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Expanding the policy dimension of farming systems research
Agricultural Systems 33 (1990) 271-287
Expanding the Policy Dimension of Farming Systems Research Roger Fox, a Tim Finan, b Scott Pearson c & Eric M o n k e a a Department of Agricultural Economics, b Bureau of Applied Research in Anthropology, University of Arizona, Tucson, Arizona 85721, USA c Food Research Institute, Stanford University, Stanford, California 94305-6084, USA (Received 17 July 1988; revised version received 12 July 1989; accepted 15 September 1989)
A BSTRA CT The contribution of economics to farming systems research (FSR) has usually been restricted to the microeconomic analysis of alternative agricultural production technologies. In the traditional approach to FSR, macroeconomic variables and government policies are treated as exogenous. This paper discusses one method for expanding the policy analysis dimension of FSR. The policy analysis matrix method allows for the explicit treatment of macroeconomic and sectoral policies, and it builds logically on the wealth of technical and microeconomic data traditionally utilized in FSR. Examples from Portuguese agriculture are used to illustrate the method.
INTRODUCTION The contribution of economics to farming systems research (FSR) has usually been restricted to the microeconomic analysis of alternative agricultural production technologies, particularly within the context of the rapid rural appraisal (Hildebrand, 1981; Shaner, 1984). FSR studies based on detailed farm surveys also have been conducted in many developing countries (e.g. Norman et al., 1982)i Good economic analysis at the farm level is essential to the development and introduction of new, locationspecific technologies. The ability to identify economic constraints and the 271 Agricultural Systems 0308-521X/90/$03.50 © 1990 Elsevier Science Publishers Ltd, England. Printed in Great Britain
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flexibility of existing systems, and to evaluate the impacts, including the distribution of benefits, of alternative technologies represents a major contribution of economists to FSR. FSR's contribution also includes direct influence on the priorities for applied agronomic research, thereby affecting research policy. In the traditional approach to FSR, macroeconomic variables and government policies are treated as exogenous (Norman, 1980; Byerlee et al., 1982; Shaner et al., 1982; Simmonds, 1984). From the perspective of the farmer, this approach is generally valid: individual farmers have little or no influence over macroeconomic and sectoral policies. However, from the perspective of development policy, knowledge of the impacts of policy on farmer decisions is extremely valuable. This is even more important when the heterogeneity of farming systems is acknowledged and policy impacts are presented on a regional basis and/or by farm size, farm type, age of farmer, cultural classification, gender of farmer, etc. Furthermore, policies can be changed. Objectives of government policymakers and their attitudes toward agricultural development are likely to alter over time. Even though individual farmers have little influence, associations of farmers may affect changes in policies and programs. Knowledge of the impacts of alternative policies thus can be as important for technical change as the microeconomic analysis of alternative technologies. Expanding the policy dimension of FSR is especially relevant (a) when a basic understanding of policy effects at the farm level is lacking, (b) when farms are not homogeneous, (c) when new policies are needed to support the introduction of technological change, (d) when significant changes in a set of policies are fairly likely (the Portugal case discussed below), (e) when policies are in a state of flux and analysis can be an input into the process of policy change, and (f) when technology generation has a long term perspective. Since most developing countries are characterized by one or more of these situations, integrating policy analysis with FSR can be extremely productive. The benefits to FSR of broader policy considerations are numerous. Since the ultimate goal of FSR is to develop, test and introduce appropriate, sustainable agricultural technologies, knowledge of the effects of economic policy alternatives becomes a critical element in making FSR recommendations and in adoption decisions. For example, changes in input and output prices resulting from exchange rate adjustments may significantly alter the profitability of alternative technologies. Conversely, the adoption of a new technology resulting from FSR efforts may change the comparative advantage of the activity and create a potential for efficient export production. In both examples, knowledge of the potential impacts of the changes is important for policymakers, FSR practitioners and farmers.
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This paper discusses one method for expanding the policy analysis dimension of FSR. In a sense, it responds to those FSR practitioners who recognize the need for policy analysis and include a policy loop in their FSR diagrams, but have not developed a methodology to accomplish their objectives (Infanger, 1985; Oasa & Swanson, 1986). The method allows for the explicit treatment of macroeconomic and sectoral policies, and it builds logically on the wealth of technical and microeconomic data traditionally utilized in FSR. Examples from Portuguese agriculture are used to illustrate the method. Many methods of policy analysis exist and some of them, such as the methods based on linear programming, are complementary with FSR and make good use of FSR data. The method presented in this paper has some unique advantages and is highly complementary with FSR efforts. Its use, however, does not preclude the need for other types of policy analysis.
METHOD The method of analysis described in this paper can be used to address a number of important policy issues that influence technical change in agriculture. For example, input and output price policies, factor market policies, and exchange rate policies can all be analyzed in terms of their impacts on farm-level decisions. The macro-micro linkages, so important for useful policy analysis, are explicitly treated in the method. The FSR contribution and linkage is clearly at the micro end of the spectrum. Simulation analysis can be used to evaluate alternative policy scenarios, both current and future. The method is variously called 'social profitability analysis', 'social and private profitability analysis', 'comparative advantage analysis' and 'policy analysis matrix' (PAM) (Monke & Pearson, 1989). The method requires the definition of commodity or whole-farm systems. The systems are defined to include activities beginning with the farm and ending with the market, usually the wholesale market, where comparable world market prices can be measured. The definition of appropriate systems at the farm level is the principal contribution that FSR can make to the analysis. Without a strong foundation built on detailed knowledge of existing and potential farming systems, the quality of the policy analysis suffers. In countries where FSR and other farm-level studies exist, application of PAM is greatly facilitated. The principal task of the policy analyst is to construct, for each system, an accounting matrix of revenues, costs and profits, first including and then excluding the effects of policy. This is done for a base year and can be projected using assumptions about changes in the underlying variables that are influenced by policy. In any given year the impact of policy can be gauged through comparison with the situation in the absence of such
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policy. This 'efficiency' calculation assumes that policymakers have available a full range of policy options. When the ability of policymakers to adjust particular variables is limited by external agreements, such as customs unions, a second calculation, of 'constrained efficiency', can be used to incorporate this limitation.
Profitability and efficiency The basic accounting identities that underlie the analysis are illustrated in Table 1. The first identity measures profits as the difference between receipts and costs, where the cost items include both purchased inputs and domestic factors of production. Private profitability, which includes the effects of policy, is calculated as the residual when marked costs of inputs--materials and factors--are subtracted from the market value of the output. Calculation of private profitability for the base year is the first step in the analysis; it shows how decision-makers have actually reacted to the incentives or disincentives created by government policy. Receipts, costs and profits are measured separately for each of the activities in the system, and then entries are aggregated to represent the entire system. In Table 1, the calculation of private profitability (entered as D) is represented in the top row; receipts (A) less input costs (B) and factor costs (C) yield profits (D), with all entries given in private (actual market) prices. The calculation of private profitability at the farm level is routinely done by economists working in FSR projects. Although the techniques of measurement may vary, the underlying concepts are universal. The calculation of private costs and returns for post-farm activities is not normally done in FSR studies and represents additional work required for the application of PAM. Evaluation of profit in social terms requires assigning prices to outputs and inputs (and hence profits) that reflect the absence of domestic economic TABLE Accounting
1
Matrix for Efficiency and Policy Analysis
Receipts
Private prices Social prices Effects o f p o l i c y a n d m a r k e t i m p e r f e c t i o n s a P r i v a t e p r o f i t , D = A - B - C. h Social profit, H = E - F - G.
" O u t p u t t r a n s f e r s , I = A - E.
A E Ic
Costs
Profits
Tradable inputs
Domestic factors
B F ja
C G Ke
d I n p u t t r a n s f e r s , J = B - F. e Factor transfers, K = C- G. s N e t p o l i c y t r a n s f e r s , L = D - H = I - J - K.
