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Abstract

Monetary Gaps1

Appendix I Statistical Tables

Table 4.

Monetary Gaps1

(In percent of common price)

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Sources: Commission des Communautés Européennes, Agri-Monétaire: Evolution des Ecarts, various issues, and Official Journal, various issues.

Applied monetary gaps at end of year. Minus sign denotes a negative monetary gap, i.e., a price in national currency that is below the common price. Data afford no indications regarding changes in monetary gaps that may have occurred in the course of a year on account of adjustments in green rates, EMS realignment, and, for countries that do not participate in the EMS exchange rate mechanism and Italy, fluctuations in the exchange rate. Applied monetary gaps (i.e., monetary gaps minus neutral margin) may vary among products because of ad hoc decisions or because of phasing of the entry into force of changes in green rates is linked to dates in the marketing year or the products concerned. For the sake of comparability, data shown here always apply to cereals.

Early July, 1988.

Following the EMS realignment of October 5, 1981, MCAs emerged between the Netherlands, on the one hand, and Belgium and Luxembourg, on the other.

Joined the Community in 1973.

Joined the Community in 1981.

As of October 7, 1974, Ireland ceased to peg its green rate to the green rate of the United Kingdom, without ending the pegging of the Irish pound to sterling. The Irish authorities wanted to have more leeway to “devalue” the green rate, i.e., to raise prices expressed in domestic currency.

Joined the Community in 1986.

Table 5.

EC: Coefficients of Nominal Protection for Selected Agricultural Products1

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Sources: Statistical Office of the European Communities, Eurostat, Agricultural Prices, and IMF, International Financial Statistics, various issues.

Coefficients of nominal protection are defined as the ratio of domestic to world market prices expressed in percent. Coefficients were calculated for individual EC member countries and averaged for the EC. Standard deviation of the coefficients of protection across countries and over time are given in parentheses.

1969–85.

Standard deviation of the average coefficients of protection during the observation period.

1961–85.

1963–85.

Table 6.

OECD: Producer Subsidy Equivalents (PSEs) by Commodity and Country1

(In percent)

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Source: Organization for Economic Cooperation and Development (1988).

A PSE attempts to measure the payment or subsidy needed to compensate producers for the removal of agricultural producer support policies (expressed here in percent of the value of output) plus direct payments minus any producer levies or taxes.

Arithmetic average.

Includes all OECD countries.

Australia only.

Table 7.

EC: Development of Agricultural Producer Prices (in real terms)1

(1980 = 100)

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Sources: Commission of the European Communities (1987a), and IMF, International Financial Statistics, various issues.

Agricultural producer prices deflated by wholesale prices or prices for industrial products.

Table 8.

EC: Ratio of Producer Prices to Input Prices1

(1979–81 = 100)

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Source: Statistical Office of the European Communities (1988).

The “cost-price squeeze” is calculated by dividing changes in the index of prices of the value of final agricultural production by changes in the index of prices of the value of inputs.

Table 9.

EC: Self-Sufficiency in Cereal Production

(In percent)

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Source: Statistical Office of the European Communities, Yearbook of Agricultural Statistics, various issues.
Table 10.

EC: Self-Sufficiency in White Sugar Production

(In percent)

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Source: Statistical Office of the European Communities, Yearbook of Agricultural Statistics, various issues.
Table 11.

EC: Self-Sufficiency in Butter Production

(In percent)

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Source: Statistical Office of the European Communities, Yearbook of Agricultural Statistics, various issues.
Table 12.

EC: Self-Sufficiency in Wine Production1

(In percent)

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Source: Statistical Office of the European Communities, Yearbook of Agricultural Statistics, various issues.

No account is taken of the very large volume of wine distilled into alcohol for human consumption or industrial use.

Table 13.

EC: Self-Sufficiency in Vegetables and Fruit Production

(In percent)

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Source: Statistical Office of the European Communities, Yearbook of Agricultural Statistics, various issues.
Table 14.

EC: Self-Sufficiency in Meat Production

(In percent)

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Source: Statistical Office of the European Communities, Yearbook of Agricultural Statistics, various issues.
Table 15.

EC: Self-Sufficiency in Pork Production

(In percent)

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Source: Statistical Office of the European Communities, Yearbook of Agricultural Statistics, various issues.
Table 16.

EC: Self-Sufficiency in Wheat Production

(In percent)

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Source: Statistical Office of the European Communities, Yearbook of Agricultural Statistics, various issues.
Table 17.

EC: Self-Sufficiency in Beef Production

(In percent)

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Source: Statistical Office of the European Communities, Yearbook of Agricultural Statistics, various issues.
Table 18.

