direct K-L ratio for selecting appropriate industries in Bangladesh. 37 and Tisdell (1988) have employed a linear regression estimate to relate the observed direct ratios to the observed total ratios. (27) Total K/L - a + b Direct K/L where (28> Total L - (1) (I - A)" 1‘: diagonalized matrix of labor coefficient (29) Total x- (k) (I - A)“ f: diagonalized matrix of capital coefficient (30) D1190: L - a, I (11 '1' $1181!) (31) DIIGCC K3 B, I (k1 + §k131j) In Figure 3.1, the lines 0A and OB mark the ratio of available labor to employed labor. In essence, this ratio depicts the average absorption of labor at the national level in order to satisfy a unit increase in final demand. This quantification of optimum capacity is certainly necessary if we manipulate the open static Leontief model to determine the total (direct and indirect) output and input (labor and capital) requirements to satisfy a unit increase in final demand. Since the focus in economic impact analysis is. on evaluating both labor and capital requirements in which the optimum capacity to absorb labor is fulfilled, then it stands to reason that there must be a comparison between these requirements and the ratio of available to employed labor. Figure 3.1 shows that all 38 sectors falling within the area circumscribed by 0AMB appear to fulfill the average labor and capital requirements with respect to the optimum capacity in absorbing labor. This means that any economic sector in the area circumscribed by OAMB is categorized as an appropriate technology in Bangladesh's economy. The analysis indicates sectors that might be given preference in Bangladesh for expansion in terms of the appropriateness of their K/L ratio as well as capital and labor requirements per unit of final demand.“ Related to the problem of agro-industry in Indonesia, equations (21), (24), (25), and (28) are applicable for estimating both total (direct and indirect) labor and total value added requirements, and both the direct labor requirement and the direct value added requirement. Also, equations (27), (28), (29), (30), and (31) can be corrected by replacing K with V to be used in selecting appropriate agro-industries for Indonesia. The reason for this assertation is that value added for each sector (V) consists of capital (K), labor (L), and other inputs that are depicted in equation (23). Therefore, an important consideration when evaluating economic impact is looking‘ at not only capital required in development, but also at value added as well. (32) Total V/L - c + d DirectV/L where (33) == (21) TotalL- III- (I-m a)“ 39 (34) = (24) Total v- 911-(1-1!) A)" (35) = (25) “1 ' (11*2311611’ (36) = (26) 91' (V: *‘f‘fiaul By adapting Alauddin and Tisdell's (1985) approach of Figure 3.1, all the above equations, i.e., equations (32), (33), (34), (35), and (36) are useful in selecting appropriate agro-industry sectors for Indonesia. Figure 3.2 is a modification of Figure 3.1 with direct value added-labor ratios in the horizontal axis and total value added-labor ratios in vertical axis. In this modification, the selection of appropriate agro-industries is based on agro- industries that fall within the area circumscribed by OCND. At this point, it is important to stress that each industry is facing three major factors of labor situations: the labor requirement for each industry’s activity; the current labor employed in each industry's activity; and the total available labor at the national level. The main question posed here is why the decision-maker needs to be concerned with relationships among these three factors. The major reason for this is that both labor and value added of each agro-industry exists within the context of labor and value added for the national economy. The ratio of available to employed labor for the national economy on the vertical and ‘horizontal lines represent the limit of the national economy in absorbing 40 labor to generate optimum value added. Every single point beyond this limit shows that the total available supply of labor exceeds that actually employed in the national economy. That is, national economic activities cannot be expanded beyond this limit to reach the optimum value added that is generated by utilizing national labor. This implies that if economic activities are conducted in circumstances in which total available supply of labor exceeds~ that actually employed, the optimum value added is not achieved. Although the above approach concern total effects on the national economy, there is no doubt that each agro- industry sector is part of the national economy activities. In the case of value added generation, if an agro-industry sector utilizes more labor than the national capacity for absorbing labor, a decreasing value added will be created not only in the agro-industry sector but also in the national economy. In other words, each agro-industry sector should maintain the condition that its value added labor- ratio is less than the ratio of available to employed labor at national level. The labor requirements that are important in production activity show the appropriate number of persons needed to get to the optimum allocation of production inputs. Too often, however, the focus of optimum allocation of production inputs is solely dependent upon the capital-labor ratios that are commonly derived in economic analysis, and do not include value added. In this study, where value 41 added—labor ratios are taken into account, however, it is possible to derive a comprehensive analysis that reveals the importance of value added in the national economy rather than capital considerations. On the other hand, both current labor employed in each industry and total available labor at the national level must be considered by this study. The reason for this is that when calculating the Total V-L ratio * x x * * ** x N D * Jk :k 3k 1k * * 3k * O C Direct V-L ratio Figure 3.2 Total V-L ratios and direct V-L ratios for selecting appropriate agro-industries in Indonesia. ratio of available to employed labor, the actual proportion of supply and demand of labor in agro-industry sector must be known. This study is concerned with the development of methods to evaluate the appropriateness of agro-industry sector performance in Indonesia so that government agencies can evaluate one sector by directly comparing it with others. 42 Also, since the main concern is with the repercussion of employment strategies in Indonesian economy, it is necessary to consider evaluation of labor supply by occupation and skill level in the context of agro-industry economic impact assessment. This effort fits within that part of the employment targeting program that focuses on the creation of employment opportunities. According to Arndt (1984), in relation to the allocation of labor between occupations, sectors, and regions, the recognition of the wage system is most important. Conceptually and operationally, however, as noted by Thompson (1985), occupational mix seems quite simple and straightforward, but bisecting observed earnings into an industry - mix component and an earnings - rate component may not really come off clearly. In the Indonesian case, McCawley and Manning (1978) notes that the wage situation in Indonesia reflects the difficulties of setting an effective minimum wage in a labor surplus economy. In addition, McCawley and Manning (1978), note that it is difficult to escape the conclusion that, given these institutional realities and the present labor market situation, minimum wages will be unlikely to affect a significant proportion of the industrial labor force. In view of these positions, labor supply by occupation and skill level data are important in evaluating the national economy, but these data are not available in the Indonesia input-output tables of 1971, 1975, and 1980. From 43 the perspective of this study, the consideration of value added - labor ratio requirements, backward and forward linkage indexes, and labor supply by occupation and skill level are required to determine the appropriate agro- industry sectors in Indonesia. From the perspective of this. study, there are four conditions that an agro—industry sector should satisfy in order to be categorized as an appropriate agro-industry: (1) the total value added - labor ratio should be less than the ratio of available labor to employed labor; (2) the direct value added - labor ratio should be less than the ratio of available labor to employed labor; (3) the backward linkage index should be at least 0.5; and (4) the forward linkage index should be at least 0.5. This study is based on the proposition that these four conditions as guidelines to development strategies, although useful, are not adequate in themselves as a basis for decision—making. The major reason for this limitation is that agro—industry development exists within the context of labor supply by occupation and skill level, and these data are not available for the years of analysis. VARIABLE SPECIFICATION AND DATA Information for constructing agro-industry sectors of the input-output transactions matrix were obtained from various Indonesian government agencies, including the Central Bureau of Statistics, Ministry of Agriculture, 44 Ministry of Trade, and Ministry of Labor. Only secondary data were used to estimate Indonesian economic activity for 1971, 1975, and 1980. To determine the sectors of the national economy that are needed in input-output analysis, both aggregation and disaggregation methods must be applied. Aggregation has a dominant role to play in the input-output studies (Malinvaud, 1954). A description of one sector in the input-output table must be clearly recognized whenever data are being aggregated. However, among sector descriptions there is both variation and similarity in terms of raw material sources, kinds of technology in processing activity, and other basic attributes. In addition, according to Barna (1954), the grouping of commodities and activities must follow certain principles. One necessarily loses information by aggregation, and the methods used should aim at minimizing information loss. As will be argued, the choice between various alternative methods, each of which is of a compromise, must depend on the purposes of the analysis. According to the Central Bureau of Statistics (1984), the main condition that a sector must meet is that the output of each of the resulting sectors be as homogenous as possible. Two main criteria to consider are: 1) grouping economic activities with similar input structures. With this criterion, two units with similar outputs but using different input structures should be placed in different sectors; and 2) grouping vertically chained production 45 processes. With this criterion vertically connected units, such as the series cording cotton, spinning yarn, weaving, dying, finishing, and printing of textiles, should be placed under the same sector provided that a change in the output of one unit is always followed by proportional changes in the output of the related units. Sectors used in this study are derived from the 175 sectors of the Indonesian Input-Output Table for 1971, 1975, and 1980. For the purpose of this analysis, a 88-sector input-output table has been used to represent the economy of Indonesia; it includes 32 agro-industry sectors (Appendix 1: Table 1). This section has presented a brief description of scope of the analysis and definitions of agro-industry sectors. Examples of simple agro—industry referred to this sector are: handpounding paddy, roasting and skinning coffee and maize, chipping cassava, smoking rubber, drying Coconut, extracting coconut oil and producing brown sugar, slicing tobacco, sawing wood in the forest area, and salting and drying fish. The agro-industry sector also covers all 'production activities whose objectives are to transform raw materials or semi-finished agriculture products into new products . that have higher value or utility. The transformation process may be mechanical, chemical, or other forms and may be performed by power-driven machines or by hand tools. In the 1971, 1975, and 1980 Input-Output Tables, 48 according to the Central Bureau of Statistics (1984), employment is defined as the number of peOple who worked, full or part time, during the year (man-year). As a general rule, 'a person is included in the labor force if he or she worked for at least one hour per day during the previous week. Those who sought employment during the previous week and have been employed are also considered as part of the labor force. (3!!£&I?1P]31R I?()IIIR INTERDEPENDENCE 0F AGRO-INDUSTRY AND OTHER SECTORS BACKWARD LINKAGE ANALYSIS The preceding section dicusses backward linkages arising from agro-industry development. It is important to recognize that agro-industry activities cannot be separated from the backward linkage analysis from which the dynamics of agro-industry structural changes can be considered. One of the uses of backward linkages is in taking into account production linkages, that is, the derived demand for agro- ‘industry inputs (e.g., raw materials) produced in different agricultural sectors and other sectors that sustain agro— industry activities (e.g., trade). The relative strength of backward linkage analysis in Indonesian strategy development is to provide information that contributes to determining potential sectors from which an agro-industry sector is supported. Such information is necessary if a model‘ is needed to explain the changing structure of the agro-industry economy. The comparison of agro-industry backward indexes for the years 1971, 1975, and 1980 is shown in Table 4.1, which summarizes data in Appendix 1: Tables 11, 12, and 13. Table 4.2, which is also 47 'v_ a:- 48 summarized from the same tables in Appendix 1, shows the agro'industry forward indexes for the years 1971, 1975 and 1980. In 1971, there were 18 agro-industry sectors that had backward linkage indexes of > 0.5 or greater. Of these, the five highest were: (1) processing and preserving of food (0.8473); (2) rice milling, cleaning and polishing (0.8472); (3) oil and fats (0.8080); (4) handpounding of rice (0.7980); and (5) wheat flour and products (0.7470). The 1975 input table for Indonesia indicates that 13 agro- industry sectors had backward linkage indexes of 0.5 or greater. The oil and fats sector was the agro-industry sector with the highest backward linkage index‘(0.8530) followed by rice milling, cleaning and polishing (0.8350), handpounding of rice (0.7920), wheat flour and products (0.7520), and processing and preserving of food (0.7320). The 1980 input-output table for Indonesia indicates that the sugar cane and brown .sugar sector was the agro-industry sector with the highest rank as measured by the backward linkage index (0.8630) followed by rice milling, cleaning and polishing (0.8010), oil and fats (0.7980), handpounding of rice (0.7810), and slaughtering (0.7670). Although the number of agro-industry sectors that have high backward linkage indexes varies in each‘year of the analysis, each of these sectors shows a trend in which the backward linkage maintains a relatively a high ranking. The main question posed here is what the economic consequences are for each agro-industry sector that has a 49 Table 4.1 Agra-industry Sectors with Backward Linkage Index 13143,, above 0.5 for 1971, 1975, and- 1980 in Indonesia. 