D° Hh Ly
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policies, or, in economics jargon, underlying scarcity values or social opportunity costs. These social prices, if reflected in actual decisions, would result in an allocation of resources that would generate the highest contribution to national income. The crucial task for efficiency analysis, therefore, is to find reasonably accurate approximations for the social prices of outputs and inputs in the system. Social prices are not necessarily socially optimal. Private market prices might be preferable, if they allow attainment of some non-efficiency objectives. The method is particularly valuable in this circumstance, because it allows explicit calculation of the opportunity costs of non-efficiency objectives. For commodities that are tradable internationally, the appropriate social prices are the world prices, the CIF (cost, insurance, freight) price for imports or the FOB (free on board) price for exports. This implies that the government always has the choice of importing to meet domestic needs. The same reasoning applies to inputs needed for domestic production; they can either be imported or domestically produced. Hence, the world price is the appropriate standard for valuing their costs in domestic use. Domestic factors of production and nontradable inputs require different treatment, however, because no world price is available to serve as a benchmark for social valuation. Labor and capital are evaluated with respect to their social opportunity cost, the amount of national income foregone by removing a unit of that factor from its next best alternative activity. Scarce factors provide valuable services in production; the social opportunity costs of each factor is a measure of that scarcity. A key distinction is made here between fixed and variable factors. Labor and capital are considered as variable factors. They are assumed to be allocated freely between alternative uses. Land, however, is considered a fixed factor in agriculture. Its price is determined as a share (not known) of the profits left over after all variable factor and intermediate input costs are subtracted from receipts. Because capital costs are treated as variable, the budgets reflect long-run rather than short-run incentives. Maintenance of the longrun perspective mandates the use of long-run average values for other variables as well, such as yields and world prices. Nontradable inputs, such as services, local transportation, and commodities with very high international transportation costs, cannot be evaluated by making world price comparisons, since by definition they do not enter international commerce. In this method, both private and social costs of nontradable inputs are disaggregated into their underlying tradable input and domestic factor costs, the two cost categories shown in Table 1. Within the current FSR framework, the determination of social prices for outputs and inputs is normally not done and therefore represents additional work. The world prices of tradable outputs and inputs are not usually
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difficult to obtain. Also, estimates of the shadow prices of labor and capital may be available from project analyses, such as those conducted by the World Bank. The disaggregation of nontradable inputs represent a more difficult problem and can require the use of disaggregation coefficients from other countries or the analysis of the economic structure of the local industries providing nontradable goods and services. The calculation of social profitability follows easily, once the receipts and costs have been evaluated in social prices. With reference to the symbols in Table 1, the social prices output (E) and of tradable inputs (F) are given by CIF import or FOB export prices, the social valuations of factors (G) are their social opportunity costs, and social profitability (H) is the difference between receipts and costs in social prices (H = E - F - G). If social profits are positive, the activity is competitive at world prices and thereby is an efficient user of scarce resources and contributor to national income. The logic for expanding the normal FSR economic analysis of private profitability to include social profitability is that FSR analysts will have an understanding of the underlying economic efficiency of the systems that they are researching. Without this knowledge, the FSR program may be unwittingly contributing to the inefficient use of scarce resources. For policymakers, an understanding of the comparative advantage or disadvantage of various farming systems is an important aspect of policy analysis and decision-making. Tradable inputs and outputs are valued directly in terms of foreign exchange, and thus the difference between the value of tradable output (E) and all tradable input costs (F) gives an indication of the balance of trade contribution of an activity. However, an economic activity can only be truly said to 'save' or 'earn' foreign exchange if it is socially profitable, because this indicates the ability of the activity to use domestic resources (G) to generate foreign exchange (E - F). So long as domestic factors are scarce, their costs need to be included in evaluating foreign exchange effects. Removal of domestic factors from the production of an alternative commodity will either reduce the exports of that commodity or require increases in imports to substitute for the decline in domestic production. The net actual foreign exchange saving is, therefore, E - F - G, which is the measure of social profitability. In this context, positive social profitability is an indication of comparative advantage or the ability to compete in international trade efficiently, i.e. without the stimulus of subsidies or other government assistance.
Effects of policy The second fundamental accounting identity in the analysis is that the
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difference between valuation of any column entry in Table 1 (receipts, costs or profits) in private prices and in social prices gives a measure of the effects of policy. This difference will also include the effects of any market imperfections, which prevent product or factor markets from allocating outputs or inputs efficiently. Market failures are ignored in the remainder of this section to allow an emphasis of the effects of policy. There is a close relationship between the calculation of social profitability and measurement of the effects of policy, as shown in the third row of Table 1. In the absence of market imperfections, only government policy can cause a divergence between private and social prices. Unless the government enacts a protection policy, for example, each importable output and input will be available at its CIF import price, which will in turn become the domestic price. In Table 1, A will equal E, and B will be the same as F. Consequently, any difference between A and E or between B and F is caused by some combination of trade restriction, price control, tax/subsidy or exchange rate policies. If A exceeds E, either domestic consumers are forced to pay higher than world prices or the government treasury is directly subsidizing production, causing an output transfer (I) equal to A - E . Similarly, if B is greater than F, tradable inputs are being taxed resulting in an input transfer (J) from the system of B - F. For domestic factors, the transfer (K) amounts to C - G; if there were a positive transfer to the system, say from a credit subsidy, then C would be less than G, and K would be negative. The social prices of tradable outputs (E) and of tradable inputs (F) are established in international markets and most countries have little or no power to influence these prices. Commodity price policies in these countries, therefore, have no significant effect on the social valuation of tradable commodities. Exchange rate policy can, however, cause the private prices of tradables (A and B) to be either higher or lower than efficiency levels (E and F) in a manner that is directly analogous to use of a trade-restrictive policy for a given output or input. This result would be achieved, for example, if the government employed a fixed exchange rate policy and chose fiscal and monetary policies that permitted a rate of inflation higher than the average rate experienced in its main trading partner countries. An overvalued exchange rate depresses the prices of tradables relative to those of nontradables and thus acts as a tax on all tradable (exporting or import-substituting) activities and as a subsidy on imports. For example, if the exchange rate were overvalued by 20%, imports of corn would be 20% cheaper in domestic currency than their social opportunity cost and local corn farmers would receive 20% less for their output (in the absence of policies affecting corn prices). In Table 1, A would be less than E by 20%, and the effect of the overvalued exchange rate policy would be shown in I. The
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tax effect of overvaluation on output would be partially offset by a subsidy effect on tradable inputs ( B - F = J would be 20% of F because of overvaluation); the corn farmer would purchase his tradable inputs at prices 20% less than what they would be if the exchange rate were in equilibrium. The social prices of domestic factors (G) are given by determination of social opportunity costs, which reflect underlying supply and demand conditions in domestic factor markets. In most cases, the effects of macro or commodity policies upon these social prices are ignored. The government can, however, enact tax or subsidy policies on capital or labor which creates a divergence between private costs (C) and social costs (G). Credit subsidies, credit rationing, minimum wage laws and employer taxes on labor use are examples of policies that can cause private factor costs to exceed or fall short of comparable social opportunity costs. The net transfer (L) from all policy equals the output transfer (I) less the input transfer (J) and the factor transfer (K). The net transfer can also be found by subtracting social profitability from private profitability (L = D - H). Depending on the net incidence, subsidy policy can thus create positive private profitability when social profits are negative, whereas taxing policy can cause negative private profits even when the activity is socially profitable. In the former case, policy is generating resource transfers to encourage production while in the latter case, policy is transferring resources away from producers and discouraging production. In summary, collection of data for private and social receipts and costs (A, B, C, E, F and G) permits calculation of private profit (D), social profit (H), net transfers from all policy (L), and output, input and factor transfers (I, J and K). The method described here thus allows measurement of private profitability or competitiveness (indicated if D is positive), social profitability or comparative advantage (indicated if H exceeds zero) and estimates of the net transfer impact of policies (net subsidy to activity if L is positive, net tax if L is negative). The latter measure shows the incentive effects of commodity and macro policies On private profitability. The contributions of FSR to this process are the data on the farm technologies (input-output coefficients, constraints, etc.) that are needed for defining the farm-level systems and the calculation of private profitability at the farm level. The definition of the post-farm technologies, the social profitabilities of the systems, and the calculation of the effects of policy result from the expansion of the policy dimension of FSR.
