Applications of the Policy Analysis Matrix

 

 

 

 

 

 

 

Applications of the Policy Analysis Matrix
in Indonesian Agriculture

 

 

 

 

 

Scott Pearson
Carl Gotsch
Sjaiful Bahri

 

 

 

 

May 2003

 

 

 

 

 


Table of Contents

 

Introduction. 5

PART ONE: THEORETICAL CONCEPTS AND EMPIRICAL PROCEDURES. 7

Chapter 1:  A Framework for Agricultural Policy Analysis. 7

Four Components of a Policy Framework. 7

Fundamental Objectives of Policy Analysis. 8

Constraints That Limit Agricultural Policy. 9

Categories of Polices Affecting Agriculture. 9

Application of the Framework to Past Rice Policy in Indonesia. 11

Analysis of Current Rice Policies in Indonesia. 14

Rice Policy in the Framework for Agricultural Policy Analysis. 15

Chapter 2:  Introduction to the Policy Analysis Matrix. 17

Issues and Purposes of PAM Analysis. 17

Identities of the Policy Analysis Matrix. 18

Research Inputs and Outputs in the Policy Analysis Matrix. 22

Chapter 3:  Private Benefit-Cost Analysis (The PAM’s Top Row) 25

Constructing PAMs for Commodity Systems. 25

The Construction of Private Budgets for PAM... 27

Tutorial Example of Private Profitability. 30

Chapter 4:  Social Benefit-Cost Analysis (The PAM’s Middle Row) 34

The Social Valuation of Products. 34

The Social Valuation of Factors of Production. 38

Tutorial Example of Social Profitability. 45

Chapter 5:  Policies and Market Failures (The PAM’s Bottom Row) 48

Output Transfers in the Policy Analysis Matrix. 48

Tradable Input Transfers in the Policy Analysis Matrix. 50

Factor Transfers in the Policy Analysis Matrix. 52

Net Transfers in the Policy Analysis Matrix. 53

Farming Systems PAM... 55

Multi-Period PAM... 56

Chapter  6.  Benefit-Cost Analysis. 58

Benefit-Cost Analysis in the PAM... 58

Single-Period Benefit-Cost Analysis. 59

Multi-Period Benefit-Cost Analysis. 60

Investment Costs. 61

Computing a Discounted Benefit-Cost Ratio. 61

Computing an Internal Rate of Return (IRR) 64

Chapter 7:  Market Failures and Environmental Externalities. 67

Environmental Market Failures. 67

Unsustainable Versus Sustainable Production Practices. 68

Environmental Externalities in the PAM... 69

Constructing a Sustainable PAM... 72

Constructing an Environmental PAM... 73

Calculating the Costs of Compliance. 74

Interpreting Environmental PAM Results. 75

Chapter 8:  Communicating PAM Results to Policymakers. 76

Importance of Communication. 76

Writing Policy Briefs. 78

Information and Interpretation. 80

Results and Ramifications. 80

Writing Policy Summaries. 81

Verbal Communication in Policy Work. 81

Focus and Versatility. 82

PART TWO: CASE  STUDIES. 84

1.  The Impact of Government Policy on Clove Production in Minahasa Regency. 84

2.  The Impact of Tariff Policy and Inter-Island Transport Cost on the Profitability of Soybean Production in Ngada Regency, NTT. 84

3. Traditional Versus Intensive Coconut Production in North Sulawesi 85

4.  Profitability and Efficiency of the Broiler Industry in Tasikmalaya. 85

5.  Analysis of Efficiency and Competition of Soybeans Farming System in Jember. 86

6.  The Efficiency and Competitiveness of Na-Oogst Tobacco and Rice Production in Jember Regency  87

7.  Competitiveness and Comparative Advantage of Beef Cattle Fattening in Bandung Regency. 87

8.  The Profitability of Rice Farming in Polmas District, South Sulawesi, Indonesia. 88

9.  The Competitiveness of Soybean Production in Blitar, East Java. 88

10.  The Competitiveness of Red Onion Production in Brebes, Central Java. 89

11.  The Impact of Agricultural Policy on Soybean Production in West Nusa Tenggara Province. 90

12.  The Effect of the Rice Tariff Policy in Minahasa Regency. 90

13.  Is Cultured Shrimp Production in West Nusa Tenggara Still Profitable?. 91

14.  The Competitiveness and Efficiency of Potato Farming in Pangalengan. 92

15. The Impact of Liberalization on the Competitiveness and Efficiency of the Cashew Systems in Nusa Tenggara Barat Province, Indonesia. 92

16. The Competitiveness and Efficiency of Rice-Farming systems in North Bengkulu District, Bengkulu Province  93

17.  The Impact of Technology Improvement on the Profitability of SoE Keprok Citrus Farming in Timor Tengah  94

18.  Efficiency and Competitiveness of Rice Production in Riau. 95

19.  The Impact of Irrigation Development on Rice Production in Lampung Province. 96

20.  Pricing of Palm Oil Fresh Fruit Bunches for Smallholders in South Sumatra. 96

PART 3: PAM LESSONS LEARNED FROM THE FPSA RESEARCH PROJECTS. 98

Organization of PAM Analysis. 98

Issues and  Systems. 98

Primary and Secondary Information. 99

Private and Social Valuations in PAM Analysis. 101

Tradable Outputs and Inputs. 101

Labor 103

Capital 105

Land. 107

Interpretation of Results from PAM Analysis. 109

Private and Social Profits. 109

Divergences. 111

 

 


Applications of the Policy Analysis Matrix in Indonesian Agriculture

 

Introduction

            The Indonesian Government is constantly searching for ways to make Indonesia’s agriculture more productive.  If greater output could be produced with the country’s land, labor, and other scarce resources, Indonesia could grow more food and raise rural incomes.  How can analysts, at both central and local levels, best evaluate proposed agricultural projects and policies to see if they would increase productivity?

 

            This book is written for Indonesian policy analysts and policy makers, especially those who work outside of Jakarta, and for students and practitioners of agricultural policy in Indonesian universities.  The purpose is to introduce a method of economic analysis to evaluate public investment projects and public policies in the agricultural sector.  An approach called the Policy Analysis Matrix (PAM) is proposed to serve that purpose.  The unique feature of the PAM method is its flexibility.  It can be used for both project and policy analysis.

 

            The PAM approach is more than two decades old, and much has already been written to explain its theoretical foundations and demonstrate its use.[1]  The method also has been used widely to analyze Indonesian agricultural issues.[2]  In this book, the authors hope to explain the conceptual essence of the PAM method, give practitioners practical exercises in applying the approach, and provide recent case studies of PAM analysis in Indonesian agriculture.  The goal is to make the PAM method easily accessible for wide use in Indonesia.

 

            Part One contains an integrated discussion of theoretical concepts and empirical procedures.  The authors firmly believe that the best way to understand an analytical approach is to try it out.  But learning-by-doing can only be successful if the analyst travels two parallel paths – understanding economic principles and applying practical concepts.  Learning through classes, books, and computer tutorials needs to be accompanied by experience in the field and in the policy maker’s office.  Part One of this book, therefore, is both conceptual and empirical.  It shows why specific types of information are needed for project and policy analysis and how to go about finding that information in Indonesia. 

 

            The second section of the book, Part Two, is a collection of case studies.  Busy policy analysts often can appreciate the value of an analytic approach most easily if they see examples of its application.  The illustrations can be especially persuasive if they contain timely analysis of recent agricultural issues in various regions of Indonesia.  The studies summarized in Part Two are all drawn from work carried out under the Food Policy Support Activity, a collaborative program involving BAPPENAS, the United States Agency for International Development (USAID), Development Alternative, Inc. (DAI), The Ministry of Agriculture, and faculty from more than forty universities in Indonesia.  These case studies illustrate well how the PAM approach can be applied fruitfully to a wide range of project and policy issues in rural Indonesia.

Topics to which the PAM methodology described in Part One has been applied include rice, soybeans, potatoes, cloves, cashews, shrimp, and broilers. Repeated interactions with FPSA staff have produced papers whose results provide interesting views on such current policy debates as the comparative advantage of rice and the desirability of subsidizing soybeans.  

 

            Part Three consists of an overview of the lessons learned from the Outreach Project’s research activities. Although there was a good deal of variability in the skill with which the research projects were carried out, most researchers had difficulty with one or more problems associated with their empirical work. Part Three focuses on the most frequently encountered issues and reviews the appropriate procedures for resolving them. The section emphasizes the importance of thinking through carefully the commodity system being studied in order to be sure that the study incorporates all the material needed to answer the policy issues being addressed.

 

            The book also contains an associated computer tutorial covering the materials discussed in Part One. The authors have much experience in teaching short courses and workshops in Indonesia and in many other developing countries.  With the introduction of inexpensive microcomputers, computer tutorials have become an integral part of successful teaching of agricultural policy analysis.  Since most Indonesian analysts and university teachers and students now have easy access to computers, computer tutorials have become a feasible and popular means of complementing and deepening written instruction.  The focus of the tutorial is on how to carry out the basic PAM method and important extensions of it.  Most students can understand concepts better and learn them more quickly if they combine reading with practice.

 

           

           

 

 


PART ONE: THEORETICAL CONCEPTS AND EMPIRICAL PROCEDURES

Chapter 1:  A Framework for Agricultural Policy Analysis

            Everyone involved in agricultural policy and project analysis should have a clear way of thinking about evaluating decisions.  On what grounds can one alternative be judged better than another?  How much policy is enough?  Is economic efficiency the only thing that matters?  For rational decision-making to take place, each of us needs a clear and logical way to evaluate policy options.  In an ideal setting, everyone would have a similar way of approaching policy decisions.  Then disagreements would be limited to genuine differences of opinion rather than including also misunderstandings about approaches to problem solving.  This chapter sets out a general logical approach for carrying out agricultural policy analysis.[3]  The specifics of the Policy Analysis Matrix (PAM) then are introduced in succeeding chapters.

 

A well-understood framework for agricultural policy analysis is needed for decision-makers and interest groups to understand the consequences of policy actions.  The clarity of definitions is critical in policy analysis.  What is meant by the term, “framework for agricultural policy analysis?”  A framework is an organized and consistent approach for clear thinking.  Without it, policy debate can quickly reduce to misunderstanding and emotionalism.  A framework is designed to permit the study of linkages in economic systems.  Good economic analysis is fascinating for economists, frustrating for non-economists, and relevant for everyone because it focuses on linkages within an economy – on why one group’s actions influence others in the system.  Agricultural refers to the production and consumption of commodities that are produced by cultivating crops or raising livestock.  Policies are government actions intended to change behavior of producers and consumers.  Analysis consists of the evaluation of government decisions to change economic behavior.  A framework for agricultural policy analysis, therefore, is a logical system for analyzing public policies affecting producers, marketers, and consumers of crops and livestock products.

Four Components of a Policy Framework

            The four central components in the framework for agricultural policy analysis proposed in this book are objectives, constraints, policies, and strategies.[4] Objectives are the desired goals of economic policy as defined by the policy makers.  Government officials wish to achieve certain ends when they intervene in economies.  Constraints are the economic realities that limit what can be accomplished.  If land is used to grow rice, it is not available to produce an alternative crop in that production season.  Policies are the instruments that governments can use to change economic outcomes.  Effective policies change the behavior of producers, marketers, and consumers and create new economic outcomes. Strategies are the sets of policy instruments that government officials can use to achieve their objectives.  Each strategy is enacted through the introduction of a coordinated set of policies.

 

            The policy framework, portrayed in Figure 1.1, is represented by a circular (clockwise) set of causal linkages among the four components.    The strategies of policy makers consist of sets of policies that are intended to improve economic outcomes (as judged by the policy makers).  The selected policies work through the constraints set by economic parameters. 

The constraints, set by supply, demand, and world price conditions, either further or impede the attainment of objectives.  An assessment of the impact on objectives permits an evaluation of the appropriateness of given strategies.  Governments thus form agricultural strategies by choosing a set of policies to further their objectives subject to the constraints on the agricultural economy. With this logical picture in mind, it is important to review each of the four components in more detail.

 

Figure 1.1.  Graphic Representation of a Policy Framework

 

 

 

   

 

 

 

 

         

 

 

 
 

 

  consist of

 

Strategies

 

Policies

 

work

through

 
 

 

 

 

 

Objectives

 

Constraints

 

further or impede impede

 
 

 

 

 


Fundamental Objectives of Policy Analysis

            Most goals of government policy fall under one of three fundamental objectives – efficiency, equity, or security.  Efficiency is achieved when the allocation of scarce resources in an economy produces the maximum amount of income and the allocation of goods and services brings highest consumer satisfaction.  Equity refers to the distribution of income among groups or regions that are targeted by policy makers.  Typically, greater equity is achieved by more even distribution of income.  However, because policy refers to government actions, the policy makers (and indirectly voters in a democracy) define equity.  Security is furthered when political and economic stability allows producers and consumers to minimize adjustment costs.  Food security refers to the availability of food supplies at affordable and stable prices.  In this framework, any goal that a policymaker is hoping achieve through government intervention will be incorporated within one of the three fundamental objectives – efficiency, equity, and security.

 

Trade-offs arise when one objective can be furthered only if another is impeded – that is, when gains for one goal result in losses for another.  When trade-offs exist, policymakers have to place weights on the conflicted objectives – by determining how much they value gains from one objective versus losses associated with a second objective.  Policy makers – not economic analysts – have the responsibility to make these value judgments and assign weights to objectives.  These government officials have the ultimate responsibility to be accountable for their policy actions.  In the rare instances when trade-offs do not arise, policy analysis and policy making are easy.  The desired result is to move forward to the extent that resources permit. 

Typically, however, trade-offs do exist.  Then economic analysts need to evaluate policies, and policy makers need to make decisions by placing weights on objectives.  The weights have to add to one (e.g., an individual policy maker might place weights of 0.6 on efficiency, 0.3 on equity, and 0.1 on security).

Constraints That Limit Agricultural Policy

The scope for agricultural policy is defined by three basic constraints – supply, demand, and world prices.  Supply, national production, is limited by the availability of resources (land, labor, and capital), technologies, relative input prices, and management capabilities.  These parameters are the components of production functions and thus limit the ability of the economy to produce agricultural commodities.  Demand, national consumption, is limited by population, income, tastes, and relative output prices.  These parameters are the components of demand functions and thus limit the ability of the economy to consume agricultural products.

 

            World prices, for internationally tradable outputs and inputs, define and limit the opportunities to import to increase domestic supply and to export to increase markets for domestic production.  These three economic parameters define the market for an agricultural commodity and are the fundamental forces that influence price formation and the allocation of resources.  The economic constraints lead to trade-offs in policy making.