1971 1975 1980 CODE* COEFFICIENT RANK COEFFICIENT RANK COEFFICIENT RANK 1 - _ - - _ - 2 0.7980 4 0.7928 3 0.7811 4 3 _ - - _ _ - 4 _ - - - - _ 5 - - _ - - _ 5 - _ - - _ _ 7 0.5786 14 0.5825 12 0.5040 14 8 - - - - 0.8630 1 9 _ _ - - _ 10 0.7140 8 - - - — 11 0.5720 15 0.5250 13 - — 12 - - - - ~ - 13 - - - - - - 14 - - - - - - 15 - - - - - - 18 - - - - - 17 - - - - - 18 - - - ~ - - 19 0.6290 13 0.6040 9 0.7670 5 20 - - - - - _ 23 - - - - - _ 27 0.8473 1 0.7320 5 0.6750 10 28 0.8060 3 0.8530 1 0.7960 3 29 0.8472 2 0.8350 2 0.8010 2 30 0.7470 5 0.7520 4 0.7590 8 31 0.5650 16 - - 0.6390 12 32 0.6740 9 0.7140 7 0.7300 7 33 0.6370 12 - - - - 34 0.6730 10 0.5970 11 0.5720 13 35 0.7040 7 0.7220 6 0.7050 9 38 0.6850 8 0.6640 8 0.6520 11 42 0.6510 11 0.6000 10 0.7100 8 Source: Summary of Appendix 1: Tables 11, 12, and 13 * Sector description is the same as sector description in Appendix 1: Table 1. - Value is less than 0.5. 50 high backward linkage index during the years under analysis. In summary, seven agro-industry sectors had backward linkageindexes in the top 10 for all three years (1971, 1975, and 1980). These were: (1) rice milling, cleaning, and polishing sector; (2) the oil and fats sector; (3) the handpounding of rice sector;7 (4) the wheat flour and products sector; (5) the processing and preserving'of food sector, (6) the food products not elsewhere classified sector; and (7) spinning industries. Since the highest priority in development should be given to those sectors that have high backward linkages, it is necessary to examine the basic attributes of each of these sectors in terms of purchasing inputs. It should be recognized that the rice milling, cleaning, and polishing sector has significant backward linkages with other sectors of national economy from which it requires inputs. The 1971, 1975, and 1980 input-output tables for Indonesia show that the rice milling, cleaning, and polishing sector has a great dependency on other sectors, including, for example, paddy, handpounding of rice, agricultural machinery, electricity and water supply, trade, transport and communication, and financial services. Therefore, we must examine these upstream activities. First, the availability of paddy is of great importance in rice milling activity. As noted by Mears (1981), from 1988 to 1978, with irrigation rehabilitation proceeding and the profitability from rice improving relative to other substitute crops, the area harvested increased on Java — the 51 main island — at the relatively slow annual rate of 0.7 percent. And with the BIMAS (Bimbingan Massal or mass guidance) intensification program, yields increased rapidly, so that total production on Java expanded at an average rate of 3.8 percent a year. Generally, the total paddy production processed by rice mills increased in order to . provide rice for consumption. That is, there were potentially adequate supplies of paddy available in the area of rice mill activity for the year of 1971, 1975, and 1980. Second, paddy is delivered to rice mills through various channels and by various means. Some paddy is gathered at village assembly centers by local traders. and then delivered and sold to the rice mill; in other cases, the individual farmers may deliver directly (Esmay et al., 1979). In terms of paddy distribution based on the region, Mears (1981) points out that the paddy marketed from the farms generally flows toward rice millers with regional excess supply moving toward deficit areas. For 1971, 1975, and 1980, the input-output tables for Indonesia show that both wholesale trade and retail trade contribute significantly to the rice milling, cleaning, and polishing sector. These marketing channels provide for the delivery of paddy from the farm-gate to the milling sites. Third, the financial service sector contributed significantly to rice milling activity during the years 1971, 1975, and 1980. Marketing of paddy from the farm-gate to the rice mill requires continuous credit or financing, but farmers are sometimes faced with inadequate credit 52 facilities. According to Mears (1981), the need for financial support from the financial service sector continues during production, after harvest, through processing and marketing, including transport, and until the rice finally is consumed. In fact, the dependency of the rice milling, cleaning, and polishing sector on the financial sector is clear in the Indonesian input-output table for the years 1971, 1975, and 1980. The oil and fats sector is another agro-industry sector that showed high backward linkage indexes in the 1971, 1975, and 1980 Indonesian input-output tables. Three major agro- industry sectors have a vital influence on the oil and fats supply, i.e., coconut, palm oil, and groundnut. According to Gwyer and Avontroodt (1974), Indonesian consumers have traditionally obtained the bulk of their edible oil from domestically produced copra. Consumption is increasing quite rapidly on account of population growth, income growth, and a relatively high income elasticity of demand. The annual increase in oil consumption was about 7 percent in the 19705 due to pOpulation increase and higher incomes per person (M011, 1987). It is implicit from these conditions that the supply of copra should be increased to meet domestic demand. One alternative is to increase coconut supply by intensifying national production. According to by M011 (1987), coconut was the major source of vegetable oil in Indonesia until 1978. Production of coconuts increased at an annual average at 1.4 percent between 1955 and 1974. It is evident from what is said 53 above that there is a significant interdependency between edible oil supply and coconut production in the period of 1971, 1975, and 1980. Palm oil has attributes different frOm those of coconut oil. Its main use is as cooking oil, but through fractioning it can be used to make a number of sophisticated and specialized products such as margarine, soap, cosmetics, and lubricants. In regard to these uses and the increasing of annual vegetable oil consumption, there are problems in balancing supply and demand of vegetable oils. In 1978 the government decided on a policy of substituting palm oil for coconut oil as the main cooking oil for domestic consumption (Arndt, 1981). The point, of course, is the crucial need to increase of palm oil supply as a source of vegetable oils. According to M011 (1987), oil palm was considered more profitable than rubber in the late 19808 and early 19705 and large areas with aged rubber stands were replanted with oil palm. Other considerations of shifting from rubber to 511 palm production are summarized by Collier and Werdaja (1972). First, farmers' returns from rubber are so low that they are forced to switch to other activities. If farmers have other crops, they put more time into their production. Second, the costs of transport are high, and the port facilities are distant; the size of holdings is small, and there are many links in the marketing chain. In regional development, the government policy ties palm oil production with the transmigration program, an attempt to solve the problem of population distribution by 54 making use of enormous uncultivated areas outside Java, Bali, and Southern Sumatra. Many transmigration areas are totally devoted to producing palm oil with transmigrants being smallholders. The Indonesian government hopes that through encouraging transmigrant to cultivate the oil palm, the uncultivated areas can be brought into productive use. As noted by Kreitman and Worth (1984), the government"can own a processing plant and provide initial financing through government banks, pay a minimum guaranteed price for the harvested palm oil and take care of the marketing and distribution of the processed oil. This is commonly known as the "nucleus estate policy," in which the estate is a collectivized grouping of small private plots. Indonesia produces oil bearing crops in addition to coconut and oil palm. The most important of these are groundnuts and soybeans, the greater proportion of which are consumed domestically (Gwyer and Avontroodt, 1974). Whiie a proportion of the groundnut crop is crushed for oil, soybeans are consumed without prior oil extraction. In view of the situation described, it is likely that coconut, palm oil, and other oil bearing crops continued to be important to the oil and fats sector during the period of 1971 to 1980; the backward linkage indexes of the oil and fats sector were higher than other sectors, i.e., 0.8060; 0.8530; and 0.7960 for 1971, 1975, and 1980 respectively. Therefore, the development of oil and fats sector cannot be separated from the upstream sectors that produce raw materials. 55 The handpounding of rice sector shows a high backward linkage index for each of the three years of analysis: 0.7980 for 1971; 0.7929 for 1975; and 0.7810 for 1980. According to the 1971, 1975, and 1980 input-output tables, this sector was mainly affected by three other sectors of economy, paddy, trade, and financial services. ‘ The handpounding of rice appeared to be driven in an integral part of paddy sector by absorbing paddy to be processed. At present, there are three rice processing techniques used in Indonesia: handpounding of rice; small rice mills; and large rice mills (Timmer, 1984). Handpounding of paddy with a mortar and pestle was probably the earliest form of rice milling in Indonesia. The small rice mills can be thought of as ranging from the now obsolete double Engelberg - type huller/polisher combinations to the smaller self - contained Japanese rice milling units. 0n the other hand, the major feature of the large rice mills is the combined use of mechanical and sun drying with modern milling equipment, either Japanese - type or conventional multi—stage. Handpounding, the traditional technique, has declined drastically in recent years. According to Mears (1981), a rapid shift from handpounding came about with the arrival of small mills that could be economically located near Villages. It is clear that there are circumstances in which handpounding is not desirable in some areas because its productivity is lower than that of rice mills. The 1971, 1975, and 1980 Indonesian input-output tables, however, show that handpounding has a high backward linkage index. This 56 means that handpounding activities tie in well with the agro-industry sectors that supply inputs to the handpounding sector. The paddy sector is, of course, the key sector in terms of supplying raw material to the handpounding sector. Because of this, the existance of handpounding sector activities does not depend solely on its productivity but its raw material supply as well. On the other hand, both the trade and financial service sectors have significant contributions to handpounding activities. The organization and structure of both paddy and rice markets have changed since the Indonesia government established KUD (KOperasi Unit Desa or Village Cooperative Center). From the perspective of the national rice market, KUD has the particular task of stimulating cooperative development and helping insure high farm prices. The cooperatives were given subsidized credit for purchasing paddy from the farmers and were paid preferential prices by the government for their paddy and milled rice. The wheat flour and products sector is the fourth agro~ industry sector that shows a high backward linkage index for the years analyzed. Despite the relatively small quantities in which it is consumed, wheat flour is an important commodity in Indonesia (Timmer, 1971). This is because the total supply of wheat flour, all of which is channeled through the central government, is derivable from aid terms ranging from grants to loans. The availability of wheat flour, all of which comes , from abroad, cannot be isolated from its consumption. As 57 noted by Magiera (1981), sharply increasing wheat imports have led to a rapid expansion of the Indonesian processing industry over the past decade. Such firms manufacture bread, cakes and the wide range of snacks consumed in Indonesia. The wheat flour and products sector generates a high backward linkage index. This is because of wheat flour’s use as an ingredient combined with other agricultural products in order to produce a wide range of snacks. The fifth agro-industry sector that shows a high backward linkage index in the years of analysis is the food processing and preserving sector. There are many agro- industry sectors involved in the food processing and preserving sector. Of particular importance are those sectors from which raw materials are supplied. These include, for example fisheries, fruit and vegetable farming, and slaughtering. In addition, the internal trade sector supports the continuity of the processing and preserving food sector. The main task of the internal trade sector is to sustain the delivery of raw materials from farms to processing and preserving operations. Fish, which is a major source of protein in Indonesia, is one of the raw materials that the processing and preserving food sector uses. The escalation of development of aquaculture, as described by Neal and Smith (1982), was basically motivated by the need to produce additional fish protein to meet demands of the rapidly increasing population. 58 It is important to note that many agricultural products, such as fruits and vegetables, are still processed in traditional ways. This is primarily because of a high cost marketing system, a lack of processing knowledge, and a lack of storage facilities. The food products not elsewhere classified sector is the sixth agro-industry sector that shows a high backward linkage index in the 1971, 1975, and 1980 input-output tables. This sector consists of tea processing, cocoa, coffee grinding, chocolate, and sugar confectionery, soybean products, and others. According to Singh (1977), a basic attribute of many of the craps processed in this sector is the high capital costs of establishing new plantings. Among recurrent costs, labor costs predominate because both cultivation and harvesting are highly labor intensive. Tea processing is a significant part of the food products not elsewhere classified sector in the 1971, 1975, and 1980 input-output tables. Although the best teas produced in the country are exported, Indonesian teas are considered to be of inferior quality in the world market. The quality of tea produced by a given factory is subject to both exogenous and endogenous influences. The exogenous factors, over which producers have little control, include climate, soils, slope, and land elevation. Endogenous factors include the choice of clones or seedlings, the fertilizers applied, disease control, the plucking procedures adopted, the technique of transporting the delicate leaves to the factory, and methods of manufacture. 