Comparison among systems The measures illustrated in Table 1 are sufficient to analyze a single agricultural system or to compare two or more systems that produce the
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same commodity. But a precise meaning cannot be attached to a comparison a m o n g systems producing different outputs; for example, no clear choice can be made between a system that yields social profits of US$1000 per tonne of beef and one that generates social profits of US$300 per tonne of wheat. The formation of certain ratios facilitates such comparisons. Five derived measures are listed in the following tabulation (where symbols are drawn from Table 1): (1) (2) (3) (4) (5)
private cost ratio = P C R = C / ( A - B) domestic resource cost ratio = D R C = G/(E - F) net transfer ratio = N T R = K/(I - J) producer subsidy equivalent = PSE = (L/A) × 100 subsidy ratio to producers = SRP = (L/E) × 100
The first three ratios allow a comparison across systems of private profitability, social profitability and net transfers, respectively. P C R is the cost of domestic resources valued in market prices required to generate a unit of value added (also in market prices). Value added is the difference between the value of output and the costs of tradable inputs; it shows how m u c h the system can afford to pay domestic factors (excluding land) and still remain competitive, that is, break even after earning normal profits. Entrepreneurs prefer to earn excess profits and thus try to minimize the private cost ratio ( < 1) by holding d o w n factor and tradable input costs. D R C shows the cost of domestic resources in social prices needed to produce a unit of value added (in world prices); it serves as a proxy measure for social profits. The D R C ratio equals one if social profit is zero. Minimizing the D R C is thus equivalent to maximizing social profits. In cross-country comparisons, D R C ratios replace social profit measures as indicators of relative degrees of efficiency. N T R compares the level of policy transfer that occurs through the factor markets (K) with the transfer taking place in c o m m o d i t y markets ( I - J). The last two measures give a convenient summary of policy transfers in percentage terms. PSE is the percentage subsidy, relative to private receipts, which would substitute for the actual mixture of c o m m o d i t y and macro policies in the system. SRP is an analogous percentage subsidy, but is relative to social receipts and thus indicates the degree of net policy transfer as a percentage of what receipts would be in the absence of policy.
MODEL APPLICATION: PORTUGAL The model described above has been utilized in a variety of situations (Pearson et al., 1981; Byerlee, 1985; Timmer, 1987; Barzelay & Pearson,
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1982). A recent application involving some of the authors of the present paper occurred in Portugal (Pearson et al., 1987). The study was designed to evaluate the impacts on agriculture of Portuguese accession to the European Community. Major changes in output, input and factor prices are expected as a result of European Community membership. Thirty-three commodity systems and six whole-farm systems were analyzed. Private and social profitabilities and the effects of policy were estimated for a base period (1983) and a 10-year transition period (1986-96) representing the adjustment path to full European Community membership. Farm-level technical change was investigated by specifying alternative technologies for individual commodities (e.g. corn) and for whole-farm systems producing a mix of crop and livestock products. In addition, regional variations in technology for the same commodity due to agroclimatic differences were studied. Although the study was not strictly an FSR project in that the development of new, appropriate technology was not one of the objectives, the results aid in understanding the dynamics of technical change in Portuguese agriculture and the formulation of future agricultural research policies and programs. Consequently, the study provides a good example of how the application of PAM can augment the normal FSR approach and how farm-level analysis is essential for good policy analysis. Traditional versus hybrid corn
In Northwest Portugal, corn has been a staple crop for human and animal consumption since the 16th century (Ferro, 1987). Regional or traditional varieties of corn have evolved that are well adapted to the region, but yields are relatively low (2500-3500 kg/ha). Hybrid varieties have been introduced that yield better (3500-4500 kg/ha), but more fertilizer and different cultural practices are required. New seed must be purchased each year, and the traditional practice of saving seed from the current crop is not feasible. The application of social profitability analysis provided a number of insights about the two corn technologies, the effects of policy and the need for additional agronomic research. Table 2 summarizes the results for the base period year, 1983. For traditional corn, private and social returns are negative and the net effects of policy are positive, indicating net subsidization of the system. However, the level of subsidization is not sufficient to make this system privately profitable. In terms of the notation developed in Table 1, D and H are negative and L is positive. For hybrid corn the outcome differs. Private returns to land and management are positive (D +), social returns are negative ( H - ) and net subsidies (L +) are large. These results illustrate the strong incentives for
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switching from traditional to hybrid corn. The switch, under the assumed input and output levels, is associated with a change from negative to positive private returns to land and management. Growing numbers of farmers in Northwest Portugal have reacted to the higher potential profits from hybrid corn and are planting it on a regular basis. The second important result is that social returns are negative for both systems. Therefore, from an economic efficiency perspective, the use of Portuguese resources for corn production in the Northwest is inefficient. TABLE 2 Private and Social Costs, Revenues, and Profits for Traditional and Hybrid Corn in Northwest Portugal, 1983
Item
Private Output value (A) Main product Secondary product Tradable inputs (B) Domestic factors (C) Labor Capital Returns (D)c Social Output value (E) Main product Secondary product Tradable inputs (F) Domestic factors (G) Labor Capital Returns (H)c Policy effectsa Output value (I) Main product Secondary product Tradable inputs (J) Domestic factors (K) Labor Capital Net effects of policy (L)
Traditional corna (Escudos/kg)
Hybrid cornb (Escudos/kg)
23.00 10-53 6.05
23"00 12-80 7.94
21.24 7-83 - 1.59
20'66 6.02 1.18
17"06 10.53 6.52
17"06 12"80 9"25
20"76 11-67 - 11"36
19"99 8"58 -7-96
+ 5.94 0 +0.47
+ 5.94 0 + 1-31
- 0.48 + 3.84 +9-77
- 0.67 + 2.56 +9-14
a Based on a yield of 3000 kg of grain per ha. b Based on a yield of 4000 kg of grain per ha. c Returns to land and risk. a Plus (+) equals a subsidy and minus ( - ) equals a tax.
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Government programs result in large subsidies that allow farmers to continue producing corn. The nature of these subsidies is indicated in Table 2. The private price of corn is greater than the social price, reflecting a policy of output price subsidies for producers. At the same time, the private costs of capital and tradable inputs are less than their social costs, representing further subsidization of producers. The subsidy on capital is the result of special credit programs for agriculture, and the subsidy on tradable inputs is primarily a reflection of government price and subsidy programs for fertilizer and limestone. Removal of these subsidies would make corn production privately unprofitable. The evaluation of the future profitabilities of traditional and hybrid corn under European Community conditions revealed some startling results (Finan, 1987). As Portugal adopts the European Community regulations for grain, subsidy levels drop significantly and both systems become highly unprofitable in both private and social terms. Consequently, unless there are major changes in the underlying parameters of the model, including technological innovations, Northern Portuguese corn farmers will face major economic difficulties as a result of European Community membership. Although the above results are disappointing for Portuguese agriculture, they are extremely useful for FSR efforts. Given the method and the data used in the analysis, it is easy to estimate the level of yield required to attain breakeven profitability and to evaluate the impacts of alternative technologies. Breakeven yields can be presented to agronomists and reasoned judgments can be made about the potential for attaining these levels. Breakeven yields can be estimated from both private and social profitability data, thereby providing an indication of yield levels associated with both competitiveness and efficiency perspectives. If the potential for improved yields is high, FSR projects can be developed. If the potential is low, alternative uses of the resources must be considered. Moreover, alternative subsidy policy scenarios can be evaluated if there are important social or political reasons for maintaining a particular production system. In this way, the FSR team contributes both to the direction of technical change in agriculture and to the evaluation of policy alternatives. In the Portugal study, field surveys turned up additional useful technical information about agricultural practices. It was discovered that many farmers saved hybrid corn from one year to plant the following year, thereby lowering potential yields. Wide variations in the quality of hybrid corn seed also were reported. Efforts to better understand these aspects of hybrid corn production and to discover cost-effective ways of increasing yields would constitute an important contribution of FSR to agricultural development in the region.