Categories of Polices Affecting Agriculture

            Policies influencing the agricultural sector fall into one of three categories – agricultural price policies, macro-economic policies, or public investment policies.  Agricultural price policies are commodity specific.  Each price policy targets only one commodity (e.g., rice) at a time.  Price policies also can influence agricultural inputs.  Macro-economic policies are nation-wide in coverage.  Macro policies thus affect all commodities simultaneously.  Public investment policies allocate capital expenditures from the public budget.  They can affect various agricultural groups – producers, traders, and consumers – differently because they are specific to the areas where the investment occurs.

Agricultural Price Policy Instruments

            All agricultural price policy instruments create transfers either to or from the producers or consumers of the affected commodity and the government budget.  Some price policies affect only two of these three groups, whereas other instruments affect all three groups.  In all instances, at least one group loses and at least one other group benefits.  Policy analysts need to consider three categories of agricultural rice policy instruments – taxes and subsidies, international trade restrictions, and direct controls. 

 

            Taxes and subsidies on agricultural commodities result in transfers between the public budget and producers and consumers.  Taxes transfer resources to the government, whereas subsidies transfer resources away from the government.  For example, a direct production subsidy transfers resources from the government budget to agricultural producers. 

 

            International trade restrictions are taxes or quotas that limit either imports or exports.  By restricting trade, these price policy instruments change domestic price levels.  Import restrictions raise domestic prices above comparable world prices, whereas export restrictions lower domestic prices beneath comparable world prices.

 

            Direct controls are government regulations of prices, marketing margins, or cropping choices.  Typically, direct controls must be accompanied by trade restrictions or taxes/subsidies to be effective.  Otherwise, “black markets” of illegal trade render the direct controls ineffective.  Occasionally, some governments have sufficient police power to enforce direct controls in the absence of accompanying trade regulations.  Direct controls of cropping choices can be enforced, for example, if the government allocates irrigation water or purchased inputs.

 Macro-economic Policies Affecting Agriculture.

             Agricultural producers and consumers are heavily influenced by macro-economic polices even though they often have little influence over the setting of these nation-wide policies.  Three categories of macro-economic policies – monetary and fiscal policies, foreign exchange rate policies, and factor price, natural resource, and land use policies – affect agriculture.[5]

 

            Monetary and fiscal policies are the core of macro-economic policy because together they influence the level of economic activity and the rate of price inflation in the national economy, as measured by increases in indexes of consumer or producer prices.  Monetary policies refer to controls over the rate of increase in the country’s supply of money and hence the aggregate demand in the economy.  If the supply of money is increased faster than the growth of aggregate goods and services, inflationary pressure ensues.  Fiscal policies refer to the balance between the government taxing policies that raise government revenue and the public expenditure policies that use that revenue.  When government spending exceeds revenue, the government runs a fiscal deficit.  That result creates inflation if the government covers the deficit by expanding the money supply.

 

Foreign exchange rate policies directly affect agricultural prices and costs.  The foreign exchange rate is the conversion ratio at which domestic currency exchanges for foreign currency.  Most agricultural commodities are traded internationally, and most countries either import or export a portion of their agricultural demand or supply.  For internationally tradable commodities, the world price sets the domestic price in the absence of trade restrictions.  The exchange rate thus directly influences the price of an agricultural commodity because the domestic price (in local currency) of a tradable commodity is equal to the world price (in foreign currency) times the exchange rate (the ratio of domestic to foreign currency).

 

            Factor price policies directly affect agricultural costs of production.  The primary factors of production are land, labor, and capital.  Land and labor costs typically make up a substantial portion of the costs of producing most agricultural commodities in developing countries.  Governments often enact macro policies that affect land rental rates, wage rates, or interest rates throughout the economy.  Other factor price policies, such as minimum wage floors or interest rate ceilings, influence some sectors more than others.  Some governments introduce special policies to attempt to control land uses or to govern the exploitation of natural resources, such as minerals or water.  These macro policies can also influence the costs of agricultural production.

Public Investment Policies Influencing Agriculture.

            The third category of policies affecting agriculture includes public investments from the country’s capital budget – in infrastructure, human capital, and research and technology.  Public investments in infrastructure can raise returns to agricultural producers or lower agricultural costs of production.  Infrastructure refers to essential capital assets, such as roads, ports, and irrigation networks, which would be underprovided by the private sector.  These assets are known as “public goods,” and they require public spending from the government’s capital budget.  Investments in infrastructure are by nature particular to specific regions and benefit mostly the producers and consumers who live in those regions.  Public investment policy is complicated by the fact that infrastructure must be maintained and renewed.

 

            Public investments in human capital include a wide range of spending from the government’s capital budget to improve the skill levels and health of agricultural producers and consumers.  Investments in formal schools, training and extension centers, public health facilities, human nutrition education, and clinics and hospitals are examples of public capital spending that could raise the level of human capital in the agricultural sector.  These investments are critical for long-term development, but they often take many years to show dividends in agriculture.

 

            Public investments in research and technology are another example of “public goods” that directly benefit agricultural producers and consumers.  Countries that enjoy rapid agricultural growth typically invest heavily in agricultural research to breed or adapt high-yielding varieties of food and cash crops developed in international research centers abroad.  These “miracle seeds” often require new agricultural production technologies, utilizing better water control and more intensive application of purchased inputs.  For some commodities, the technological breakthroughs, funded by public investment, are in agricultural processing rather than in farming.

Application of the Framework to Past Rice Policy in Indonesia

A study done by the Food Research Institute, Stanford University in the late 1980s provides an illustration of applying the framework for agricultural policy analysis.[6]  The framework included rice strategy targets (“strategies”), rice policy instruments (“policies”), principal economic variables (“constraints”), and fundamental food policy objectives (“objectives”).  Figure 1.2 is drawn from that study.

 

 

Figure 1.2.  The Framework Applied to Past Rice Policy in Indonesia

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


            The rice strategy targets consisted of three alternatives.  One was to strive for regular exports of rice by attempting to achieve an annual growth rate for rice production of 4 percent.  Another was to aim for regular imports of rice by expanding rice production at an annual rate of 1 percent.  The third was to hope for an annual growth rate of rice output of 2.5 percent to retain self-sufficiency in rice production on trend (by importing some rice in poor production years and exporting some rice in good production years).  The study assessed the likely impact of each of these three strategies.

 

            The RPI book assessed the reasons for Indonesia’s success during the Green Revolution period of the 1970s and 1980s.[7]  During that period, Indonesia evolved from being the largest importer of rice in the world to achieving rice self-sufficiency on trend for a decade beginning in 1984.  Among the five available types of rice policy instruments, government decisions in four areas were essential for success.

 

            Price policy instruments altered the level of domestic rice prices.  Price stabilization policies reduced the fluctuation of domestic rice prices.  Public investments, especially in infrastructure and research, affected prices, costs, and yields of rice production systems.  Macro-economic policies, notably those affecting inflation and the exchange rate, influenced rice production costs and the value of the rice produced.  But rural regulations impeded some rice farmers’ ability to plant rice.

 

            Rice price level policy was neutral.  The government desired to have efficient rice expansion so it kept domestic rice prices close to the trend of world rice prices, providing neither protection nor disprotection to rice production.  However, to encourage farmers to adopt the new technologies featuring high-yielding varieties of rice seeds, the government heavily subsidized chemical fertilizers during this period, thereby reducing costs of rice production.

 

            Rice price stabilization policy was very positive.  The National Logistics Agency, BULOG, stabilized domestic rice prices so that domestic rice price fluctuations were considerably less than world rice price fluctuations.  BULOG had a monopoly on international trade in rice and varied imports or exports to meet domestic needs.  The agency maintained a public buffer stock in rice by buying paddy at a guaranteed floor price and injecting the milled rice into the markets when prices rose.  This stabilization policy was expensive but largely successful.

 

            Public investment policy in rural infrastructure, health and education facilities, and agricultural research and extension was a key component of Indonesia’s success in tripling rice yields and production and thus in achieving temporary rice self-sufficiency.  The government invested heavily in rural roads, ports, and irrigation facilities and for a period devoted as much as 30 percent of its capital budget to rural infrastructure and agricultural research.

 

            Macro-economic policies during the 1970s and 1980s were appropriately neutral.  The annual rate of inflation typically was held beneath 10 percent, and the exchange rate was devalued periodically to offset the difference between inflation rates in Indonesia and those of its main trading partners.  Rice producers thus were neither implicitly taxed nor subsidized by longstanding disequilibrium exchange rates, and they could count on quite stable macro-economic conditions in planning their investments and annual production inputs.

 

            Rural regulations were the only negative area of policy affecting rice production in the 1970s and 1980s.  In parts of East and Central Java, many farmers were forced by a policy decision to grow sugarcane when they preferred to plant rice.  This decision led to less rice production, lower farmer incomes, and less employment relative to levels that would have been created under a free choice of cropping patterns.

 

            These policy instruments affected levels of rice production through their influence on three principal economic variables – the amount of rice produced domestically, the level of rural income that was generated directly in rice production or indirectly from the investment or consumption of rice-related incomes, and the level of rural employment created directly or indirectly by rice production.

 

            Each of these three variables in turn influenced the three fundamental food policy objectives.  Regular increases in domestic rice output contributed to food security and price stability by reducing exposure to world price fluctuations.  The efficient generation of income through rice expansion led to rapid income growth regionally and nationally.  The creation of additional rural jobs, directly in rice production or indirectly in rice-related activities, improved the distribution of income between urban and rural areas.

 

            The RPI book concluded that the strategy of trend self-sufficiency was likely to be the one preferred by policy makers in the early 1990s.[8]  An effort to achieve regular rice exports would have been inefficient and required regular subsidies, whereas a strategy to import regularly in the early 1990s would have left efficient production opportunities unrealized.

Analysis of Current Rice Policies in Indonesia

Current rice price policy in Indonesia attempts to raise domestic rice prices to levels about 30 percent higher than they would be if they were instead set wholly by rice import prices.  The strategy is to assist rice producers during a period when world rice prices are low, about one-fourth less than their expected long-run trend levels.  However, this strategy prevents Indonesian consumers of rice from benefiting from the low world prices and thus has adverse impacts on human nutrition and poverty alleviation..

 

            The policy instrument used to implement this strategy is a specific tariff on rice imports of Rupiah 430/kilogram.  If this tariff were collected on all imports of rice, the policy would raise domestic prices to levels about 30 percent higher than they would be in the absence of policy.  Recent observed levels of domestic rice prices in Indonesia have been about 25-30 percent higher than comparable import prices of rice.  However, this outcome does not mean that the tariff is being collected fully and that smuggling is absent.  The highly uncertain economic and political environment in Indonesia has caused rice importers to charge a premium of perhaps 10-20 percent to cover the risks of exchange rate changes and the costs of extra banking charges.

 

            The policy of protecting rice furthers the goal of increasing rice farmers’ income within the broader equity objective.  However, the policy leads to important trade-offs because it penalizes poor rural and urban consumers of rice.  The tariff does not improve economic efficiency because it causes scarce resources to be used inefficiently.  In an era of low and relatively stable world rice prices, the rice tariff does little to contribute to food security.  Raising the price of rice also has serious consequences for the nutrition of poor people, and it creates additional poverty by pushing more poor families beneath the poverty line.

 

            In principle, the government could assist rice farmers by using a different price policy instrument – a direct production subsidy through which farmers would receive a government subsidy according to the amounts of rice marketed.  This policy would avoid raising the domestic price of rice and thus would eliminate the trade-offs between producers and consumers.  However, the subsidy policy would be difficult to implement and it would put great pressure on the government budget during a time of fiscal stringency.  Some analysts argue that scarce government resources instead should be used to assist rice farmers to switch gradually to higher valued commodities.

Impact of Current Rice Policies on Objectives

            In contrast to the rice policy during the Green Revolution period of the 1970s and 1980s, current rice policy in Indonesia has not been very successful.  Rice policy has floundered since the mid-1990s and especially since the macro-economic crisis began in mid-1997.

 

            The appropriateness and effectiveness of the policy to raise rice prices has been hotly debated.  The specific tariff of Rupiah 430/kilogram of rice and the rice traders’ risk premium have together raised domestic rice price levels about 25-30 percent above comparable import prices.  Many government officials appear to feel that the gain to rice producers offsets the loss for rice consumers and the poor, but the issue is under frequent review.

 

            Price stabilization policy has fallen into disrepair.  Since 1997, BULOG, the agency charged with stabilizing rice prices, has been unable to stabilize domestic rice prices.  During 1998, the agency was forced to abandon its effort to prevent rice price increases and the domestic price of rice doubled in four months.  In December 1998, the government set an unrealistically high floor price for paddy, and BULOG has not been able to defend that floor price.  The agency instead buys about enough rice for its own distribution needs and fails to defend either floor or ceiling prices for rice.  Due to ineffective price stabilization, the government removed BULOG’s international trade monopoly on rice imports in 1999.

 

            Public investment policy for rice has continued as before, but at lower and less effective levels.  Some of the earlier irrigation and transport infrastructure now requires rehabilitation and greater maintenance.  Budgetary stringency during the macro crisis has added greatly to the difficulties of expanding rural infrastructure.

 

            Macroeconomic policies became much less stable because of the macro crisis.  With the important exception of 1998 (when the annual rate of inflation exceeded 80 percent), the government’s monetary and fiscal policies have kept inflation in reasonable check (8-12 percent per year).  But enormous uncertainty for the Indonesian economy has come from the widely fluctuating foreign exchange rate, which depreciated from about Rupiah 2,500 per US dollar in mid-1997 to over 16,000 in early 1998 before settling in a range of 8,000-12,000 thereafter.

 

            Rural regulations have been reformed.  Rice farmers in East and Central Java are no longer required to plant sugarcane for mills operated by the Ministry of Agriculture.  However, some Javanese farmers complain that local government officials still attempt to regulate their choices of cropping patterns.

Rice Policy in the Framework for Agricultural Policy Analysis

            In principle, governments form agricultural strategies by choosing a set of policies to further their objectives subject to the constraints on the agricultural economy. This conceptual framework has been illustrated by contrasting rice policy in Indonesia in two periods – the Green Revolution of the 1970s and 1980s and the macro crisis period of 1997-present.  The earlier period is analyzed in the RPI book, whereas the recent period is examined in numerous papers written by the FPSA team, all available in the “Food Policy Agenda” section of the project website (www.macrofoodpolicy.com).

 

            During the Green Revolution, rice strategy was to introduce a new technology of high-yielding varieties, improved water control, chemical fertilizer applications, and better marketing and irrigation infrastructure.  Fertilizer subsidies, stable rice prices, free irrigation water, better roads, and stable macro-economic conditions complemented this new technology and encouraged its rapid dissemination.  These policies significantly altered the economic constraints and allowed a tripling of output and incomes from rice.

 

            These happy circumstances promoted all three primary objectives – efficiency, equity, and security.  The increases in rice production were created by improved technologies, not policy transfers, rice prices were maintained at about the trend of world prices, and efficiency was improved.  Technological gains permitted increases in rice farmer profits and incomes while consumers of rice benefited from the gradually declining world and domestic rice prices.  Hence, there were few trade-offs in equity.  Food security improved as Indonesia eliminated rice imports with efficient increases in domestic output, in an environment of relatively stable domestic rice prices.  The strategy to promote the dissemination of new high-yielding technologies was thus successful on nearly all accounts.