59 In addition to the export market, Indonesia, unlike some other major exporting countries, such as Sri Lanka and East Africa countries, has a very large domestic market. The country has a large population, and the habit of tea drinking in widespread. The final agro-industry sector that has a high backward linkage index for the years 1971, 1975, and 1980 is the spinning industries sector. This sector consists of several industries such as cotton yarn, silk yarn, sisal yarn, coconut yarn, regenerated cellulose rayon, and threads. Cotton yarn industries are the focus of this backward linkage analysis because, as noted by Boucherie (1969), Indonesia's raw cotton requirements are met almost entirely by imports. The lack of raw cotton, together with the low capacity of utilization, results in sales and profit performance that does not permit the buying of spare parts, much less the purchase of large pieces of machinery to increase production. In terms of prospective demand for textiles in Indonesia, traders, including those not in the import business, argue that even an increase in the per capita income of the lower income groups would result in little increase of sales of domestic products at existing prices and quality (Boucherie, 1969). In contrast, the 1971, 1975, and 1980 input-output tables show that the spinning industries sector, to which cotton yarn industries provide a significant contribution, has a high backward linkage. This means that the development of spinning industries and the increasing consumption of textiles 80 occurred simultaneously. That is, the improvement of domestic products quality was achieved at prices affordable by consumers. FORWARD LINKAGE ANALYSIS Having determined the backward linkage index of each agro-industry sector, I now turn to the forward linkage index. Table 4.2 summarizes data from Appendix 1: Tables 11, 12, and 13, which depict the forward linkage index for each agro-industry sector and its rank for the years 1971, 1975 and 1980. The table shows that there are seven agro- industry sectors with forward linkage indexes in the top 10 for the years 1971, 1975, and 1980. These are (1) the paddy sector; (2) the other farm food crops sector such as peanuts and soybeans; (3) the cloves sector; (4) the other crops sector such as cotton and cocoa; (5) the livestock sector; (8) the spinning industries sector; and (7) the rubber products sector. One of the purposes of this study is to analyze each agro-industry sector that has a high forward linkage index. This analysis is critical in order to evaluate and determine agro-industry development at national level. The Indonesian input-output table for the years 1971 and 1980 clearly show that paddy sector generates the highest forward linkage index compared with other sectors, i.e., 0.9999 and 0.9872 respectively. However, in 1975, the paddy sector shows a forward linkage index of 1.0000 which means that the entire sector's output is equal to the sum of its 61 intermediate demand and its final demand. This is always true in a demand—driven model but not in a supply-driven model. The downstream sectors that are determined by the paddy sector activity are varied and include not only farm activities, such as handpounding rice, rice milling and livestock, but also paper and paper products. For human consumption availability, paddy has to be processed, which .consists of separating the grain from the husk and polishing the grains. According to input-output data analyzed in this study, handpounding and rice milling are the two sectors that the output of paddy sector mainly flows into. These sectors are the main downstream sectors needed in order to support the supply of rice for national consumption. Conceptually, the economic demand for rice depends on the tastes of consumers, their incomes, the price of rice, the price of substitutes and complements goods, and the population. According to the Weitz-Hettelsater Engineers (1972), these factors take on different values in different parts of Indonesia and change continuously over time. Precise estimation of the aggregate demand function for rice is impossible given the data available. It is necessary, therefore, to rely heavily on population growth rates, past consumption trends, and the few empirical observations and studies. With the vast majority of Indonesians still depending on rice as a basic necessary foodstuff, it remains the most important agricultural product of the Indonesian economy. 62 Table 4.2 Agro-industry Sectors With Forward Linkage Coefficient iju / Z, above 0.5 for 1971, 1975, and 1980 in Indonesia. 1971 1975 1980 CODE* COEFFICIENT RANK COEFFICIENT RANK COEFFICIENT RANK % 0.9999 1 1.0000 2 0.9672 1 3 ._ _ _ .. 4 _ — _ _. .. _ 5 .. _ - .. .. _ 6 0.5656 10 0.5966 6 0.5797 10 7 ._ .. _ _ .. _ 8 0.7549 7 0.5148 11 0.7446 6 9 0.6609 6 0.5831 9 0.5220 11 10 - - - — - - 11 0.5309 11 0.6061 4 0.7661 .6 12 - - - - - — 13 - - - - — - 14 0.9960 2 0.9958 3 0.9559 2 15 ~ - - ~ — ~ 16 - - - - — - 17 0.6745 5 0.7707 7 0.6369 5 16 0.7920 6 1.0076 1 0.6692 .. 4 19 - - - - — - 20 - - - - - 23 - - _ - 27 - - - - - - 26 - - - — - - 29 - — - - 0.9545 3 30 - - 0.5240 10 - - 31 - - - - - 32 - - - - - - 33 0.6531 9 - — - - 34 _ - _ _ _ - 35 0.9464 3 0.6039 5 0.7617 7 36 .. _ .. _ .. .. 42 0.9099 4 0.7671 6 0.7102 9 Source: Summary of Appendix 1: Tables 11, 12, and 13. * Sector description is the same as sector description in Appendix 1: Table 1. - Value is less than 0.5. 83 There is general recognition that the population in Indonesia was growing at an increasing rate during the period under analysis. With this growth, the number of persons who need rice as a basic necessary foodstuff also increases. As noted by the Mears (1981), among the starchy staples, rice is an important source of calories. The dietary proportion of calories supplied by rice rose to 74 percent in 1972 and averaged above 70 percent from 1988 to 1977. The absolute total of rice calories available for the average diet increased from 981 per day in 1988 to 1,232 in 1973. In view of these facts, it should be possible to depict the significant forward linkage of paddy sector with those sectors in which paddy is processed. In short, the implication of a growing population, which requires rice as the main source of calories, is that paddy processing sectors are very useful in terms of producing rice for domestic supply. The 1971, 1975, and 1980 Indonesian input- output tables illustrate this kind of implication. The livestock sector and the poultry sector are other downstream sectors to which the output of the paddy sector activity moves. The main sub-sectors of the livestock sector are cattle raising, milk cow raising, and other livestock raising (water buffalo, goats, sheep, swine, and horses). The poultry sector contains sub-sectors such as chickens, ducks, and geese. In the years 1971, 1975, and 1980, all these sub-sectors contributed to the paddy sector in terms of demanding inputs from paddy sector activity. 64 According to Weitz~Hettlesater Engineers (1972), rice bran and polishings are sometimes used in feed for poultry, dairy cattle, and hogs together with corn meal, soybean meal, oil cake meal, and other products. In addition, poultry are often herded into the stubble of the harvested fields to pick up the leftover grains. Other sectors that have significant linkages on paddy sector activity are the paper products and printing sector and the trade sector. These sectors have different attributes in terms of absorbing paddy sector output. The paper products and printing sector requires paddy stalk as raw material in producing pulp, printing paper, cardboard, boxes, paperbags, etc. The internal trade sector deals with the distribution of paddy from farmegate to the places where it needed. In general, rice distribution flows from the farmer's house through local assembly points, regional assembly points and finally to terminal distributors, wholesalers, and retailers (Mears, 1981). The rice distribution involves not only private enterprises but also government involvement. According to Weitz-Hettelsater Engineers (1972), the Government of Indonesia has been involved in the rice trade for many years by establishing BULOG (Badan Urusan Logistik, the National Food Stock Authority). BULOG's administrative structure extends up to the President of Indonesia with one of its tasks being to stabilize prices by withdrawing rice from the market when and where prices are low and returning these quantities of rice to the market when and where prices are high. 85 The cloves sector is another of the agro-industry sectors that had a high forward linkage index for the years 1971, 1975, and 1980. According to Gwyer (1976), Indonesia occupies a unique position in the market for cloves, being the largest producer, consumer and importer of this spice. The main end use of cloves is in the manufacture of "kretek" cigarettes. "Kretek" cigarette smoking appears to be a habit unique to Indonesia and is especially popular in Java. The practice started at the end of the last century in the small town of Kudus in Central Java where smokers began to mix cloves with tobacco in their handrolled cigarettes (Castles, 1965). The new product, called "kretek" because of the crackling noise it makes as it burns, became popular throughout much of Indonesia. It should be noted that, to the extent that the principal end use for cloves is in the manufacture of "kretek" cigarettes, the supply of cloves is. largely absorbed by "kretek" cigarettes industries. This implies that cloves' forward linkage index will be high. One way to look at the cloves’ forward linkage is to consider this sector on the basis of national cigarette production. According to Gwyer (1976), the production of ”kretek“ cigarettes has increased rapidly from 13 billion units in 1989 to more than 29 billion units in 1973. That is, the high forward linkage index of the cloves sector is maintained parallel to the manufacturing of "kretek" cigarettes development. 66 _ Another agro-industry sector that generates a high forward linkage index is the livestock sector. This sector consists of the raising cattle, water buffalo, goat, sheep, swine, etc. with the primary objective of supplying the domestic demand for meat through the slaughtering sector. The domestic demand for meat and meat products has been rising steeply in urban areas where annual per capita consumption, now estimated at around 3.3 kg, is growing at 8 percent a year (Leake, 1980). In rural areas, by contrast, consumption per capita is estimated at around 1.5 kg per year, with demanding growing at only about 4 percent a year. Thus, it is: clear that there is'a high forward linkage of the livestock sector as a result of the increasing demand for fresh meat as well as other uses of livestock such as transportation, source of traction, and manure. Leake (1980) notes that beef marketing is likely to continue to take its traditional form of live transport from rural areas to urban slaughter houses for immediate sales of fresh meat. Of course, these two downstream activities of livestock sector (i.e. supply of meat and transportation) will be required in order to fulfill needs of Indonesian as its population increases. To determine optimal development strategies for the agro-industry sector, however,. it necessary to consider another factor beyond just backward and forward linkages. The backward and forward linkages alone do not provide adequate guidelines to appropriate agro-industry development strategies. This is because backward and forward linkages 67 are concerned mainly with a sector’s mutual linkages to other sectors, that is, with exogenous linkages, in terms of both demanding inputs and producing outputs. There are also endogenous linkages in each agro—industry sector in which the production activity cannot be separated from the consideration of technology use and its consequences. ANALYSIS OF APPROPRIATE AGRO-INDUSTRY The usual orientation in evaluating appropriate development strategies for agro-industry is to acknowledge both backward and forward linkages. Although these acknowledgements have been important, and continue to be crucial, this orientation does not provide a comprehensive analysis of technologies in terms of employment generation effects and value added. According to Choi and Lee (1983), the concept of appropriate technology means employing the technologies that are aimed at employment generation, regional development and the deveIOpment of resources. In the case of efficiency, as noted by Robinson (1979), an appropriate technology shall be an efficient technology, and at the same time one which fully reflects the abundance or scarcity of particular resources in the composition of the necessary inputs, substituting, for example, more direct labor where desirable for capital within a given total cost in an economy in which labor is plentiful and capital is scarce. Appropriate employment analysis varies greatly among economists. Breyev (1972) describes input-output analysis 68 as a major tool of labor analysis and planning. The main question posed here is what are the advantages of analyzing the Indonesian input-output tables for 1971, 1975, and 1980 in terms of appropriate agro-industry and its effect on domestic employment. As noted by Diamond and Chappelle (1981), a very important use of input-output analysis is to develop multipliers, e.g. income multipliers, employment multipliers, and output multipliers. Employment multipliers are often included in regional analysis to evaluate impacts on employment of industrial expansion. However, according to Chappelle et al. (1988), multipliers do not reflect comparative advantage or opportunities for expansion in various industrial sectors. ‘ Since the majority of the Indonesian population still depends on agriculture, which covers a huge array of crops, products, and techniques, the agricultural sector will remain the major sector of the Indonesian economy. Therefore, when the government is concerned with agricultural development, it is necessary to aim at creating as many employment opportunities as possible in the agro— industry sector. Hoyle (1974) states that relationships between agriculture and industry have occupied a good deal of attention and represent another kind of continuum; the two sectors have sometimes been thought of as mutually exclusive, and many have argued that industrial expansion offers the fastest - road towards a higher level of development. It is evident from what we have said that it is essential that the agro-industry sectors promoted for 69 economic development be those that provide for the most rapid growth of the national economy. As noted by Johnston and Kilby (1975), because agriculture is both the largest and the