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Whole-farm analysis The production and use of corn in Northwest Portugal is much more complicated than the simple commodity systems analysis presented in the previous section. Most of the corn is produced for on-farm consumption by animals and humans. One study indicated that 95% of the farms surveyed produced corn but 80% had never sold corn (Fox et al., 1984, pp. 32-5). Corn is a basic intermediate input in milk production and is produced in rotation with other grain and fodder crops. Intercropping of corn and beans also is very common. Crop and livestock choices, resource allocation decisions and investment plans are made within the context of the whole farm and not exclusively on the basis of individual crop or livestock profitabilities. Furthermore, a wide range of farm sizes and technologies exist in an environment of fairly rapid technical change. The FSR approach recognizes the importance of considering technical change within the context of the whole farm. Social profitability analysis can be applied to analyze the effects of policy on representative whole farms. By nature, social profitability analysis of whole farms is complicated and requires detailed knowledge of the existing farming systems. FSR researchers usually possess this knowledge, and consequently the two approaches are highly complementary. In the Portugal study, four whole-farm systems that produced milk as the primary output were analyzed. The activities comprising these systems are described in Table 3. Variations in yields provide an indication of the differences in technology across systems. The associated variations in input use that explain the yield variations are not presented in Table 3. For example, greater uses of fertilizer and limestone as well as the switch from traditional to hybrid varieties are associated with the higher corn yields. Milk yields increase on the larger farms as a result of better quality cows and higher feed inputs. Potato yields vary in accordance with seed quality and fertilizer use. Substitution among factors of production, an important aspect of technical change, is represented by different labor-capital combinations. For example, the traditional general farm uses animal traction and large amounts of labor per hectare. In contrast, the large milk farm has two tractors, a full complement of machinery, and uses much less (1/39th) labor per hectare. The four whole-farm milk systems were used to describe and analyze one path of technical change that is occurring in Northwest Portugal: traditional general to small milk to medium milk to large milk. The economic incentives for change are derived from the estimates of private profitability (Table 3). The constraints on change were found by studying the land and capital requirements of each technology and by considering the availability of
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TABLE 3 C h a r a c t e r i s t i c s o f t h e W h o l e - F a r m S y s t e m s for M i l k P r o d u c t i o n in N o r t h w e s t P o r t u g a l
Item
C u l t i v a t e d a r e a (ha) N u m b e r o f milk c o w s Milk p r o d u c t i o n p e r c o w p e r y e a r (liters)
Traditional general
Small milk
1'0 2a
Medium milk
1.0 2
Large milk
3'0 12
10'0 36
1 000
3 400
4 000
5 000
3 000 -30 000 --15 000 11 000
4 000 -30 000 --15 000 11 000
-40 000 30 000 --20 000 11 000
-50 000 -60 000 85 000 20 000 --
--
--
M a j o r c r o p yields ( k g / h a ) Corn-grain Corn-silage Rye grass Mixed forages Pasture Potatoes Wine grapes A r e a p e r f a r m (ha) Summer Corn/beans Corn-silage Potatoes Pasture Grapes Winter Rye grass Mixed forages Pasture Grapes
0-7
0"7 --
0-1
0'1
0'2
0.2
--
2.4 0-4
6"0 0-5 3"5
--
0'9 b
0.9 h --
0.2
P r i v a t e profitability, 1983 ( E s c u d o s / h a )
- 40 285
Social profitability, 1983 ( E s c u d o s / h a )
- 1 3 2 193
N e t effects o f policy, 1983 ( E s c u d o s / h a ) c
+ 9 1 908
0.2
--
2.8
--
--0"2
- 7 629
6"5 3-5 0"2
173 790
--
174 562
-198506
-307068
-370498
+ 2 0 6 135
+480858
+545060
T r a d i t i o n a l w o r k breeds. , b I n c l u d e s 0.1 h a p l a n t e d u n d e r t h e g r a p e vines. c Plus ( + ) e q u a l s a net s u b s i d y .
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managerial skills. For example, it was found that it is much easier, within the organized milkshed, to go from traditional general tO small milk than to move into the medium and large milk farms. Land, capital and management constraints all inhibit efforts to increase size beyond that represented by the small milk farm. Social profitability and the net effects of policy also were estimated for each whole-farm system (Table 3). These estimates show the high level of subsidization associated with milk production in Northwest Portugal. Also, the per-hectare value of the net subsidy increases with farm size, giving some indication of the distributional impacts of government policies.
CONCLUSIONS As demonstrated in this paper, important contributions to agricultural policy analysis can result from the incorporation of social profitability analysis in FSR projects. The method used to determine social profitability and the effects of policy builds on the technical and microeconomic data normally collected in FSR studies. When the FSR effort includes farm-level survey data, it is possible through aggregation to derive regional estimates by different farm characteristics of the impacts of specific sectoral and macroeconomic policies. This capability is extremely important in most Third World settings where census data are scarce and the links between changes in macro policies and local (regional) responses are virtually unknown. The linking of the PAM method with FSR efforts makes sense from the perspective of the efficient use of resources for research. The application of PAM requires good farm-level technical and economic data. Integrating PAM with FSR programs could eliminate duplication of effort and save time compared to the current situation in which the application of PAM is made independently of any link with FSR. The authors are attempting to forge this link in a new project that is being initiated in Senegal. Important e x a n t e as well as e x p o s t analyses of policies can be conducted using the PAM method. The ability to conduct e x a n t e analysis is obviously constrained by the availability of realistic policy parameters (prices, taxes, subsidies, etc.) that reflect the range of policy options under consideration. This necessity means that FSR teams in cooperation with policy analysts must have access to policy planners and decision makers at the national and regional level. Often the key individuals with the desired information will not be in the ministries of agriculture or rural development. Instead, they will be found in the ministries of finance and planning and the central bank. The
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use of trained professionals with access to the right sources could add significantly to the policy dimension of the FSR effort. The usual FSR technique of partial budgeting to evaluate specific technical alternatives in a farming system can also be used to evaluate a specific policy change. For example, the impacts on private profitability of a change in fertilizer price can be easily determined once the basic budgets have been formulated. This type of calculation is easy to do if the budgets have been formulated on a microcomputer using spreadsheet software (Monke & Pearson, 1989). More complicated and detailed simulations can be developed to represent policy changes that are associated with changes in technology. Important interactions between policy changes and technical change can be treated explicitly. For example, the effects of a subsidy on a new seed variety can be investigated in terms of the individual commodity system, the wholefarm systems, and regionally thorough aggregation. Per-unit, per-farm and regional subsidy costs can be estimated on the basis of expected adoption rates. The analysis can then be extended to examine the impact of alternative subsidy levels. The potential for useful policy analysis within the context of FSR projects is enormous. The amount and nature of the policy analysis undertaken is a matter of choice. In some projects, major attention can be given to farm-level and agronomic issues. In other projects, the need for analysis of macro policies may predominate. Some projects may give little attention to future policy scenarios, whereas others might focus on expected policy changes, technical innovations and investment requirements. A redefinition of FSR to incorporate social valuation and policy analysis merits continued attention.
ACKNOWLEDGEMENTS The research on Portugal reported in this paper was supported by USDA/ OICD under Contract No. 58-319R-4-410. The authors, while accepting full responsibility for the contents of this paper, wish to thank Jim Longmire and Robert Tripp of C I M M Y T for their comments on an earlier draft.
REFERENCES Barzelay, M. & Pearson, S. R. (1982). The efficiency of producing alcohol for energy in Brazil. Economic Development and Cultural Change, 31, 131~,4.