 

            During the recent macro-economic crisis, rice strategy has fallen into disarray.  The rice strategy has been to attempt to aid rice farmer incomes in a period of unusually low world rice prices.  In contrast to the earlier period, there has not been any new technology to disseminate.  Nearly all Indonesian farmers now plant high-yielding varieties of rice.  Severe budgetary pressure and the consequent need to limit government capital spending have hampered the government’s ability to make further improvements in irrigation and transportation.  Struck by fiscal limitations, contradictory policies, and charges of corruption and mismanagement, BULOG has not been able to stabilize rice prices.  Rapid and sizeable swings in the exchange rate have greatly increased the uncertainties in rice production and marketing.

 

            Difficult trade-offs now affect rice policy.  The principal policy instruments have been the specific tariff on rice imports, which has helped to raise domestic prices by 25-30 percent, and a limited subsidy on rice consumption in selected poor villages and urban centers.  The rural and urban poor have been compensated only partly for the increase in rice prices caused by policy.  Public opinion favoring rice farmers argues for maintaining or even raising the rice tariff, especially to offset unusually low world rice prices.  The opposite opinion, favoring poor rice consumers, argues that the country should take advantage of low world rice prices to benefit the nutrition of poor Indonesians and to alleviate their poverty.  The weights that policy makers place on these conflicting objectives thus take center stage in the policy debate as Indonesia seeks to identify a consistent and successful rice strategy.    


Chapter 2:  Introduction to the Policy Analysis Matrix

 

In their efforts to raise agricultural productivity, the central, provincial, and local governments in Indonesia can intervene in agriculture by using three different kinds of policies – agricultural price policies, public investment policies, and macro-economic policies.  Macro-economic policies can only be imposed at the central level and require separate analysis by specialists in macroeconomics.  Agricultural economists study the impacts of price and investment policies.  Fortunately, the efficacy of both agricultural price policies and public investments in agriculture can be studied with one approach – the Policy Analysis Matrix (PAM).  PAM results show the individual and collective effects of price and factor policies.  The PAM also provides essential baseline information for benefit-cost analysis of agricultural investment projects.  The main purpose of this chapter is to show how and why the PAM method can apply to both price and project analysis.  

Issues and Purposes of PAM Analysis

            The PAM methodology provides information to help central and regional policy makers address three central issues of agricultural policy analysis.[9]   One issue is whether agricultural systems are competitive under existing technologies and prices – that is, whether farmers, traders, and processors earn profits facing actual market prices.  Prospective price policies would change the value of output or the costs of inputs and thus the private profitability of the system.  A comparison of private profitability before and after the policy change measures the impact of the policy change on competitiveness in market prices.

 

            A second issue is the impact of new public investment in infrastructure on the efficiency of agricultural systems.  Efficiency is measured by social profitability, the valuation of profits in efficiency prices.  Successful public investment (in irrigation or transportation) would raise the value of output or lower the costs of inputs.  A comparison of social profits before and after the new public investment measures the increase in social profits.

 

            A third issue, closely related to the second, is the impact of new public investment in agricultural research or technology on the efficiency of agricultural systems.  Successful public investment in new seeds, farming techniques, or processing technologies would enhance farming or processing yields and thus would increase revenues or decrease costs.  A comparison of social profits before and after the investment in research measures the gain in social profitability.

 

            The three principal purposes of the Policy Analysis Matrix (PAM) methodology are to provide information and analysis to assist policy makers in these three central areas of agricultural policy.[10]  The construction of a PAM for an agricultural system allows one to calculate private profitability – a measure of the competitiveness of the system at actual market prices.  Similar analyses of other systems permit a ranking of the competitiveness of agricultural systems at market prices.  The calculation of private profitability or competitiveness is carried out in the first (top) row of the PAM matrix.  This result serves as the baseline for benefit-cost analysis in actual market (private) prices, as explained in Chapter 3.

 

            A second purpose of the PAM approach is to estimate the agricultural system’s social profitability – the result if products produced and inputs used are valued in efficiency prices (social opportunity costs).  Complementary analyses of other systems allow a ranking of the efficiency of agricultural systems.  The calculation of social profitability is carried out in the second (middle) row of the PAM matrix.  This outcome provides baseline information for social benefit-cost analysis, using efficiency prices, as shown in Chapter 4.

 

            The third purpose of PAM analysis is to measure the transfer effects of policies.  By contrasting revenues and costs before and after the imposition of a policy, one can determine the impact of that policy.  The PAM method captures the effects of policies influencing both products and factors of production (land, labor, and capital).  The measurement of the transfer effects of policies is carried out in the third (bottom) row of the PAM matrix, as demonstrated in detail in Chapter 5.  

 Identities of the Policy Analysis Matrix

A matrix is an array of numbers (or symbols) that follows two rules of accounting – one defining relationships across the columns of the matrix and the other defining relationships down the rows of the matrix.  These accounting relationships are termed the identities of the matrix because they are true by definition.[11]  An analyst can specify any identities in a matrix so long as the definitions are applied consistently.  The PAM matrix consists of two accounting identities – the profitability identity and the divergences identity.

 

            The profitability identity in PAM is the accounting relationship across the columns of the matrix.  Profits are defined as revenues less costs.  All entries in the PAM matrix under the column defined “profits” thus are identically equal to the difference between the columns containing “revenues” and those containing “costs” (including both costs of tradable inputs and costs of domestic factors).

 

            The divergences identity in PAM is the relationship down the rows of the matrix.  Divergences cause private prices to differ from their social counterparts.  A divergence arises either because a distorting policy intervenes to cause a private market price to diverge from an efficient price or because underlying market forces have failed to provide an efficient price.  All entries in the PAM matrix under the third row, defined as “effects of divergences,” thus are identically equal to the difference between entries in the first row, measured in “private prices,” and those in the second row, measured in “social prices.”  

Profitability Identity – Private Profits

Figure 2.1 shows only the entries for the first row of a PAM, which contains measures of prices in private prices (the observed market prices).  The symbol A measures revenues in private prices, the symbol B stands for tradable input costs in private prices, the symbol C represents domestic factor costs in private prices, and the symbol D is private profit.

 

 

 

                                                         

Figure 2.1.  Private Profits in the Policy Analysis Matrix

 

 

Revenues

Costs

Profits

 

 

Input

Factor

 

Private (observed market) Prices

Private

A

B

C

D

Social

 

 

 

 

Divergences

 

 

 

 

 

In empirical PAM analysis, the revenue and cost categories in private prices (entries A, B, and C) are based on data from farm and processing budgets.  The symbol D, profits in private prices, is found by applying the profitability identity.  According to that accounting principle, D is identically equal to A - (B + C).  Private profits in PAM thus are a residual discovered by subtracting private costs from private revenues.[12]

 

            The calculation of private profits, from data in farm and processing budgets, measures the competitiveness of agricultural systems.  One key result for agricultural policy thus is obtained from the first row of the PAM matrix.  Procedures for the empirical estimation of private profitability are outlined in Chapter 3.

 

            To compare results from agricultural systems that produce unlike outputs, analysts compute ratios.[13]  In the calculation of ratios, the unit of measurement (sometimes called the numeraire), such as Rupiah per kilogram of rice, cancels out.  The computation of ratios thus avoids having to compare profits per kilogram of rice, for example, with profits per kilogram of soybeans.  The comparison of competitiveness of unlike systems is facilitated by computing the private benefit-cost ratio (PBCR) for each system and then comparing these ratios across all the systems.  The PBCR is equal to the ratio of private revenues to private costs, or PBCR = A/(B + C).

Profitability Identity – Social Profits

Figure 2.2 depicts only the entries for the second row of a PAM, which contains measures of prices in social prices (prices that would result in the best allocation of resources and thus the highest generation of income). 

                                                         

Figure 2.2.  Social Profits in the Policy Analysis Matrix

 

 

Revenues

Costs

Profits

 

 

Input

Factor

 

Social (efficiency) Prices

Private

 

 

 

 

Social

E

F

G

H

Divergences

 

 

 

 

 

            The symbol E measures revenues in social prices, the symbol F stands for tradable input costs in social prices, the symbol G represents domestic factor costs in social prices, and the symbol H is social profit.  Countries achieve rapid economic growth by promoting activities that generate high social profits (large positive H).

 

            In an empirical PAM analysis, the revenue and cost categories in social prices (entries E, F, and G) are based on estimates of the social opportunity costs of commodities produced and inputs used in production.  These estimated social (or efficiency) prices then are applied to the original quantities of outputs and inputs (those used in the calculation of private profits in the top row of PAM).  The symbol H, profits in social prices, is found by applying the profitability identity.  According to that accounting principle, H is identically equal to E - (F + G).  Social profits in PAM thus are a residual discovered by subtracting social costs from social revenues.[14]

 

            The calculation of social profits, from estimates of social prices applied to input-output data in farm and processing budgets, measures the efficiency of agricultural systems.  A second key result for agricultural policy thus is obtained from the second row of the PAM matrix.  Procedures for the empirical estimation of social profitability are summarized below and detailed in Chapter 4.

 

            The social (efficiency) prices for tradable outputs and inputs are the comparable world prices – import prices for commodities that are partly imported (importable) or export prices for commodities that are partly exported (exportable).  The efficiency value (social opportunity cost) of producing an additional ton of an importable commodity (e.g., rice in Indonesia) is the amount of foreign exchange saved by replacing a ton of imports – given by the import price.  Similarly, the social opportunity cost of producing an additional ton of an exportable commodity (e.g., palm oil in Indonesia) is the amount of foreign exchange earned by increasing exports by a ton – given by the export price.

 

            The social (efficiency) prices for domestic factors of production (land, labor, and capital) are estimated also by application of the social opportunity cost principle.  Because domestic factors are not tradable internationally and thus do not have world prices, their social opportunity costs are estimated through observations of rural factor markets.  The intent is to find how much output and income are foregone because the factor is used to produce the commodity under analysis (e.g., rice) rather than the next best alternative commodity (e.g., sugarcane).

 

            To compare social results from agricultural systems that produce unlike outputs, analysts again compute ratios.  Comparison of the efficiency of unlike systems is done by computing the social benefit-cost ratio (SBCR) for each system and then comparing these ratios across all the systems.  The SBCR is equal to the ratio of social revenues to social costs, or SBCR = E/(F + G).

Divergences Identity

            Figure 2.3 shows all twelve entries for a PAM, given by the letter symbols A through L.  It adds a third row termed the Effects of Divergences row.  As noted above, divergences arise from either distorting policies or market failures.  Either source of divergence causes observed market prices to differ from their counterpart efficiency prices.[15]  The symbol I measures divergences in revenues (caused by distortions in output prices), the symbol J stands for divergences in tradable input costs (caused by distortions in tradable input prices), the symbol K represents divergences in domestic factor costs (caused by distortions in domestic factor prices), and the symbol L is the net transfer effect (arising from the total impact of all divergences).

 

                                                         

Figure 2.3.  Divergences in the Policy Analysis Matrix

 

 

Revenues

Costs

Profits

 

 

Input

Factor

 

Private

A

B

C

D

Social

E

F

G

H

Effects of Divergences

I

J

K

L

 

            In empirical PAM analysis, the effects of divergences (in the third, bottom row) are found by applying the divergences identity.  According to that accounting principle, all entries in the PAM matrix under the third row (defined as Effects of Divergences) are identically equal to the difference between entries in the first row (measured in private prices) and entries in the second row (measured in social prices).  Therefore, I is identically equal to (A – E), J is identically equal to (B – F), K is identically equal to (C – G), and L is identically equal to (D – H).  The sources of divergences are introduced below, and procedures for the empirical estimation of divergences are detailed in Chapter 5.

 

            One source of divergence is the existence of a market failure.  A market fails if it does not generate competitive prices that reflect social opportunity costs and lead to an efficient allocation of products or factors.  Three basic types of market failures create divergences.  The first is monopoly (seller control over market prices) or monopsony (buyer control over market prices).  The second are negative externalities (costs for which the imposer cannot be charged) or positive externalities (benefits for which the provider cannot receive compensation).  The third are factor market imperfections (inadequate development of institutions to provide competitive services and full information).

 

            Efficient policy is a government intervention to correct a market failure and thus offset a divergence.  For example, successful regulation of a monopoly would reduce seller prices, cause private and social prices to become equal, and increase income.

 

            The second source of divergence is distorting government policy.  Distorting policy, implemented to further non-efficiency objectives (equity or security), prevents an efficient allocation of resources and thus creates divergences.  A tariff on rice imports, for example, could be imposed to raise farmer incomes (equity objective) and increase domestic rice production (security objective), but it would create efficiency losses if the replaced rice imports were cheaper than the costs of domestic resources used to produce the additional rice.  Hence, a trade-off would arise, and policy makers would need to assign weights to these conflicting objectives to decide whether to introduce the tariff.

 

            The most efficient outcome could be achieved, in principle, if the government were able to enact efficient policies that offset market failures and if the government were to decide to override non-efficiency objectives and remove distorting policies.  If these actions – the introduction of efficient policies and the removal of distorting policies – could be carried out, divergences would be offset and the effects of divergences (measured in the bottom row of PAM) would be zero.  In this idealized example, all entries in the bottom row of the PAM matrix – I, J, K, and L – would be zero.  Hence, the entries in the top row would be identical to those in the second row, i.e., private revenues, costs, and profits would be the same as social revenues, costs, and profits (A = E, B = F, C = G, and D = H).

Research Inputs and Outputs in the Policy Analysis Matrix

            The principles and practices of the PAM are illuminated through examination of the research inputs and research outputs in the matrix.  Because the PAM is based on two accounting identities, the analyst needs only to enter data into half of the entries of the matrix (called the research inputs).  The remaining entries then become results of the analysis (called the research outputs).  Of the twelve entries in the PAM matrix, therefore, only six need to be data or research inputs.  The remaining six entries then can be found as research results by applying the profitability or divergences identities.

Research Inputs for Efficiency and Policy Analysis

The six categories of research inputs in empirical PAM analysis (A, B, C, E, F, and K) are underlined in the PAM matrix shown in Figure 2.4.

 

Figure 2.4.  Research Inputs in the Policy Analysis Matrix

 

 

Revenues

Costs

Profits

 

 

Input

Factor

 

Private

A

B

C

D

Social

E

F

G

H

Effects of Divergences

I

J

K

L

 

            Most of the data for the six research inputs are obtained from the activity budgets (farming, marketing, and processing) for each agricultural system.  The data for private revenues (A) and costs (B, C) typically come directly from these budgets.  These budgets usually are based on both secondary data (gathered by other researchers) and primary data (obtained by the field research team), as described in Chapter 3.