EC: Self-Sufficiency in Egg Production

(In percent)

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Source: Statistical Office of the European Communities, Yearbook of Agricultural Statistics, various issues.
Table 19.

World Production and the EC’s Share in Trade of Selected Agricultural Products (1983–85)1

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Source: Commission of the European Communities (1988a).

Community of 12.

Metric tons.

Exports (excluding intra-EC trade) and excluding processed products.

Net balance EC trade/world trade.

Cereals as grain; processed products excluded.

Including salted meat.

Excluding salted meat for trade.

Table 20.

OECD: Share of Each Country in OECD Agricultural Exports

(Percent of agricultural exports in U.S. dollars)

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Source: OECD, Foreign Trade Statistics, Series C, various issues.

Including Luxembourg.

Table 21.

OECD: Share of Each Country in OECD Agricultural Imports

(Percent of agricultural imports in U.S. dollars)

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Source: OECD, Foreign Trade Statistics, Series C, various issues.

Including Luxembourg.

Table 22.

OECD: Share of Agricultural Imports in Total Imports1

(Percent of merchandise imports in U.S. dollars)

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Source: OECD, Foreign Trade Statistics, Series B, various issues.

Agricultural imports are Standard International Trade Classification categories 0 and 1 (food, beverages, and tobacco).

Including Luxembourg.

Table 23.

OECD: Share of Agricultural Exports in Total Exports1

(Percent of merchandise exports in U.S. dollars)

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Source: OECD, Foreign Trade Statistics, Series B, various issues.

Agricultural exports are Standard International Trade Classification categories 0 and 1 (food, beverages, and tobacco).

Including Luxembourg.

Table 24.

EC: Ratio of Stocks to Production for Selected Commodities and Countries

(Percent of midyear stocks in the volume of annual output)

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Source: Organization for Economic Cooperation and Development. Note: EC intervention (EAGGF) stocks are included in all EC totals.

Cereals excluding rice.

Excluding Ireland.

Table 25.

OECD: Share of Agricultural Value Added in GDP1

(Percent of nominal value added)

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Source: OECD, National Accounts, various issues.

Agriculture includes hunting, forestry, and fishing.

1981–84 for Canada, Luxembourg, Netherlands, Portugal, Australia, and New Zealand.

Excluding Iceland and Switzerland. Aggregates were calculated using purchasing power parities for GDP of the current year. OECD estimates for 1985 for Canada, Luxembourg, Netherlands, Portugal, Australia, and New Zealand are included in the OECD total.

Table 26.

OECD: Growth of Agricultural Employment1

(Average annual percentage change)

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Source: OECD, Labour Force Statistics, various issues.

Agriculture includes hunting, forestry, and fishing. According to International Labor Organization guidelines, unpaid family workers are included in employment irrespective of the number of hours worked during the specified period. Some of the above countries may exclude such workers, however, if they worked less than a number of specified hours per week.

OECD estimates for 1985 for Iceland are included in the OECD total.

Table 27.

OECD: Share of Agriculture in Civilian Employment1

(Percentages)

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Source: OECD, Labour Force Statistics, various issues.

Agriculture includes hunting, forestry, and fishing. According to International Labor Organization guidelines, unpaid family workers are included in employment irrespective of the number of hours worked during the specified period. Some of the above countries may exclude such workers, however, if they worked less than a number of specified hours per week.

OECD estimates for 1985 for Iceland are included in the OECD total.

Table 28.

EC-10: Holdings—Number and Area Covered by Agriculture1

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Sources: Commission of the European Communities, The Agricultural Situation in the Community (Brussels; Luxembourg: CEC), various issues; and Statistical Office of the European Communities, Eurostat, Yearbook of Agricultural Statistics, 1986 (Luxembourg).

Holdings smaller than 1 hectare not included. Totals may not add because of rounding and overlapping categories.

Table 29.

EC-10: Average Size of Agricultural Holding per Member State

(In hectares)

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Sources: Commission of the European Communities (1988a); and Statistical Office of the European Communities, Eurostat, Yearbook of Agricultural Statistics, 1986 (Luxembourg).

1977 national survey.

Table 30.

EC: Distribution of Farm Sizes in 1985 by Country

(In percent of total)

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Source: Commission of the European Communities, The Agricultural Situation in the Community (Brussels; Luxembourg: CEC), various issues.

Measured in European size unit.

Table 31.

OECD: Relative Labor Productivity in Agriculture1

(Total economy = 100)

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Sources: OECD, National Accounts and Labour Force Statistics, various issues.