slowest growing sector of an underdeveloped economy, the optimal net flow of resources will, over the long run, be from agriculture to those sectors where the growth potential and returns on investment are higher. This implies that it is extremely important that comparative advantage analysis of each agro-industry sector be conducted before advocating changes in the national economic structure. Table 4.3 summarizes value added - labor ratios (total and direct requirements) for final demand of 32 agro- industry sectors in 1971. In fact, these value added - labor ratios are closely related to national employment. This is because Indonesian employment has a unique character in that labor is abundant and normally available throughout the whole year. To keep track of the national employment base it is necessary that value added - labor ratios be compared with the ratio of available to employed labor at at national level. These comparisons depict the capacity of each agro-industry sector in terms of generating value- added in which its labor requirement does not exceed the ratio of available to employed labor at the national level. In the case of appropriate technology for agro-industry sectors, the consideration of both value added - labor ratios and the ratio of available to employed labor at the 70 Table 4.3 Value-Added - Labor Ratios (Total and Direct Requirements) for Final Demand by Thirty-Two Agro-Industry Sectors, 1971. CODE* TOTAL RANK DIRECT RANK 1 0 0554 25 0.0576 25 2 0 0451 28 0.0445 26 3 0 0339 30 0.0328 28 4 0.0134 32 0.0132 30 5 0.0229 31 0.0221 29 6 0.0386 29 0.0375 27 7 0.1255 16 0.2498 12 8 0.1578 13 0.1869 17 9 0.2238 8 0.2200 15 10 0.3209 7 0 7118 10 11 0.0752 22 0 1182 21 12 0.1883 11 0 2418 13 13 0.1370 15 0.1401 20 14 0.5331 2 0.7549 14 15 0.3583 5 0 3656 8 16 0.1901 10 0 1931 16 17 0.2006 9 0 2298 14 18 0.1613 12 0.1547 19 19 0.4612 3 1.1558 3 20 0.9655 1 4 8319 1 23 0.1230 17 0.2849 9 27 0.0697 24 0.0070 32 28 0.1419 14 0 2570 11 29 0.0532 26 0 2829 10 30 0.0969 20 0 1154 .22 31 0.1181 18 1 7097 2 32 0.0497 27 0.1656 18 33 0.3376 8 0.7396 5 34 0.1112 19 0.0019 31 35 0.0873 21 0.0911 24 38 0.0728 23 0.0941 23 42 0.4112 4 0.6383 7 Source: Summary of Appendix 1: Tables 14 and 17. * Sector description is the same as sector description in Appendix 1: Table 1. 71 national level should be integrated with the backward and forward linkage indexes for each agro-industry sector. Figure 4.1 shows these relationships agro-industries for that satisfy the value added - labor ratios requirement 600 5.004 4.00« 3.004 2.00:-1 L0 0 P 1.00- a 20 Total V—L ratio o 00 C '3‘ ‘ 1 I I ' I r l fir I ' o 0.00 1.00 W 2.00 .100 4.00 5.00 6.00 Direct V-L ratio Figure 4.1 Total V-L Ratios and Direct V-L Ratios for Selecting Appropriate Agro-Industries in 1971. and their ratios of available labor to employed labor at national level. Figure 4.1 is constructed from data in Table 4.3 which summarizes value added - labor ratios (total and direct requirements) in 1971 and a calculation of available to employed labor ratio at the national level in 1971. The lines 0C and OD depict the average ratio of available to employed labor at the national level (1.4899) as an estimation of the optimum level of economic activities 72 to absorb labor at the national level. This means that in order to satisfy a unit increase in final demand and to fulfill the total (direct and undirect) and direct value added and labor requirements, the utilization of labor in economic activities at national level cannot exceed the above estimation. From Figure 4.3, it is clear that only two agro industry sectors have higher value added - labor ratios than the value added - labor ratio requirements, i.e., the poultry and poultry products sector and “the sugar refining sector. At this point it may be important to compare the 1971 input-output data with the data for the years, 1975 and 1980. By adapting the framework of analysis used for 1971 input-output data, Figure 4.4, which based on Table 4.4, and Figure 4.5, which based on Table 4.5, show circumstances in which agro-industry sectors do not satisfy the value added — labor ratio requirement for 1975 and 1980 respectively. In 1975, only one agro-industry sector, the cigarettes sector, can be classified as an agro-industry sector where the value added - labor ratio is higher than the available to employed labor ratio (1.4313, lines 0C and 00). On the other hand, in the 1980 data, there are six agro-industry sectors that have value added - labor ratios higher than their available to employed labor ratios (1.3928, lines 0C and OD): the rubber sector; the processing and preserving food sector; the sugar refining sector; beverage industries sector; the cigarettes sector; and the rubber products sector. Table 4.4 Value-Added - Labor Ratios (Total and Direct Requirements) for Final Demand by'ThirtyJTwo Agro-Industry Sectors, 1975. CODE* TOTAL RANK DIRECT RANK 1 0.0823 25 0.1385 27 2 0.0508 28 0.0814 29 3 0.0590 26 0.0812 32 4 0.0712 23 0.0894 28 5 0.0535 27 0.0668 31 6 0.0885 24 0.0718 30 7 0.3845 11 0.4238 18 8 0.1760 19 0.4388 11 9 0.2928 13 0.4198 18 10 0.1741 20 0.4289 12 11 0.0005 31 0.4251 14 12 0.4188 8 0.4251 15 13 0.4212 7 0.4255 13 14 0.4381 4 0.4203 17 15 0.4146 9 0.4187 19 16 0.4124 10 0.4135 20 17 0.2682 15 0.4028 21 18 0.0028 30 0.4581 8 19 0.0005 32 0.4519 9 20 0.4260 8 0.4490 10 23 0.3690 12 0.4598 7 27 0.4349 5 0.5936 5 28 0.1985 18 0.3405 24 29 0.0303 29 0.3817 22 30 0.2174 17 0.5768 8 31 0.8875 3 1.3413 2 32 0.2765 14 0.3778 23 33 0.9428 2 1.3268 3 34 2.6074 1 2.6894 1 35 0.1880 21 0.2570 25 36 0.0845 22 0.1861 28 42 0.2555 18 0.9639 4 Source: Summary of Appendix 1: Tables 15 and 18. * Sector description is the same as sector description in Appendix 1: Table 1. 74 600 iflfi 4.00- iMh Total V-L ratio 3: 2.00-1 I.“ D LooJ . 0.00—'..°,.1.,.r. o 0.00 1.00 W 2.00 3.00 4.00 500 5.00 Direct V—L ratio Figure 4.2 Total V-L Ratios and Direct V-L Ratios for Selecting Appropriate Agro—Industries in 1975. Table 4.5 Value-Added - Labor Ratios (Total and Direct Requirements) for Final Demand by Thirty-Two Agro~Industry Sectors, 1980. OODE* TOTAL RANK DIRECT RANK - 1 0.3800 28 0.3194 27 2 0.2937 29 0.2783 28 3 1.2103 9 0.1211 32 4 0.1994 31 0.1939 30 5 0.1524 32 0.1479 31 8 0.2118 30 0.1940 29 7 1.4281 5 1.4404 8 8 0.8809 23 0.8383 23 9 0.9621 17 0.9533 18 10 1.0118 15 0.9945 14 11 0.4752 28 0.4367 25 12 1.0907 12 1.0930 12 13 1.0397 13 1.0388 13 14 1.2418 8 1.1821 9 15 0.8887 22 0.8864 21 18 0.8935 20 0.8918 19 17 1.1851 10 1.1946 8 18 1.0062 16 1.3294 'Z 19 0.5615 24 0.5242 24 20 1.3304 6 0.9793 15 23 0.9513 19 0.9398 17 27 1.5224 3 1.5574 4 28 1.0953 11 1.1024 11 29 1.0304 14 1.1071 10 30 0.8872 21 0.8887 20 31 1.4769 4 1.4915 5 32 0.9588 18 0.8597 22 33 2.6553 2 2.8120 3 34 4.8175 1 5.2468 1 35 0.5255 25 0.9298 18 36 0.4313 27 0.4066 26 42 1.3125 7 4.6465 2 Source: Summary of Appendix 1: Tables 16 and 19. * Sector description is the same as sector description in Appendix 1: Table 1. 76 6N} 5NE :- 4.00-q a. Total V-L ratio 0 331,, ‘3. fi' 12 1.00- .4 a”. ' C 0.00 I l l I l 0 000 1.00“ 2.00 300 4.00 5.00 6.00 Direct V-L' ratio Figure 4.3 Total V-L Ratios and Direct V-L Ratios for Selecting Appropriate Agra-Industries in 1980 77 The 1971, 1975, and 1980 input-output tables for Indonesia show that only seven of 32 agro-industry sectors can be classified as appropriate agro-industry sectors in terms of value added — labor ratio requirements, backward and forward linkage indexes. These are: (1) the spinning industries sector; (2) the rice milling, cleaning, and polishing sector; (3) the wheat flour and products sector; (4) the rubber products sector; (5) the sugar cane and brown sugar sector; (6) the tobacco leaves and processing sector; and (7) the beverages industries sector. The spinning industries sector is the only sector out of these seven agro-industry sectors that shows a significant economic impact in terms of appropriate agro-industry to the Indonesian economy in the all years examined (1971, 1975, and 1980). The other six agro-industry sectors appear have fluctuating impacts on Indonesian economy. For example, in 1980 analysis, the rice milling, cleaning, and polishing sector shows a higher ranking in terms of appr0priateness than in the 1971 and 1975 analysis. As noted above, the spinning industries sector can be categorized as an appropriate agro-industry sector for 1971, 1975, and 1980. A reason for this is provided by Grant (1984) who mentions that over the last 15 years, the growth rate of Gross Domestic Product (GDP) in industry as a whole has been around 10 percent. The textiles industry constitutes about 13 percent of this growth, and those involved with the industry think of it as being the spearhead of the whole industrialization process. This confidence in the 78 importance of textiles comes as a result of the labor intensive nature of the industry and because textiles are beginning to become a major foreign exchange earner. Also, until around 1976, garment making was very much a home industry with just a few old—fashioned machines, but since then exports have been increasing and the industry is booming. Although the textile industry output is increasing in order to fulfill export requirements there is a serious problem in the international trade of textiles. Arndt (1975) points out that the textile industry continued to demand more protection from import competition. This problem stems primarily from the fact that although quality is comparable, in terms of output Indonesian textiles still lags behind. In deciding on economic development strategies in the textile industry in which most of the raw material comes from the spinning industry, it is necessary to consider international trade circumstances. Determination of appropriate agro-industry development tasks cannot proceed without examining the international trade links. The rice milling, cleaning, and polishing sector is another agro-industry sector that can be classified as appropriate for the 1971, 1975 and 1980 analyses. A clear understanding of the relationships between rice production and its processing is essential to understanding the economic impact analysis of rice processing. There is no doubt that Indonesian rice production is processed domestically and that rice milling, cleaning, and polishing 79 sector is an agro-industry sector which is characterized by raw material dependence primarily on the total quantity of national production. According to Hears (1981), during the period of 1968 - 1978, total rice production in Java expanded at an average rate of 3.6 percent a year and outside Java eXpanded at 4.1 percent a year. Since the advantage of both private and government rice milling is to absorb the total national production of rice, then it stands to reason that there must be an increase in the number of rice mills parallel with the increase in total rice production. As noted by McCawley and Tait (1979), much of the expansion in the food sector between 1970 and 1973 was due to a rapid increase in employment recorded in rice milling, and it was during this period that the number of rice mills increased rapidly. The wheat flour and products sector is one of the seven agro-industry sectors that became an important element of the Indonesian government's food stabilization program. According to Magiera (1981), per capita flour consumption rose from 3.3 kg a year in 1988 to 5.6 kg a year in 1977; most of the wheat flour is consumed in some processed form such as bread, biscuits, noodles, and cake. Wheat is not produced in Indonesia, and wheat imports continued to increase during the 19705. During this period, there were two significant changes in the way in which wheat was imported. One of these changes came after the establishment of three wheat flour mills in 1971 and 1972. Thereafter, only small quantities of wheat flour were imported as 80 Indonesia switched almost entirely to grain imports. This implies that the Indonesian government was attempting to increase the value added of grain imports and to increase employment opportunities through the milling industry. In addition, wheat bran, the major by-product of the milling industry and an important source of profits, is sold as animal feed in Indonesia and is exported, primarily to Singapore and to the European Community. Thus, the role of the wheat flour and products sector has been not only to provide an alternative to other staple rfoods produced in the country, but also to provide additional employment opportunities. This is important in determining whether or not the wheat flour and products sector should be expanded in the future. Although the sugar cane and brown sugar sector can be classified as an appropriate agro-industry sector in this study, it should be recognized that sugar production and its consumption in Indonesia. According to Arndt (1975), despite a very rapid rise in domestic sugar production in recent years, at an average annual rate over 9 percent since 1970, sugar has had to be imported in the past two years at a government subsidized price. Expansion of sugar production in Java is hampered by the competing demands on land to produce rice. In 1971, the Indonesian government Sponsored the Indonesia Sugar Study (de Boer, 1978). On the basis of this study, the government launched a rehabilitation program design to achieve sugar self-sufficiency in 1982. However. 81 after recovering rapidly from the low levels of the mid- 19605, sugar production peaked in 1979, following land area expansion. Yields fell with the introduction of the TRI (Tebu Rakyat Intensifikasi), a program of conversion from estate to smallholder production, and declined in 1980, while sugar consumption has continued to rise rapidly (Arndt, 1981). In regard to declining sugar yields, Mubyarto (1977) noted that the sugar industry may present old and new problems. The major old problem that remains is that unless farmers are assured of a reasonable price for their sugar from the mills, or are permitted to sell their sugar in a free market, they will continue, as in the past, to prefer to grow rice rather than sugar. 