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1 Agricultural & Applied Economics Association U.S. Agriculture in a General Equilibrium Framework: Analysis with a Social Accounting Matrix Author(s): Irma Adelman and Sherman Robinson Source: American Journal of Agricultural Economics, Vol. 68, No. 5, Proceedings Issue (Dec., 1986), pp Published by: Blackwell Publishing on behalf of the Agricultural & Applied Economics Association Stable URL: Accessed: 21/05/ :11 Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use. Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at Each copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printed page of such transmission. JSTOR is a not-for-profit organization founded in 1995 to build trusted digital archives for scholarship. We work with the scholarly community to preserve their work and the materials they rely upon, and to build a common research platform that promotes the discovery and use of these resources. For more information about JSTOR, please contact support@jstor.org. Blackwell Publishing and Agricultural & Applied Economics Association are collaborating with JSTOR to digitize, preserve and extend access to American Journal of Agricultural Economics.

2 Doable General Equilibrium Models (Brian D. Wright, University of California, Berkeley, presiding) U.S. Agriculture in a General Equilibrium Framework: Analysis with a Social Accounting Matrix Irma Adelman and Sherman Robinson Traditionally, the analysis of U.S. agricultural policy has been carried out in a partial equilibrium framework. It has thus ignored the linkages of the agricultural sector with the rest of the economy. It is only recently that the importance of various economic linkages has started being recognized in work on U.S. agriculture. The importance to the agricultural sector of exchange rates and other instruments of monetary and fiscal policies was first emphasized by Schuh. His seminal work sparked other studies of the interaction between agricultural production and incomes and traditional instruments of macroeconomic policy. See also Shei; Chambers and Just; Freebairn, Rausser, and de Gorter. The partial equilibrium analysis of U.S. agriculture stands in sharp contrast to traditional approaches to the formulation of agricultural policy in developing countries. Development economists have long been sensitive to the importance of leakages from policies aimed at the agricultural sector to the rest of the economy and vice versa. In this paper, we discuss how multisectoral models of the sort often used in developing countries can be used to analyze such issues in the United States. We construct a U.S. social accounting matrix (SAM) for 1982 and use a variety of multiplier models to analyze the impact of different exogenous shocks on agriculture, focusing on the links between the agricultural and nonagricultural sectors. A longer version of this article is provided by Adelman and Robinson. Irma Adelman is a professor of economics and agricultural economics, and Sherman Robinson is a professor of agricultural economics, University of California, Berkeley. Giannini Foundation Paper No. 825 (reprint identification only). Financial support for the research reported in this paper was provided by the Giannini Foundation of Agricultural Economics. The authors wish to thank Dominique Van der Mensbrugghe and David Wells Roland-Holst for computer programming and research assistance. They would also like to thank Engineering Economics Associates for allowing them to use their updated U.S. input-output table for Social Accounting Matrices A standard input-output model includes the intersectoral flows of intermediate inputs and so captures one major source of linkages in the economy. However, the input-output model ignores the flows from producing sectors to factors of production (value added) and then on to entities such as government and households and finally back to demand for goods. A social accounting matrix expands the inputoutput accounts to include a complete specification of the circular flow in the economy. The development of SAMs was partly motivated by the need to reconcile the national income and product accounts (NIPA) with the input-output accounts within a unified framework.' The SAM describes the full circular flow of money and goods in an economy. The rows and columns represent the receipt and expenditure accounts of economic actors. Thus, a defining characteristic of a SAM is that it is a square matrix whose row and column sums must balance. The conventions of doubleentry bookkeeping guarantee that there will be no leakages or injections into the system, and there is no room for any "statistical discrepancy"-every flow must go from some actor to some other actor. Tables 1 and 2 present a multisectoral SAM which has been constructed starting from the U.S. input-output matrix for The particular aggregation used was chosen with a view to facilitating tracing through the linkages between agriculture and the rest of the economy.2 Agriculture is disaggregated into seven This work was strongly influenced by Sir Richard Stone, who was instrumental in the development both of SAMs and of the United Nations standard System of National Accounts (SNA). See Stone, United Nations, and Pyatt and Round (1985) for discussions of SAMs. 2 The full input-output table has 528 sectors and was produced by Engineering Economics Associates of Berkeley, California, Copyright 1986 American Agricultural Economics Association

3 Table 1. Aggregate SAM for the United States, 1982 Activities Value Added Institutions Households Agric. Labor Capital Indirect Propri- Enter- Agric. Related Other Income Income Taxes Labor etors prises Low 40% Med. 40% High Account Activities ($ billions) 1 Agriculture Ag. related act Other activities Sum Value added 4 Labor income Capital income Ind. bus. taxes Sum Institutions 7 Labor Proprietors Enterprises Sum Households 10 Low 40% Med. 40% High 20% Sum Capital account Government Rest of the world Totals Source: data provided by Engineering Economics Associates.