Labor productivity is measured as value added in constant market prices divided by employment. For the United Kingdom, value added is in constant factor prices.

For the period 1981–84 for Canada, Luxembourg, Australia, EC, and OECD.

Excluding Ireland.

Excluding Iceland, Ireland, New Zealand, Portugal, and Switzerland. Aggregates were calculated using 1980 purchasing power parities for GDP.

Table 32.

EC-10: Revenue of the Agricultural Sector

(Average of 1979–81 = 100)

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Source: Statistical Office of the European Communities (1987).

Per annual work unit, that is, the equivalent of the work done by one full-time worker in one year, deflated by the GDP deflator.

Price index of final output divided by price index of intermediate consumption.

Table 33.

Expenditure by the European Agricultural Guidance and Guarantee Fund, by Country

(In percent; or millions of ECUs)

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Source: Commission of the European Communities, Official Journal of the European Communities, Vol. 30 (C336), December 15, 1987.
Table 34.

Expenditure by the European Agricultural Guidance and Guarantee Fund, by Product

(In percent of total guarantee expenditures)

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Source: Commission of the European Communities, Official Journal of the European Communities, Vol. 30 (C336), December 15, 1987.
Table 35.

EC-9: Agricultural Expenditure by the Member States in 1975 and 1980

(In percent of expenditure by the EAGGF)

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Source: Commission des Communautés Européennes (1984).

Social security outlays for 1977.

Social security outlays for 1979.

Table 36.

EC-9: Agricultural Expenditure by the Member States and the EAGGF in 1975 and 1980

(In percent of total)

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Source: Commission des Communautés Européennes (1984).

Social security outlays for 1977.

Social security outlays for 1979.

Table 37.

Welfare Effects of the CAP on EC Members

(In billions of 1980 U.S. dollars per year)

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EC- 9 comprises Belgium, Denmark, France, the Federal Republic of Germany, Ireland, Italy, Luxembourg, the Netherlands, and the United Kingdom; EC-10 is EC-9 plus Greece; EC-12 is EC-10 plus Portugal and Spain.

PE = partial equilibrium (single- or multisector) and GE = general equilibrium.

The transfer ratio is defined as the cost to the economy of increasing farmers’ incomes by 1 unit; in other words, columns (a)+(b)(c).

The Thomson and Harvey (1981) results are for 1980, but their model used data from 1975 for calibration.

Results are for 1985, but the model is calibrated to data from 1980–82.

Includes change in net government revenue and profits from storage.

Table 38.

Welfare Effects of the CAP by Country in 1980

(In millions of U.S. dollars)

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Sources: Buckwell and others (1982), pp. 90–134; and Fund staff calculations.
Table 39.

Trading Position of the EC

(In billions of U.S. dollars)

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Source: Commission of the European Communities (1988a).

Excludes intra-EC trade.

Table 40.

EC: Export Share in World Agricultural Exports1

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Source: Koester and Bale (1984), p. 5.

EC export quantities as percentage of world export quantities, excluding intra-EC trade.

Table 41.

EC: Exports of Agricultural Products to Various Groups of Countries1

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Source: Commission of the European Communities, The Agricultural Situation in the Community, various issues.

EC-12, product groups SITC 0, 1, 21, 22, 232, 24, 261–265 + 268, 29, 4, 592.11 + 12.

Not including confidential, ships’ stores, etc.

Austria, Finland, Iceland, Norway, Sweden, Switzerland, Yugoslavia.

Australia, Canada, New Zealand, South Africa.

Algeria, Cyprus, Egypt, Israel, Jordan, Lebanon, Libya, Malta, Morocco, Syrian Arab Republic, Tunisia, Turkey.

Table 42.

EC: Imports of Agricultural Products from Various Groups of Countries1

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Source: Commission of the European Communities, The Agricultural Situation in the Community, various issues.

EC-12, product groups SITC 0, 1, 21, 22, 232, 24, 261–265 + 268, 29, 4, 592.11 + 12.

Not including confidential, ships’ stores, etc.

Austria, Finland, Iceland, Norway, Sweden, Switzerland, Yugoslavia.

Australia, Canada, New Zealand, South Africa.

Algeria, Cyprus, Egypt, Israel, Jordan, Lebanon, Libya, Malta, Morocco, Syrian Arab Republic, Tunisia, Turkey.

Table 43.

Effects of the CAP on International Prices

(Percent change in world market prices following complete liberalization)

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All studies cited base their results on partial equilibrium analysis.

EC- 9 comprises Belgium, Denmark, France, Federal Republic of Germany, Ireland, Italy, Luxembourg, the Netherlands, and the United Kingdom; EC-10 is EC-9 plus Greece; EC-12 is EC-10 plus Portugal and Spain.