0n the other hand, the main new problem is that yields may decline as a result of the change from estate to smallholder cultivation. Another new problem is the near impossibility of efficiently managing literally thousands of small plots of land in commercial cane growing; since consolidation among farmers is so difficult, the rich farmers or private companies are now taking over the role of the mills, renting the land from the small farmers and to dealing with the mill. The other three agro-industry sectors that are classified as appropriate for the 1971, 1975 and 1980 analyses are the rubber product sector, the tobacco leaves and processing sector, and the beverages industry sector. These three industries have in common that their analysis must be based not only upon their production and consumption but also on international trade. It should be noted that to 82 the extent that agro-industry development is determined by its production, consumption, and international trade, the framework of analysis that was used for the first—four agro— industry sectors is applicable for the last three agro- industry sectors, including the historical development of agro-industry sector. STRUCTURAL CHANGES IN EMPLOYMENT Knowledge of economic impacts of the agro-industry sector can be very useful in guiding economic development efforts. One major concern of agro-industry impacts concerns changes in the employment structure generated by raw material flows from the agriculture sector to agro— oriented industries. According to Lewis (1954) and Hellor (1978), employment linkages involve derived demand for labor in the agricultural and industrial sectors. Employment opportunities induce migration of labor from the rural- agricultural to the urban-industrial sector. Furthermore, as noted by Bulmer-Thomas (1982), with industrial final demand growing rapidly, industry will be generating employment directly and indirectly not only in the industrial sector, but also in the primary and tertiary sectors. According to Soemantri (1982), primary industry is that section of industry that produces raw materials for the manufacturing industry. This includes agriculture, forestry, fishing, mining, and quarrying. Tertiary industry is that group of enterprises that produces all kinds of 83 Table 4.6 Total Persons Employed in Seven Agra-industry Sectors in 1971, 1975, and 1980. CODE*) 1971 1975 1980 (PERSONS) (PERSONS) (PERSONS) 8 131,673 116,313 261,287 11 234,736 134,538 347,755 29 115,015 493,318 547.061 30 39,019 71.604 122.321 33 9,320 16,314 21,121 35 84,172 102,807 122,073 42 6,643 18,021 . 24,462 Source: The 1971, 1975, and 1980 Indonesian InputrOutput Tflfles. *) Sector description is the same as sector description on Appmxfix:1: Tmbheln services with the purpose of increasing utilities of the goods produced for the ultimate consumers. Thus, it is extremely important that before the Indonesian government attempts to influence change in the agro-industrial structure, it should examine comparative employment change in each agro-industry. One objective of this comparison is to measure the contribution of each agro- industry in terms of labor utilization at any particular time. Table 4.6 summarizes employment growth in the appropriate agro-industrial sectors from the Indonesian Input—Output Tables for the years 1971, 1975, and 1980. It shows that employment shares changed significantly among appropriate agro-industry sectors in terms of both absolute numbers and percentages. There is a general recognition that among appropriate agro-industry sectors total persons 84 employed grows at an increasing rate from 1971 to 1980. The highest increasing rate (375.64 percent) is held by the rice milling, cleaning, and polishing sector (Code: 29) followed by the rubber products sector (Code: 42; 268.24 percent), the wheat flour and products sector (Code: 30; 213.29 percent), the beverages industries sector (Code: 33; 126.82 percent), the sugar cane and brown sugar products sector (Code: 8; 98.44 percent), the tobacco leaves and processing sector (Code: 11; 48.15 percent), and the spinning industries sector (Code 35; 45.03 percent). As noted above, the rice milling, cleaning, and polishing sector has played a major role in absorbing labor. That is, the rapid progress being made in expansion of rice mills means that more employment opportunities will be generated per unit of rice. The usual orientation in evaluating rice processing techniques in Indonesia is to focus on employment generation. A rapid shift from handpounding was accompanied the arrival of the small mills that could be economically located near villages (Nears, 1981). This is illustrated by the fact that in 1957 about 90 percent of production was hand pounded. By 1988 it was estimated that handpounding had declined to 80 percent. Then came a flood of over 35,000 small mills with the KUDs adding another 1,500 after 1973. A rough sample in 1979 suggested that only 8 percent of the crop was still being handpounded. As noted by Timmer (1984), although the employment potential of the entire rice economy -- production, harvesting, processing, transporting, 85 storing, selling ~- is enormous, the effect of the introduction of rice mills may have been to destroy jobs and distribution of income. It is true, as describe by Arndt and Sundrum (1980), that the introduction of high—yielding varieties and consequent changes in harvesting methods and of the replacement of handpounding by small rice hullers, was labor displacing. But there are also reasons to believe, though as yet there is little hard evidence, that the new technology is at least potentially labor absorbing because of the shorter growing period of new varieties. The point here, however, is that the introduction of rice milling should be seen not only from labor displacing point of view, but also from the point of view of its ability to create value added and jobs simultaneously in shorter activity time than the existing activity. This type of approach can be applied to other agro-industry sectors as well. From the perspective of this study, the impact of the introduction of rice mills should generate value-added and job Opportunities as quickly as possible. Given the above propositions, the task at hand is to discover the most efficient production techniques in national agro—industry sectors by focusing on the production period. Table 4.6 shows that the seven appropriate agro- industry sectors have similar basic attributes in terms of the production period in processing activities. These agro- industry sectors, which utilize new processing technology, may be characterized as producing outputs in shorter time 88 than the agricultural sector which depends heavily on the planting and harvest seasons. This implies that the time factor is the crucial consideration in producing outputs. In essence, the faster the agro-industry sectors operate, the more time can be saved by those who work in that agro- industry sector and the more time can be applied to other activities. Therefore, from the employee point of view, the agro-industry sectors provide additional opportunities for those who work in agro-industry activities to become involved in other jobs and engage in multiple activities in several different economic sectors (e.g. agriculture, trade, construction) each day. On the other hand, from the employer point of view, the agro-industry sectors create the most production techniques. This implies that the efficiency of production in terms of output for a given period of time can be increased in agro-industry activities. It is important that the agro-industry sectors selected for expansion be those from which the processing activities have a significant comparative advantage in terms of backward and forward linkages, value-added generated, labor absorption, and the timeliness of processing. This implies that one or more of the agro-industry sectors classified in this study as appropriate agro-industry sectors should be targeted by the government for expansion. The other agro-industry sectors should be targeted for contraction unless the government can provide incentives for expansion. lClilflEWITEEl 1?]?V13 THE FUTURE DEVELOPMENT OF AGED-INDUSTRY IN INDONESIA The national development base of Indonesia consists of a series of REPELITA (Rencana Pembangunan Lima Tahun or Five Year Development Plans), each of which has its own policy objectives. According to Robison (1988), the embodiment of the concept of progressively deepening the structure of manufacture is to be found in the policy objectives of the various REPELITA. REPELITA I: 1989 - 1974 Concentration on manufactures supporting agriculture and provision of basic needs. REPELITA II: 1974 - 1979 Concentration on the processing of raw materials to a higher stage of value added. REPELITA III: 1979 - 1984 Resource processing plus the establishment of capital goods (engineering) industries. REPELITA IV: 1984 - 1989 Resource processing, capital goods and the manufacture of technology. 87 88 The Government of Indonesia considers that REPELITA IV and REPELITA V, which emphasize industrial strength supported by a strong agricultural sector, as laying the foundations from which the Indonesian economy can "take off". From the purpose of this study, it is important to examine the past performance of the Indonesian economy in each REPELITA and the prospects for the agriculture sector, particularly as the main source of raw material for agro-industry sectors. Under the First Five Year Plan (1989 — 1974), the rate of growth of GDP in the first year was high at 7.0 percent per year. The sectors showing the highest rates of growth were mining, manufacturing industries, construction, trade, and banking (Nangkusuwondo, 1973). One feature of development during REPELITA I that should be noted is that the growth of the economy took place not only in the non- agricultural sectors mentioned above, but also in agricultural sectors. Agricultural growth between 1989 and 1971 was 4.9 percent. Since agriculture's share of the total GDP is almost 50 percent, the growth of agriculture has a major impact on the overall growth rate. Therefore, the relatively high growth rate of the GDP after 1968 was, to a large extent, due to the development of the agricultural sector. In 1979 Indonesia’s overall rate of growth of GDP fell to 4.9 percent. This compares unfavorably with the 8.8 percent growth in 1978. According to Herr (1980), it seems that this performance can be attributed to: (1) the 89 relatively tight monetary policy that accompanied the November 1978 devaluation; (2) the effect of the devaluation on business uncertainty; (3) the effect on inflationary expectations, both of consumers and producers; (4) a somewhat disappointing rice harvest in 1979; (5) the April 1979 increase in the domestic prices of petroleum products, and (8) the general economic slowdown among Indonesia's trading partners. There is no question that the Indonesian economy performed well in the first years of development planning. However, while in the first years of the plan the annual target of 7.5 percent growth in GDP was met or surpassed, in the 1982/1983 period, the growth in GDP was only 2 percent (Cooke, 1984). The main question posed here is will the performance of agriculture sector continues as the most important sector for agro-industry development in Indonesia? According to Cooke (1984), in 1989 agriculture made up 46.9 percent of GDP. In 1983 this figure was 29.3 percent, and it is estimated it will further decrease to 28.5 percent in 1989. From the perspective of this study, Indonesian agro- industry sectors have certain characteristics that distinguish them from other sectors of the economy. This distinction lies primarily in the fact that agro-industry activities involve processing agricultural outputs. The agricultural products that are required in the agro-industry sector are affected by many factors: (a) seasonal supply due 90 to weather conditions; (b) perishability of outputs, which requires appropriate storage facilities; (0) the availability of transport and communication infrastructure because of the wide geographic spread of farm activities; (d) seasonal prices variations following the seasonal harvest pattern; (e) institutional involvement to provide finance and credit needs; and (f) whether the commodity can be imported or exported. Another way to look at Indonesian agro-industry sectors is to consider them on the basis of the number of people typically involved. As noted by Chuta and Liedholm (1984), the evidence available from national censuses and various regional and rural surveys indicates that nonfarm activities provide an important source of primary rural employment in developing countries. In the vast majority of the eighteen developing countries, including Indonesia, one—fifth or more of the rural labor force is primarily engaged in nonfarm activities. According to Abey et al. (1981), the high rate of population growth (still around 2 percent in 1980) shown by the preliminary results of the 1980 Population Census re- emphasizes the importance of expanding employment opportunities in Indonesia. As in many developing countries, unemployment is a problem in both urban and rural areas, particularly among young people. As noted by the World Bank (1985), unemployment rates in 1977 — 1978 were three to four times higher in the urban than in the rural area. Within the urban area it was 8.7 percent for male and 91 4.64 percent for female, while in rural area the unemployment rates of male and female were 1.98 percent and 1.25 percent respectively. This figure, however, needs to be evaluated with the recognition that unemployment rates in Indonesia are fictional. The very definition of "employed" and the method used to calculate unemployment rates insure that unemployment will be grossly underestimated. For example, even though persons worked only a few hours a day, they are counted as employed. Even with the rapid growth experienced in non- agricultural sectors in recent years, there is still an urgent need to expand employment opportunities in agriculture as a means of coping with increasing population pressure. With the majority of Indonesians depending on the agriculture and agro-industry sectors for their living, these sectors continue to be important sectors in the Indonesian economy. Thus, in evaluating agro-industry sectors it is necessary to focus on raw material supply from the agriculture sector and on employment opportunities, but these alone do not provide a comprehensive prediction of agro-industry performance in the future. This can probably be better illustrated by the findings of this study in Chapter 4. For example, to consider an appropriate agro-industry sector for the year 1971, 1975, and 1980, the rubber products sector is a labor intensive agro-industry and a 92 major foreign exchange earner. In this study, the rubber products sector can be classified as an appropriate agro- industry sector in terms of value added - labor ratio requirements and backward and forward linkage indexes. At first glance, the figures are quite impressive, especially compared with other agro-industry sectors that are labor intensive but are not classified as appropriate agro— industry sectors, for example, the paddy sector and the cigarettes sector. The point here is that the rubber products sector cannot be separated from domestic rubber production and marketing. According to Montgomery (1978), although peninsular Malaysia exceeds Indonesia in estate rubber land area with over 800,000 hectares in 1972, Indonesia has the largest area under smallholder rubber in the world. Of the world total rubber estate area of 1.7 million hectares, Indonesia accounts for 29 percent; of the world total of 5.2 million hectares of smallholder rubber, Indonesia's share is 36 