4 Table 2. Sectoral Activity Accounts, U.S. SAM, 1982 Input-Output Flows: Dairy, Meat Food Feed Cotton Fruits Tobacco Prcssd Chemi- Whlsale Poultry Animals Grains Grains & Oil Nuts Sugar Sum Food cals Utilities Retail Agriculture 1 Dairy, poultry, eggs 2 Meat animals 3 Food grains 4 Feed grains, etc. 5 Cotton, oil crops 6 Fruits, nuts, veget. 7 Tob., sugar, other Sum ($ billion) Agriculture related 8 Food & tob. prod. 9 Chemicals 10 Utilities 11 Whlsale & retail trade 12 Bank, ins. & real est. 13 Services Sum Other activities Total intermediate Value added 15 Ag empl. comp. 16 Ag prop. inc. 17 Ag ind. bus. tax 18 Non-ag empl. comp. 19 Non-ag prop. inc. 20 Non-ag ind. bus. tax Total value added Total gross output Rest of the world Total supply

5 Adelman and Robinson Doable General Equilibrium Models 1199 Table 2. Continued. Sectoral Activity Accounts, U.S. SAM, 1982 Final Demands Households Total Capital Total Row Low 40% Med. 40% High 20% Consmpt Account Govt. Exports Fnl Dmnd Totals Agriculture ($ billion)-. 1 Dairy, poultry, eggs Meat animals Food grains Feed grains, etc Cotton, oil crops Fruits, nuts, veget Tob., sugar, other Sum Agriculture related 8 Food & tob. prod Chemicals Utilities Whlsale & retail Bank, ins. & real est Services Sum Other activities Total final demand Source: data provided by Engineering Economics Associates. sectors. The aggregation of the nonagricultural sectors has been chosen so that the sectors that have large linkages with agriculture are kept separate. All other sectors are aggregated into single sectors (row 14, table 2). In the SAM, value added is distributed to three types of institutions: workers, proprietors, and incorporated enterprises.3 The institutions, in turn, distribute their incomes to three types of households: the poorest 40%, the next 40%, and the richest 20%. There is one capital account, which consolidates all financial markets, serving to collect savings and purchase investment goods.4 The SAM in table 1 provides a framework for reconciling the input-output and national income and product accounts (NIPA) for the United States. For example, the sum of value added, $3,069 billion, equals gross national product (GNP) in The various entries in starting from the 1977 U.S. table produced by the U.S. Department of Commerce. The 1977 table is described in U.S. Department of Commerce. 3 These definitions follow the conventions used in the U.S. National Income and Product Accounts. 4 As defined, the SAM does not specify investment by sector of destination. To distinguish investment by sector of destination requires disaggregating the capital accounts. 5 Total value added equals GNP rather than gross domestic product (GDP) because the U.S. input-outputable includes a sector called "rest-of-the-world industry" which includes net factor income from abroad. In most other countries, value added from the input-outputable equals GDP. the institutional accounts in the body of the SAM have all been reconciled with the published macro accounts. An examination of table 2 indicates that the linkages among the agricultural sectors are rather small, except for the large expenditure flows from dairy and poultry (1) and meat animals (2) to feed grains. The leakages from agriculture to the rest of the economy, however, are quite large. About 60% of total gross agricultural expenditures are on purchases of nonagricultural inputs. By contrast, agriculture represents only 3.2% of aggregate gross production and accounts for only 2.2% of aggregate value added. In terms of final demand, agriculture represents only one percent of aggregate consumption (and 9.7%, adding in processed food, beverages, and tobacco). Agricultural exports are about 6% of total exports (10.2%, adding in processed food, beverages, and tobacco).6 In sum, agriculture is a relatively small sector in the U.S. economy. There are significant backward linkages from agriculture to the rest of the economy through intermediate inputs and some forward linkages, especially in food 6 As is common with input-output data, there are problems distinguishing between agriculture and processed food. Trade data reported by the Department of Agriculture use different definitions, including part of the processed food sector in the inputoutput table in agriculture.