Reported figure refers to barley only.

Reported figure refers to beef only.

Average of estimated effect on the prices of pork and poultry.

Reported figure refers to butter only.

Same results also reported in Tyers (1985).

Results for 1985, but the model is calibrated to data from 1980–82.

Average of estimated effect on the prices of beef and mutton.

Table 44.

Effects of the Abolition of the CAP on World Trade1

(Change in volume following complete liberalization; in millions of tons)2

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All the studies cited base their results on partial equilibrium analysis.

Metric tons.

EC- 9 comprises Belgium, Denmark, France, Federal Republic of Germany, Ireland, Italy, Luxembourg, the Netherlands, and the United Kingdom; EC-10 is EC-9 plus Greece; EC-12 is EC-10 plus Portugal and Spain.

Results for 1985, but the model is calibrated to data from 1980–82.

Reported figure refers to barley and maize only.

Table 45.

Effects of a Complete Liberalization of the CAP on the Welfare of Non-EC Countries

(Change in real income following complete liberalization; in billions of 1980 U.S. dollars)

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EC- 9 comprises Belgium, Denmark, France, Federal Republic of Germany, Ireland, Italy, Luxembourg, the Netherlands, and the United Kingdom; EC-10 is EC-9 plus Greece; EC-12 is EC-10 plus Portugal and Spain.

PE = partial equilibrium model.

Australia, Canada, Japan, New Zealand, and the United States.

Koester’s developed countries group also includes Austria, Switzerland, and the Nordic countries.

Anderson and Tyers estimate the final effects in 1990 of a 2 percent a year reduction in CAP support prices from 1981 to 1990.

Results for 1985, but the model is calibrated to data from 1980–82.

Table 46.

Effects of the CAP on International Price Stability

(Percent share of variability of the world price owing to the CAP)

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All the studies cited base their results on partial equilibrium analysis.

EC- 6 comprises Belgium, France, Federal Republic of Germany, Italy, Luxembourg, and the Netherlands; EC-9 is EC-6 plus Denmark, Ireland, and the United Kingdom; EC-10 is EC-9 plus Greece; EC-12 is EC-10 plus Portugal and Spain.

D = change in the price level following a 5 percent production shortfall; SD = standard deviation; CV = coefficient of variation.

The reported figure applies to a price index for wheat and coarse grains.

Table 47.

EC-10: Agricultural Support Prices and Inflation, 1981/82–1988/89

(Change in percent over preceding year)

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Sources: Commission of the European Communities, The Agricultural Situation in the Community, various issues; and Commission of the European Communities (1987b).

The marketing year begins on April 1.

EC-12.

Proposal submitted by the European Commission to the Council of Ministers in March 1988.

As measured by the GDP deflator.

Calendar year, EC-12.

Projection by the European Commission.

Appendix II The Arithmetic of the Monetary Compensatory Amounts (MCAs)

The CAP has always made use of a unit of account to express decisions involving prices. Initially, when the Bret-ton Woods system was still in force and the member states had par values expressed in dollars, it was the dollar that served as a unit of account. During the period August-December 1971, when the dollar floated for the first time, the member states decided not to let their currencies float against each other and to keep them within the bilateral fluctuation margins originally derived from their respective fluctuation margins around the dollar. The unit of account thus began to lead a life of its own: its value was no longer equal to the dollar but had to be derived from the par values of the member states. In the spring of 1973, the link between the dollar and the currencies of the member states was again severed. The problem this posed for the unit of account was solved in the same way as the first time round. The arrangement was given a permanent character by the fact that the conversion rates of the unit of account were based on the central rates of the countries participating in the European narrow margins agreement (the “snake”). In April 1979, the month following the creation of the EMS, the ECU was substituted for the unit of account without affecting the common price level expressed in national currencies.73

The unit of account has always been converted into the member states’ currencies at fixed rates. For a country that participates in the EMS exchange rate mechanism, this means that the conversion rate of the unit of account—commonly known as the green rate—is in principle equal to the central rate and that exchange rate fluctuations within the allowable margins are disregarded. When the currency of a member state floats independently, or when its agricultural prices are not adjusted fully in terms of its national currency at the time of an exchange rate realignment, the green rate no longer corresponds to the central rate. MCAs are then created to prevent this “monetary gap” from giving rise to trade distortions. MCAs are called positive when the currency has appreciated against the green rate, and they serve as import levies and export subsidies; they are negative when the currency has depreciated, and they serve as import subsidies and export levies. There have been significant adjustments over time in the way MCAs are calculated but finding the monetary gap remains the first step.