percent. Given this, the task at hand is to determine the best way to develop rubber production and its marketing in ways favorable to smallholder rubber. Collier and Nerdaja (1972) state that any attempt to improve the quality and increase the quantity of rubber exports in Indonesia must be concentrated primarily on the smallholders. If the farmers are going to increase their income from their rubber smallholdings in the future, they must rely on greatly increased yields. However, most rubber growers cannot 93 improve yields until they use improved clones or planting materials. It should be noted that the above example stresses that agro-industry sectors' outputs should be considered on the basis of raw material availability and number of people typically involved in supplying products for both domestic use and export. However, the importance of this study is the point that raw material availability and people's involvement are not the only concerns for agro-industry expansion or contraction in the future. There is another concern in such decisions in that prospects for the expansion of economic activity in the industrial countries remain uncertain and world prices of some of Indonesia's major exports have been receding (Arndt, 1977). Of course, concerns associated with either expansion or contraction of an agro-industry sector appear to be driven as part of the national economy. In economics, industrialization and growth are considered from four perspectives in order to increase production of a particular sector (Chenery, 1988). These are: (1) the expansion of domestic demand which includes the direct demand for one commodity plus the indirect effects on this sector of the expansion of domestic demand in other sectors; (2) export expansion or the total effect on output from one sector of increasing exports; (3) import substitution or the total effect on output from one sector of increasing the preportion of demand that is supplied from domestic 94 production; and (4) technological change or the total effect on one sector of changing input-output coefficients throughout the economy as wages and income level rise. Of these four factors, the one with the strongest basis in theory is domestic demand, for which generalized systems of Engel functions have been estimated in many countries. It is evident from what is stated above that expansion of domestic demand is a crucial factor in determining industrial expansion in which agro-industry is a part of the industrialization. From the domestic demand perspective, population growth is a major factor in determining output from a certain industry sector. Population growth implies that the domestic market will absorb a larger quantity of products of the agro-industry sectors. This does not mean, however, that the expansion or contraction of particular agro- industry sector can be evaluated in isolation from other domestic market factors such as consumer preferences, products quality, products price, and comparative advantage point of view. From the perspective of comparative advantage and development policy, Chenery (1979) notes that the modern version of the comparative cost doctrine is essentially a simplified form of static general equilibrium theory. The Optimum pattern of production and trade for a country is determined from a comparison of the opportunity cost of producing a given commodity with the price at which the 95 commodity can be imported or exported. In terms of value added, Robison (1988) states that exploiting comparative advantage in resource based, energy-intensive industries. capital investment was channelled into large projects that processed raw materials to a higher stage of value added for export and for domestic use. At this point, it is important to stress that trends in imports and exports are important to consider when looking at comparative advantage of agro- industry sectors. This study is concerned with the development of agro- industry sectors to determine whether expansion or contraction should be targeted by Indonesian government: As noted in the above discussion, the principal consideration of agro-industry development is essentially concerned with supplies of raw material, domestic demand, and trends in both imports and exports. Another way to look at agro- industry development is to learn from other countries' experience. A major lesson learned from the development experiences in Taiwan and Japan is that rice yield increases resulting from the adoption of improved technology were associated with simultaneous improvement over a period of at least half a century of applied technological research, infrastructure, and institutional innovations (Mears, 1970). Although these experiences reflect the success of rice production, nowadays agro-industrial development in Indonesia can also exercise these other approaches to increase agro-industry output. 96 In the case of agro-industrial improvement programs, therefore, the Indonesian government can normally expect that the above experiences will be implemented not only by government enterprise but private enterprise as well. First, applied technological research is necessary to maximize the output of processing activities, minimize losses, increase cost effectiveness, and satisfy consumer preferences. Second, a physical infrastructure of processing site (building), storage facilities, and transportation is required to achieve the potential productivity determined by research. Third, institutional innovations are essential to extend research results to processors at the site of processing activities, to consolidate the products and their marketing, and to finance the dissemination of new technology of processing. With this in mind, the seven appropriate agro-industry sectors determined in this study for the years 1971, 1975 and 1980 can be expanded as appropriate agro-industry sectors as long as the value added - labor ratio requirement is satisfied, both backward and forward linkage indexes are high, and the three factors discussed above, i.e., technological research, infrastructure, and institutional innovations, are maintained. If these factors are provided to the other agro-industry sectors in the same proportion in terms of government involvement, agro-industry development will be beneficial not only as sources of national products but as sources of individual income as well. 97 Another important consideration, as noted by Todaro (1971), concerns the institutional structure of the economy and the relative roles envisaged for the public and private sectors in the develooment process. Political stability, for example, is obviously a very important non-economic consideration. In Indonesia development programs, it is necessary for the Indonesian government to maintain political and social stability in order to attract both domestic and foreign investment as sources of funding which contribute to the expansion of national economy. (ZIIAHEWFIEEI £3138: SUMMARY, CONCLUSIONS AND RECONMENDATIONS SUMMARY A major responsibility of the Indonesian government is to achieve and stabilize food self-sufficiency throughout the country at a price that is affordable by the Indonesian people. This task includes development of the agriculture sector as a raw material supplier as well as the agro- industry sectors necessary for processing raw materials to fulfill domestic consumption and export needs. Over the past 20 years, the agro-industry sectors of the Indonesian economy have been a national concern to sustain economic development. This concern has spurred Indonesian government efforts to provide for revitalization of the national economy through a target Five Year Development Plan (REPELITA). The agro‘industry plan has included efforts at the national level not only in encouraging industries converting agricultural raw materials into industrial raw materials, but also in encouraging industries converting raw materials into finished goods. Indonesian government efforts targeting the agro- industry program are distinct. Achievement of the program 98 99 depends upon the identification of specific sections of targeted agro-industry sectors likely to advance important Indonesian development goals. Of particular significance is the generation of both more value added and more employment opportunities in Indonesia. In addition, the evaluation of both backward and forward linkages of each agro-industry sector to the national economy plays a major role in the evaluation of agro-industry development. To evaluate agro- industry sectors of the Indonesian economy it is necessary to correctly measure the economic impacts of agro-industry changes in the national economy by looking at the appropriateness factors, i.e., value added - labor ratio requirements, and backward and forward linkages. The approach taken in this study is to examine the appropriateness of agro-industry sectors with the goal of determining sectors that should be targeted by the government for expansion or contraction. Using data from the Indonesian input-output tables of 1971, 1975, and 1980, it was found that only seven of 32 Indonesian agro-industry sectors can be categorized as appropriate. These are the spinning industries sector, the wheat flour and products sector, the rubber product sector, the sugar cane and brown sugar sector, the rice milling, cleaning, and polishing sector, the tobacco leaves and processing sector, and the beverages industries sector. In terms of economic impact analysis these seven agro-industry sectors should be expanded by the Indonesian government. It 100 appears that the other agro-industry sectors were inappropriate in the years of analysis and should be contracted. This does not mean the other agro—industry sectors currently operating in Indonesia must be curtailed. It is possible to improve the inappropriate agro-industry sectors through a modification of the current development program by providing incentives or subsidizing business expansion. At this point it may be important to stress that there are important analytical tasks where such research do have to place. For example, whenever one is trying to improve industrial targeting, such research which emphasizes value added and employment opportunities can be very useful. CONCLUSIONS Theoretically, it is possible to use many evaluation techniques in agro-industry economiC' impact analysis. The problem is that most economic impact analysis does not depict intersectoral dependencies wherein the flows of both input and output of each sector of the national economy are clearly defined. Therefore, to evaluate each agro-industry sector for the purpose of guiding economic development, it is necessary to examine the basic attributes of each agro- industry sector, especially its linkage to the agricultural sector as the main source of raw materials. The basic attributes of the various agro-industry sectors are diverse, and these basic attributes must be recognized in evaluating the economic development of 101 Indonesia. Differences in such characteristics as seasonal quantity due to agricultural product supply, storage facilities requirements, transport and communication infrastructure requirements, domestic and world prices fluctuation, and institutional involvement must be recognized in evaluating the agro-industry economy. Other factors in the agro-industry sector are the number of people involved in processing activities and the number of people needing agro-industry products. Essentially, these are the population factors in national development. The first population factor concerns the employment opportunities required to promote the optimum capacity of each agro-industry to utilize domestic labor. In this approach, value added - labor ratios are the main measurement in optimizing capacity of agro-industry activities. However, the generalized data systems maintained by the Indonesian Input-Output Tables of 1971, 1975, and 1980 are not adequate for the conduct of economic impact evaluation in agro-industry. There is serious deficiency in the data for labor supply by occupation and skill level from which the national employment distribution is derived. It is essential that these data be included in the analysis so that it will be possible to measure economic impacts of agro—industry development on employment distribution by occupation and skill level. The implication of this analysis is that the economic evaluation of agro- 102 industry sectors will fit within the national program of creating employment opportunities. The second population factor concerns domestic population growth, which implies that domestic demand expands with increasing population growth. The essential idea is that increasing population growth is peculiarly basic in the sense that it determines overall final demand. Final demand is an exogenous variable to be estimated in order to determine, through input-output analysis, the extent to which production levels of agro-industry sectors should be changed. Hence, it is clear that population growth in the economy does affect the evaluation of targeted agro-industry sectors. RECOMMENDATIONS It is recommended that the agro-industry sectors to be developed by the Indonesian government be evaluated in terms of value added - labor ratio requirements and both backward and forward linkages. The results of these basic factors of evaluation should be interconnected with the current development programs. The current development programs for the agro—industry sectors appear to have only one major orientation, that is, post-processing. However, the pre- processing development factors of agro—industry sectors are related to post—processing factors. This means that the pre—processing development factors of agro-industry sectors cannot be overlooked. 103 A general pre-processing orientation can focus on applied technological research, physical infrastructure, and institutional innovations in regard to basic attributes of each agro-industry sector. In the case of agro—industry enhancement or improvement programs, therefore, we Ican normally expect that growth in the national economy will increase to sustain many of its functions at higher contributions in value added when supporting activities such as applied technological research, infrastructure, and institutional innovations are made. Also, it is important that national political and social stability be maintained in order to stimulate agro-industry development through both domestic and foreign investments. Finally, it should be noted that this study stresses agro-industry performance and is based on appropriateness in terms of sector linkages and value added - labor requirements. However, it is very important that the labor supply by occupation and skill level be integrated into the analyses that are carried out to determine comprehensive strategies for agro-industry development. 