6 1200 December 1986 processing. Property income constitutes about 70% of agricultural value added. Taxes, both personal and business, are about 9% of value added in agriculture and 16% outside of agriculture; the sector thus receives significant tax breaks. SAM Multipliers Within the SAM framework, the simplest way to create a model is to assume that the various column coefficients are all constant, as in the input-output model. One problem, however, is that the matrix is square and the coefficients in every column sum to one. There are no exogenous elements and hence no multipliers. One approach to modeling is to specify one or more accounts as being exogenous. The result is a partitioned SAM, with some columns specified as exogenous and some rows excluded: (1) Activities A O F Value added A* = V 0 0 Endogenous institutions 0 Y T where A* is the matrix of SAM coefficients (n + m + k, n + m + k); A, matrix of inputoutput coefficients (n, n); V, matrix of value added coefficients (m, n); Y, matrix of income distribution coefficients (k, n); F, matrix of expenditure coefficients (n, k); T, matrix of interinstitutional transfer coefficients (k, k); n, number of sectors; m, number of value added categories; and k, number of endogenous institutions. Given the choice of exogenous accounts, the balance equations can be written (2) x ex A* v = ev, y ey where x is the vector of sectoral supply (n, 1); v, vector of value added by categories (m, 1); y, vector of institutional incomes (k, 1); ex, vector of exogenous sectoral demand (n, 1); ev, vector of exogenous value added (m, 1); and ey, vector of exogenous institutional incomes (k, 1). Inverting A*, we can write the multiplier matrix equation relating changes in sectoral supply, value added, and institutional income to changes in the exogenous variables: (3) x v Y ex = M e, ey where M = (I - A*) 1. The choice of which accounts to specify as being exogenous is important. Standard practice is to pick one or more of the capital, government, and rest-of-the-world accounts, justifying the choice on the basis of macroeconomic theory. The resulting multiplier model is completely demand driven, since no constraints on supply are specified, and is thus very Keynesian in spirit. In each case, a shock is defined as a change in elements of the exogenous columns. The computed multipliers will be sensitive to the choice, and the realism of the resulting model must be judged on the basis of the particular question under study. In the empirical results presented below, we have chosen to make the government and restof-the-world accounts exogenous and keep the capital account endogenous. Given the swings in foreign trade and government expenditure during the early 1980s, it seems reasonable to make those accounts exogenous. It is also reasonable to make investment endogenous, adjusting to the changes in savings resulting from the swings in the balance of trade and government fiscal policy. The SAM model thus focuses on the adjustment of the economy to shocks arising from changes in government expenditures and exports. Decomposition of SAM Multipliers Amer. J. Agr. Econ. The SAM presented in table 1 has a characteristic structure relating to the circular flow of income. From equation (3) it can be seen that one cycle from activities back to activities is achieved in three steps. First, the V coefficients map the flow of income from activities to factors of production. Second, the Y coefficients map the flow from factors to institutions. Finally, the F coefficients map from institutional income back to demand for activities. The elements on the main diagonal [the A and T coefficients in equation (3)] capture interactions within these blocks of the SAM independently of links between blocks. Given this structure, it has been shown that the multiplier matrix M can be decomposed

7 Adelman and Robinson into the sum of four terms involving three additive multiplier matrices:7 (4) M = I + (C1 - I) + C2 + C3, where (I - A)- C1 = (I - T) C2 is a matrix with blocks of zeros down the main diagonal and nonzero elements off the diagonal, and C3 is a block diagonal matrix. The elements of the C2 and C3 matrices are based on the partitioned inverse of A* defined in equation (1).8 Each element can thus be written as a function of the elements of A*. The fact that the decomposed multiplier matrices have an off-diagonal and diagonal block structure follows from the structure of A*. The first term, I, represents the impact effect of the exogenous shock. The second term, Cl - I, gives the net contribution of "transfer multiplier effects," or multiplier effects within the blocks of accounts.9 The two together, C1, define the "own effects" multipliers. The upper left element of Cl is simply the leontief inverse. If the other two blocks of accounts are treated as exogenous, the model collapses to the usual input-output multiplier model. The third term, C2, describes the net contribution of "open-loop" or "cross-multiplier" effects. These represent the impact of linkages between blocks of accounts. Finally, the fourth term, C3, describes the net contribution of "closed-loop" or "circular-multiplier effects." These are within-block effects that arise from the shock after passing from a block, through the open-loop effects, and back to the block. In terms of the structure of the particular SAM used here, the first two terms of the multiplier decomposition describe the direct, within-block effects. For example, for a shock which consists only of an exogenous increase in some sectoral demands by government or exports, the only relevant part of the C1 matrix is the leontief inverse, and the within See Pyatt and Round (1979) and Stone. Pyatt and Round use a multiplicative decomposition, while the additive version we present below is from Stone. 