 

            The entries for social revenues (E) and social tradable input costs (F) come partly from the system budgets and partly from government documents or industry sources, as detailed in Chapter 4.  The information on input-output relationships (quantities of inputs needed per hectare or per ton of output) typically is assumed to be the same in both private and social analysis and thus is obtained from the system budgets (and then from the first row of PAM).  However, social prices differ from their private counterparts if distorting policy or market failures cause divergences.  The social prices for tradable outputs and inputs are comparable import or export prices, found in government or industry documentation.

 

            The entries for social valuation of domestic factor costs (G) cannot be observed directly in the field or taken from government or industry documents (because comparable world prices do not exist for factors).  Instead, field researchers study rural factor markets to search for the presence or absence of divergences in each factor market – effective distorting policies or significant market failures.  Hence, the entry for factor divergences (K) becomes a research input, which then is used to estimate social factor prices from observed private factor prices.  This empirical procedure for factor markets is described in Chapter 4

 

            The six categories of research results in empirical PAM analysis (D, G, H, I, J, and L) are underlined in the PAM matrix shown in Figure 2.5.

 

                                                         

Figure 2.5.  Research Results in the Policy Analysis Matrix

 

 

Revenues

Costs

Profits

 

 

Input

Factor

 

Private

A

B

C

D

Social

E

F

G

H

Effects of Divergences

I

J

K

L

 

            Research results in the PAM approach flow directly from application of either the profitability identity or the divergences identity.  Since these accounting principles govern the relationships in the PAM matrix, the key results are obtained from straightforward subtraction among entries of research inputs.

 

            The first two results – private profits (D) and social profits (H) – are obtained from application of the profitability identity (revenues less costs equal profits).  Private profits (D), a measure of competitiveness, equal private revenues (A) less private costs (tradable input costs (B) and domestic factor costs (C)).  Similarly, social profits (H), a measure of efficiency, equal social revenues (E) less social costs (tradable input costs (F) and domestic factor costs (G)).  The calculation of social profits (H), however, must await the estimation of social factor prices (G), itself a research result.

 

            The next two results – output transfers (I) and tradable input transfers (J) – are obtained from application of the divergences identity (entries in private prices less entries in social prices equal the effects of divergences).  Output transfers (I), a measure of the implicit tax or subsidy on outputs, equal private revenues (A) less social revenues (E).  In turn, tradable input transfers (J), a measure of the implicit tax or subsidy on tradable inputs, equal private tradable input costs (B) less social tradable input costs (F).

 

            The last two results – social factor prices (G) and net transfers (L) – are less straightforward.  As noted above, social factor prices (G) are found by adjusting private factor prices (C) for observed divergences causing factor price transfers (K).  Because the divergences identity requires that (C – G) = K, it is also true that (C – K) = G.  The final result, net transfers (L), can be found by applying either the profitability identity (I – (J + K) = L) or the divergences identity (D – H = L).  The net transfer (L) thus can be interpreted either as the net effect of all divergences or as the difference between private and social profitability.  This single measure thus shows the extent to which distorting policies and market failures implicitly subsidize an agricultural system (by transferring resources into the system) or tax that system (by transferring resources away from the system).       


Chapter 3:  Private Benefit-Cost Analysis (The PAM’s Top Row)

            The empirical application of the Policy Analysis Matrix (PAM) begins with an assessment of revenues, costs, and profits in private (actual market) prices.  Data on private revenues and costs are entered in the top row of the PAM, often termed the “private row.”  Figure 3.1 shows the entries for the top row of PAM, which contains measures in private prices (the observed market prices).  As noted in Chapter 2, the symbol A measures revenues in private prices, the symbol B stands for tradable input costs in private prices, the symbol C represents domestic factor costs in private prices, and the symbol D is private profit.  Application of the profitability identity (D = A - (B + C)), introduced in Chapter 2, to private revenues and costs gives private profits. 

 

Figure 3.1.  Private Profits in the Policy Analysis Matrix

 

 

Revenues

Costs

Profits

 

 

Input

Factor

 

Private (observed market) Prices

Private

A

B

C

D

Social

 

 

 

 

Effects of Divergences

 

 

 

 

 

The purpose of this chapter is to explain how an analyst goes about the practical task of deciding what data to use in the top row of PAM and how to find that information.

Constructing PAMs for Commodity Systems

            Most agricultural policymakers are interested mainly in understanding competitiveness and efficiency at the farm-gate, since they are concerned with farmer welfare.  But comparable world prices are needed to assess efficiency (as explained in Chapter 4).  For many agricultural commodities, there are no comparable world prices until after the raw commodity has been processed (e.g., from paddy to milled rice).  Comparable world prices for processed goods are available only at the nearby wholesale markets.  Hence, PAM analysts need to define their studies of commodity systems to include four activities – farm production, farm-to-processor transportation, processing, and processor-to-wholesale-market transportation.  Figure 3.2 gives a visual representation of these four activities in a single commodity system and summarizes the content of each activity.

 

            The numeraire (unit of account) typically differs across the four activities within a commodity system.  In most instances, the analyst chooses the numeraire for the processed product in the nearby wholesale market (e.g., Rupiahs per kilogram of milled rice).  Occasionally, it is appropriate to use instead a numeraire that measures revenue per hectare (e.g., Rupiahs per hectare), the farm-gate unit of account.  In either case, it is necessary to use conversion ratios as one moves from the budget for one activity to another within a commodity system.  These conversion ratios (Figure 3.3), contain important physical information such as yields (tons of paddy per hectare) and milling conversion ratios (tons of rice per ton of paddy).

 

 

 

Figure 3.2.  The Structure of a Commodity System for PAM Analysis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


Source:  Adapted from PAM, p. 133

 

 

Figure 3.3.  Conversion Ratios Used in the Calculation of System Cost and Returns

 

Activity

Original units of measure for the activity

Conversion ratios for activity and secondary product revenues

Adjusted units of measure for activity

Farm

rupiahs/hectare

(hectares/mt paddy)  X  (mt paddy/mt milled rice)

rupiahs/mt milled rice

Farm-to-processor

rupiahs/mt paddy

mt paddy/mt milled rice

rupiahs/mt milled rice

Processing

rupiahs/mt milled rice

None

rupiahs/mt milled rice

Processor-to-market

rupiahs/mt milled rice

None

rupiahs/mt milled rice

 

 

 

 

Farm

rupiahs/hectare

None

rupiahs/hectare

Farm-to-processor

rupiahs/mt paddy

mt paddy/hectare

rupiahs/hectare

Processing

rupiahs/ mt milled rice

(mt milled rice/mt paddy) X (mt paddy/hectare)

rupiahs/hectare

Processor-to-market

rupiahs/mt milled rice

(mt milled rice/mt paddy) X (mt paddy/hectare)

rupiahs/hectare

 

Source:  PAM, p. 135 

The Construction of Private Budgets for PAM

            What kinds of data should be entered in the top (Private) row of a PAM?  Empirical application of the PAM approach is based on the compilation of data in budgets.[16]  Because the PAM approach is based on budgets, PAM input data are revenues and costs and profits are found by subtraction as a research result.  Four different budgets are put together for each agricultural system – one on farming, a second on marketing (from the farm to the processing center), a third on processing, and a fourth on marketing (from the processing center to the wholesale market).[17] But before beginning the search for budget information, the PAM analyst needs to select the representative commodity systems that will be studied.  That choice depends on the policy questions that will be addressed by the results of the study. 

Selecting Representative Commodity Systems   

            PAM analysis is carried out at the individual commodity level (for rice, soybeans, coconuts, or cloves).  An early issue that PAM researchers confront is how many agricultural commodity systems to study.[18]  This decision depends critically on the nature of the questions to be addressed in the study.  If the policy of interest were a tariff on rice, for example, the analysts would want to choose a wide range of rice-production systems, including some marginal ones that might require tariff protection to maintain private profitability.  Or if the question were a subsidy on chemical fertilizers, the researchers would want to select a range of crops that use fertilizer, including some systems that might have negative profits without the subsidy. 

 

            In general, researchers need to stratify the population of farmers according to a subset of several variables – the commodities of interest, the geographic regions or agro-climatic zones (distinguished by rainfall, soils, elevation, and slope), the seasons of production and cropping rotations (one wet season and one or two dry seasons), the agricultural technologies (differentiated by water control, inter-cropping, high-yielding seeds, modern inputs, and mechanization), and the areas cropped (owned, rented-in, and rented-out).  By choosing a subset of these stratification variables, researchers can select a workable number of agricultural systems for which to create PAMs.  These variables need to be chosen carefully, because the choice of only four variables, for example, leads to sixteen commodity systems.  That number is near the maximum that any study can easily cover, and it is usually preferable to narrow the system coverage to half that number or even less.

Constructing Farm Budgets

            A number of guidelines assist the compilation of farm budgets.[19]  For most PAM analyses, the farm budgets should be based on actual data from a recent time period, not on optimal performance.  The budgets are intended to be representative of current average farming behavior, not that of the best and most progressive farmers.  The data in the budgets should be measures of average costs and returns.  In this important respect, PAM analysis differs from efforts to build supply schedules of agricultural commodities, which are based on marginal (incremental) costs of production.  The numeraire (the units used to denominate entries in the PAM) is usually domestic currency units per quantity (ton or kilogram) of output, since only farming budgets (and not marketing and processing budgets) can be done using domestic currency units per hectare.  The categories and quantity and price measures for inputs and outputs in farm activity budgets are summarized in Figure 3.4.

 

Figure 3.4.  Inputs and Outputs in Farm Activity Budgets

 

Category

Quantity measure per numeraire

Price measures

Fixed inputs: buildings, fences, land development

Investments, irrigation infrastructure and equipment, machinery, machinery accessories, tools, work animals

 

Useful life

 

Share of annual use

 

Purchase price

 

Salvage value, rate of return

 

Direct labor: unskilled male, female, child; skilled labor, by task

 

Days or hours

 

Wage per day or wage per hour

Intermediate inputs: seeds, fertilizers, insecticides, custom machinery services, repair and servicing equipment

 

Weight or volume; most services charges are not quantifiable

 

Farm-gate price per unit

 

Outputs: main products

 

Weight or volume

 

Farm-gate price per unit

 

Source:  PAM, p. 157

 

            Empirical PAM analysis usually begins with the compilation of synthetic budgets based on secondary data collected by other researchers.  These early budgets are synthetic in two senses – they are not the result of original fieldwork and thus are somewhat artificial, and they are syntheses of existing work.  The purpose of compiling synthetic budgets is to guide the researcher toward essential missing or conflicting information.  Actual fieldwork ideally then can focus on completion, verification, and updating of the synthetic budgets rather than starting from the beginning and building all new budgets.  The computation of synthetic budgets also encourages researchers to carry out a systematic review of existing work on their commodities and regions of interest and thus grounds their research reports firmly in the existing literature.

 

            In carrying out PAM analyses, most of the time spent by researchers is devoted to interviewing farmers, traders, transporters, and processors in the field.  Careful fieldwork is crucial to understanding the farming systems, but it is also expensive in consuming scarce manpower and other project resources.  The budget data needed for PAM entries can be based on relatively small samples of farmers, traders, and processors.  PAM entries are modal values (central tendencies), not econometrically-estimated parameters drawn from statistically valid samples.  Field observations and the allocation of researchers’ time in fieldwork take advantage of this property.  Researchers are encouraged to seek a wide range of informed and expert opinion about the agricultural systems rather than to meet imposed standards of large sample size.

 

            The key to successful fieldwork is to make every effort to ensure that respondents understand the questions asked.  To verify their responses it is important to check key answers (yields, fertilizer applications, output prices, wage rates, and land rental rates) with local experts – traders, brokers, the village head, agricultural officials, and local representatives of the Central Bureau of Statistics.  But errors inevitably creep into all field investigations. 

 

            PAM researchers carrying out fieldwork thus need to be aware of ways to cross check the reliability of the data they are collecting.  If private profits are negative, the farmer must be able to explain this result (usually because of unexpected poor weather or interrupted marketing of inputs or outputs).

 

            Researchers also need to check for possible inconsistencies in data from various respondents.  Variations in yields (output per hectare) need to be consistent with applications of fertilizers and labor.  In processing, conversion factors (e.g., quantity of milled rice per quantity of paddy) and qualities of outputs (e.g., percentage of broken kernels in milled rice) need to be analyzed consistently across processing units.  In cleaning their raw data, PAM researchers should search for inexplicable outliers and then formulate and apply consistent rules for accepting or rejecting interview data.  Particularly with small sample sizes, however, researchers should be cautious before rejecting the results of an apparently inconsistent and inaccurate interview. 

 

            In making estimates of private and social prices in farm budgets, the principle of opportunity costs needs to be applied consistently and widely.  Private opportunity costs reflect market choices.  The opportunity cost of hired labor, for example, is given by the market wage rate, adjusted for any meals and transportation provided by the farmer, trader, or processor.  In contrast, the opportunity cost of family labor is approximated by the market wage rate (if the worker otherwise could find a job off the farm at that rate).  The rental value of a certain quality and location of land depends closely on the productivity of that land in producing various crops – as reflected in the land rental rate or in the land-rent equivalent of share-cropping arrangements. 

 

            Social opportunity costs, in contrast, reflect foregone national income (as explained and illustrated in Chapter 4).  The social rental rate for land devoted to producing rice, for example, is given by the social profitability of that land in its best alternative use.  The opportunity cost principle – that the value of resources is best reflected by the worth of those resources in alternative uses – is the main underlying conceptual principle in budget-based analyses, such as the PAM approach.

Constructing Post-farm Budgets

            The principles and procedures for putting together post-farm (processing and transportation) budgets are similar to those used for farm budgets.[20]  In both instances, researchers select representative activities (farm and post-farm) based on the policy issues under study.  Budgets for both on-farm and post-farm activities require careful compilation of data on revenues and costs and strict application of the opportunity cost principle.  Although the post-farm budgets require different numeraires than those used for on-farm budgets (as explained earlier in this chapter), all of the other procedures outlined for farm budgets apply for post-farm budgets.  Both are based on average, rather than marginal, cost data.  Analysts in both cases should begin by compiling synthetic budgets from secondary information and then verify results through field surveys.  In both types of budgets, researchers can rely on small sample sizes to construct the budgets.  All PAM activity budgets need to be crosschecked for data accuracy and quality. 

 

            Post-farm budgets differ from their on-farm counterparts in two main ways.  Because typically there are far fewer processors and transporters than there are farmers, primary surveys are easier to carry out for the post-farm activities and coverage in the post-farm sample is wider.  Further, most farmers in Indonesia use little, if any, fixed capital equipment.  In contrast, processing and transportation usually involve high fixed capital costs.  Hence, economies of size – declining costs per unit handled as quantities processed or transported increase – are much more important in the post-farm activities than in farming.  Measuring the effects of size economies and estimating depreciation and returns to capital thus are critical issues in post-farm budgets but of little importance in farm budgets.