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Byerlee, D. R. (1985). Comparative advantage and policy incentives tbr wheat production in Ecuador. CIMMYT Economics Program, Working Paper 01/85, El Batan, Mexico. Byerlee, D., Harrington, L. & Winkelmann, D. L. (1982). Farming systems research: Issues in research strategy and technology design. American Journal of Agricultural Economics 64, 897 904. Ferro, M. M. (1987). A agricultura do Noroeste. Camiana, IX(14), 157-91. Finan, T. Jr (1987). Intensive agriculture in the Northwest. In Portuguese Agriculture in Transition, ed. S. R. Pearson et al. Cornell University Press, Ithaca, NY, pp. 141-63. Fox, R., Finan, T., Netting, R. & Bentley, J. (1984). Variations in agricultural technology and investment in Northwest Portugal. Policy and Economic Studies Team Report to PROCALFER and USDA/OICD. University of Arizona and Stanford University, CA, p. 112. Hildebrand, P. E. (1981). Combining disciplines in rapid appraisal: The Sondeo approach. Agricultural Administration, 8, 423 32. Infanger, C. L. (1985). Recognizing structural constraints on implementation of a farming systems approach within a national agricultural program: Some views from Thailand. Networking Paper No. 9, FSSP. University of Florida, Gainesville. Monke, E. A. & Pearson, S. R. (1989). The Policy Analysis Matrix for Agricultural Development. Cornell University Press, Ithaca, NY. Norman, D. W. (1980). The farming systems approach: Relevancy for the small farmer. MSU Rural Development Paper No. 5. Department of Agricultural Economics, Michigan State University, East Lansing, MI, 26 pp. Norman,, D. W., Simmons, E. B. & Hays, H. M. (1982). Farming Systems in the Nigerian Savana: Research Strategies ./'or Development. Westview Press, Boulder, CO. Oasa, E. K. & Swanson, L. E. (1986). Limits of farming systems research and development: Should development administrators be interested? Agricultural Administration, 23, 1 21. Pearson, S. R., Stryker, J. D., Humphreys, C. P. et al. (1981). Rice in West Africa: Policy and Economics. Stanford University Press, Stanford, CA. Pearson, S. R., Avillez, F., Bentley, J. W. et al. (1987). Portuguese Agriculture in Transition. Cornell University Press, Ithaca, NY. Shaner, W. W. (1984). Stratification: An approach to cost-effectiveness for farming systems research and development. Agricultural Systems, 15, 101-23. Shaner, W. W., Philipp, P. F. & Schmehl, W. R. (1982). Farming Systems Research and Development Guidelinesfor Developing Countries. Westview Press, Boulder, CO. Simmonds, N. W. (1985). Farming systems research--A review. World Bank Technical Paper No. 43. The World Bank, Washington DC. Timmer, P. C. (ed.) (1987). The Corn Economy of Indonesia. Cornell University Press, Ithaca, NY.
Expanding the Policy Dimension of Farming Systems Research Roger Fox, a Tim Finan, b Scott Pearson c & Eric M o n k e a a Department of Agricultural Economics, b Bureau of Applied Research in Anthropology, University of Arizona, Tucson, Arizona 85721, USA c Food Research Institute, Stanford University, Stanford, California 94305-6084, USA (Received 17 July 1988; revised version received 12 July 1989; accepted 15 September 1989)
A BSTRA CT The contribution of economics to farming systems research (FSR) has usually been restricted to the microeconomic analysis of alternative agricultural production technologies. In the traditional approach to FSR, macroeconomic variables and government policies are treated as exogenous. This paper discusses one method for expanding the policy analysis dimension of FSR. The policy analysis matrix method allows for the explicit treatment of macroeconomic and sectoral policies, and it builds logically on the wealth of technical and microeconomic data traditionally utilized in FSR. Examples from Portuguese agriculture are used to illustrate the method.
INTRODUCTION The contribution of economics to farming systems research (FSR) has usually been restricted to the microeconomic analysis of alternative agricultural production technologies, particularly within the context of the rapid rural appraisal (Hildebrand, 1981; Shaner, 1984). FSR studies based on detailed farm surveys also have been conducted in many developing countries (e.g. Norman et al., 1982)i Good economic analysis at the farm level is essential to the development and introduction of new, locationspecific technologies. The ability to identify economic constraints and the 271 Agricultural Systems 0308-521X/90/$03.50 © 1990 Elsevier Science Publishers Ltd, England. Printed in Great Britain
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flexibility of existing systems, and to evaluate the impacts, including the distribution of benefits, of alternative technologies represents a major contribution of economists to FSR. FSR's contribution also includes direct influence on the priorities for applied agronomic research, thereby affecting research policy. In the traditional approach to FSR, macroeconomic variables and government policies are treated as exogenous (Norman, 1980; Byerlee et al., 1982; Shaner et al., 1982; Simmonds, 1984). From the perspective of the farmer, this approach is generally valid: individual farmers have little or no influence over macroeconomic and sectoral policies. However, from the perspective of development policy, knowledge of the impacts of policy on farmer decisions is extremely valuable. This is even more important when the heterogeneity of farming systems is acknowledged and policy impacts are presented on a regional basis and/or by farm size, farm type, age of farmer, cultural classification, gender of farmer, etc. Furthermore, policies can be changed. Objectives of government policymakers and their attitudes toward agricultural development are likely to alter over time. Even though individual farmers have little influence, associations of farmers may affect changes in policies and programs. Knowledge of the impacts of alternative policies thus can be as important for technical change as the microeconomic analysis of alternative technologies. Expanding the policy dimension of FSR is especially relevant (a) when a basic understanding of policy effects at the farm level is lacking, (b) when farms are not homogeneous, (c) when new policies are needed to support the introduction of technological change, (d) when significant changes in a set of policies are fairly likely (the Portugal case discussed below), (e) when policies are in a state of flux and analysis can be an input into the process of policy change, and (f) when technology generation has a long term perspective. Since most developing countries are characterized by one or more of these situations, integrating policy analysis with FSR can be extremely productive. The benefits to FSR of broader policy considerations are numerous. Since the ultimate goal of FSR is to develop, test and introduce appropriate, sustainable agricultural technologies, knowledge of the effects of economic policy alternatives becomes a critical element in making FSR recommendations and in adoption decisions. For example, changes in input and output prices resulting from exchange rate adjustments may significantly alter the profitability of alternative technologies. Conversely, the adoption of a new technology resulting from FSR efforts may change the comparative advantage of the activity and create a potential for efficient export production. In both examples, knowledge of the potential impacts of the changes is important for policymakers, FSR practitioners and farmers.
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This paper discusses one method for expanding the policy analysis dimension of FSR. In a sense, it responds to those FSR practitioners who recognize the need for policy analysis and include a policy loop in their FSR diagrams, but have not developed a methodology to accomplish their objectives (Infanger, 1985; Oasa & Swanson, 1986). The method allows for the explicit treatment of macroeconomic and sectoral policies, and it builds logically on the wealth of technical and microeconomic data traditionally utilized in FSR. Examples from Portuguese agriculture are used to illustrate the method. Many methods of policy analysis exist and some of them, such as the methods based on linear programming, are complementary with FSR and make good use of FSR data. The method presented in this paper has some unique advantages and is highly complementary with FSR efforts. Its use, however, does not preclude the need for other types of policy analysis.
METHOD The method of analysis described in this paper can be used to address a number of important policy issues that influence technical change in agriculture. For example, input and output price policies, factor market policies, and exchange rate policies can all be analyzed in terms of their impacts on farm-level decisions. The macro-micro linkages, so important for useful policy analysis, are explicitly treated in the method. The FSR contribution and linkage is clearly at the micro end of the spectrum. Simulation analysis can be used to evaluate alternative policy scenarios, both current and future. The method is variously called 'social profitability analysis', 'social and private profitability analysis', 'comparative advantage analysis' and 'policy analysis matrix' (PAM) (Monke & Pearson, 1989). The method requires the definition of commodity or whole-farm systems. The systems are defined to include activities beginning with the farm and ending with the market, usually the wholesale market, where comparable world market prices can be measured. The definition of appropriate systems at the farm level is the principal contribution that FSR can make to the analysis. Without a strong foundation built on detailed knowledge of existing and potential farming systems, the quality of the policy analysis suffers. In countries where FSR and other farm-level studies exist, application of PAM is greatly facilitated. The principal task of the policy analyst is to construct, for each system, an accounting matrix of revenues, costs and profits, first including and then excluding the effects of policy. This is done for a base year and can be projected using assumptions about changes in the underlying variables that are influenced by policy. In any given year the impact of policy can be gauged through comparison with the situation in the absence of such
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policy. This 'efficiency' calculation assumes that policymakers have available a full range of policy options. When the ability of policymakers to adjust particular variables is limited by external agreements, such as customs unions, a second calculation, of 'constrained efficiency', can be used to incorporate this limitation.
