The Policy Analysis Matrix and Agricultural Planning

Good policy analysts know that one key ingredient of success in their profession is to stay ahead of the game. In most instances, policy-makers claim to need answers within periods of time that are too short to permit analysis to be done. "I need it done yesterday" is the common request. If unprepared, the policy analyst has to employ methods without proper reflection on their appropriateness, cut corners in gathering and cleaning data, and rush results into drafts without time for reflection and full interpretation. In contrast, a prepared policy analyst is fully aware that the process of decision making in government will often leave inadequate time for complete analysis. Preparation entails adopting methods that can be flexible (that is, carried out with varying degrees of completeness) and gathering essential data in advance on a regular basis. The key, therefore, is to choose a small number of flexible methods and to do basic data gathering and analysis ahead of requests for information.

The purpose here is not to suggest an ideal set of methods and analyses that might be appropriate for any agricultural planning agency; the division of policy responsibilities differs enough among countries to make such a task unworkable. Rather, the idea is to show how PAM analyses can form an integral part of three types of agricultural policy analysis-agricultural prices, public investment projects, and public agricultural research allocations. Policy-makers typically want to know how agricultural price policies affect farm incomes, where new public investments in agriculture should be made, or why public funds should be spent on one line of agricultural research instead of another. If a planning agency were assigned responsibility for all three policy areas, the PAM could assist that agency in setting its research agenda.

The PAM and Price Policy Analyses

Policies are enacted with the intent of bringing about change. But to measure change, one needs to know the existing situation and to understand something about how it has evolved during the recent past. For price policy analysis, PAMs fulfill the first of these needs. One purpose of PAMs is to show the extent to which policies and market failures have influenced the levels of revenues and costs facing producers in some recent base year. The PAM method is designed specifically to permit a clear demonstration to policy-makers of the effects of agricultural and macroeconomic policies.

For price policy analysis, the PAM demonstrates empirically the relationships among different policies and market failures that cause private prices to diverge from their social values. It allows calculation of competitiveness (private profits), and it shows how profits change as policies are altered. The accounting framework is a consistent means of tabulating information required for price policy analysis. The results need to be qualified to permit comparisons of the PAM's efficiency focus with nonefficiency objectives.

Ideally, one would like to construct PAMs for all main systems biannually over a fifteen-to-twenty-year period in order to trace the evolution of policy effects. For nearly all countries, this goal is unattainable because of data limitations. As a partial substitute, one can usually construct price policy graphs for up to two decades. These graphs are drawn separately, using annual data, for each main agricultural commodity and input. Each graph shows the domestic wholesale price of the commodity (or input), the comparable world price (cif import or fob export), and the domestic policy prices (floor price for producers and ceiling prices for consumers), if such exist. The graphs provide visual interpretations of the recent history of price policy and complement PAMs constructed for one or two recent years. Reasonably up-to-date PAMs and price policy graphs are thus two essential pieces of baseline information needed for price policy analysis. An illustration of a price policy graph, showing rice prices in Indonesia between 1974 and 1985, is presented in Box 12.6. An example of the PAM method used to undertake analysis of the projected impact of policy changes in agricultural system profits is summarized in Box 12.7.


Box 12.6. Price Policy Graph for Rice In Indonesia
A price policy graph is an illustrative device to permit easy visual comparisons of year-to-year movements in three kinds of price series-world prices (cif import or fob export, adjusted to a domestic wholesale market level), domestic market prices (at both the wholesale and farm levels), and domestic policy prices (guaranteed floor price to producers and announced ceiling prices to consumers). Price policy graphs allow quick visual reviews of the patterns of price levels and price stability. One item of interest is the extent to which domestic prices are higher or lower than world prices because of price policy. For price stability, the issues are whether intrayear domestic prices have been successfully maintained between announced producer floor and consumer ceiling prices, because of trade and buffer stocking policy, and whether interyear domestic or world prices, both adjusted for inflation, have been more variable. Such historical graphs, when continuously updated, are excellent complements to PAMs. The following figure describes rice prices in Indonesia between 1974 and 1985. The National Food Logistics Agency (BULOG) successfully implemented a buffer stock policy for rice. Through good management and well-designed and well-located warehouses, BULOG defends a paddy floor price to farmers by buying at the announced floor price. The success of the floor price is demonstrated in the price policy graph; the wholesale price in East Java (the main production and consumption region in Indonesia) only rarely and temporarily fell beneath the policy-determined floor price. The graph also shows the annual and trend levels of Indonesian and comparable world prices of rice. In setting domestic rice price levels, Indonesian policy-makers have attempted for the most part to approximate the expected trend of world prices. Between 1973 and 1982, the trend domestic price on average was somewhat lower than the trend world price. This disincentive to production was countered with technology and investment policies and with substantial subsidies on fertilizer to induce adoption of fertilizer-intensive high yielding varieties of rice.

PAM and Investment Policy Analysis

If the planning agency has constructed PAMs for the country's major agricultural systems, these matrices can also provide results that aid in the process of determining the allocation of public investment in agriculture. PAMs show the levels of efficiency (social profitability, or H) of each agricultural system studied. Calculation of domestic resource cost ratios (DRCs) allows the comparison of efficiency among systems that produce unlike outputs. These DRCs offer useful information to investment planners.