8 After dividing A* into the sum of two matrices, one consisting of its main diagonal and the other of the off-diagonal elements. Use is also made of the series expansion of the inverse. 9 The term is from Pyatt and Round (1979). Their terms for the other effects will also be used below. Doable General Equilibrium Models 1201 block effects consist only of the intersectoral or input-output multipliers. The third and fourth terms, taken together, capture the net effect of expanding the model to include the value added and institutional linkages. They thus might be described as the "net SAMlinkage effects," which supplement the inputoutput linkage effects. SAM Multipliers for the U.S. Economy The matrix of SAM multipliers, M, is given in table 3. Table 4 gives the percentage shares of the net SAM-linkage effects, or the sum of the elements of the last two terms in the decomposition (C2 + C3, defined above) divided by the elements of the total induced multipliers, removing the initial injection; that is, (M - I). Consider, for example, the multipliers in column 1 of table 3. An increase of $1 billion of exogenous demand for dairy and poultry output induces an additional increase of $47 million (over and above the original billion demand injection). Other sectors with significant increases include feed grains, food processing, chemicals, utilities, wholesale and retail trade, services, and finally, banking, insurance, and real estate. The original increase of a billion dollars of demand for dairy products generates an induced additional demand of $640 million for agricultural output and a $4.47 billion increment in demand for nonagricultural production. Of the $640 million induced indirect increase in agricultural demand arising from the increase in demand for dairy products, the decomposition calculation indicates that only 14.9% can be attributed to net SAM-linkage effects (see table 4). Most of the indirect feedback to the agricultural sectors comes from input-output linkages. For all the agricultural sectors, however, there is an asymmetry between the leakages into and out of the sectors. Most of the income generated by an increase in agricultural demand leaks out of agriculture. From table 3, the nonagricultural value-added multipliers for demand increases in the agricultural sectors range from 1.8 to 2.1, while the nonagricultural value-added multipliers range from 0.3 to 0.7. This "leakage across" phenomenon is a characteristic feature of the response in all the agricultural sectors. There are two causes for this leakage-across effect. First, for most of the agricultural sec-

8 1202 December 1986 Amer. J. Agr. Econ. Table 3. The Multiplier Matrix, M Activities Dairy Meat A Food G Feed G Cotton Fruits Tob., S Food & T Chemic Utilit Whlsal Bank, I Servic Other Activities 1 Dairy, poultry, eggs Meat animals Food grains Feed grains, etc Cotton, oil crops Fruits, nuts, veget Tob., sugar, other Sum Food & tob. prod Chemicals Utilities Whlsale & retail Bank, ins. & real est % Services Sum Other activities Value added 15 Ag empl. comp ' Ag prop. inc Ag ind. bus. tax Sum Non ag. empl. comp Non ag. prop. inc Non ag. ind. bus. tax Sum Endogenous institutions 21 Labor force Proprietors Enterprises Sum Low 40% households Med. 40%households High 20% households Sum % Capital account tors, intermediate inputs come largely from the nonagricultural sectors. Second, demand for agriculture is a small proportion of total final demand, even taking into account processed foods. So the SAM-linkage effects benefit mostly the nonagricultural sectors. The size of the linkages with processed food on the output side and with wholesale and retail trade on the input side emphasizes the importance of middlemen in U.S. agriculture. Since the SAM distinguishes households by income quantiles, it is possible to trace the impact of a given shock on the size distribution of income. For example, consider again a billion dollar increase in demand for dairy products. The resulting overall increment in household incomes is distributed quite unequally: the poorest 40% of households receive an increase of $190 million, the next 40% an increase of $713 million, and the richest 20% an increase of $848 million. There is thus a trickle-up of income. And the distribution of the marginal increment is more unequal than the original distribution of disposable income, so the relative distribution worsens as well. From the 1982 SAM, the share of aggregate disposable income of the poorest 40% of households was 17%; of the next poorest 40%, it was 40%; and of the richest 20%, it was 43%. The distribution of the marginal increment in household income generated by the multiplier process from an increase in dairy demand is 10% to the poorest, 41% to the next 40%, and 48% to the richest 20%. The net marginal effect of the multipliers is to transfer income from the poorest 40% to the richest 20%. A similar story holds for the multipliers for the other agricultural sectors.