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"arr, P. G "Survey of Recent Developments Summary - production - the rice crop- petroleum- balance of payments - monetary developments". WWW. Vol XVI, No. 3. Australian National University. November, 1980. Neitz—Hettelsater Engineers. Repuh11c_g£_lndgnesia.A Division of the Heitz Company, Inc. Kansas City, Missouri. October, 1972. Williamson, H. F. and 6’. Tait. "Regional Economic Models“. The W.V01.LVIL Number 2. Hay. 1968. APPENDICES APPENDIX 1. Table 1 Sixty-six Sector Classification for 1971, 1975, and 1980 Input-Output Table for Indonesia. Code Sector Description I.S.I.C Code 1. Paddy 1110-01 2. Handpounding of rice 3118-01 3. Maize 1110—02 4. Root crops 1110-03 5. Vegetables and fruits 1110-5 6. Other farm food crops 1110-6 7. Rubber 1110—10; 3552-01 8. Sugar cane and brown sugar 1110-11; 3118-01 9. Coconut 1110-12 10. Coconut and palm oil 1110-13; 3115-01 11. Tobacco leaves and processed 1110-15; 3140-01 12. Roasted coffee 1110-18; 3121-023 13. Tea leaves and farm.processed tea 1110-17; 3121-025 ‘ 14. Cloves 1110-18 15. Nutmeg 1110;19 16. Other spices 1110-20 17. Other crops 1110-14 18. Livestock 1110-22, 23, 24 19. Slaughtering 3111-01 20. Poultry and poultry products 1110-25 21. Logging and saw milling 1220-02; 3311-01 22. Other forest products 1220-1; 1220-2 23. Fisheries 1301-01; 1302-01; 3114-01 24. Coal and metal or mining 2100-01; 2301-01; 2302-01; 2302-02; 2302-03; 2302-04 25. Petroleum & natural gas mining 2200-1 28. Other quarrying 2901-01. 02. 03. 09 27. Processing & preserving of food 3111-02; 3112-01; 3113—01; 3114-01 28. Oils and fats 3115-01: 3115-02 29. Rice milling, cleaning and polishing 3116-01 30. Wheat flour and products 3116-2; 3117-01. 02 31. Sugar refining 3118'01 32. Food products not elsewhere classified 3119—01; 3121-01, 02, 03, 04 3131-01; 3132-01; 3133-01; 3134-01 3140-02 33. Beverage industries 34. Cigarettes 111 112 Table 1 (cont'd.) Code Sector Description I.S.I.C Code 35- Spinning'industries 3211-01; 3211-02 3211-03; 3211-04 36. Textiles, leather and wearing apparel 3212-01; 3213-01, 3215-01; 3220-01; 3221-01; 3231-01; 3233-01; 3240-01 37. Hood and wood products 3311-01; 3312-01; 3320-01 38. Paper & paper products and printing 3411-01; 3412-01; 3419-01; 3420-01 39. Fertilizer & pesticides 3512-01 40. Chemical industries 3511-01; 3521-01; 3522-01; 3523-01; 3523-02; 3529-01 41. Petroleum refinery 3530—01 42. Rubber products 3551-01; 3559-01 43. Non-metallic mineral products 3810-01; 3620-01; 3691-01; 3699-01 44. Cement 3692-01 45. Iron & steel basic industries 3710-01 48. Non-ferrous basic metal industries 3720-01 47. Prefabricated metal products 3811-01; 3812-01; 3813-01; 3819-01 48. Machinery, electrical appliances, 3821-01; 3822-01; apparatus and accessories 3823-01; 3824-01; 3825-01; 3929-01; 3831-01; 3832-01; 3833-01; 3839-01; 3839-02 49. Manufacture & repair of transport 3841-01; 3842-01; equipment 3843‘01; 3844-01; 3844-02; 3845-01 50. Other manufacturing industries, 3351-01; 3352‘023 not elsewhere classified 3901-01; 3902'013 3903-01; 3909-01 51. Electricity, gas & water supplies 4101-01; 4102-01; 4200-01 52. Construction 5000-01; 5000-02; 5000-03; 5000—04; 5000-05; 5000-08; 5000-07 53. Trade 6100-01; 6200-01 54. Restaurants & Hotels gfig‘gii 6320‘01 55' Railways 7112-01; 7114-01 58. Road transport 113 Table 1 (cont'd.) Code Sector Description I.S.I.C Code 57. Water transport 7121-01; 7122-01; 7123-01 58. Air transport 7131-01; 7132-01 59. Service allied to transport 7191-01; 7192-02 80. Communication 7200-01 81. Financial services 8101-01; 8200-01; 8200-02 82. Real estate & business services 8301-01; 8321-01; 8322-01; 8323-01; 8324-01; 8325-01; 8329-01; 8330-01 83. Public administration & defence 9100-01 84. Social & community services 9200-01; 9310-01; 9320-01; 9331-01; 9339-01; 9340-01; 9350-01; 9391-01 85. Recreational, cultural, personal 9411-01; 9412-01, 02 9413-01; 9414-01; 9420-01; 9490-01; 9510-01; 9520-01; 9530-01; 9591-01; 9599-01 88. Unspecified and professional sector 9900-01, 02 Source: Input-Output Table Indonesia 1971, 1975 and 1980. 114 Table 2 Gross Value—Added, Labor and Total Output for Sixty-Six Sector 1971 Input-Output Table for Indonesia. CODE GROSS VALUE-ADDED (VA-g) LABOR (La) TOTAL OUTPUT (01) (in RP 10") (Person) (in RP 103) 1 431,599.88 7,489,982 483,798.18 2 78,510.71 1,717,440 379,801.23 3 34,488.95 1,054,739 37,228.70 4 78,753.30 5,954,802 107,804.81 5 155,878.47 7,020,288 185,054.10 8 38,378.77 989,778 41,757.30 7 80,553.20 242,319 143,715.80 8 24,815.47 131,873 39,524.45 9 57,210.49 259,954 59,848.20 10 31,853.51 44,485 88,750.78 11 27,290.94 234,738 83,812.89 12 29,018.85 119,954 45,097.04 13 15,313.83 109,288 29,054.79 14 15,353.25 20,337 18,145.10‘ 15 2,142.48 5,880 2,542.50 18 10,915.99 58,530 11,878.90 17 8,894.23 29,988 7,802.08 18 45,777.53 295,741 49,918.40 19 22,507.89 19,473 84,139.84 20 45,583.85 9,433 49,942.40 21 105,594.90 107,338 149,118.97 22 20,824.47 18,984 21,828.00 23 159,889.74 581,017 222,785.81 24 20,818.25 22,335 . 29,548.11 25 282,511.75 43,182 279,345.98 28 27,107.83 20,331 31,095.19 27 2,448.10 34,571 9,778.89 28 13,212.23 51,407 88,372.02 29 32,539.30 115,015 213,014.55 30 4,505,23 39,019 17,855.48 31 28,087.88 18,421 84,842.48 32 28,720.12 181,340 82,052.83 33 8,895.89 9,320 18,999.49 34 27,891.30 145,818 85,375.81 35 7,875.51 84,172 25,984.53 38 73,899.78 784,908 235,105.58 37 9,909.58 424,073 34,818.57 ' 38 21,940.73 50,490 40,240.75 39 872.35 2,049 3,232.14 40 24,940.73 . 28,002 85,279.58 41 83,932.58 104,910 190,770.00 42 4,229.88 8,843 12,122.88 115 Table 2 (oont’d.) 030E GROSS VALUE-ADDED (VAj) LABOR (L3) TOTAL OUTPUT (91) (in Rp 103) (person) (in Rp 103) 43 18,218.37 137,738 32,373.80 44 5,088.22 89,781 , 18,778.55 45 1,392.38 3,014 5,229.81 48 8,514.17 10,207 17,724.40 47 20,141.88 35,758 55,313.88 48 7,925.42 38,059 17,984.73 49 102,888.71 231,833 194,188.81 50 5,832.54 80,058 14,839.32 51 40,259.21 37,359 82,875.87 52 195,893.89 878,472 548,748.20 53 753,811.84 3,323,070 870,018.92 54 89,708.27 938,491 281,290.23 55 3,475.28 88,085 10,445.54 58 211,579.11 870,221 324,958.81 57 48,378.50 159,427 98,402.78 ‘ 58 15,327.72 9,789 27,088.90 59 40,189.25 9,825 49,182.10 80 9,571.07 38,207 17,382.20 81 39,898.97 81,873 58,718.45 62 122,793.47 31,589 158,137.87 83 185,853.85 1,325,888 185,853.85 64 84,084.93 990,473 88,816.12 65 148,859.08 1,803,413 189,803.48 88 - 1,878,199 a - 118 Table 3 Diagonal Matrix of Value-Added Coefficients for S1xty-Six Sector of Indonesian 1971 Input-Output Table. CODE VALUE-ADDED COEFFICIENT‘ (0) 1 0.930580 2 0.210449 3 0.925816 4 0.730518 5 0.943184 6 0.871195 7 0.136488 8 0.622790 9 0.955926 10 0.480409 11 0.427871 12 0.843431 13 0.527080 14 0.950954 15 0.842886 13 0.943838 17 0.906889 13 0.917083 19 0.350915 20 0.912724 21 0. 708134 22 0.954112 23 0 . 717684 24 0.697718 25 0.939738 26 0.871762 27 0.250197 28 0.193240 29 O . 152756 30 0.252318 31 0.434511 32 0.325648 33 0.382951 34 0.328688 35 0.295615 38 0.314325 37 0.284608 38 0.545238 39 0.289898 40 0.387979 41 0.335829 42 0.348905 43 0.562753 117 Table 3 (cont'd.) CODE VALUE-ADDED COEFFICIENT' 09) 44 0.303174 45 0.266239 48 0.367421 47 0.384137 48 0.441185 49 0.529882 50 0.379588 51 0.486952 52 0.357922 53 0.866201 54 0.266784 55 0.332702 56 0.851095 57 0.501837 58 0.565872 59 0.817151 80 0.550624 61 0.679462 62 0.776496 63 1.000000 64 0.721320 65 0.783226 86 0.000000 118 Table 4 Diagonal Matrix of Labor Coefficients for Sixty- Six Sector of Indonesian 1971 Input-Output Table. 0000' LABOR.COEFFICIENT‘ (1) 1 0.000016149296443 2 0.000004521944281 3 0.000028331341143 4 0.000055235133266 5 0.000042533120959 3 0.000023224154818 7 0.000001888100883 8 0.000003331431557 9 0.000004343555883 10 0.000000646756487 11 0.000003678504456 12 0.000002859908500 13 0.000003760756832 14 0.000001259639147 15 0.000002304818092 16 ' 0.000004841182163 17 0.000003944720247 18 0.000005924726142 19 0.000000303602254 20 0.000000188877587 21 0.000000719824176 22 0.000000869788326 23 0.000002518192266 24 0.000000755885909 25 0.000000154510904 26 0.000000653831027 27 0.000003538083842 28 0.000000751871891 29 0.000000539939643 30 0.000002165269940 31 0.000000254028080 32 0.000001986298947 33 0.000000490539483 34 0.000001705611929 35 ' 0.000003241807188 36 0.000003338534117 37 0.000012179508510 38 0.000001254698285 39 0.000000633945312 40 0.000000398317514 41 0.000000549929234 42 0.000000547982044 43 0.000004254577804 0.000005351577052 119 Table 4 (cont’d.) 0005 LABOR COEFFICIENT' (1) 45 0.000000578311588 46 0.000000848420031 47 0.000000646420031 48 0.000002118540050 49 0.000001193978520 50 0.000005394991145 51 0.000000451873080 52 0.000001240922238 53 0.000003819537626 54 0.000003591758952 55 0.000006326623612 56 0.000002062479857 57 0.000001653759706 58 0.000000381392407 59 0.000000195701282 60 0.000002082992947 61 0.000001053723319 62 0.000000199756074 63 0.000007132848884 64 0.000011151950795 85 0.000009501474894 88 0.000050170422461 120 Table 5 Gross Value-Added, Labor, and Total Output for Sixty-Six Sector of Indonesian 1975 Input-Output Table. CODE GROSS VALUE-ADDED (VAJ) LABOR(LJ) TOTAL OUTPUT (Qd) (in RP 103) (Person) (in RP 103) 1 1,285,590.05 9,286,359 1,384,488.85 2 127,709.29 1,567,848 616,538.19 3 155,154.92 2,532,922 169,414.76 4 314,295.87 3,513,208 408,959.68 5 535,960.01 8,035,855 567,136.50 6 158,687.44 2,208,992 178,315.05 7 106,720.92 251,780 255,645.88 8 51,149.74 116,313 83,838.05 9 135,910.10 323,677 158,651.05 10 64,383.15 150,814 118,711.81 11 57,963.88 134,538 .122,080.17 12 80,303.22 141,719 88,848.18 13 33,571.83 78,627 58,148.00 14 39,084.25 92,975 41,931.05 15 9,258.38 22,213 10,254.09 18 15,693.41 37,950 18,663.39 17 25,984.83 84,489 28,410.69 18 100,208.31 218,104 111,707.74 19 81,839.41 177,769 207,055.78 20 118,862.61 262,978 127,707.79 21 232,400.91 183,389 117,758.81 22 39,583.85 34,531 42,087.03 23 269,812.60 573,486 198,013.90 24 88,488.96 22,839 97,598.33 25 2,390,493.86 11,088 464,583.17 28 85,845.15 356,058 96,765.59 27 16,820.87 27,997 62,024.00 28 9,898.99 29,059 67,450.10 29 188,318.48 493,318 1,145,060.66 30 41,308.48 71,604 186,202.25 31 79,116.08 58,981 136,902.32 32 72,518.12 192,010 .253,956.53 33 21,845.72 18,314 33,020.72 34 127,072.68 47,248 315,835.28 35 28,371.53 102,607 95,184.34 36 170,780.21 917,541 509,458.72 37 41,613.53 732,171 115,451.77 38 58,442.20 55,483 121,230.42 39 24,610.48 4,308 34,971.75 40 82,198.57 103,960 208,392.75 41 92,314.83 15,116 340,136.53 42 17,371.95 18,021 43,473.56 121 Table 5 (cont'd.) CODE GROSS VALUE-ADDED (VAJ) LABOR(LJ) TOTAL OUTPUT (Qa) (in Rp 103) (person) (in Rp 103) 43 51,078.16 259,787 95,802.40 44 18,883.52 93,393 34,440.54 45 4,461.80 8,546 15,308.98 46 17,214.84 27,235 48,790.92 47 54, 167.63 172,058 171,964.33 48 45,870.67 46,793 118,331.45 49 270,511.33 889,247 717,409.42 50 14,945.32 178,814 37,302.73 51 83,548.85 58,379 164,699.43 52 722,100.46 1,381,598 1,988,733.49 53 1,839,573.52 4,745,599 2,145,908.05 54 199,921.25 1,282,011 $84,801.31 55 6,137.86 33,048 18,709.72 56 149,662.57 912,459 628,452.29 ' 57 161,748.04 368,549 .294,605.33 58 56,808.83 10,069 114,910.58 59 92,151.79 175,248 118,456.41 60 33,537.75 39,561 53,963.37 61 230,821.06 57,298 289,006.44 62 376,675.78 27,238 454,491.25 63 705,030.05 1,570,198 705,030.05 64 317,420.80 877,188 408,437.09 65 377,078.93 2,455,954 511,137.97 66 0.00 0 0.00 122 Table 8 Diagonal Matrix of Value-Added Coefficients for Sixty-Six Sector of Indonesian 1975 Input-Output Table. ‘CODE VALUE-ADDED COEFFICIENT' (07 1 0.927520 2 0.207139 3 0.915828 4 0.768524 5 0.945028 8 0.889927 7 0.417458 8 0.809970 9 0.858880 10 0.542348 11 0.474801 12 0.878722 13 0.597918 14 0 4932107 15 0.902899 13 0.941789 17 0.913910 18 0.897057 19 0.395252 20 1,074415 21 0.731375 22 0.940048 23 0.877897 24 0 . 701743 25 0.989938 28 0.887145 27 0.287974 28 0.148730 29 0.184481 30 0.248543 31 0.577901 32 0.285553 33 0.855519 34 0.402593 35 0.277057 38 0.335218 37 0.380440 38 0.482075 39 0.703724 40 0.298458 41 0.271404 42 0.399598 43 0.533181 123 Table 8 (cont'd.) .L CODE VALUE-ADDED COEFFICIENT’ 009 44 0.547712 45 0.291449 48 0.352824 47 0.314993 48 0.387845 50 0.400649 51 0.507279 52 0.383453 53 0.857247 54 0.341861 55 0.328057 56 0.887771 57 0.549032 58 0.492633 59 0.777938 80 0.821491 61 0.798870 62 0.828785 83 1.000000 84 0.777159 85 0.737720 66 0.000000 124 Table 7 Diagonal Matrix of Labor Coefficients for Sixty- Six Sector of Indonesian 1975 Input-Output Table. S LABOR.00EFFICIENT' (1) 1 0.000006791094396 2 0.000002542994273 3 0.000014951011352 4 0.000008590597489 5 0.000014169172677 6 0.000012388141102 7 0.000000984877988 8 0.000001387386783 9 0.000002040181896 10 0.000001268736447 11 0.001102046302852 12 0.000001595069252 13 0.000001400352639 14 0.000002217330594 15 0.000002166257562 16 0.000002269885033 17 0.000002269885033 18 0.000001952451997 19 0.000858556168638 20 0.000002059216591 21 0.000000577132700 22 0.000000820466543 23 0.000001440869276 24 0.000000231960936 25 0.000000004498124 26 0.000003679593128 27 0.000000451389785 28 0.000000430822193 29 0.000000430822591 30 0.000000430824492 31 0.000000430825424 32 0.000000756074278 33 0.000000494053431 34 0.000000149691758 35 0.000001077981945 36 0.000001801011474 37 0.000006341791035 38 0.000000457665659 39 0.000000123185142 0.000000498865723 0.000000044440978 0.000000414527819 0.000002711898158 0.000002711717064 £8838 125 Table 7 (cont'd.) CODE LABOR.OOEFFICIENT' (1) 45 0.000000558234448 46 0.000000558198124 47 0.000001000544706 48 0.000000395440096 49 0.000001239525124 50 0.000004793590174 51 0.000000354457814 52 0.000000695397843 53 0.000002211464280 54 0.000002192216361 55 0.000001766354601 56 0.000001451914512 57 0.000001250992302 58 0.000000087624656 59 0.000001479413398 60 0.000000733108403 61 0.000000198251638 62 0.000000059930747 63 0.000002227136276 64 0.000002147669792 65 0.000004804874895 88 0.000000000000000 126 Table 8 Gross value-Added, Labor, and Total Output for Sixty~Six Sector of Indonesian 1980 Input-Output Table. CODE GROSS VALUE-ADDED (VAJ) LABOR(L5) TOTAL OUTPUT (03) (In RP 10°) (Person) (in RP 103) 1 3,135,130.10 9,815,521 3,438,221.00 2 300,688.90 1,080,352 1,373,919.90 3 337,578.80 2,786,333 382,653.50 4 614,545.20 3,187,928 714,214.70 ~ 5 1,315,875.40 8,891,353 1,397,649.50 6 398,838.50 2,055,538 449,878.00 7 475,115.10 329,830 958,078.10 8 219,039.70 261,287 339,889.00 ' 9 390,992.40 410,137 412,592.00 10 191,095. 10 192, 138 5 335, 141.90 11 151,878.10 347,755' 235,068.00 12 389,088.70 355,952 527,021.00 13 172,639.10 168,533 194,556.30 14 289,883.70 228,304 290,117.90 15 23,008.80 25,598 25,293.80 18 49,930.10 55,986 51,894.90 17 77,958.90 65,259 85,492.40 18 538,978.20 405,428 597,148.50 19 173,251.30 330,448 748,299.50 20 478,739.90 488,840 577,475.10 21 1,194,883.00 427,494 1,391,982.00 22 217,437.50 84,282 233,330.20 23 792,590.10 844,157 1,011,105.90 24 305,858.80 55,883 430,759.10 25 11,808,849.30 28,611 13,238,896.4O 28 322,228.90 284,570 371,850.90 27 72,573.70 48,597 223,407.90 28 48,084.80 43,800 235,986.50 29 605,859.80 547,081 3,045,981.10 30 108,713.60 122,321 451,650.60 31 113,892.40 76,380 318,105.20 32 220,008.00 255,910» 818,707.80 33 59,394.00 21,121 109,841.50 34 522,174.80 99,521 1,222,090.90 35 113,507.50 122,073 385,980.90 36 462,913.50 1,138,333 1,332,168.80 37 334,460.40 1,092,836 711,008.40 38 125,898.50 82,892 388,485.10 39 118,234.40 13,761 319,784.40 40 296,044.30 130,692 707,428.70 41 94,025.30 23,027 1,823,111.50 42 113,665.20 24,462 393,089.40 Table 8 (cont'd.) 127 CODE 09085 VALUE-ADDED (VAJ) LABOR.