For a country with a central rate, the monetary gap is the difference between this rate and the green rate, expressed as a percentage.74 Fluctuations of the exchange rate within the agreed margins around the central rate are disregarded, because their incidence on prices is believed to be insignificant. This is not the case with currencies that float independently—the drachma, the escudo, the peseta, and the pound sterling—and with the lira, which has a fluctuation margin that is considered too wide for the purposes of the common price policy (6 percent, against 2.25 percent for the other currencies in the EMS exchange rate mechanism). For these currencies, the monetary gap is calculated as the difference between the market rate of exchange and the green rate. The monetary gaps of these currencies are calculated anew every week and the MCAs are changed whenever the calculation yields a rate that differs by 1 percentage point or more from that of the preceding week.75 Thus, while it takes a realignment to modify MCAs of countries participating in the EMS exchange rate mechanism, the MCAs of other countries are liable to change frequently.

There is a significant departure from the principle that a country’s MCAs correspond to its monetary gap. Since 1973, a “neutral margin” is deducted in the calculation of negative MCAs as a means to save money for the common budget. It was extended to positive MCAs in 1979 to satisfy the demand that all countries be treated alike. The upshot is a reduction in the extent to which MCAs can be used to maintain price differences among the member states. At present, the neutral margin stands at 1 point for the Netherlands and 1.5 points for the other member countries, except that it amounts to 5 points for wine and for poultry and eggs, and to 10 points for olive oil. How MCAs are computed when a neutral margin needs to be deducted, is illustrated in Example 1 of Table 48.

Table 48.

The Computation of Monetary Compensatory Amounts—Illustrative Examples for the French Franc

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Source: Derived from historical data presented in the Commission of the European Communities (1987d).

In mid-1984, it was decided to phase out positive MCAs by basing the system on the strongest currency participating in the EMS exchange rate mechanism, that is, the currency that has been revalued most on the occasion of the latest realignment. There were actually two measures. First, there was the conversion of part of the stock of positive MCAs in countries with an undervalued green rate (i.e., with support prices in domestic currency higher than the Community-wide level) into negative MCAs in other countries. This decision, referred to as the “switch over,” amounted to an increase in the common price level, as shown by the narrowing of the margin by which prices in the Federal Republic of Germany and the Netherlands exceeded the common level. Second, the common price level was tied to the strongest currency in the event of new realignments. Thus, realignments would no longer create a need to lower prices expressed in domestic currency in the country with the strongest currency and, correspondingly, there would be more scope than under the old system for raising prices in the other countries.

These decisions could have been implemented by adopting the deutsche mark as the new numeraire. Instead, it was decided to compute the monetary gap as the difference between the green rate and an adjusted central rate, called the “green central rate.” The latter is obtained by multiplying the central rate by a “correcting factor” so as to devalue notionally all currencies against the ECU (by increasing the number of currency units per ECU). In the case of the switch over, the correcting factor is derived by calculating the rate of devaluation of the central rate of the deutsche mark needed to obtain the desired reduction in positive MCAs, (The logic behind this is that, when the green rate is kept unchanged, positive MCAs can decline only on account of a lowering of the central rate.) Example II of Table 48 shows how this is done and what the impact is on France’s negative MCAs. As may be seen from Example III, the inverse route is followed in the computations made on the occasion of a realignment. Here, the increase in the correcting factor is given by the rate of revaluation of the deutsche mark and is used to shift downward the entire grid of MCAs.

Appendix III The Effects of the CAP: A Survey of the Literature

Sections III and IV of the main paper discussed the costs and benefits of the Common Agricultural Policy, first, within the EC and then for the rest of the world. The objective there was only to highlight the main domestic and international effects of EC agricultural policies. That presentation, however, drew upon a detailed survey of the literature which is presented more fully in this appendix.

For the purposes of the analysis here, the “domestic effects” are the welfare gains and losses of producers, consumers, and taxpayers, the effects on other sectors, and the deadweight costs to the economy as a whole. The “international effects” are the effects on world commodity prices, the volume and pattern of international agricultural trade, and the welfare of the rest of the world. Also included in this category is the effect of the CAP on the stability of world commodity prices.

To facilitate a comparison and evaluation of the empirical evidence, the discussion begins with a restatement of the standard conceptual framework for the welfare analysis of price support and of its limitations. Subsequently, the evidence is examined under four headings: domestic welfare, international trade, welfare of non-EC countries, and stability of world prices. The appendix ends by focusing on the conclusions that may be culled from the literature and their relevance to the current debate on agricultural policy reform.