 

            Once the PAM researcher has compiled the secondary (based on others’ studies) and primary (field-based) information on private revenues and costs for farm and post-farm budgets, s/he is in position to complete the top row of the PAM.  The PAM for a commodity system is the summation of the PAMs for the four component activities (farm, farm-to-processor, processing, and processor-to wholesale-market).  Application of the profitability identity (D = A - (B+C)) gives private profits, an indicator of competitiveness in private (actual market) prices.  This calculation is identical to that done for private benefit-cost analysis.  The usual indicator is the private benefit-cost ratio (PBCR = A/(B+C), which gives a numeraire-free ranking of private profitability.

Tutorial Example of Private Profitability

            The computer tutorial contains a full explanation of how to calculate private costs, returns, and profits in PAM analysis.  The illustrative example used is a high-yielding paddy system in Indonesia.  The analysis proceeds in three steps that are summarized here.  The reader is encouraged to carry out the computer exercise after completing this chapter, because the tutorials are designed to complement the discussion here.

 

            The first step is to construct a table of physical input-output relationships for the paddy system.  This numerical description of the production function summarizes the technology used in this system.  The entries in Table 3.1 are measures of quantities per hectare planted to paddy.  In this illustrative system, among the many inputs used the representative farmer applies 240 kilograms of urea fertilizer and 600 labor hours for crop care per hectare of paddy land.  The average yield of paddy is 6,000 kilograms per hectare.  These input-output coefficients are drawn from the synthetic budgets, the farm interviews, and local expert information.

   

Table 3.1. Physical Input-Output

I-O

Quantities

HY Paddy

Tradables

Fertilizer (kg/ha)

 

 

Urea

            240

 

SP-36

            100

 

KCl

              20

 

ZA

            150

 

Chemicals

 

 

Liquid pesticide (liters/ha)

               3

 

Granulated pesticide (kgs/ha)

              15

 

Seed (kg/ha)

              35

 

Fuel (liters/ha)

              65

Factors

Labor (hr/ha)

 

 

Seedbed Prep

            100

 

Crop Care

            600

 

Harvesting

            200

 

Threshing

            150

 

Drying

              -  

 

Capital

 

 

Working Capital (Rp/ha)

   2,000,000

 

Tractor Services (hr/ha)

              20

 

Thresher (hr/ha)

              35

 

Land (ha)

               1

Output

(kg/ha)

         6,000

 

            The second step is to compile a table of private (actual market) prices for each of the inputs used and outputs produced in the system.  These prices should be representative of the base year of the study.  The private prices for the high-yielding paddy system are presented in Table 3.2.  For example, the cost of urea fertilizer is Rp 1,100 per kilogram, the wage rate for labor used in crop care is Rp 1,600 per hour, and the farm-gate price of the paddy produced is Rp 1,250 per kilogram.   

           

Table 3.2.  Private Prices

P-Prices

Quantities

HY Paddy

Tradables

Fertilizer (Rp/kg)

 

 

Urea

         1,100

 

SP-36

         1,400

 

KCl

         1,600

 

ZA

         1,000

 

Chemicals

 

 

Liquid insecticide (liters/ha)

       30,000

 

Granulated insecticide (kg/ha)

         8,000

 

Seed (Rp/kg)

         2,500

 

Fuel (Rp/liter

         1,500

Factors

Labor (Rp/hr)

 

 

Seedbed Prep

         1,600

 

Crop Care

         1,600

 

Harvesting

         1,600

 

Threshing

         1,600

 

Capital

 

 

Working Capital (%)

5%

 

Tractor Services (Rp/hr)

       12,500

 

Thresher (Rp/hr)

         1,500

 

Land (Rp/ha)

   1,500,000

Output

(Rp/kg)

         1,205

 

            The third and final step is to create a budget in private (actual market) prices by multiplying the quantity entries in the input-output table times the price entries in the private prices table.  Table 3.3 shows the result of this calculation for the high-yielding paddy system.  For this rice system, private profit (after paying land rent) is 37 percent of private revenues and the private benefit-cost ratio (PBCR) is Rp 7,230,000/ Rp 4,548,500 or 1.59.

 

Table 3.3.  Private Prices Budget

P-Budget

Quantities

HY Paddy

Tradables

Fertilizer (Rp/ha)

 

 

Urea

      264,000

 

SP-36

      140,000

 

KCl

       32,000

 

ZA

      150,000

 

Chemicals

              -  

 

Liquid insecticide (Rp/ha)

       75,000

 

Granulated insecticide (Rp/ha)

      120,000

 

Seed (Rp/ha)

       87,500

 

Fuel (Rp/ha)

       97,500

Factors

Labor (Rp/ha)

              -  

 

Seedbed Prep

      160,000

 

Crop Care

      960,000

 

Harvesting

      320,000

 

Threshing

      240,000

 

Capital

              -  

 

Working Capital (Rp/ha)

      100,000

 

Tractor Services (Rp/ha)

      250,000

 

Thresher (Rp/ha)

       52,500

 

Land (Rp/ha)

   1,500,000

Output

Total Revenue (Rp/ha)

   7,230,000

 

Total Cost (excluding land) (Rp/ha)

   3,048,500

 

Profit (excluding land) (Rp/ha)

   4,181,500

 

Net Profit (including land) (Rp/ha)

   2,681,500

 



Chapter 4:  Social Benefit-Cost Analysis (The PAM’s Middle Row)

 

            The second step in the empirical application of the Policy Analysis Matrix (PAM) is an assessment of revenues, costs, and profits in social (efficiency) prices.  Data on social revenues and costs are entered in the middle row of the PAM, commonly called the “social row.”  Figure 4.1 illustrates the entries for the middle row of PAM, which contains measures in social prices (prices that would result in the best allocation of resources and thus the highest generation of income).  As mentioned in Chapter 2, the symbol E measures revenues in social prices, the symbol F stands for tradable input costs in social prices, the symbol G represents domestic factor costs in social prices, and the symbol H is social profit.  Application of the profitability identity (H = E - (F + G)), introduced in Chapter 2, to social revenues and costs gives social profits.  Countries achieve rapid economic growth by promoting activities that generate high social profits (large positive H).

                                                        

Figure 4.1.  Social Profits in the Policy Analysis Matrix

 

 

Revenues

Costs

Profits

 

 

Input

Factor

 

Private

 

 

 

 

Social (efficiency) Prices

Social

E

F

G

H

Effect of Divergences

 

 

 

 

 

 

            The purpose of this chapter is to explain how an analyst goes about the practical task of deciding what data to use in the middle (“social”) row of PAM and how to find that information.

The Social Valuation of Products

            Whereas the compilation of budgets for the top row of PAM is the most time-consuming empirical task in PAM analysis, the estimation of social valuations for products and factors of production is the most challenging analytical task in project and policy analysis.  Because the information needed for this task is vast and often impossible to find, social valuations can only be approximations.  The key to successful PAM analysis is to be able to make reasonable approximations of social prices.  If these estimates are good enough to convince policy makers and other economic analysts of their quality and applicability, they will place credence in the calculations of social profitability (efficiency), given by H in PAM, and of divergences (policy transfers and market failures), given by I, J, K, and L in PAM).  The central goal is to explain carefully how these social valuations are estimated and to stress that they, by their nature, must be rough approximations.

Social Prices for Tradable Outputs and Inputs

            Guidelines for the empirical estimation of the prices of tradable goods are identical for importables and exportables and for outputs and inputs.[21]  The private prices of tradable commodities (for the top row of the Policy Analysis Matrix) are found in the farm budgets from actual market prices at the farmgate, as discussed in Chapter 3.  The counterpart social prices are border prices (comparable import prices for importables and export prices for exportables).

 

            The social (or efficiency) prices of tradable commodities are given by comparable world prices because the import or export price is the best measure of the social opportunity cost of the commodity.  For an importable, the import price indicates the opportunity cost of obtaining an additional unit to satisfy domestic demand.  For an exportable, the export price is a measure of the opportunity cost of an additional unit of domestic production since that unit would be exported, not consumed domestically.

 

            Many international commodity markets are heavily influenced by agricultural price policies, especially those in industrialized economies (the European Union, Japan, and the United States).  These world markets thus do not operate efficiently from the point of view of allocating global resources to their best advantage.  Agricultural protection and subsidization in rich countries create excess supplies and force world commodity prices downward to levels substantially below what they would be in the absence of policies.  But even these distorted international prices provide a useful approximation of the social opportunity cost of importables or exportables in a developing country like Indonesia.  If the other countries’ policies are not expected to change in the foreseeable future, the policy-affected world prices still represent the opportunity costs of Indonesian import substitution or export promotion.  In this perspective, efficiency for Indonesia is a national concept, not a global one, since Indonesia’s policies only directly affect domestic prices and not international prices for nearly all tradable commodities.

 

            The world price in domestic currency units is equal to the world price in foreign currency times the foreign exchange rate (the conversion ratio given in domestic currency units to foreign currency units).  Hence, both the world price in foreign currency and the exchange rate are required to calculate the world price in domestic currency.  If the analysis is addressing the issue of long-run efficiency (or international comparative advantage), it is appropriate to use long-run trend measures of both the world price (in foreign currency) and the exchange rate.  Alternatively, if the study is looking at the historical experience of a recent period (for which the data for the PAM were gathered), it is appropriate to use recent historical data for both world prices (in foreign currency) and the exchange rate.

 

            How can PAM analysts find data on comparable world prices for tradable outputs and inputs?  The first place to look is in published international trade statistics.  If appropriate world prices are not available from the country’s own statistical bureau, they might be found in trade data published by neighboring countries, industry groups, or international organizations (the International Monetary Fund, the World Bank, the Asian Development Bank, or United Nations agencies).  In the rare cases when world prices cannot be found directly, it is sometimes possible to estimate them indirectly.  If there are no market failures and all policies are known and readily measurable, the researcher can adjust the observed private prices (in entries A and B of PAM) for the effects of divergences (entries I and J) and find the social prices (E and F) as residuals.  From the divergences identity, it is known that (A – E = I and B – F = J) and so also (E = A – I and F = B – J).  But this procedure can only be done if the effects of divergences, I and J, are measurable, i.e., if there are no quantitative restrictions affecting trade.

 

            When finding comparable world prices for tradable outputs and inputs, PAM researchers need to take into account three dimensions – location, time, and quality (or form) – of the commodity.  The comparison of a domestic price with a world price must be done at an identical location (e.g., the nearby wholesale market), over the same time period (e.g., the main harvest season), and with a comparable quality of product (e.g., 25 percent broken rice).  Otherwise, the prices will not be comparable because of errors introduced by transportation costs (different locations), the costs of or returns to storage (different time periods), and the costs of processing (different qualities or forms of the product).  Transformations over location, time, and form are the three roles of agricultural marketing.  Comparisons of domestic with world prices of tradables thus need to be done at an identical point in the marketing chain.

 

            If divergences are not important in post-farm activities (farm-to-processor transportation, processing, and processor-to-whole-market transportation), it is convenient to collapse the four activities of the PAM into one and thus to carry out the domestic and world price comparisons at the farmgate level.  For this purpose, the researcher needs to find the import parity prices for goods that substitute for imports and the export parity prices for goods that enter export markets.  For import parity prices, the costs of domestic transportation and handling are added to the import price at the port, because the imports would have to be moved from the port to the nearby wholesale market to compete with local production.  But for export parity prices, the costs of domestic transportation and handling are subtracted from the export price at the port, because the domestic production would have to be moved from the nearby wholesale market to the port before it could be sold abroad. 

 

            Table 4.1 provides an example of the calculations used to compute the social import parity price of paddy.  The calculation of that price begins with the fob (free on board) export price in the exporting country (e.g., $150 per ton of 25 percent broken rice in Bangkok, Thailand).  To find the cif (costs, insurance, freight) import price in a domestic port, one adds international freight and insurance costs (e.g., $15 per ton of rice from Bangkok to Jakarta, Indonesia).  That cif Jakarta cost in US dollars is then converted into local currency with an appropriate exchange rate (e.g., Rp 9000/US$1).  If the calculation hereafter is to be carried out in kilograms rather than tons, that conversion is made.  Transportation and handling costs from the port to the nearby wholesale market are added to move the product to that location.  Because the desired farmgate price is in a different product form, paddy not milled rice, a processing conversion factor is used to convert from milled rice to paddy (e.g., 1 kg paddy = .64 kg milled rice).  Corrections also have to be made for milling costs, losses, and moisture content.  The last step is to add transportation costs from the processor to the farmgate.  Additional procedures and illustrations for calculating import parity and export parity prices are spelled out in the computer tutorial that accompanies this book.

 

Table 4.2. Adjustment of International Prices to Farmgate Level

F.o.b. Thailand ($/ton)

                               150.00

Freight & Insurance ($/ton)

                                 20.00

C.i.f. Indonesia ($/ton)

                               170.00

Exchange rate (Rp/$)

9,000

Exchange rate premium (%)

0%

Equilibrium exchange rate (Rp/$)

                                 9,000

C.i.f. Indonesia in domestic currency (Rp/ton)

1,530,000

Weight conversion factor (kg/ton)

1000

C.i.f. Indonesia in dom. curr. (Rp/kg)

1530.0

Transportation and handling costs to wholesale market (Rp/kg)

133

Value before processing (Rp/kg)

1663.0

Processing conversion factor (%)

0.64

Cost of rice milling net of the value of rice bran

50

Import parity value (Rp/kg)

1014.3

Distribution costs to farm (Rp/kg)

50

Import parity value at farm gate (Rp/kg)

964.3

 

The process behind the import parity price computations in the table is illustrated in Figure 4.2.  Similar calculations are required for tradable inputs such as fertilizer, chemicals, and fuel.     

Figure 4.2.  Adjustment of International Rice Prices to Farmgate Level

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


Social Prices for Nontradable Outputs

            Different guidelines are proposed for the empirical estimation of the prices of nontradable commodities.  As with tradables, the private prices for nontradables are taken from the private budgets at the farmgate level.  But no border prices exist to serve as efficiency valuations for nontradables.  Hence, the social prices of nontradable outputs are estimated by correcting their private prices for divergences (distorting policies and market failures).

 

            Sometimes it is very difficult to estimate the social prices for nontradable commodities.  The first step is to correct the private prices of nontradable outputs for identifiable divergences.  As noted above for tradable products, the researcher tries to adjust the observed private prices (A and B) for the effects of divergences (I and J) and thus find the social prices (E and F) as residuals.  Often, however, the effects of divergences, especially of market failures and sometimes also of distorting policies, are nearly impossible to measure.  If the effects of divergences cannot be estimated, the next step is to search for the price of a close substitute commodity to use as a proxy for the social price of the nontradable commodity.  If that search fails, the last step is to seek the price of the same commodity (or a close substitute) in a neighboring country.