9 Adelman and Robinson Doable General Equilibrium Models 1203 Value Added Endogenous Institutions Ag Emp Ag Pro Ag Ind Non-Ag Non-Ag Non-Ag Labor Propri Enterp Low 40 Med. 40 High 2 Capita Trade and Transfer Experiments In this section, we use the SAM to perform several experiments to analyze how different shocks would affect U.S. agriculture. Table 5 summarizes the results of four experiments, each of which involves a $10 billion increase in demand or injection into the SAM spread over different exogenous accounts. The experiments are (1) an increase in agricultural exports, (2) an increase in manufacturing exports, (3) an increase in agricultural value added, and (4) an increase in household incomes. Each experiment is described in three columns: the first column describes the sectoral or institutional distribution of the injection (the distribution of the injection is spread across.across the affected accounts in proportion to t the original flows); the second column gives the changes in the receipts of each endogenous account in the SAM; the third column presents the results in terms of percentage changes. The first two experiments are straightforward. The third experiment, an injection of value added to the agricultural sectors, can be seen as reflecting a mix of policies. For example, price supports, keeping quantities unchanged, result in direct increases in value added with no change in input demand. Alternatively, input subsidies combined with output controls also result in an effective subsidy to value added.10 The third experiment can be 10 Such subsidies include, for example, the farm credit program. Another example is subsidized provision of irrigation water. In developing countries, there are often major subsidies to inputs such as fertilizers and pesticides.

10 1204 December 1986 Amer. J. Agr. Econ. Table 4. Net SAM-Linkage Effects Dairy Meat A Food G Feed G Cotton Fruits Tob., S Food & T Chemical Utility Trade Bank Svcs Other Agriculture (%) 1 Dairy, poultry, eggs Meat animals Food grains Feed grains, etc Cotton, oil crops Fruits, nuts, veget Tob., sugar, other Sum Agriculture related 8 Food & tob. prod Chemicals Utilities Whlsale & retail Bank, ins., real est Services Sum Other activities Notes: Net SAM-linkage effects (C1) as a percent share of total induced multiplier (M - I). See text for explanation. Table 5. Results of the Experiments 1982 Value Experiment 1 Experiment 2 Experiment 3 Experiment 4 $10b Increase of Agric. $10b Increase of Mfg. $10b Transfer to $10b Transfer to Exports Exports Agric. Value Added Households Shock Change % Change Shock Change % Change Shock Change % Change Shock Change % Change Activities 1 Dairy, poultry, eggs Meat animals Food grains Feed grains, etc Cotton, oil crops Fruits, nuts, veget Tob., sugar, other Sum Food & tob. prod Chemicals Utilities Whlsale & retail Bank, ins. & real est Services Other activities Sum Value added 15 Ag. empl. comp. 16 Ag. prop. inc. 17 Ag. ind. bus. tax Sum Non-ag. empl. comp Non-ag. prop. inc Non-ag. ind. bus. tax Sum Endogenous institutions 21 Labor force 22 Proprietors 23 Enterprises Sum Low 40% households Med. 40% households High 20% households Sum Capital account

11 Adelman and Robinson seen as describing the result of such policies, although the SAM does not directly incorporate price effects. The fourth experiment, an exogenous injection of income to households, is intended to reflect a general increase in prosperity. Given the definition of the exogenous accounts in the SAM, it can be viewed as being brought about through an increase in government transfers to households or a general cut in individual taxes. The results in table 5 indicate that farmers benefit most from direct income transfers. A direct transfer of $10 billion to farmers yields an increase in their value added of $10.37 billion (15%). This transfer, however, generates large absolute leakages into nonagricultural incomes. Nonagricultural value added rises by $19 billion. The indirect multiplier on nonagricultural value added is thus 1.9, compared to for agricultural value added. This large "leakage across" effect may help explain why agricultural support policies have such wide political support. However, since agriculture is a relatively small share of the aggregate economy, the trickle-across effects of the income transfer to agriculture, while large in absolute terms or as a share of agricultural value added, yield only small percentage changes outside of agriculture. In terms of its impact on agricultural incomes, the next most potent experiment is an