The Theory

Although the structure of the CAP is complicated, for the large majority of products the basic method of implementation is through price support. This is achieved by a variety of instruments, such as intervention purchases, market withdrawals, export restitutions, minimum import prices and import levies.76 Other price support devices (e.g., deficiency payments) and nonprice support instruments (storage aids, input subsidies, voluntary export restraint (VER) agreements with nonmembcr countries, etc.) are also used but on a more limited scale.

The simplest way to examine the effects of price support on domestic welfare is the single-good partial equilibrium analysis. Chart 2, panel (a) illustrates the case of a small importing country. If the world price is Pw but the domestic price is maintained at pc by a tariff, production is at Sc, consumption at Dc, and the difference is imports. Reducing consumption below and increasing production above what they would be if the world price prevailed entails a consumer loss of A + B + C + D, a producer gain of A and an increase in government revenue of C. The net welfare loss (or, alternatively, the net welfare gain of liberalizing) is B + D. Price support in an exporting country by means of an export subsidy is illustrated in panel (b). Here the consumer loss is J + E, the government expenditure E + G + H, and the producer gain J + E + G; by subtraction the net welfare loss is E + H.

This simple domestic welfare analysis treats the EC as a single entity. To examine the country-specific effects of the CAP the previous analysis has to be modified in three ways. First, it has to allow for intra-EC commodity trade (Buckwell and others, 1982). Some of the imports of an importing country will now originate in other Community members and, therefore, be priced at the CAP support level. Consequently, part of the tariff revenue C will now be forgone. Similarly, part of the government expenditure for subsidies in an exporting country will now be avoided, since the gain to producers is generated directly by sales to other Community members at the high protected prices.

Second, the analysis has to capture the function of the so-called agri-monetary system of the EC. The MCAs that came into effect in the early 1970s to protect farmers from national currency fluctuations essentially allow member countries to maintain domestic prices different from the common CAP support levels. Importers in a country with a domestic price lower than Pc can be thought of as paying Pc a at the border for imports from other members and then getting a subsidy to allow these imports to compete in the domestic market. Exporters in that country must pay a tax on their exports in order not to undermine the higher prices in the rest of the Community. The situation in a member country that maintains a domestic price higher than Pc is the opposite.

Third, the principle of common financing, which means that the Community is collectively responsible for paying the subsidies for (and receiving the tariff revenue generated by) all products covered by the CAP, requires that additional transfers between the EC and members’ budgets be taken into account.

Chart 2.
Chart 2.

The Economics of Price Support: The Single-Country Case

Even after introducing these additional considerations to make the model capture the supranational character of the CAP, the partial equilibrium analysis still retains its simplicity. Its usefulness is limited, however, by the strong assumptions that underlie it.77 In what follows, the main difficulties of assessing the effects of price support by means of the partial equilibrium model are outlined, and ways of dealing with these difficulties are discussed.

1. The analysis of price support, even when amended to take into account the aforementioned intra-EC transfers, is designed to capture the effects of one specific policy. There are, however, many different CAP price-support instruments, not all of which have the same effect. Deficiency payments, for example, differ from export subsidies in that, as consumers pay the world price, there are no consumer losses. Nontariff barriers or variable import levies do not generate the same revenues as ad valorem tariffs. These differences are very hard to capture in the model.

2. The analysis in Chart 2 implicitly assumes that the country is a price taker in the world market. This “small country” assumption means that, no matter what the level of domestic protection is, the world price remains unaffected. The welfare effects of price support can then be accurately measured with reference to that world price. It also means that these effects are limited to the home country; there is no room for international repercussions. This is clearly unsatisfactory in the case of the CAP; the EC is large enough to influence world markets.

3. Partial equilibrium analysis assumes that the prices of all other goods remain constant. This means that substitutability and complementarity in consumption and production between the good studied and other commodities is ignored. To correct this shortcoming one has to model the interactions between markets for different goods explicitly. The choice of the relevant group of goods is, however, a difficult task, since the chain of substitution can extend from commodities very close to the one studied (e.g., different varieties of wheat) to nonagricultural goods.

4. The preceding discussion also assumes that all demand is final. This is obviously not true for many agricultural products. The demand for those products has to be derived from the cost function of the food industry. Moreover, many commodities use other agricultural products as inputs; beef, for example, requires animal feed. The true degree of protection for beef, therefore, is captured by the effective, rather than the nominal rate.

5. Price-support policies in agriculture, especially in cases like the CAP where a wide range of commodities is covered, can have a considerable effect on total employment and the allocation of capital and labor. This, in turn, affects other sectors of the economy. The size and direction of the effects depend mainly on relative factor intensities and the policies implemented in the other sectors. Such interactions can exert a significant influence on the actual welfare gains or losses from agricultural policies.