Decomposition of Nontradable Input Costs

            Nontradable input costs cannot be inserted directly into separate columns of a PAM, because there is no direct way of assigning social valuations to this category of costs.  There are no comparable world prices for nontradable inputs.  The desired solution is to decompose these costs, that is, to disaggregate the cost of producing the nontradable goods or services into their underlying tradable input costs and domestic factor costs (skilled and unskilled labor, capital, and land).  Where possible, all nontradable intermediate input costs are allocated among these four PAM categories of costs, and this decomposition is done in both private and social prices.[22]

 

            But this decomposition procedure, straightforward in principle, can be extraordinarily time-consuming in practice.  It involves carrying out full PAM analyses of nontradable products and services (e.g., electricity) and thereby diverts the researchers’ attention from agricultural policy.  To conserve scarce research resources, separate budgeting exercises to disaggregate nontradable costs should be avoided unless a nontradable input makes up more than 5 percent of total costs of production.  Two time-saving approaches can be employed to make rapid approximations in disaggregating nontradable input costs.  The first is to use input-output matrices of the national income accounts to allocate labor and capital shares of nontradable inputs in private prices.  Land costs are ignored, and the residual is allocated to tradable input costs.  The analyst then adjusts the private cost estimates to obtain social approximations.  The second, a last resort if no input-output table is available, is to employ an operational rule of thumb and allocate one-third of nontradable costs each to the capital, labor, and tradable input cost categories.  If the need to make these kinds of arbitrary allocations is widespread, the researcher will need to return to the field for additional information.                   

The Social Valuation of Factors of Production

            For convenience in teaching the PAM approach, all of the costs of primary domestic factors of production – wage, interest, and land rental costs – are considered together in the matrix column titled domestic factor costs.[23]  However, each factor market and sub-market is studied separately in the empirical application of PAM.  In practice, there are separate columns of data entries for each type and quality of factor (e.g., skilled male labor). 

Approach to Studying Factor Markets

            Domestic factor costs are treated differently from tradable input costs because there are no international prices for domestic factors that appropriately establish their social opportunity costs.  A portion of some domestic factors, such as labor and capital, is mobile and receives employment abroad.  But the opportunity costs of these factors are set in domestic markets, not in international markets.  Wage, interest, and land rental rates are determined mostly by domestic supply and demand for factors, not by opportunities to employ factors overseas.  Factors thus are not fully tradable internationally, and there are no international factor prices that can serve as good approximations of domestic opportunity costs.

 

            This absence of world prices for factors means that social (or efficiency) prices for factors have to be approximated.  The approach used in PAM analysis is to find the social prices of factors by adjusting the observed private prices for divergences.  Field researchers study each rural factor market to search for the presence or absence of divergences – effective distorting policies or significant market failures.  Hence, the entry for factor divergences (K) becomes a research input, which then is used to estimate social factor prices from observed private factor prices, as noted in Chapter 2.

 

            In PAM analysis, therefore, social factor prices (G) are found by adjusting private factor prices (C) for observed divergences causing factor price transfers (K).  Because the divergences identity requires that (C – G) = K, it is also true that (C – K) = G.  In empirical application of PAM, the entries for G cannot be observed directly or found by using international prices.  Hence, the entries for C and K are research inputs and those for G are research results.  Factor Costs in the PAM are illustrated in Figure 4.3.

 

                                                       

Figure 4.3.  Factor Costs in the Policy Analysis Matrix

 

 

Revenues

Costs

Profits

 

 

Input

Factor

 

Private

 

 

C

 

Social

 

 

G

 

Effect of Divergences

 

 

K

 

 

Fragmentation in Factor Markets

            Fragmentation is the separation of factor sub-markets caused by immobility of factors or lack of free exit and entry.  When fragmentation occurs, a factor sub-market is not well integrated and differing factor prices are observed from one fragment of the market to another.  In seeking to find the extent of factor transfers (K), the PAM researcher’s task is to identify the causes of factor market fragmentation.

 

            All factor markets are fragmented to some degree, by geography or types of actors.  Some fragmentation is immutable. Regional land markets differ by distance from urban centers or ports, agro-climatic zone, soil quality, and slope of land.  In some regions land has higher agricultural productivity than in others. Differing land rental rates reflect these physical differences and agricultural productivities and are not necessarily indicative of imperfections in the land markets.

 

            Other fragmentation is caused by factor market failures.  In rural areas of developing countries, institutions to assist the provision of factor services often are in short supply or entirely missing.  Imperfect capital markets, for example, arise when banks or other providers of financial intermediary services are poorly represented in rural areas.  In other instances, the lack of reliable information networks cause factor markets to fail to operate efficiently.  Rural laborers seeking daily work need to know where employment can be found.  

 

            Much fragmentation is caused by distortions, policies that cause the costs of factors to be higher (taxing factor use) or lower (subsidizing factor use) than their efficient, market-determined costs. Some governments in developing countries enact regulations to set ceilings (usually for interest rates) or floors (usually for wage rates) for factor prices in hopes of speeding development or redistributing income. Other governments tax or subsidize factor use.  Legislated employer contributions to pension or health care plans for their employees increase the costs of hiring labor and tax labor use. Subsidized interest rates decrease the cost of borrowing capital for those who benefit from them.  

 

            The concept of fragmentation is useful for empirical study of factor markets.  The researcher begins by separately considering each factor market and its sub-markets (e.g., skilled and unskilled, male and female laborers constitute four sub-markets within the labor market).  Next within each factor sub-market, the researcher looks for the causes and extent of fragmentation.  If fragmentation is immutable, such as within regional land markets, it is noted but not included as a source of divergence in land rental rates.  Other fragmentation can be caused by divergences – market failures or distorting policies.  The often complicated task for the field researcher is to try to sort out how much of the observed fragmentation is due to market failures – lack of institutions or information – and how much is due to distorting government policies – regulations or taxes/subsidies.[24]

Factor Price Determination

            The demand for factors of production is mostly a derived demand.  Some factors are hired directly by people who benefit from the factor services, but most factors are used in the production of other goods and services.  Therefore, the demand for factors varies with changes in factor and output prices and with the productivity of factors in production processes.  Firms demand factor services only to the extent that it is profitable for them to employ the factors.  Higher factor prices thus translate immediately into lower demand by firms for the services of the more costly factors. 

 

            The supply of factors is determined by individual decisions of factor owners to provide factor services.  Each individual capable of providing labor or management skills establishes how much he or she will be willing to work at various rates of remuneration (known as the labor-leisure trade-off).  Owners of capital (savers) decide how much they will save and make available to others (borrowers) at various rates of interest.  Similarly, owners of land decide how much land they will rent out according to the rental rates they will receive.  In all three instances, more factor services will be offered at higher rates of return for those services.

 

            Price determination in factor markets then takes place in a manner similar to that discussed for goods (summarized in Chapter 5).  The factor market is in equilibrium when the amount of factor services offered at a given factor price equals the amount of those services demanded at that price.  Price formation thus is a simultaneous process determined by the joint actions of the willingness of factor owners to provide factor services and the desire of firms and others to hire those factors.  The factor price will be determined efficiently unless the market is fragmented by the presence of market failures or distorting policy.

Estimation of Factor Prices

            The social (efficiency) prices for domestic factors of production (land, labor, and capital) are estimated by application of the social opportunity cost principle.  Because domestic factors are not tradable internationally and thus do not have world prices, their social opportunity costs are estimated through observations of rural factor markets.  The intent is to find how much output and income are foregone because the factor is used to produce the commodity under analysis (e.g., rice) rather than the next best alternative commodity (e.g., sugarcane).

 

            The empirical estimation of social prices of factors of production involves making a series of educated guesses.  The estimated parameters are at best approximations.  Formal modeling procedures cannot give reliable estimates for developing countries.

 

            The process of approximating social factor prices begins by observing and collecting private market prices for each type and quality of factor of production used in the agricultural system under analysis.  These data on private factor prices then are entered in box C in the PAM.

 

The next step is to identify the extent of fragmentation of factor markets and its causes – natural (immutable), market failure (changeable with institutional development), and distortion (policy-induced).  Fragmentation results if the prices for one type of factor differ across sub-markets.  PAM field researchers need to compare prices for the same type and quality of factor across separated (fragmented) markets to identify the extent of fragmentation.

 

Important evidence of the existence or lack of market failures is obtained by checking the degree of freedom of entry or exit of factors in the fragmented markets.  If providers of factor services can easily move into and out of sub-markets, it is unlikely that monopolies or monopsonies are responsible for the differing factor prices.

 

If market failures do not seem to be causing the fragmentation, the divergence must be caused by distorting policy.  The researcher then searches for the existence of enforceable policies that would cause the market fragmentation.  After identifying the market failures and distorting policies (the entries in K in the PAM), the social factor prices (G) are found by adjusting the observed private factor prices (C) for the divergences (K), since G = (C – K).

Estimation of Private and Social Wage Rates

To compile detailed farm budgets, PAM researchers classify labor into categories according to gender (female or male), age (child or adult), and skill level (unskilled, semi-skilled, skilled, or managerial).  The key issue is whether labor productivity differs enough between categories to cause differences in equilibrium wage rates.  The observed data on private wage rates (multiplied by the labor input coefficients) are then entered into box C in the PAM.

 

The next step is to search for the existence or lack of market failures and of policy distortions in each labor sub-market.  Quantitative estimates of these divergences are then entered in box K of the PAM as a research input.

 

Two types of market failures that might affect rural labor sub-markets in developing countries are monopsonies or oligopsonies (where one or a few large hiring firms collude to depress wage rates) and trade union power (where an organized group of workers legally forces wages upward).  Easy entry and exit of laborers in each sub-market is strong evidence of the ineffectiveness of market power exercised by either hiring firms or trade unions.

 

Two types of distorting policies that might affect rural labor sub-markets in developing countries are minimum wage laws and pension and health insurance taxes (where the government requires employers to contribute to their employees’ pension and health plans and thus raises the cost of hiring labor).  These kinds of policies are widespread in developing and developed countries, but they often are not well enforced in agriculture (except in plantations and processing plants).  Policies that do not change labor costs, because they are not widely enforced, are ineffective and can be ignored in PAM analysis.[25]

Estimation of Private and Social Interest Rates

Both private and social interest rates need to be estimated in PAM analysis.  During each interview with a farmer, trader, or processor, it is desirable to seek information on sources of credit and on the private interest rates paid with each credit source.  Four sources of agricultural credit, and four corresponding levels of private interest rates, are commonly found in developing countries. 

 

1)      Farm household savings, from on-farm and off-farm activities, often provide most finance in farming because they usually are the lowest cost.  Savings reflect foregone consumption or investment.  The opportunity cost of self-financing production from household savings is thus the amount given up by not earning interest in a savings account.

 

2)      Formal credit market institutions, such as commercial and government banks and other financial institutions, typically offer relatively little lending to small-scale farmers and traders, although their interest rates are moderate.  These institutions are under-represented in rural areas and have high collateral requirements.

 

3)      Kiosk-owners and other traders that sell fertilizer and related agricultural inputs often are an important source of credit for farmers, although with quite high interest charges.  Informal credit flows between farmers, on one side of the transaction, and traders or suppliers of labor services, on the other, can vary across seasons so that farmers are borrowers in one part of the year and lenders in another.

 

4)      Local money-lenders generally are the most expensive source of agricultural credit.  Because their interest charges can exceed 10 percent per month, farm households avoid money-lenders for agricultural production and use them mostly in family emergencies.

 

Some governments offer subsidized agricultural credit.  The subsidized interest rates are rarely representative of the private interest rates facing farmers because the subsidy programs typically fail to reach most farmers.  PAM field researchers need to ascertain the effectiveness of subsidized credit programs to judge the rate of subsidy for representative farmers in the agricultural systems under study (and thus the entry in box K in the PAM).

     

Capital costs in PAM analysis are classified into two categories – working capital and investment capital.  Working capital is the finance that a farmer, trader, or processor needs to cover cash costs of production (purchased inputs, hired labor, storage) within a production year.  Investment capital refers to expenditures on assets that provide productive services for periods longer than one year.  With investment capital, costs are incurred in one (or a few) year(s) but benefits (or productive services) are spread over a number of future years.

 

Capital market failures are usually widespread in developing countries because of the shortage of financial institutions in rural areas.  The observed private interest rates, listed above, thus typically are a poor approximation of the social interest rates even if the government does not intervene with distorting policies, such as rural credit subsidies or interest rate ceilings.

 

Because of the complexity of possible market failures and distorting policies affecting rural credit markets, it is virtually impossible to measure the extent of these divergences.  In PAM analysis (and in most other applications of social benefit/cost analysis), researchers are forced to adopt a different approach to estimate social interest rates.  In principle, the social return to capital is represented by the rate of return on the next public or private investment that would be undertaken with additional investment funds.  In practice, to estimate the social rates of interest for working capital and for investment capital, PAM researchers use an arbitrary rule of thumb – the experience of other developing and developed countries when they were at similar levels of development as the country in question.[26]

Estimation of Social Land Rental Rates

            Land is a fixed factor in agricultural production.  Unlike labor and capital, which are mobile and can move to alternative activities, land is immobile.  Unless the land happens to be located near an urban center and has residential or industrial uses, the opportunity cost of land planted to one crop (or cropping rotation) depends on its value in growing the next best alternative crop.  Farmers allocate their land according to the relative profitability of various crops (along with household food needs and risk).  The value of agricultural land in land sales markets or in land rental markets depends on its productivity and hence its profitability for farmers who might buy or rent in the land.

 

The social valuation of land follows the social opportunity cost principle.  From the point of view of the national economy, the social land rental rate is found by estimating the social profit (H) of the land in its best alternative use when all costs of land are excluded.  For example, the social cost of using a plot of land to grow rice in one season is found by estimating the foregone social profit from not planting that land to the next most profitable crop (e.g., sugarcane).  However, this approach requires the researcher to identify the best alternative crop and to carry out a full PAM analysis on it.

 

If it is not practical to study the alternative crops that might substitute for the crop of primary interest, a different approach can be taken in PAM analysis.  Profitability is re-defined to include returns to land and management (rather than only returns to management).  Land costs then are omitted from both private and social calculations.  Because of the difficulty and expense of studying alternative crops to estimate social land rental rates, many PAM analysts adopt this modified approach.[27]

Factor Price Estimation for Indonesian Agriculture

Estimation of social factor prices can be illustrated with reference to an ongoing series of PAM analyses of Indonesian agriculture carried out by researchers from the Center for Agro-Socio Economic Research in Bogor, Indonesia (CASER).[28]  A comparative PAM study of rice systems in Indonesia was carried out in the late 1980s by Stanford University’s Food Research Institute.[29]

 

Both the Stanford and the CASER studies find minimal divergences affecting rural labor markets in Indonesia.  Distortions are insignificant, because the minimum wage legislation is not enforced in agriculture and has limited impact elsewhere in the Indonesia economy.  Fragmentation across labor sub-markets is minor, because of free entry and exit across sub-markets, good information on job opportunities, and widespread use of labor contractors.  Therefore, the private wage rates for all categories of rural labor are good approximations for the social wage rates (in PAM terms, K is minimal, so G about equals C).