Profitability and efficiency The basic accounting identities that underlie the analysis are illustrated in Table 1. The first identity measures profits as the difference between receipts and costs, where the cost items include both purchased inputs and domestic factors of production. Private profitability, which includes the effects of policy, is calculated as the residual when marked costs of inputs--materials and factors--are subtracted from the market value of the output. Calculation of private profitability for the base year is the first step in the analysis; it shows how decision-makers have actually reacted to the incentives or disincentives created by government policy. Receipts, costs and profits are measured separately for each of the activities in the system, and then entries are aggregated to represent the entire system. In Table 1, the calculation of private profitability (entered as D) is represented in the top row; receipts (A) less input costs (B) and factor costs (C) yield profits (D), with all entries given in private (actual market) prices. The calculation of private profitability at the farm level is routinely done by economists working in FSR projects. Although the techniques of measurement may vary, the underlying concepts are universal. The calculation of private costs and returns for post-farm activities is not normally done in FSR studies and represents additional work required for the application of PAM. Evaluation of profit in social terms requires assigning prices to outputs and inputs (and hence profits) that reflect the absence of domestic economic TABLE Accounting
1
Matrix for Efficiency and Policy Analysis
Receipts
Private prices Social prices Effects o f p o l i c y a n d m a r k e t i m p e r f e c t i o n s a P r i v a t e p r o f i t , D = A - B - C. h Social profit, H = E - F - G.
" O u t p u t t r a n s f e r s , I = A - E.
A E Ic
Costs
Profits
Tradable inputs
Domestic factors
B F ja
C G Ke
d I n p u t t r a n s f e r s , J = B - F. e Factor transfers, K = C- G. s N e t p o l i c y t r a n s f e r s , L = D - H = I - J - K.
D° Hh Ly
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policies, or, in economics jargon, underlying scarcity values or social opportunity costs. These social prices, if reflected in actual decisions, would result in an allocation of resources that would generate the highest contribution to national income. The crucial task for efficiency analysis, therefore, is to find reasonably accurate approximations for the social prices of outputs and inputs in the system. Social prices are not necessarily socially optimal. Private market prices might be preferable, if they allow attainment of some non-efficiency objectives. The method is particularly valuable in this circumstance, because it allows explicit calculation of the opportunity costs of non-efficiency objectives. For commodities that are tradable internationally, the appropriate social prices are the world prices, the CIF (cost, insurance, freight) price for imports or the FOB (free on board) price for exports. This implies that the government always has the choice of importing to meet domestic needs. The same reasoning applies to inputs needed for domestic production; they can either be imported or domestically produced. Hence, the world price is the appropriate standard for valuing their costs in domestic use. Domestic factors of production and nontradable inputs require different treatment, however, because no world price is available to serve as a benchmark for social valuation. Labor and capital are evaluated with respect to their social opportunity cost, the amount of national income foregone by removing a unit of that factor from its next best alternative activity. Scarce factors provide valuable services in production; the social opportunity costs of each factor is a measure of that scarcity. A key distinction is made here between fixed and variable factors. Labor and capital are considered as variable factors. They are assumed to be allocated freely between alternative uses. Land, however, is considered a fixed factor in agriculture. Its price is determined as a share (not known) of the profits left over after all variable factor and intermediate input costs are subtracted from receipts. Because capital costs are treated as variable, the budgets reflect long-run rather than short-run incentives. Maintenance of the longrun perspective mandates the use of long-run average values for other variables as well, such as yields and world prices. Nontradable inputs, such as services, local transportation, and commodities with very high international transportation costs, cannot be evaluated by making world price comparisons, since by definition they do not enter international commerce. In this method, both private and social costs of nontradable inputs are disaggregated into their underlying tradable input and domestic factor costs, the two cost categories shown in Table 1. Within the current FSR framework, the determination of social prices for outputs and inputs is normally not done and therefore represents additional work. The world prices of tradable outputs and inputs are not usually
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difficult to obtain. Also, estimates of the shadow prices of labor and capital may be available from project analyses, such as those conducted by the World Bank. The disaggregation of nontradable inputs represent a more difficult problem and can require the use of disaggregation coefficients from other countries or the analysis of the economic structure of the local industries providing nontradable goods and services. The calculation of social profitability follows easily, once the receipts and costs have been evaluated in social prices. With reference to the symbols in Table 1, the social prices output (E) and of tradable inputs (F) are given by CIF import or FOB export prices, the social valuations of factors (G) are their social opportunity costs, and social profitability (H) is the difference between receipts and costs in social prices (H = E - F - G). If social profits are positive, the activity is competitive at world prices and thereby is an efficient user of scarce resources and contributor to national income. The logic for expanding the normal FSR economic analysis of private profitability to include social profitability is that FSR analysts will have an understanding of the underlying economic efficiency of the systems that they are researching. Without this knowledge, the FSR program may be unwittingly contributing to the inefficient use of scarce resources. For policymakers, an understanding of the comparative advantage or disadvantage of various farming systems is an important aspect of policy analysis and decision-making. Tradable inputs and outputs are valued directly in terms of foreign exchange, and thus the difference between the value of tradable output (E) and all tradable input costs (F) gives an indication of the balance of trade contribution of an activity. However, an economic activity can only be truly said to 'save' or 'earn' foreign exchange if it is socially profitable, because this indicates the ability of the activity to use domestic resources (G) to generate foreign exchange (E - F). So long as domestic factors are scarce, their costs need to be included in evaluating foreign exchange effects. Removal of domestic factors from the production of an alternative commodity will either reduce the exports of that commodity or require increases in imports to substitute for the decline in domestic production. The net actual foreign exchange saving is, therefore, E - F - G, which is the measure of social profitability. In this context, positive social profitability is an indication of comparative advantage or the ability to compete in international trade efficiently, i.e. without the stimulus of subsidies or other government assistance.
Effects of policy The second fundamental accounting identity in the analysis is that the
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difference between valuation of any column entry in Table 1 (receipts, costs or profits) in private prices and in social prices gives a measure of the effects of policy. This difference will also include the effects of any market imperfections, which prevent product or factor markets from allocating outputs or inputs efficiently. Market failures are ignored in the remainder of this section to allow an emphasis of the effects of policy. There is a close relationship between the calculation of social profitability and measurement of the effects of policy, as shown in the third row of Table 1. In the absence of market imperfections, only government policy can cause a divergence between private and social prices. Unless the government enacts a protection policy, for example, each importable output and input will be available at its CIF import price, which will in turn become the domestic price. In Table 1, A will equal E, and B will be the same as F. Consequently, any difference between A and E or between B and F is caused by some combination of trade restriction, price control, tax/subsidy or exchange rate policies. If A exceeds E, either domestic consumers are forced to pay higher than world prices or the government treasury is directly subsidizing production, causing an output transfer (I) equal to A - E . Similarly, if B is greater than F, tradable inputs are being taxed resulting in an input transfer (J) from the system of B - F. For domestic factors, the transfer (K) amounts to C - G; if there were a positive transfer to the system, say from a credit subsidy, then C would be less than G, and K would be negative. The social prices of tradable outputs (E) and of tradable inputs (F) are established in international markets and most countries have little or no power to influence these prices. Commodity price policies in these countries, therefore, have no significant effect on the social valuation of tradable commodities. Exchange rate policy can, however, cause the private prices of tradables (A and B) to be either higher or lower than efficiency levels (E and F) in a manner that is directly analogous to use of a trade-restrictive policy for a given output or input. This result would be achieved, for example, if the government employed a fixed exchange rate policy and chose fiscal and monetary policies that permitted a rate of inflation higher than the average rate experienced in its main trading partner countries. An overvalued exchange rate depresses the prices of tradables relative to those of nontradables and thus acts as a tax on all tradable (exporting or import-substituting) activities and as a subsidy on imports. For example, if the exchange rate were overvalued by 20%, imports of corn would be 20% cheaper in domestic currency than their social opportunity cost and local corn farmers would receive 20% less for their output (in the absence of policies affecting corn prices). In Table 1, A would be less than E by 20%, and the effect of the overvalued exchange rate policy would be shown in I. The
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tax effect of overvaluation on output would be partially offset by a subsidy effect on tradable inputs ( B - F = J would be 20% of F because of overvaluation); the corn farmer would purchase his tradable inputs at prices 20% less than what they would be if the exchange rate were in equilibrium. The social prices of domestic factors (G) are given by determination of social opportunity costs, which reflect underlying supply and demand conditions in domestic factor markets. In most cases, the effects of macro or commodity policies upon these social prices are ignored. The government can, however, enact tax or subsidy policies on capital or labor which creates a divergence between private costs (C) and social costs (G). Credit subsidies, credit rationing, minimum wage laws and employer taxes on labor use are examples of policies that can cause private factor costs to exceed or fall short of comparable social opportunity costs. The net transfer (L) from all policy equals the output transfer (I) less the input transfer (J) and the factor transfer (K). The net transfer can also be found by subtracting social profitability from private profitability (L = D - H). Depending on the net incidence, subsidy policy can thus create positive private profitability when social profits are negative, whereas taxing policy can cause negative private profits even when the activity is socially profitable. In the former case, policy is generating resource transfers to encourage production while in the latter case, policy is transferring resources away from producers and discouraging production. In summary, collection of data for private and social receipts and costs (A, B, C, E, F and G) permits calculation of private profit (D), social profit (H), net transfers from all policy (L), and output, input and factor transfers (I, J and K). The method described here thus allows measurement of private profitability or competitiveness (indicated if D is positive), social profitability or comparative advantage (indicated if H exceeds zero) and estimates of the net transfer impact of policies (net subsidy to activity if L is positive, net tax if L is negative). The latter measure shows the incentive effects of commodity and macro policies On private profitability. The contributions of FSR to this process are the data on the farm technologies (input-output coefficients, constraints, etc.) that are needed for defining the farm-level systems and the calculation of private profitability at the farm level. The definition of the post-farm technologies, the social profitabilities of the systems, and the calculation of the effects of policy result from the expansion of the policy dimension of FSR.