increase in agricultural exports. An increase of exports of $10 billion increases agricultural value added by $5.3 billion (7.83%) and gross farm sales by $12.7 billion. As before, however, its impact on nonagricultural incomes is larger. Nonagricultural value added rises by $20.6 billion, a multiplier of 2.06 compared to 0.53 for agriculture. An increase in agricultural exports thus generates more leakages than a direct transfer to farmers. The reason for the increased leakages is that, in contrast to the transfer experiment, agricultural output also increases, leading to increased demand for intermediate inputs. Value added in the major sectors providing inputs to agriculture thus rises. The $12.7 billion increase in agricultural sales generates the following increases in value added for sectors that are major suppliers of agricultural inputs: chemicals, $1.0 billion; utilities, $1.9 billion; wholesale and retail trade, $3.1 billion; banking, insurance, and real estate, $4.5 billion; and services, $4.6 billion. Experiments 2 and 4 indicate that farmers do not benefit much from an increase in pros- Doable General Equilibrium Models 1205 perity in the nonfarm sector. In experiment 2, an increase in nonmanufacturing exports has a multiplier of only on agricultural production and of on agricultural value added, compared to 2.12 for nonagricultural value added. Note that the increase in nonagricultural incomes generated by an increase in nonagricultural exports is only slightly higher than that generated by an increase in agricultural exports (a multiplier of 2.12 as compared to a multiplier of 2.06). The leakage from agriculture is dramatic, with most of the increase in both cases accruing to the nonagricultural sectors. In experiment 4, a general rise in household incomes has very little effect on the farm sector. The gross output multiplier for agriculture is only 0.13 and the value-added multiplier is only 0.042, while the multiplier on nonagricultural value added is The increase in food consumption is a small share of the increase in total consumption, and most of it is in the form of demand for processed foods. Middlemen and suppliers of agricultural inputs capture most of the induced effects of increases in food consumption. It is interesting to examine the income distribution effects of the experiments. All of them make the relative size distribution of income substantially more unequal. The percentage changes they induce in the incomes of the poorest households are smaller than their average income share, and the percentage increases in the incomes of the richest households are larger than their average share. The smaller marginal share of the poorest households in the induced multipliers is due largely to the fact that government transfers, which remain unaffected by the experiments, represent about half of their disposable income. The experiments all lead to increases in aggregate income. However, government transfer payments are fixed exogenously and do not increase, thus leaving the poorest households behind. This phenomenon arises from our choice of exogenous accounts but also reflects a real structural feature of the U.S. economy. Much of government transfer income consists of pensions and social security as well as welfare payments. These tend to be fixed in nominal terms and do not increase with economic expansion. Insofar as they also do not fall in a recession, any general contraction will lead to a decrease in relative inequality. While all the experiments lead to a trickle up of income from the poor to the rich, those which transfer more income to agriculture

12 1206 December 1986 have the most unequalizing effects. This result is due to the fact that the share of property income in agricultural value added is higher than in nonagricultural value added, and property income is distributed more unequally than wage income. In summary, a number of lessons can be drawn from these experiments for the role of agriculture in the U.S. economy. First, given the small trickle across to agriculture of income-raising measures outside of agriculture, if one decides to formulate policies that benefit farmers, these policies must be targeted directly at them. This result is in strong contrast to the situation of the farm sector in developing economies, where farmers capture a large share of the benefit of urban income increases. Second, because of the large trickle across out of agriculture, partial equilibrium analysis of the impact of policy upon farmers is likely to be misleading. Third, the antimiddleman