 

This conclusion does not hold true in the urban labor markets in which much of the post-farm processing and marketing take place.  The wage rates for all categories of labor in the urban markets are influenced by two kinds of policy distortions, although not importantly by market failures.  Minimum wage legislation is enforced in urban markets.  But the distortions are very small since the minimum wage rate is not much different from the comparable market wage rate.  In the urban labor markets, social legislation (for pensions and medical insurance) is enforced and causes somewhat higher labor costs.  Adjustments thus are made for these distorting policy impacts (in PAM terms, K is slightly positive, reflecting a small tax on labor, so G is less than C).

The CASER and Stanford studies also provide current and historical estimates of social prices for capital and land in Indonesian agriculture.  For capital investment, the private interest rates vary widely (among different financial intermediaries, types of borrowers, and locations).  Based on the experience of other countries at comparable stages of development, the social interest rate for capital investment in Indonesia is likely to be about 10-15 percent per annum (plus the rate of inflation).  For working capital, the private interest rates also vary widely.  From other countries’ experiences, the social interest rate for working capital in Indonesia is likely to be about 15-20 percent per annum (plus the rate of inflation).

 

The private land rental rate in Indonesian agriculture differs according to land quality and location (usually reflecting the private profitability of farming).  Where possible, the social land rental rate is found by valuing land at the social profitability of the next best alternative crop (or cropping rotation).  Otherwise, land costs are excluded from the estimation of both private and social profitability and private and social profits are re-defined to include the returns to land and management.

Tutorial Example of Social Profitability

            The calculation of social profitability for the illustrative high-yielding rice system in Indonesia is also presented in the accompanying computer tutorial.  Like the estimate of private profitability, that for social profits proceeds in three steps.  For most PAM applications, the assumption is made that the input-output coefficients are identical for both private and social analyses.  Hence, the input-output data reported above in Table 3.1 are used also in the calculation of social costs and returns.

 

            The challenges in social analysis thus arise in finding appropriate social prices for all inputs and products.  For tradable inputs and outputs, the key issues are assessing the comparable import or export prices in foreign currency, converting those prices with a suitable exchange rate, and adjusting the domestic currency prices to the farm-gate level.  This process of conversion and adjustment for form, time, and location was illustrated above for paddy output in Table 4.1 and Figure 4.2.  The full set of social prices for the illustrative paddy system is presented in Table 4.2. 

 

Table 4.2.  Social Prices

S-Prices

Quantities

HY Paddy

Tradables

Fertilizer (Rp/kg)

 

 

Urea

         1,100

 

SP-36

         1,400

 

KCl

         1,600

 

ZA

         1,000

 

Chemicals

 

 

Liquid insecticide (liters/ha)

       40,000

 

Granulated insecticide (kg/ha)

       10,000

 

Seed (Rp/kg)

         2,500

 

Fuel (Rp/liter

         1,500

Factors

Labor (Rp/hr)

 

 

Seedbed Prep

         1,600

 

Crop Care

         1,600

 

Harvesting

         1,600

 

Threshing

         1,600

 

Capital

 

 

Working Capital (%)

8%

 

Tractor Services (Rp/hr)

       12,500

 

Thresher (Rp/hr)

         1,500

 

Land (Rp/ha)

              -  

Output

(Rp/kg)

            964

 

            As in the creation of a private budget, the final step in creating a social budget is to multiply the quantities in the input-output table (Table 3.1) times the efficiency prices in the social prices table (Table 4.2).  The resulting values become the entries in the social budget table (Table 4.3).  For this high-yielding rice system, social profit (returns to management and land) is 45 percent of social revenue and the social benefit-cost ratio (SBCR) is Rp 5,784,000/ Rp 3,163,500 or 1.8.

Table 4.3.  Social Prices Budget

S- Table 4.Budget

Quantities

HY Paddy

Tradables

Fertilizer (Rp/ha)

 

 

Urea

      264,000

 

SP-36

      140,000

 

KCl

       32,000

 

ZA

      150,000

 

Chemicals

              -  

 

Liquid insecticides (Rp/ha)

      100,000

 

Granulated insecticides (Rp/ha)

      150,000

 

Seed (Rp/ha)

       87,500

 

Fuel (Rp/ha)

       97,500

Factors

Labor (Rp/ha)

              -  

 

Seedbed Prep

      160,000

 

Crop Care

      960,000

 

Harvesting

      320,000

 

Threshing

      240,000

 

Capital

              -  

 

Working Capital (Rp/ha)

      160,000

 

Tractor Services (Rp/ha)

      250,000

 

Thresher (Rp/ha)

       52,500

 

Land (Rp/ha)

              -  

Output

Total Revenue (Rp/ha)

   5,784,000

 

Total Cost (excluding land) (Rp/ha)

   3,163,500

 

Profit (excluding land) (Rp/ha)

   2,620,500

 

Net Profit (including land) (Rp/ha)

 


     Chapter 5:  Policies and Market Failures (The PAM’s Bottom Row)

The types of results available from PAM analysis were introduced in the previous three chapters.  Profitabilities follow from application of the profitability identity, whereas the effects of divergences are derived from application of the divergences identity.  Private profitability, defined in PAM as D = A – (B + C), measures competitiveness in actual market prices. 

Social profitability, defined in PAM as H = E – (F + G), measures efficiency (or comparative advantage) in efficiency prices.

 

            This chapter focuses on identifying and interpreting the effects of divergences.[30]  A divergence causes an actual market price to differ from a counterpart efficiency price.  Divergences arise from either of two sources – market failures or distorting policies

 

            A market failure occurs if a market fails to provide a competitive outcome and an efficient price.  Common types of market failures are monopolies, externalities, and factor market imperfections.  A distorting policy is a government intervention that forces a market price to diverge from its efficient valuation.  Taxes/subsidies, trade restrictions, or price regulations could lead to this result.  Distorting policies usually are enacted to further non-efficiency objectives (equity or security).

Output Transfers in the Policy Analysis Matrix

A divergence in output prices, causing private revenues (A) to differ from social revenues (E), creates an output transfer (I = (A – E)).  The output transfer (I) is illustrated in Figure 5.1.  This divergence can be either positive (causing an implicit subsidy or transfer of resources in favor of the agricultural system) or negative (causing an implicit tax or transfer of resources away from the system).

                                                           

Figure 5.1.  Output Transfers in the Policy Analysis Matrix

 

 

Revenues

Costs

Profits

 

 

Input

Factor

 

Private

A

 

 

 

Social

E

 

 

 

Effect of Divergences

I

 

 

 

 

            For example, Indonesia currently imposes a tariff on rice imports, causing domestic rice prices to be about 25 percent higher than the world price (the efficiency price).  This distorting policy creates a positive divergence (entry I in the PAM matrix), and the effect of the divergence is the difference between the domestic price (entry A in PAM) and the social (import) price (entry E in PAM).  The tariff thus creates an implicit subsidy to rice production because it causes the domestic rice price to be higher than in the absence of policy.  In this example, a part of the divergence is caused by a rice traders’ risk premium and the remainder is due to the tariff on rice (as discussed in Chapter 1).

Interpretation of Output Transfers

The PAM entries for output transfers are I = (A – E).  The unit used to denominate every entry in the PAM matrix is called a numeraire.  All entries in a PAM, including measures of output transfers, are denominated in local currency units per kilogram (or per ton) of the primary commodity produced (and sold) for comparisons of agricultural systems producing one commodity.  To compare rice production systems in Indonesia, for example, the numeraire would be Rupiah per kilogram of milled rice at the mill or Rupiah per kilogram of wet paddy (unmilled rice) at the farm gate.

 

            Ratios, which are free of currency or commodity distinctions, are used to compare unlike outputs (e.g., rice and sugarcane).  The ratio formed to measure output transfers is called the Nominal Protection Coefficient on Output (NPCO), a term taken from the literature on international trade.  NPCO = A/E.  This ratio shows how much domestic prices differ from social prices.  If NPCO exceeds one, the domestic price is higher than the import (or export) price and thus the system is receiving protection.  If NPCO is less than one, the domestic price is lower than the comparable world price and the system is disprotected by policy.  In the absence of policy transfers (i.e., if I equals zero), the domestic and world prices would not differ and the NPCO would equal one.

 

            PAM analysts need to search carefully for the existence or absence of market failures – monopolies or externalities – affecting output markets.  Past studies of agricultural systems in developing countries have found that significant market failures influencing outputs are rare.  Monopolies that were found typically were established by government regulations.

 

            Most output transfers, where they occur, have been caused by distorting policies.  One source of distortions is price policy – trade restrictions or taxes/subsidies – enacted to promote non-efficiency objectives.  A second source of output transfers comes from disequilibrium exchange rates arising from macro-economic policies that are not in balance.  The efficiency prices for outputs are set by comparable world prices.  Distorting price policy forces a departure of domestic prices from those efficiency prices, and inappropriate exchange rate policy means that the wrong conversion factor is used to convert world prices from foreign exchange to domestic currency.

Example of Output Transfers

An illustration of output transfers in the high-yielding Indonesian rice system is presented in Table 5.1.

 

Table 5.1. Example of Output Transfers

Revenues (rupiahs per hectare)

Private

        7,230,000

 

A

 

Social

        5,784,000

 

E

 

Divergences

        1,446,000

 

I

 

 

 

 

 

 

I

 A-E

   1,446,000

 

 

NPCO

A/E

1.25

 

 

 

 

            In that example, the commodity system produced only one output – milled rice. The value of milled rice in private prices (Rp 7,230,000 per hectare) was about 25 percent higher than the value in social prices (Rp 5,784,000 per hectare).  The output transfer (Rp 1,446,000 per hectare) was caused by a specific tariff of Rp 430/kilogram on rice imports, which resulted in a tariff-equivalent of 25 percent.

 

            The Nominal Protection Coefficient on Output (NPCO) or A/E was 1.25.  Because of the tariff on milled rice imports, the value of total output was 25 percent higher than it would have been in the absence of policy.

Tradable Input Transfers in the Policy Analysis Matrix

A divergence in tradable input prices, causing private tradable input costs (B) to differ from social tradable input costs (F), creates a tradable input transfer (J = (B – F)).  The tradable input transfer within PAM is demonstrated in Figure 5.2.  This divergence can be either positive (causing an implicit tax or transfer of resources away from the system) or negative (causing an implicit subsidy or transfer of resources in favor of the agricultural system).

 

                                                                                                      

Figure 5.2.  Tradable Input Transfers in the Policy Analysis Matrix

 

 

Revenues

Costs

Profits

 

 

Input

Factor

 

Private

 

B

 

 

Social

 

F

 

 

Effect of Divergences

 

J

 

 

 

            A subsidy on pesticides, for example, would mean that farmers would pay only (B), a portion of the full cost of pesticides (F).  The government treasury would pay the remainder (J) as the pesticide subsidy.  The entry, J = (B – F), would be negative (since B is less than F by the amount of the subsidy).  A subsidy reducing input costs thus enters the PAM matrix as a negative entry in the Effects of Divergences row.

 

            The opposite holds true for taxes on tradable inputs.  A tax on fuel, for instance, would mean that fuel cost paid by farmers (B) would exceed the opportunity cost given by the world price (F) by the amount of the tax (J), and the entry, J = (B – F), would be positive.

Interpretation of Tradable Input Transfers

The PAM entry for tradable input transfers is J = (B – F).  The interpretation of tradable input transfers is similar to that for tradable output transfers because both are based on comparisons of actual market (private) prices with world (social) prices.

 

Ratios, which are free of currency or commodity distinctions, are used to compare unlike tradable inputs (e.g., fertilizer and fuel).  The ratio formed to measure tradable input transfers is called the Nominal Protection Coefficient on Inputs (NPCI), a term also taken from the literature on international trade.  NPCI = B/F.  This ratio shows how much domestic prices of tradable inputs differ from their social prices.  If NPCI exceeds one, the domestic input cost is higher than the input cost at world prices and the system is taxed by policy.  If NPCI is less than one, the domestic price is lower than the comparable world price and the system is subsidized by policy.  In the absence of policy transfers (i.e., if J equals zero), the domestic and world prices of tradable inputs would not differ and the NPCI would equal one.

 

            A second ratio, the Effective Protection Coefficient (EPC), can be calculated directly using entries from the PAM matrix.  This ratio compares valued added in domestic prices (A – B) with value added in world prices (E – F).  EPC = (A – B)/(E – F).  The purpose of the EPC is to show the joint effect of policy transfers affecting both tradable outputs and tradable inputs. The EPC is a variant of the Effective Rate of Protection (ERP), a common measure of trade distortions.  ERP = (EPC – 1) x 100%.[31]

 

            PAM analysts need to search carefully for the existence or absence of market failures – monopolies or externalities – affecting tradable input markets.  Past studies of agricultural systems in developing countries have found that significant market failures influencing tradable inputs are rare.  As in the markets for tradable outputs, most monopolies found were established by government regulations, not by private cartels.

 

           

Most tradable input transfers thus are caused by distorting policies.  As with tradable outputs, two sources of divergences affect the prices of tradable inputs – price policies (trade restrictions or taxes/subsidies) and disequilibrium exchange rates.

   Example of Tradable Input Transfers

An illustration of tradable input transfers in the Indonesian rice system is presented in Table 5.2.  In that example, the rice system used three tradable inputs – fertilizer, chemicals, and other (seed and fuel).

Table 5.2. Example of Tradable Input Transfers

Tradable input costs (rupiahs per hectare)

 

Fertilizer

Chemicals

Other

Total

 

Private

           586,000

      195,000

         185,000

        966,000

B

Social

           586,000

      250,000

         185,000

      1,021,000

F

Divergences

                   -  

       (55,000)

                 -  

         (55,000)

 J

 

 

 

 

 

 

I

B-F

       (55,000)

 

 

 

NPCI

B/F

0.95

 

 

 

 

            The cost of chemicals (insecticides and herbicides) in private prices (Rp 195,000 per hectare) was much less than the cost of chemicals in social prices (Rp 250,000 per hectare).  The entire negative tradable input transfer (-55,500 per hectare) was caused by a subsidy on chemicals of about 28 percent.

 

            For all tradable inputs, the total tradable input policy transfer (J) thus was –Rp 55,000 per hectare.  The Nominal Protection Coefficient on Inputs (NPCI) was B/F or 195,000/250,000 = .78.  Because of the subsidy on chemicals, the total cost of tradable inputs was only about 75 percent of what it would have been in the absence of policy.

Factor Transfers in the Policy Analysis Matrix

Divergences can influence the prices of domestic factors (skilled labor, unskilled labor, capital, and land).  Factor market divergences cause private factor costs (C) to differ from social factor costs (G) and thus create a factor transfer (K = (C – G)).  Factor transfers are illustrated in the PAM framework in Figure 5.3.  As with divergences affecting tradable input costs, this factor divergence can be either positive (causing an implicit tax or transfer of resources away from the system) or negative (causing an implicit subsidy or transfer of resources in favor of the agricultural system).