Comparison among systems The measures illustrated in Table 1 are sufficient to analyze a single agricultural system or to compare two or more systems that produce the
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same commodity. But a precise meaning cannot be attached to a comparison a m o n g systems producing different outputs; for example, no clear choice can be made between a system that yields social profits of US$1000 per tonne of beef and one that generates social profits of US$300 per tonne of wheat. The formation of certain ratios facilitates such comparisons. Five derived measures are listed in the following tabulation (where symbols are drawn from Table 1): (1) (2) (3) (4) (5)
private cost ratio = P C R = C / ( A - B) domestic resource cost ratio = D R C = G/(E - F) net transfer ratio = N T R = K/(I - J) producer subsidy equivalent = PSE = (L/A) × 100 subsidy ratio to producers = SRP = (L/E) × 100
The first three ratios allow a comparison across systems of private profitability, social profitability and net transfers, respectively. P C R is the cost of domestic resources valued in market prices required to generate a unit of value added (also in market prices). Value added is the difference between the value of output and the costs of tradable inputs; it shows how m u c h the system can afford to pay domestic factors (excluding land) and still remain competitive, that is, break even after earning normal profits. Entrepreneurs prefer to earn excess profits and thus try to minimize the private cost ratio ( < 1) by holding d o w n factor and tradable input costs. D R C shows the cost of domestic resources in social prices needed to produce a unit of value added (in world prices); it serves as a proxy measure for social profits. The D R C ratio equals one if social profit is zero. Minimizing the D R C is thus equivalent to maximizing social profits. In cross-country comparisons, D R C ratios replace social profit measures as indicators of relative degrees of efficiency. N T R compares the level of policy transfer that occurs through the factor markets (K) with the transfer taking place in c o m m o d i t y markets ( I - J). The last two measures give a convenient summary of policy transfers in percentage terms. PSE is the percentage subsidy, relative to private receipts, which would substitute for the actual mixture of c o m m o d i t y and macro policies in the system. SRP is an analogous percentage subsidy, but is relative to social receipts and thus indicates the degree of net policy transfer as a percentage of what receipts would be in the absence of policy.
MODEL APPLICATION: PORTUGAL The model described above has been utilized in a variety of situations (Pearson et al., 1981; Byerlee, 1985; Timmer, 1987; Barzelay & Pearson,
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1982). A recent application involving some of the authors of the present paper occurred in Portugal (Pearson et al., 1987). The study was designed to evaluate the impacts on agriculture of Portuguese accession to the European Community. Major changes in output, input and factor prices are expected as a result of European Community membership. Thirty-three commodity systems and six whole-farm systems were analyzed. Private and social profitabilities and the effects of policy were estimated for a base period (1983) and a 10-year transition period (1986-96) representing the adjustment path to full European Community membership. Farm-level technical change was investigated by specifying alternative technologies for individual commodities (e.g. corn) and for whole-farm systems producing a mix of crop and livestock products. In addition, regional variations in technology for the same commodity due to agroclimatic differences were studied. Although the study was not strictly an FSR project in that the development of new, appropriate technology was not one of the objectives, the results aid in understanding the dynamics of technical change in Portuguese agriculture and the formulation of future agricultural research policies and programs. Consequently, the study provides a good example of how the application of PAM can augment the normal FSR approach and how farm-level analysis is essential for good policy analysis. Traditional versus hybrid corn
In Northwest Portugal, corn has been a staple crop for human and animal consumption since the 16th century (Ferro, 1987). Regional or traditional varieties of corn have evolved that are well adapted to the region, but yields are relatively low (2500-3500 kg/ha). Hybrid varieties have been introduced that yield better (3500-4500 kg/ha), but more fertilizer and different cultural practices are required. New seed must be purchased each year, and the traditional practice of saving seed from the current crop is not feasible. The application of social profitability analysis provided a number of insights about the two corn technologies, the effects of policy and the need for additional agronomic research. Table 2 summarizes the results for the base period year, 1983. For traditional corn, private and social returns are negative and the net effects of policy are positive, indicating net subsidization of the system. However, the level of subsidization is not sufficient to make this system privately profitable. In terms of the notation developed in Table 1, D and H are negative and L is positive. For hybrid corn the outcome differs. Private returns to land and management are positive (D +), social returns are negative ( H - ) and net subsidies (L +) are large. These results illustrate the strong incentives for
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switching from traditional to hybrid corn. The switch, under the assumed input and output levels, is associated with a change from negative to positive private returns to land and management. Growing numbers of farmers in Northwest Portugal have reacted to the higher potential profits from hybrid corn and are planting it on a regular basis. The second important result is that social returns are negative for both systems. Therefore, from an economic efficiency perspective, the use of Portuguese resources for corn production in the Northwest is inefficient. TABLE 2 Private and Social Costs, Revenues, and Profits for Traditional and Hybrid Corn in Northwest Portugal, 1983
Item
Private Output value (A) Main product Secondary product Tradable inputs (B) Domestic factors (C) Labor Capital Returns (D)c Social Output value (E) Main product Secondary product Tradable inputs (F) Domestic factors (G) Labor Capital Returns (H)c Policy effectsa Output value (I) Main product Secondary product Tradable inputs (J) Domestic factors (K) Labor Capital Net effects of policy (L)
Traditional corna (Escudos/kg)
Hybrid cornb (Escudos/kg)
23.00 10-53 6.05
23"00 12-80 7.94
21.24 7-83 - 1.59
20'66 6.02 1.18
17"06 10.53 6.52
17"06 12"80 9"25
20"76 11-67 - 11"36
19"99 8"58 -7-96
+ 5.94 0 +0.47
+ 5.94 0 + 1-31
- 0.48 + 3.84 +9-77
- 0.67 + 2.56 +9-14
a Based on a yield of 3000 kg of grain per ha. b Based on a yield of 4000 kg of grain per ha. c Returns to land and risk. a Plus (+) equals a subsidy and minus ( - ) equals a tax.
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Government programs result in large subsidies that allow farmers to continue producing corn. The nature of these subsidies is indicated in Table 2. The private price of corn is greater than the social price, reflecting a policy of output price subsidies for producers. At the same time, the private costs of capital and tradable inputs are less than their social costs, representing further subsidization of producers. The subsidy on capital is the result of special credit programs for agriculture, and the subsidy on tradable inputs is primarily a reflection of government price and subsidy programs for fertilizer and limestone. Removal of these subsidies would make corn production privately unprofitable. The evaluation of the future profitabilities of traditional and hybrid corn under European Community conditions revealed some startling results (Finan, 1987). As Portugal adopts the European Community regulations for grain, subsidy levels drop significantly and both systems become highly unprofitable in both private and social terms. Consequently, unless there are major changes in the underlying parameters of the model, including technological innovations, Northern Portuguese corn farmers will face major economic difficulties as a result of European Community membership. Although the above results are disappointing for Portuguese agriculture, they are extremely useful for FSR efforts. Given the method and the data used in the analysis, it is easy to estimate the level of yield required to attain breakeven profitability and to evaluate the impacts of alternative technologies. Breakeven yields can be presented to agronomists and reasoned judgments can be made about the potential for attaining these levels. Breakeven yields can be estimated from both private and social profitability data, thereby providing an indication of yield levels associated with both competitiveness and efficiency perspectives. If the potential for improved yields is high, FSR projects can be developed. If the potential is low, alternative uses of the resources must be considered. Moreover, alternative subsidy policy scenarios can be evaluated if there are important social or political reasons for maintaining a particular production system. In this way, the FSR team contributes both to the direction of technical change in agriculture and to the evaluation of policy alternatives. In the Portugal study, field surveys turned up additional useful technical information about agricultural practices. It was discovered that many farmers saved hybrid corn from one year to plant the following year, thereby lowering potential yields. Wide variations in the quality of hybrid corn seed also were reported. Efforts to better understand these aspects of hybrid corn production and to discover cost-effective ways of increasing yields would constitute an important contribution of FSR to agricultural development in the region.