Box 12.7. The Projected Impact of Price Policy Changes on the Private Profitability of Portuguese Agricultural Systems
The following table contains the results of private profitability calculations for thirty-three Portuguese agricultural systems during the base year of data collection, 1983, and projections for 1996. The set of agricultural prices that faced producers in 1983 will undergo major changes because Portugal joined the European Community in 1986. Moreover, until 1996, the country will gradually align its agricultural prices to those of the Common Agricultural Policy. The projected private profitabilities for 1996 thus reflect projections of CAP prices and hence of Portuguese prices for that year. Complete PAM analysis was carried out for all thirty-three systems, organized by commodity, region, and technology. But only the private profits are reported in the table, because the policy question is whether adoption of the CAP price regime will cause the need for large adjustments in any of Portugal's agricultural regions. The projection results indicate that relatively easy adjustments are in store for the main farming systems in the center (the Ribatejo) and in the good-soil areas in the south (the Alentejo); wheat and corn are projected to become less profitable and sunflowers, sugar beets, tomatoes, melons, and rice more profitable within the CAP regime. The private profits of dairying in the Azores will decline but will remain positive, so no major difficulty is foreseen there. Large losses in private profits are projected for the poor-soil areas of the south (the Alentejo) and for the northwest. The large farms in the south might need to convert their grain farms to pasture, forages, or forestry. But the very-small-scale farmers in the densely populated northwest are likely to experience a process of accelerated structural change if CAP prices cause private profits to be as negative as those projected. In this way, construction of PAM budgets for all of Portugal's principal commodity systems permits identification of whether large changes in price policy will likely trigger difficult or easy regional adjustment. Nearly all public investments in agriculture are made with the intention of reducing social costs in agricultural systems. (The exceptions are those made to introduce new crops or technologies.) A critical element in deciding on a strategy for a sequence of public investments is to know the social profitabilities of the existing systems. Social benefits to public investment are additions to positive social profits. Negative social profits could be reversed by removal of distorting policies. Hence, it is critical for planners to know how socially profitable or unprofitable systems are before the investment. PAMs provide this necessary baseline information. They must be complemented with complete social benefit-cost analyses of the most promising projects, selected on the basis of the baseline social profits and expected improvements from the investments.


Farm-level profitability by soil type and crop, 1983 and 1996 (in thousands of escudos per hectare)
	1983 Profitability	1996 Profitability(base case)
The Alentejo
Dryland, A and B soils:
Wheat	23.0	1.1
Sunflowers	2.8	2.6
Dryland, C and D soils:
Wheat	7.6	-8.0
Sheep, medium-technology	10.8	-1.3
Sheep, high-technology	3.8	-1.0
Beef, pasture-fed	2.4	-0.8
Irrigated:
Rice	64.9	83.6
Tomatoes	79.3	85.1
The Ribatejo
Dryland, sprinkler irrigation:
Wheat	60.2	24.0
Corn	87.5	28.4
Sunflowers	31.9	33.8
Sugar beets	140.5	35.4
Wine
Flood irrigated:
Tomatoes	48.8	51.8
Melons	139.6	126.4
Rice	77.6	105.8
The Azores
Dryland:
Milk	36.0	24.4
The Northwest
Dryland, traditional technologies:
Milk	-85.4	-137.9
Corn	-0.5	-31.8
Potatoes	48.2	31.5
Wine	-43.4	-45.5
Dryland, medium technologies:
Milk	75.9	-94.6
Corn	9.6	-34.3
Potatoes	61.4	48.4
Wine, ramada	27.7	19.0
Dryland, specialized technologies:
Milk	56.5	-116.6
Potatoes	78.8	65.2
Wine,cordao	243.8	236.3

Evaluations of alternative investment projects, therefore, can use the PAM baseline results to discover which systems are currently socially profitable and which are creatures of supportive policy. Project analysis consists of carefully altering certain costs or technical coefficients and comparing discounted time streams of costs and returns. The main caveat is that critical parameters-world prices, factor prices, and technologies-can change in the future; such changes must also be considered in project analysis.

PAM and Agricultural Research Policy Analysis

A similar situation arises in the analysis of public expenditures for agricultural research. Almost all such expenditures are intended to improve crop yields or to reduce input needs, thereby raising profits in existing agricultural systems. But it is not enough to know that the improved technology will reduce costs in a system. The key issue in choosing which system should receive attention is to know the relative social profitabilities of all of the systems for which technological improvements are possible. No social benefits accrue if technological change merely offsets existing negative social profit. Complementary analyses include projections of changes in world prices and factor prices along with technological changes arising from agricultural research, since the new technologies would be used in the future under differing economic environments.

The baseline PAMs show how well current systems are operating. The technological changes (yield increases or cost reductions) needed to arrive at improved private or social profits can then be determined relative to some starting point. Efficiency and nonefficiency objectives need to be evaluated separately, especially when potential technologies are developed for systems that begin with large negative social profits. An application of partial budgeting is described in Box 12.8; the example considers labor-saving technical changes in rice-farming systems in three West African countries-Burkina Faso, Mali, and Niger.