(L3) TOTAL OUTPUT (93) (in RP 103) (person) (in RP 108) 43 128,294.90 308,649 289,664.80 44 115,662.50 110,959 215,569.00 45 145,211.00 12,442 363,702.10 46 73,516.50 40,409 379,977.70 47 151,977.20 190,724 495,562.30 48 452,209.30 98,765 1,217,005.50 . 49 435,289.60 503,683 1,440,868.80 50 62,270.00 293,934 109,818.70 51 230,600.90 62,951 523,477.30 52 2,582,425.90 1,578,467 7,532,682.10 53 5,730,663.20 5,578,120 6,375,656.90 54 1,008,871.30 1,353,099 2,315,097.30 55 21,873.50 55,462 51,298.50 56 1,269,734.70 1,239,002 2,058,972.80 57 317,067.80 489,241 633,897.90 ‘ 58 151,108.80 11,347 438,551.60 59 300,809.90 195,256 429,347.60 60 150,328.40 43,655 285,192.70 61 765,151.60 98,628 930,890.40 62 1,589,255.10 191,363 1,841,169.80 63 2,468,094.20 2,022,547 2,488,094.20 64 1,297,114.60 1,200,927 1,779,902.20 85 0.00 3,581,832 2,077,625.90 66 0.00 O 0.00 128 Table 9 Diagonal Matrix of Value-Added Coefficients for Sixty-51x Sector of Indonesian 1980 Input-Output Table. CODE VALUE-ADDED COEFFICIENT (in 1 0.912377 2 0.218854 3 0.882199 4 0.860448 5 0.941348 6 0.886543 7 0.495905 8 0.844482 9 0.947649 10 0.570191 11 0.646102 12 0.738279 13 0.887347 14 0 . 930255 15 0.909661 13 0.962138 17 0.911881 13 0.902586 19 0.232147 20 1.208239 21 0.858248 22 0.931887 23 0.783884 24 0.710040 25 0.891966 26 0.886554 27 0.324848 28 0.203893 29 0.198838 30 0.240713 31 0.380299 32 0.269381 33 0.540724 34 0.427279 35 0.193705 36 0.347488 37 0.470402 38 0.341865 39 0.223820 40 0.418479 41 0.057929 42 0.289158 0.442908 tbs (.0 129 Table 9 (cont'd.) CODE VALUE-ADDED COEFFICIENT 09) 44 0.536545 45 0.399258 48 0.193475 47 0.306676 48 0.371575 49 0.302102 50 0.587025 51 0.440517 52 0.342829 53 0.898834 54 0.435892 55 0.428398 56 0.616883.. 57 0.500187 58 0.344583 59 0.700155 60 0.568864 81 0.821956 62 0.883176 63 1.000000 64 0.728756 65 0.000000 68 0.000000 130. Table 10 Diagonal Matrix of Labor Coefficients for Sixty- Six.Sector of Indonesian 1980 Input-Output Table. 0005 LABOR.00EFFICIENT' (1) 1 0.000002856487112 2 0.000000786328228 3 0.000000728160856 4 0.000004435540181 5 0.000006361647180 3 0.000004569100956 7 0.000000344262841 8 0.000000768787386 9 0.000000994049812 10 0.000000573303428 11 0.000001479380435 12 0.000000675403826 13 0.000000855963030 14 0.000000786935243 15 0.000001026180329 16 0.000001078834336 17 0.000000763331010 18 0.000000678936646 19 0.000000442782020 20 0.000000846512689 21 0.000000307111730 22 0.000000361213422 23 0.000000834884852 24 0.000000129267147 25 0.000000002161132 26 0.000000765279847 27 0.000000208573645 28 0.000000184771991 29 0.000000179600917 30 0.000000270831036 31 0.000000241565150 32 0.000000313343401 33 0.000000192286158 34 0.000000081435023 35 0.000000316268945 36 0.000000854496195 37 0.000001537022629 38 0.000000224953465 39 0.000000043032118 40 0.000000184742293 41 0.000000014186949 42 0.000000062230119 43 0.000001065538512 0.000000514728143 131 Table 10 (cont 'd. ) ICODE LABOR.COEFFICIENH? (I) 45 0.000000034209316 48 0.000000108345714 47 0.000000384883820 48 0.000000081154111 49 0.000000349588955 50 0.000002678538895 51 0.000000120255453 52 0.000000209549133 53 0.000000874909062 54 0.000000584487443 55 0.000001081162217 56 0.000000601757401 57 0.000000740248970 58 0.000000025873808 59 0.000000454773708 80 0.000000184818145 61 0.000000103799545 82 . 0.000000103935552 63 0.000000819477231 64 0.000000874715161 65 0.000001724002382 68 0.000000000000000 132 Table 11 Backward Linkage Index (Ida) and Forward Linkage Index (Li?) for Sixty-Six Sector of Indonesian 1971 Input-Output Table. 0001-: L58 Li? 1 0.069419 0.999957 2 0.798550 0.029441 3 0.074183 0. 121926 4 0.289481 0.247533 5 0.056815 0.100631 6 0.128804 0.565622 7 0.578659 0.425497 8 0.377209 0.754901 9 0.044073 0.680926 10 0.714133 0.465991 11 0.572328 0.530904 12 0.356590 0.462683 13 0.472939 0.332987 14 0.049045 0.998002 15 0.157935 0.244499 16 0.064335 0.115321 17 0.106368 0.874512 18 0.108414 0.792098 19 0.629714 0.190562 20 0.154571 0.489538 21 0.268782 0.569384 22 0.045896 0.757949 23 0.282315 0.321750 24 0.302281 0.374981 25 0.060263 0.370398 26 0.128237 0.844258 27 0.847279 0.428212 28 0.806759 0.337771 29 0.847243 0.036008 30 0.747683 0.385020 31 0.585488 0.039779 32 0.674353 0.171105 33 0.637048 0.653184 34 0.673310 0.089830 35 0.704384 0.948423 36 0.685674 0.303401 37 0.715307 0.529382 38 0.454763 0.623622 39 0.730101 0.999363 40 0.632020 0 - 536058 41 0.664871 0.663390 42 0.651094 0.909965 43 0.436940 0 - 887461 Table 11 (cont'd.) 133 CODE LjB LiF 44 0.675367 1.000000 45 0.733780 0.930316 46 0.632578 0.675929 47 0.610027 0.677734 48 0.558436 0.095038 49 0.470070 0.500718 50 0.620431 0.325823 51 0.513047 0.761932 52 0.642077 0.079875 53 0.133798 0.328422 54 0.733215 0.135586 55 0.671028 0.584693 56 0.348904 0.390626 57 0.498622 0.176174 58 0.434127 0.276443 59 0.182848 0.269933 80 0.449375 0.447562 81 0.320537 0.842705 82 0.223503 0.219728 83 0.000000 0.000000 84 0.278879 0.047427 85 0.218773 0.085295 88 0.999999 0.821186 134 Table 12 Backward Linkage Index (L59) and Forward Linkage Index (Li?) for Sixty-Six Sector of Indonesian 1975 Input-Output Table. (DUE LjB Lip 1 0.072479 1.000000 2 0.792860 0.063061 3 0.083876 0.110258 4 0.231475 0.230658 5 0.054971 0.073720 6 0.110072 0.596600 7 0.582543 0.493141 8 0.390122 0.514822 9 0.143339 0.583154 10 0.457651 0.127750 11 0.525901 0.806140 12 0.320311 0.267519 13 0.402083 0.293413 14 0.067892 0.995697 15 0.097300 0.431278 16 0.056210 0.214986 17 0.086089 0.770746 18 0.102942 1.007889 19 0.604747 0.128018 20 0.069258 0.263624 21 0.441712 0.480993 22 0.061742 0.948932 23 0.321913 0.252479 24 0.298256 0.507697 25 0.030061 0.086142 26 0.112854 0.892963 27 0.732025 0.362850 28 0.853417 0.285327 29 0.835538 0.048092 30 0.752684 0.524045 31 0.422098 0.260361 32 0.714446 0.108508 33 0.344480 0.389818 34 0.597406 0.000830 35 0.722942 0.803983 36 0.664781 0.337209 37 0.641291 0.684382 38 0.517924 0.551704 39 0.296275 0.998145 40 0.701541 0.670802 41 0.728595 0.469945 42 0.600401 0.787165 0.466838 0.915297 Table 12 (cont'd.) 135 CODE L 33 Li? 44 0.452287 0.998344 45 0.708550 0.840458 48 0.847175 0.611459 47 1.731735 0.804051 48 0.612354 0.289305 49 0.822933 0.382902 50 0.599350 0.175040 51 0.971888 0.726104 52 0.598824 0.079883 53 0.142752 0.333383 54 0.858138 0.157714 55 2.489179 0.321210 56 0.332228 0.335032 57 0.450967 0.348397 58 0.507368 0.209159 59 0.222061 0.496457 60 0.378508 0.424080 61 0.201329 0.883217 62 0.171214 0.236293 63 0.021257 0.000000 84 0.296967 0.057611 85 0.319871 0.098061 66 0.000000 0.904726 136 Table 13 Backward Linkage Index (LjB) and Forward Linkage Index (Li?) for Sixty-Six Sector of Indonesian 1980 InputrOUtput Table. CDDE LjB Lip 1 0.087822 0.987251 2 0.781145 0.063081 3 0.117800 0.141288 4 0.139551 0 172305 5 0.058650 0.069077 3 0.113458 0.579741 7 0.504094 0.382360 8 0.863946 0.744633 9 0.137180 0.522030 10 0.436032 0.281088 11 0.353897 0.788183 12 0.261720 0.198916 13 0.112652 0.225247 14 0.069744 0.955908 15 0.090338 0.302953 18 0.037861 0.141143 17 0.088118 0.838942 18 0.097413 0.889208 19 0.787852 0.243992 20 0.170973 0.287607 21 0.141753 0.390879 22 0.088112 0.762833 23 0.216114 0.185793 24 0.289959 0.620852 25 0.108033 0.131448 28 0.133445 0.945463 27 0.675151 0.233187 28 0.798308 0.274171 29 0.801181 0.954526 30 0.759297 0.309174 31 0.839700 0.205927 32 0.730818 0.224326 33 0.459275 0.480331 34 0.572720 0.023187 35 0.705924 0.781705 36 0.652511 0.368087 37 0.529597 0.534884 38 0.858334 ' 0.796106 39 0.638522 0.908307 40 0.590437 0.685468 41 0.942070 0.559695 42 0.710840 0.710214 0.557091 0.911840 43 Table 13 (cont'd.) 137 (DOE L53 Li? 44 0.483454 0.983855 45 0.600741 0.952256 46 0.808524 0.350710 47 0.693323 0.811085 48 0.628424 0.424453 49 0.697897 0.289809 50 0.434818 0.288934 51 0.559482 0.692433 52 0.657170 0.087679 53 0.101185 0.374479 54 0.564311 0.115184 55 0.573428 0.285799 56 0.383316 0.295850 57 0.499812 0.282490 58 0.655438 0.266738 59 0.299844 0.605854 60 04433135 0.450758 61 0.178043 0.718324 62 0.136823 0.321168 63 0.000000 0.000000 64 0.271243 0.031917 65 0.455998 0.406334 66 0.000000 0.045140 138 Table 14 Direct Value-Added Requirement - Direct Labor Requirement Ratio 51/11 and Its Rank for Sixty-Six Sector of Indonesian 1971 Input- Output Table. CODE 0 ,/1, RANK 1 0.0576 56 2 0.0445 59 3 0.0326 61 4 0.0132 64 5 0.0221 63 6 0.0375 60 7 0.2498 34 8 0.1869 41 9 0. 2200 38 10 0. 7118 16 11 0.1162 47 12 0.2418 35 13 0.1401 45 14 0. 7549 14 15 0. 3658 26 16 0.1931 40 17 0.2298 36 18 0.1547 43 19 1.1558 8 20 4.8319 2 21 0.9837 11 22 1. 0969 9 23 0. 2849 30 24 0.9230 13 25 6.0812 1 23 1.3332 7 27 0.0707 53 23 0. 2570 33 29 0.2829 31 30 0.1154 48 a 1.mm 5 32 0.1656 42 33 0. 7396 15 34 0.0019 65 35 0. 0911 50 33 0. 0941 49 37 0.0233 62 38 0. 4345 24 39 0.4249 25 40 0.9235 12 41 0.6094 20 42 0.6363 19 139 Table 14 (cont’d.) 0008 MN, RANK 43 0.1322 46 44 0.0566 57 45 0.4817 22 46 0.6381 18 47 0.5632 21 48 0.2082 39 49 0.4337 23 50 0.0703 54 51 1.0775 10 52 0.2884 29 53 0.2267 37 54 0.0742 52 55 0.0525 58 56 0.3156 27 57 0.3034 28 58 1.5657 6 59 4.1750 3 60 0.2843 32 61 0.6447 17 82 3.8866 4 63 0.1402 44 64 0.0646 55 65 0.0824 51 66 0.0000 66 140 Table 15 Direct Value-Added Requirement - Direct Labor Requirement Ratio 51/1, and Its Rank for Sixty-Six Sector of Indonesian 1975 Input- Output Table. 0008 B JM? 1 RANK 1 0.1385 58 2 0.0814 61 3 0.0612 64 4 0.0894 59 5 0.0666 63 6 0.0718 62 7 0.4238 37 8 0 4388 31 9 0.4198 39 10 0.4269 33 11 0.4251 36 12 0.4251 35 13 0.4255 34 14 0.4203 38 15 0.4167 40 16 0.4135 41 17 0.4026 42 18 0.4581 27 19 0 4519 28 20 0.4490 29 21 1.2672 12 22 1.1456 13 23 0.4598 25 24 3.0251 7 25 215.5212 1 23 0.2410 51 27 0.5936 20 23 0.3405 47 23 0 3817 44 30 0 . 5768 21 31 1.3413 10 32 0.3776 45 33 1.3268 11 34 2.6894 3 35 0 2570 50 33 0.1861 54 37 0.0568 55 33 1.0532 14 39 5.6965 4 40 0.5982 19 41 6.1035 3 42 0.9639 15 Table 15 (cont'd.) 141 CODE 5 ,l1 1 RANK 43 0. 1968 53 44 0.2019 52 45 0.4704 24 46 0.6320 18 47 0.3148 48 48 0.9802 15 49 0.3041 49 50 0.0835 60 51 1.4309 9 52 0.5220 23 53 0.3876 43 54 0. 1559 56 55 0. 1857 55 56 0.4585 26 57 0.4274 32 58 5.6213 5 59 0.5228 22 60 0.8477 17 61 4.0274 6 62 13.8244 2 63 0.4397 30 64 0.3618 46 65 0. 1535 57 66 0.0000 86 142 Table 16 Direct Value-Added Requirement - Direct Labor Requirement Ratio 31/1, and Its Rank for Sixty-Six Sector of Indonesian 1980 Input- Output Table. 0008 B 1/11 RANK 1 0.3194 57 2 0.2783 59 3 0.1211 64 4 0.1939 62 5 0 1479 63 6 0.1940 61 7 1.4404 24 8 0.8383 48 9 0.9533 40 10 0.9945 38 11 0.4367 53 12 1 0930 32 13 1.0368 35 14 1.1821 28 15 0.8864 45 16 0.8918 43 17 1.1946 27 18 1.3294 25 19 0.5242 52 20 0.9793 39 21 2 . 7945 15 22 2 . 5798 13 23 0.9389 41 24 5 . 4928 7 25 412 . 7282 1 23 1 . 1323 29 27 1 . 5574 20 23 1 . 1024 31 23 1.1071 30 33 0.8887 44 31 1 4915 23 32 0 . 8597 47 33 2.8120 14 34 5 . 2468 8 35 0 . 9298 42 33 0.4066 55 37 0 . 3080 58 33 1.5188 22 39 8 . 4461 4 43 2.2652 17 41 4.0822 11 42 4.6465 9 Table 16 (cont'd.) 143 0008 B ,/Y 3 RANK 43 0.4156 54 44 1.0423 34 45 11.6708 3 46 1.8193 18 47 0.7968 49 48 4.5786 10 49 0.8642 46 50 0.2118 60 51 3.6631 12 52 1.6360 19 53 1.0273 36 54 0.7454 50 55 0.3943 56 56 1.0248 37 57 0.6757 51 58 13.3170 2 59 1.5395 21 60 3.4435 13 61 7.9186 6 62 8.3049 5 63 1.2202 26 64 1.0800 33 65 0.0000 65 66 0.0000 68 144 Table 17 Total Value-Added uirement - Direct Labor Requirement Ratio ( Wig/EL”) and Its Rank for Sixty-Six Sector of Indonesian 1971 Input- Output Table. 0008 Emu/2:0,, RANK 1 0.0554 57 2 0.0451 60 3 0.0339 83 4 0.0134 66 5 0.0229 65 6 0.0386 62 7 0.1255 41 8 0.1578 32 9 0.2238 21 10 0.3209 14 11 0.0752 48 12 0.1883 28 13 0.1370 37 14 0.5331 5 15 0.3583 11 16 0.1901 26 17 0.2006 20 18 0.1613 31 19 0.4612 7 20 0.9655 1 21 0.1752 30 . 22 0.4054 9 23 0. 1230 42 24 0. 5024 3 25 0.3223 13 23 0. 5741 4 27 0.0697 50 23 0.1419 35 23 0.0532 58 33 0.0969 46 31 0. 1181 43 32 0.0497 59 33 0.3376 12 34 0. 1112 44 33 0.0873 4'7 33 0.0726 49 37 0.0309 64 33 0.2231 21 39 0 . 2802 17 43 0.1390 37 41 0 1487 33 A N P. b H [G 00 Table 1'? (cont 'd . ) 145 0008 Emu/21.1, RANK 43 0.1363 39 44 0.0618 55 45 0.3656 10 46 0.2638 18 47 0.1476 34 48 0.2069 24 49 0. 1763 29 50 0.0686 51 51 0.2167 23 52 0.1891 27 53 0. 1051 45 54 4 0.0626 54 55 0.0564 56 56 0.1289 40 57 0.2389 20 58 0.7732 2 59 0.8973 3 60 0.2440 19 81 0.2836 18 62 0.2843 15 63 0.1403 36 64 0.0677 52 65 0.0629 53 66 0.0043 61 146 Table 18 Total Value-Added uirement - Direct Labor Requirement Ratio ( Ina/2L”) and Its Rank for Sixty-Six Sector of Indonesian 1975 Input- Output Table . 0008 Emu/2L4, RANK 1 0.0623 52 2 0.0508 56 3 0.0590 53 4 0.0712 49 5 0.0535 54 6 0.0885 51 7 0.3845 18 8 0.1760 32 9 0.2926 20 10 0.1741 33 11 0.m05 64 12 0.4188 .11 13 0.4212 9 14 0.4381‘ 7 15 0.4146 12 16 0.4124 13 17 0.2682 22 13 0.0026 53 19 0 . £005 65 23 0.4260 8 21 0.1392 39 22 0.4195 10 23 0.3690 17 24 0.8517 3 25 0 . 2444 24 23 0.1882 28 27 0.4349 6 23 0.1965 26 23 0.0303 80 33 0.2174 25 31 0 . 6875 4 32 0 . 2765 21 33 0 . 9428 4 34 2.6074 1 35 0 . 1880 34 36 0 . 0845 43 37 0 . 0454 58 33 0.1789 31 33 0.0687 50 43 0.0999 42 41 0.0732 47 42 0.2555 23 Table 18 (cont 'd . ) 147 0008 Emu/2L4; RANK 43 0.1588 35 44 0. 1839 30 45 0.3072 19 46 0.3237 18 47 0.0725 48 48 0. 1873 29 49 0.0327 59 50 0.0800 46 51 0. 1431 38 52 0.0458 57 53 0.0172 62 54 0.0522 55 55 0. 1480 37 58 0.0207 61 57 0.0818 45 58 0.4055 14 59 0. 1499 36 60 0.3924 15 61 0.0827 44 62 0. 1194 40 63 0.4490 5 64 0. 1949 27 65 0. 1023 41 68 0.0 66 148 Table 19 Total Value-Added R Requirement Ratio ( Wig/2L”) and Its Rank for uirenent - Direct Labor Sixty-Six Sector of Indonesian 1980 Input- Output Table . c118: 2:2233/2183, RANK. 1 0.3600 59 2 0.2937 61 3 1.2103 29 4 0.1994 64 5 0.1524 65 6 0.2118 63 7 1.4216 16 8 0 8809 48 9 0.9621 39 10 1.0118 37 11 0.4752 15 12 1.0907 32 13 1.0397 35 14 1.2418 28 15 0.8867 47 16 0.8935 45 17 1.1651 30 18 1 0062 38 19 0.5815 54 20 1.3304 20 21 1 .3303 21 22 2. 1241 .10 23 0.9513 41 24 3. 1367 4 25 5.6505 2 23 1 .0688 34 27 1 .5224 13 23 1.0953 31 29 1 .0304 36 30 0.8872 46 31 1.4769 14 32 0.9588 40 33 2.6553 7 34 4.8175 3 33 0.5255 55 33 0.4313 57 37 0.3432 60 33 1.3202 23 33 0.7736 51 43 1.3760 17 41 1.3284 22 42 1.3125 24 Table 19 (cont 'd. ) 149 CODE 132331/1201, RANK 43 0.4448 56 44 0.9238 _44 45 2.4385 ' 9 46 1.3416 18 47 0.9312 43 48 2.0530 11 49 0.7419 52 50 0.2155 82 51 1.6753 12 52 1.3343 19 53 0.8479 49 54 0.8025 50 55 0.3997 58 56 0.9320 42 57 0.7028 53 58 6.8783 1 59 1.2922 25 80 2.7439 6 61 2.4636 8 62 3.0055 5 63 1.2203 28 64 1.0731 33 65 0.2357 .27 66 0.0 66 r) Lo . 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