                                                                                                                                                                         

Figure 5.3.  Factor Transfers in the Policy Analysis Matrix

 

 

Revenues

Costs

Profits

 

 

Input

Factor

 

Private

 

 

C

 

Social

 

 

G

 

Effect of Divergences

 

 

K

 

 

Interpretation of Factor Transfers

The PAM entry for factor transfers is K = (C – G).  Divergences in factor markets result from both market failures and distorting policies.

 

            Past studies of agricultural systems in developing countries have found that significant market failures influencing factor prices are common.  Researchers thus should assume that factor markets are imperfect unless careful examination shows that private factor prices appear to be reasonable approximations of social factor prices.  Approaches to identifying imperfections in factor markets are outlined in Chapter 4.

 

            Factor transfers can also result from distorting policies.  Distortions in labor and capital markets arise from taxes or subsidies (e.g., a pension tax on wages or a credit subsidy), price regulations (e.g., minimum wage floors or interest rate ceilings), or distorting macro-economic policies (e.g., inflationary monetary policy).  Approaches to identifying policy distortions in factor markets are also outlined in Chapter 4.

Example of Factor Transfers

            An illustration of factor transfers in the Indonesian rice system is presented in Table 5.3.  In that example, the rice system used two factor inputs –labor and capital.  Divergences in the market for unskilled labor in rural Indonesia were insignificant, as explained in Chapter 4.  Hence, the private unskilled wage rate was assumed to be a good proxy for the social unskilled wage rate.

 

Table 5.3. Example of Factor Transfers

 

Factor Costs (rupiahs per hectare)

 

 

Labor

Capital

Total

 

Private

        1,680,000

      402,500

      2,082,500

C

Social

        1,680,000

      462,500

      2,142,500

G

Divergences

                   -  

       (60,000)

         (60,000)

K

 

            The subsidy on capital costs was implicit rather than an explicit subsidy from the government treasury.  The implicit subsidy appears because the social opportunity cost of working capital in the example was taken as 24 percent annually (8 percent per season) whereas the private annual interest rate for working capital was assumed to be only 15 percent (5 percent per season).  The factor transfer on capital was a subsidy amounting to 15 percent of total capital costs, or Rp 60,000 per hectare.  The net factor transfer was a subsidy of only 3 percent of total factor costs, because the credit subsidy was small relative to total costs.

Net Transfers in the Policy Analysis Matrix

Positive output transfers (I) create subsidies for an agricultural system (because they lead to higher revenues), whereas negative tradable input transfers (J) and factor transfers (K) denote subsidies (because they indicate reduced costs of production).  Similarly, negative output transfers impose taxes on a system, whereas positive tradable input and factor transfers create taxes.  The net transfer (L), shown in the PAM framework in Figure 5.4, is the sum of these positive and negative transfer effects on revenues and costs.

                                                                                                                                                                                                                                 

 

Figure 5.4.  Net Transfers in the Policy Analysis Matrix

 

 

Revenues

Costs

Profits

 

 

Input

Factor

 

Private

A

B

C

D

Social

E

F

G

H

Effect of Divergences

I

J

K

L

 

Interpretation of Net Transfers

The net transfer, designated by entry L in the PAM, is found by applying either of the two PAM accounting identities.  From the profitability identity, L = (I – J – K).  The net transfer is the sum of output, tradable input, and factor transfers.  From the divergences identity, L = (D – H).  The net transfer explains the difference between private and social profits.  If efficient policies exactly offset market failures and all distorting policies are removed, divergences disappear and the net transfer becomes zero. The net transfer also becomes zero if distortions in output prices are offset by equal and opposite distortions in input prices.

 

            Calculation of two ratios assists the comparison of PAM results among agricultural systems that produce unlike commodities.  The profitability coefficient (PC) measures the impact of all transfers on private profits.  PC equals the ratio of private profits to social profits, or PC = D/H = (A – B – C)/(E – F – G).  The PC ratio uses the same data as the calculation of net transfer, L = (D – H), and thus allows a comparison of net transfers among unlike systems.  The PC also is an expansion of the EPC to include factor costs (along with revenues and tradable input costs).

 

            The subsidy ratio to producers (SRP) is a single measure of all transfer effects.  The SRP is the output tariff equivalent if the net effect of all policy transfers were carried out solely through a tariff on output.  This ratio is a comparison of the net transfer to the value of output in world prices, or SRP = L/E.  The SRP indicates the extent to which the system’s revenues are increased or decreased because of transfers.  If market failures are minor, the SRP shows the net impact of distorting policies on system revenues.

   Example of Net Transfers

            An illustration of the net transfer in the Indonesian rice system is presented in Table 5.4.  In that example, the net transfer for the system and the summary ratios are calculated and interpreted.

           

Table 5.4. Net Transfer, Profitability Coefficients, and Subsidy Ratios

to Producers in Indonesian Rice Systems

 

Revenues

Costs

Profits

 

 

 

Input

Factor

 

 

Private

        7,230,000

      966,000

      2,082,500

      4,181,500

 

Social

        5,784,000

   1,021,000

      2,142,500

      2,620,500

 

Divergences

        1,446,000

       (55,000)

         (60,000)

      1,561,000

             -  

 

 

 

 

 

 

 

EPC

(A-B)/(E-F)

1.32

 

 

 

NPCI 

B/F

.95 

 

 

 

NPCO

A/E

1.25

 

 

 

PC

D/H

1.60

 

 

 

SRP

L/E

0.27

 

 

 

            The rice system is socially profitable in the absence of policy (H = Rp 2,620,500 per hectare).  The net transfer is the sum of all divergences (L = (I – J – K)) and also is the difference between private and social profits (L = (D – H)).  The net transfer for the rice system, Rp 1,561,000 per hectare, is the sum of the output transfer (Rp 1,446,000 per hectare), caused by a specific tariff on rice, the tradable input transfer (Rp 55,000), resulting from subsidies on chemicals, and the factor transfer (Rp 60,000 per hectare), deriving from imperfections in the market for working capital.  The net transfer also is the difference between private profits and social profits, or Rp 4,181,500 less Rp 2,620,500 = Rp 1,561,000.

 

            The Profitability Coefficient (PC) for the system, the ratio of private profits to social profits, or PC = D/H, is Rp 4,181,500/2,620,000 = 1.6.  The net transfer of Rp 1,561,000   permitted private profits to be more than one and one-half times greater than they would have been without policy transfers.  Researchers thus need to discover why policy makers in Indonesia enacted policies to assist an agricultural system that was very profitable without the aid of policy transfers.

 

            The Subsidy Ratio to Producers (SRP), the ratio of net transfer to revenues in social prices, or L/E, is Rp 1,561,000 per hectare/Rp 5,784,000 per hectare = .27.  The net transfer could be created solely by a tariff on rice of 27 percent if all other divergences were eliminated.  If there were no divergences affecting tradable inputs or factors, the NPCO would have to be increased only from 1.25 to 1.27 to maintain a net transfer equivalent to Rp 1,625,500.  This result indicates that nearly all the subsidy to rice producers comes from the tariff on rice and very little is transferred from the subsidy on chemicals and the implicit subsidy on working capital costs.

Farming Systems PAM

            The previous PAM was created under the assumption that the social opportunity cost of land could not be identified. However, in many areas of Indonesia, soybeans could be grown on land used for rice. Soybean profits therefore provide an opportunity cost for land that can be incorporated into a complete “farming systems” rice PAM. Table 5.5, the soybean PAM, is derived from the same budget analysis illustrated in Chapters 3 and 4.

 

Table 5.5. PAM for Soybeans

 

Revenue

Tradable

Domestic Resources

Profits

 

 

Inputs

Labor

Capital

 

Private

 2,824,000

    168,000

    579,325

    85,942

  1,990,733

Social

 2,468,500

    168,000

    579,325

  112,099

  1,609,076

Divergences

    355,500

            -  

            -  

   (26,157)

     381,657

 

           

            The farming systems PAM for rice (Table 5.6) requires the addition of a column that shows the price of land as derived from the profits of growing the next best alternative, soybeans. The virtue of the farming systems PAM is that it provides a quantitative estimate of the comparative advantage of a commodity from a farmer’s perspective. Positive profits for rice means, for example, that rice production is the optimal use of the farm’s resources.

 

            Conversely, if the same exercise were carried out for the soybeans PAM, the substantial rice profits—and the resulting high land values—would produce negative profits for soybeans. Negative profits would indicate clearly that soybeans do not have a comparative advantage in the farming system from which the data are drawn.

 

Table 5.6. Farming Systems PAM for Rice

 

Revenue

Tradable

Domestic Resources

Profits

 

 

Inputs

Labor

Capital

Land

 

Private

 7,230,000

    966,000

 1,680,000

  402,500

  1,990,733

 2,190,767

Social

 5,784,000

 1,021,000

 1,680,000

  462,500

  1,609,076

 1,011,424

Divergences

 1,446,000

     (55,000)

 

   (60,000)

     381,657

 1,179,343

Multi-Period PAM

            Previous PAMs  have been based on seasonal crops. These dominate Indonesian agriculture. However, there are a number of commodities whose planting and harvesting takes place over time. Examples include such crops as rubber, cloves, and vanilla, as well as investments in livestock production.

 

            Computing PAMs for commodities that stretch over a number of periods requires constructing a PAM for each period, then computing the net present value of the entire series. Discounting is necessary because the value of future costs and returns is less than the value of costs and returns measured in the present. T he fact that alternative returns to revenues and expenditures —their opportunity cost—increases at a compound rate, e.g., bank account deposits,  needs to be accounted for in the multi-period PAM.

 

            The formula for computing the NPV for revenue is:

 

 

where i is the discount (interest) rate and t is the number of time periods over which the commodity is grown.

 

            Table 5.7 shows the budgets for vanilla over the 10-year period that comprises the normal  production cycle. In the first two periods, the crop requires inputs and resources, but yields no revenues. Output increases until the 5th year when the crop reaches maturity. After than, output declines until the 10th year when the vanilla is hardly worth harvesting.

 

Table 5.7. Multi-period Vanilla Budgets (Private Prices in Rps 000,000)

Year

Revenue

Tradable

Domestic Factors

Profit

 

 

Inputs

Labor

Capital

 

Interest rate

15%

 

 

 

1

0.0

3.0

5.0

1.0

-9

2

0.0

0.6

6.0

1.0

-8

3

16.0

0.9

9.0

2.0

4

4

35.0

1.1

9.0

2.0

23

5

39.0

1.0

9.0

2.0

27

6

31.0

0.8

9.0

2.0

19

7

33.0

1.0

8.0

2.0

22

8

26.0

1.3

6.0

1.0

18

9

20.0

0.3

6.0

1.0

13

10

11.0

0.3

5.0

1.0

5

NPV

92.6

6.1

36.2

7.6

43

 

             The second row of the multi-period PAM (social prices) is computed using the same methodology. The NPV’s for revenues, inputs, and domestic resources are then organized in the traditional PAM format. The multi-period PAM results indicate the total profits and the total policy and market related divergences for the period, all discounted by an interest rate.

 

Table 5.8. Multi-period Vanilla PAM (Rps. 000,000)

 

Revenue

Tradable

Domestic Factors

Profit

 

 

Inputs

Labor

Capital

 

Private

              93

              6

36

              8

              43

Social

              75

              5

              32

              9

              28

Divergence

              18

              1

                4

             (2)

              15

 

            The multi-period PAM is interpreted in the same way as a single-period PAM. Table 5.6 shows that producers are receiving substantial subsidies through government policies, either in the direct purchase of the crop from trade policy that affects the output price.

 


Chapter  6.  Benefit-Cost Analysis

 

            The farm budgets and PAM analyses presented in previous chapters were used to determine the profitability and efficiency of Indonesian rice systems.  With some additions to the database used in Chapters 3 and 4, this same PAM methodology can used as a point of departure for evaluating the economic feasibility of capital investments.[32]  Two pieces of additional information are needed – the effect of the capital investment on the input-output relationships in a rice production system and the cost of the investment.

Benefit-Cost Analysis in the PAM

            To compute the benefit-cost (B-C) ratio for an investment in an Indonesian rice system, a policy analyst follows four steps:

 

  1. Gather data on technical relationships to construct two input-output tables, one representing a production system without the project, the other with the project.  Using the existing private and social prices, compute two PAMs to represent the with and without conditions.

 

(The budgets and PAMs constructed in previous chapters are assumed to represent production in an area that has good water control. These data therefore represent estimates of the increased output that would be forthcoming with the project.  The without project data are assumed to come from an area with poor water control that is being considered for an irrigation project.)

  1. Estimate the components and then the total cost of the investment in private and social prices.

  2. Subtract the (private and social) profitability of the without project PAM from the (private and social) profitability of the new PAM to determine the incremental (private and social) benefits generated by the investment.

  3. Divide the incremental benefit of the investment by its cost, both properly discounted, to determine the benefit-cost ratios at both private and social prices.  Benefit-cost ratios greater than one indicate that implementing the project would be profitable.

 

      These four steps are illustrated below, first in a single-period framework where benefits and costs occur in the same year, then in a multi-period framework where benefits and costs occur over time.  The presence of time requires that the elements of the analysis be discounted to reflect the fact that rupiahs earned or paid in the present are worth more than amounts earned or paid in the future.  (A rupiah earned in the present can be deposited in a bank to earn interest; hence it is worth more than one obtained in the future, which cannot.)

The formula for discounting a single element is:

 

 

where = the difference between the profitability of the two PAMs, i = the discount rate, and t =  the time elapsed since the start of the project.  Amounts that occur when t is small (early in the project) will be discounted less heavily than when t is large (late in the project).  Typically, costs, which usually appear at the beginning of a project’s net benefit stream, are discounted less heavily than benefits, because benefits are generated well into the future.  This means that if projects are dragged out and not completed in a timely fashion, the realized benefit-cost ratio can be much lower than the one estimated by planners.

Single-Period Benefit-Cost Analysis

            The PAM for the poor water control system reflects what is known in the project appraisal literature as the “without project” case.  It shows what would happen if there were no intervention in the farming system.  The second “with project” PAM, indicated by primes on the symbols of Table 6.1, incorporates the effects of changes in yields that would result from the application of additional fertilizer or chemical inputs.  Figure 6.1 illustrates the calculation of a single-period benefit-cost B-C ratio for the use of inputs such as fertilizers and chemicals.  In the single-period example, both the investment and the returns to the investment occur in the same year.

 

            Incremental benefits from the investment are obtained by subtracting the private and social profitabilities of the without project PAM from those of the with project PAM, resulting in ΔD, the change in private profitability, and ΔH, the change in social profitability.  These incremental benefits are the numerators of the benefit-cost ratios, the costs of the fertilizer and chemicals, measured in private and social prices, are the denominators.  (The private benefit-cost ratio thus is ΔD/IP and the social benefit-cost ratio is ΔH/IS.)

 

Table 6.1.  Single-Period Benefit-Cost Analysis

 

Private Calculations

 

 

 

Revenues

Costs

Profits

Investment