6. Because of the range of coverage of policies like the CAP, macroeconomic considerations also enter the picture. Changes in the price support policies for many commodities can have sizable effects on the external balance of the economy and, consequently, the exchange rate, or the relative price of tradables and nontradables. Either could then shift the supply and demand curves in Chart 2 endogenously.

7. Externalities and market distortions, if present, represent the greatest challenge to the welfare analysis of price-support policies. Even if they are absent from the agricultural sector proper but exist elsewhere, externalities and distortions can affect the calculation of welfare costs and benefits in a variety of ways. Empirical work has shied away from these problems by routinely postulating perfectly competitive structures, full information, and complete markets.

These shortcomings of the simple partial equilibrium model have prompted analytical efforts in several directions. First, to simplify the empirical question at hand and take care of the problem raised in point (1) above, most researchers convert all sorts of price-support instruments into tariff equivalents (nominal or effective, as the case may be). Alternative policy options are then described in terms of changing this notional rate of protection, without specifying how exactly this is to be done. Harling (1983) and Valdes and Zietz (1980) discuss at length the methods of calculating tariff equivalents and the ensuing problems.

Second, “large-country” effects, substitution of agricultural commodities in production and consumption, and backward and forward linkages with other sectors are incorporated in the analysis by applying partial equilibrium techniques in a multicountry multisector framework. This approach is used extensively in evaluating policies such as the CAP, which affect many agricultural commodities simultaneously. Trouble spots (2) through (4) from the previous list are dealt with in this way.

Multicountry multicommodity models differ fundamentally from the simple analysis in Chart 2 in one respect: the world price loses its meaning as a reference point for the measurement of the welfare costs of protection. Since the home country is “large,” a change in domestic policies will affect the world price. The effects of the policy must be estimated with respect to what the world price would be, had the policy been absent. The calculation of that hypothetical price requires formulating demand and supply functions for the country(ies) and commodity(ies) involved and solving the system at a notional, unobserved equilibrium. This is called counterfactual analysis.

Counterfactual analysis is necessary for the effects of domestic policies on international trade and other countries to be addressed. Once counterfactual world equilibria have been computed, the resulting prices and trade flows can be compared with the actual ones and the distortions implied by the existing policies can be demonstrated. Moreover, the effects of the policies on the real income of other countries can also be calculated. Multicountry multisector partial equilibrium models that use counterfactual analysis to estimate both domestic and international effects of price support can get quite complicated.

Probably the most advanced model in this category is that of Tyers, used by the World Bank in the 1986 World Development Report.78 It incorporates 7 agricultural commodities and 30 countries or country groups. The intersectoral links are captured by cross-elasticities in both supply and demand. Supply is represented by a mechanism of “partial adjustment” of production to prices (Nerlove, 1958). It models government action explicitly by using “transmission elasticities,” which determine what proportion of a world price shock is passed through to domestic producers and consumers, it includes stock-holding behavior endogenously, and it estimates welfare effects on consumers and producers and changes in government budgets and stockholders’ profits. Finally, it is dynamic in nature, in the sense that it allows for differences in the short- and long-run effects of a shock or policy change.

Even a model of such sophistication, however, is essentially limited by the constraints of partial equilibrium methodology. Computable general equilibrium (CGE) models make one further step and bring nonagricultural sectors, factor markets, and the macroeconomy into the picture. Thus, the problems raised above in points (5) and (6) are addressed directly in CGE models.

CGE world models are essentially higher dimensional analogs of the traditional two-sector Heckscher-Ohlin international trade model. Each region has a production function with primary and intermediate inputs and demand functions derived from utility maximization. The Armington heterogeneity assumption, which postulates that similar goods from different countries are imperfect substitutes, is usually made to account for the cross-hauling of goods observed in international trade. The countries are constrained by their total factor endowments. The balance of payments, or parts thereof, is modeled explicitly and constrained by an external condition. A global general equilibrium is characterized by a set of international prices for all goods and factors such that (i) all markets clear, (ii) the zero-profit conditions are met in all industries, and (iii) the external accounts of each country satisfy the constraints.79

The issues raised earlier in point (7) are not dealt with successfully in either advanced partial equilibrium or general equilibrium analysis. Externalities, in particular, are hard to handle because market prices do not reflect the true social valuations of different activities.

The discussion so far has focused on different ways of measuring the effects that price support policies have on domestic welfare, international trade, and the welfare of other countries. Such policies in large countries or regions, however, have other effects as well. One that has attracted considerable attention is the effect on the stability of international commodity prices.