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Whole-farm analysis The production and use of corn in Northwest Portugal is much more complicated than the simple commodity systems analysis presented in the previous section. Most of the corn is produced for on-farm consumption by animals and humans. One study indicated that 95% of the farms surveyed produced corn but 80% had never sold corn (Fox et al., 1984, pp. 32-5). Corn is a basic intermediate input in milk production and is produced in rotation with other grain and fodder crops. Intercropping of corn and beans also is very common. Crop and livestock choices, resource allocation decisions and investment plans are made within the context of the whole farm and not exclusively on the basis of individual crop or livestock profitabilities. Furthermore, a wide range of farm sizes and technologies exist in an environment of fairly rapid technical change. The FSR approach recognizes the importance of considering technical change within the context of the whole farm. Social profitability analysis can be applied to analyze the effects of policy on representative whole farms. By nature, social profitability analysis of whole farms is complicated and requires detailed knowledge of the existing farming systems. FSR researchers usually possess this knowledge, and consequently the two approaches are highly complementary. In the Portugal study, four whole-farm systems that produced milk as the primary output were analyzed. The activities comprising these systems are described in Table 3. Variations in yields provide an indication of the differences in technology across systems. The associated variations in input use that explain the yield variations are not presented in Table 3. For example, greater uses of fertilizer and limestone as well as the switch from traditional to hybrid varieties are associated with the higher corn yields. Milk yields increase on the larger farms as a result of better quality cows and higher feed inputs. Potato yields vary in accordance with seed quality and fertilizer use. Substitution among factors of production, an important aspect of technical change, is represented by different labor-capital combinations. For example, the traditional general farm uses animal traction and large amounts of labor per hectare. In contrast, the large milk farm has two tractors, a full complement of machinery, and uses much less (1/39th) labor per hectare. The four whole-farm milk systems were used to describe and analyze one path of technical change that is occurring in Northwest Portugal: traditional general to small milk to medium milk to large milk. The economic incentives for change are derived from the estimates of private profitability (Table 3). The constraints on change were found by studying the land and capital requirements of each technology and by considering the availability of
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TABLE 3 C h a r a c t e r i s t i c s o f t h e W h o l e - F a r m S y s t e m s for M i l k P r o d u c t i o n in N o r t h w e s t P o r t u g a l
Item
C u l t i v a t e d a r e a (ha) N u m b e r o f milk c o w s Milk p r o d u c t i o n p e r c o w p e r y e a r (liters)
Traditional general
Small milk
1'0 2a
Medium milk
1.0 2
Large milk
3'0 12
10'0 36
1 000
3 400
4 000
5 000
3 000 -30 000 --15 000 11 000
4 000 -30 000 --15 000 11 000
-40 000 30 000 --20 000 11 000
-50 000 -60 000 85 000 20 000 --
--
--
M a j o r c r o p yields ( k g / h a ) Corn-grain Corn-silage Rye grass Mixed forages Pasture Potatoes Wine grapes A r e a p e r f a r m (ha) Summer Corn/beans Corn-silage Potatoes Pasture Grapes Winter Rye grass Mixed forages Pasture Grapes
0-7
0"7 --
0-1
0'1
0'2
0.2
--
2.4 0-4
6"0 0-5 3"5
--
0'9 b
0.9 h --
0.2
P r i v a t e profitability, 1983 ( E s c u d o s / h a )
- 40 285
Social profitability, 1983 ( E s c u d o s / h a )
- 1 3 2 193
N e t effects o f policy, 1983 ( E s c u d o s / h a ) c
+ 9 1 908
0.2
--
2.8
--
--0"2
- 7 629
6"5 3-5 0"2
173 790
--
174 562
-198506
-307068
-370498
+ 2 0 6 135
+480858
+545060
T r a d i t i o n a l w o r k breeds. , b I n c l u d e s 0.1 h a p l a n t e d u n d e r t h e g r a p e vines. c Plus ( + ) e q u a l s a net s u b s i d y .
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managerial skills. For example, it was found that it is much easier, within the organized milkshed, to go from traditional general tO small milk than to move into the medium and large milk farms. Land, capital and management constraints all inhibit efforts to increase size beyond that represented by the small milk farm. Social profitability and the net effects of policy also were estimated for each whole-farm system (Table 3). These estimates show the high level of subsidization associated with milk production in Northwest Portugal. Also, the per-hectare value of the net subsidy increases with farm size, giving some indication of the distributional impacts of government policies.
CONCLUSIONS As demonstrated in this paper, important contributions to agricultural policy analysis can result from the incorporation of social profitability analysis in FSR projects. The method used to determine social profitability and the effects of policy builds on the technical and microeconomic data normally collected in FSR studies. When the FSR effort includes farm-level survey data, it is possible through aggregation to derive regional estimates by different farm characteristics of the impacts of specific sectoral and macroeconomic policies. This capability is extremely important in most Third World settings where census data are scarce and the links between changes in macro policies and local (regional) responses are virtually unknown. The linking of the PAM method with FSR efforts makes sense from the perspective of the efficient use of resources for research. The application of PAM requires good farm-level technical and economic data. Integrating PAM with FSR programs could eliminate duplication of effort and save time compared to the current situation in which the application of PAM is made independently of any link with FSR. The authors are attempting to forge this link in a new project that is being initiated in Senegal. Important e x a n t e as well as e x p o s t analyses of policies can be conducted using the PAM method. The ability to conduct e x a n t e analysis is obviously constrained by the availability of realistic policy parameters (prices, taxes, subsidies, etc.) that reflect the range of policy options under consideration. This necessity means that FSR teams in cooperation with policy analysts must have access to policy planners and decision makers at the national and regional level. Often the key individuals with the desired information will not be in the ministries of agriculture or rural development. Instead, they will be found in the ministries of finance and planning and the central bank. The
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use of trained professionals with access to the right sources could add significantly to the policy dimension of the FSR effort. The usual FSR technique of partial budgeting to evaluate specific technical alternatives in a farming system can also be used to evaluate a specific policy change. For example, the impacts on private profitability of a change in fertilizer price can be easily determined once the basic budgets have been formulated. This type of calculation is easy to do if the budgets have been formulated on a microcomputer using spreadsheet software (Monke & Pearson, 1989). More complicated and detailed simulations can be developed to represent policy changes that are associated with changes in technology. Important interactions between policy changes and technical change can be treated explicitly. For example, the effects of a subsidy on a new seed variety can be investigated in terms of the individual commodity system, the wholefarm systems, and regionally thorough aggregation. Per-unit, per-farm and regional subsidy costs can be estimated on the basis of expected adoption rates. The analysis can then be extended to examine the impact of alternative subsidy levels. The potential for useful policy analysis within the context of FSR projects is enormous. The amount and nature of the policy analysis undertaken is a matter of choice. In some projects, major attention can be given to farm-level and agronomic issues. In other projects, the need for analysis of macro policies may predominate. Some projects may give little attention to future policy scenarios, whereas others might focus on expected policy changes, technical innovations and investment requirements. A redefinition of FSR to incorporate social valuation and policy analysis merits continued attention.
ACKNOWLEDGEMENTS The research on Portugal reported in this paper was supported by USDA/ OICD under Contract No. 58-319R-4-410. The authors, while accepting full responsibility for the contents of this paper, wish to thank Jim Longmire and Robert Tripp of C I M M Y T for their comments on an earlier draft.
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