attitude of farmers has a strong basis in fact; middlemen do capture the lion's share of benefits from farm production. Fourth, the widespread view of farmers that exports of agricultural products have a large impact on their income is correct. This means, inter alia, that general trade policy matters to the farm sector. Fifth, programs to raise farm incomes lead to a trickle up of income in the overall economy. This again contrasts with the situation in developing countries in which the overwhelming majority of the poor are farmers and agricultural laborers. In developing countries, policies that benefit farmers, even after leakages are taken into account, reduce economywide inequality. Conclusion The SAM-based analysis has enabled us to explore important structural features of U.S. agriculture and has given upper bounds on the quantitative impact of various types of interventions intended to benefit farmers. While the behavioral specification used in the SAMbased multiplier analysis emphasizes important linkages in the economy, it is too simple for much policy analysis. The model is demand driven and completely ignores issues of resource allocation, productivity, and factor utilization. With its fixed coefficients, the model ignores substitution possibilities in consumption, production, imports, and exports triggered by changes in relative prices. It also ignores possibilities for partial shifting of the incidence of taxes, tariffs, and subsidies through interactions between supply and demand. Finally, the model does not capture the behavior of economic agents interacting across markets in response to shifts in price signals, which constitute the major mechanism by which (nontransfer) government policies affect the economy. These deficiencies can be remedied by embedding optimizing behavior in the description of the behavior of the various institutions in the SAM and allowing the production and demand functions to be more flexible. The next step in the research agenda is to use the SAM accounting framework as a basis for constructing a computable general equilibrium (CGE) model."1 Such a model incorporates price-responsive supply and demand behavior, and its solution yields relative prices as well as quantities and all the nominal accounts in the SAM. By simulating the workings of a market economy, a CGE model can provide a useful framework for doing policy analysis in an environment in which changes in prices (such as the exchange rate) and the resulting changes in incentives are important determinants of performance. References Amer. J. Agr. Econ. Adelman, I., and S. Robinson. The Application of General Equilibrium Models to Analyze U.S. Agriculture. Dep. Agr. and Resour. Econ. Work. Pap. No. 423, University of California, Berkeley, Chambers, R. G., and R. E. Just. "Effects of Exchange Rates on U.S. Agriculture: A Dynamic Analysis." Amer. J. Agr. Econ. 63(1981): Dervis, K., J. de Melo, and S. Robinson. General Equilibrium Models for Development Policy. Cambridge: Cambridge University Press, Freebairn, J. W., G. C. Rausser, and H. de Gorter. Monetary Policy and U.S. Agriculture. Dep. Agr. and Resour. Econ. Work. Pap. No. 266, University of California, Berkeley, Pyatt, G., and J. I. Round. "Accounting and Fixed-Price Multipliers in a Social Accounting Matrix Framework." Econ. J. 89(1979): , eds. Social Accounting Matrices: A Basis for Planning. Washington DC: World Bank, Robinson, S. Multisectoral Models of Developing Countries: A Survey. Dep. Agr. and Resour. Econ. Work. Pap. No. 401, University of California, Berkeley, CGE models applied to developing countries are surveyed in Robinson and in Dervis, de Melo, and Robinson. CGE models of developed countries are surveyed in Scarf and Shoven.

13 Adelman and Robinson Doable General Equilibrium Models 1207 Scarf, H. E., and J. B. Shoven. Applied General Equilibrium Analysis. Cambridge: Cambridge University Press, Schuh, G. E. "The Exchange Rate and U.S. Agriculture." Amer. J. Agr. Econ. 56(1974):1-13. Shei, Shun-Yi. "The Exchange Rate and United States Agricultural Products Markets: A General Equilibrium Approach." Ph.D. thesis, Purdue University, Stone, J. R. N. "The Disaggregation of the Household Sector in the National Accounts." Social Accounting Matrices: A Basis for Planning, ed. G. Pyatt and J. I. Round. Washington DC: World Bank, U.S. Department of Commerce, Bureau of Economic Analysis. The Detailed Input-Output Structure of the U.S. Economy, Washington DC, United Nations. Towards a System of Social and Demographic Statistics. Series F, No. 18. New York, 1975.