Price instability, especially in agricultural markets, has long been an issue. The conventional view is that policies that insulate domestic markets from international price movements tend to increase world price instability. This happens because if a country does not let its domestic consumption accommodate, for example, a world production shortfall, the consumption of everybody else must fall disproportionately. To ration the reduced world output, world prices must rise by more. This, in turn, causes farmers’ incomes to fluctuate. Farmers with utility functions with the usual convexity properties react with aversion to risk in their supply decisions and, in this way, affect the economy as a whole. Moreover, the poorer the country whose commodities are affected the more undesirable these fluctuations are, because farmers there tend to be more numerous and impoverished and because they are more vulnerable to income fluctuations owing to the reduced access to insurance markets.

This view is not completely accurate for two reasons. First, it is unclear whether all price-support measures increase instability or whether they increase it to the same extent. Bale and Lutz (1978 and 1979b) show that some policy instruments have no impact on world price stability while others transfer different degrees of instability from one country to another.80 Second, world prices in theory can be stabilized even if most countries insulate their markets, as long as countries or private individuals operating on the free market hold big enough stocks. The issue is, ultimately, an empirical one.

To measure empirically how much the insulation of particular domestic markets adds to price instability in the world, the partial or general equilibrium models used need to be modified to take into account price fluctuations. This is done by introducing stochastic supply and demand shocks in the models (see, for example, Tyers and Anderson, 1986a) and observing how the specific policies change the variance of prices.

A final methodological point that ought to be mentioned has to do with the scope of counterfactual equilibrium analysis. There is no hard and fast rule for the choice of the appropriate counterfactual “base case”; it depends on what the specific question addressed is. If the focus is on a cost-benefit analysis of the CAP, then the free trade competitive equilibrium is the obvious choice. If, on the other hand, the objective is an evaluation of an alternative policy package (such as maintaining unchanged nominal support prices for a certain period of time, or reducing protection of some communities or across the board), then this is the appropriate counterfactual. The first option has the additional advantage of being conceptually simple and familiar. The second is obviously more interesting from a policymaker’s point of view but requires a detailed spelling out of the components of the alternative policy package.81

The Evidence

Effects of the CAP on EC Members

This section presents a survey of recent empirical literature on the domestic effects of the CAP. Most studies treat the Community as one entity; some, however, provide estimates of the effects on a country-by-country basis. Most provide a breakdown of the total welfare cost into consumer and taxpayer (or government) loss and producer benefit. Table 37 in Appendix I summarizes the evidence from all the existing studies that report results in a comparable form. Also presented and discussed are studies that focus on different aspects of the domestic effects of the CAP or that formulate their questions in a different way. The cost estimates in columns (a) through (d) are all converted into 1980 U.S. dollars.

All but one of the studies presented are multisector models, covering all or most of the CAP commodities. Koester and Schmitz (1982) is the only exception. They examine the effects of the EC Sugar Protocol (a mixed system of price support and quotas) on developing countries, intra-EC transfers, and Community welfare. The welfare costs are calculated with a free trade counterfactual world price as the reference point, which was taken to be equal to 38 percent of the EC support price. This counter-factual world price was arrived at by a series of computations of free trade counterfactual equilibria under different assumptions about demand and supply elasticities in the Community and the rest of the world. No exact information about the elasticities, however, was available and, in addition, the computed counterfactual equilibria were very sensitive to the elasticity values. The welfare calculations, therefore, do not seem very reliable.

Morris (1980) estimates the effects of price support for the main CAP commodities (the exceptions are wine, tobacco, fruit, and vegetables). A serious drawback of this study is that the counterfactual free trade prices do not come out of a demand and supply system but are instead postulated ad hoc. Since these counterfactual prices are not listed in the study, it is impossible to tell a priori whether the paper tends to over- or underestimate the welfare costs.

Thomson and Harvey’s (1981) paper models the markets for 16 groups of agricultural commodities. Their interaction is captured by a set of cross-elasticities. The study evaluates the CAP with respect to its stated objectives and does not address the wider social costs. The closest one could come to a measure of overall efficiency is the transfer ratio of 1.77. The transfer ratio is the cost to the economy of an increase in farmers’ income by one unit.

A very comprehensive study of agricultural protection in the EC is the one by the Australian Bureau of Agricultural Economics (Australia, Bureau of Agricultural Economics, 1985). It treats the Community as one country, but distinguishes between different commodities, as do Thomson and Harvey, and makes adjustments to account for their interaction. It considers the CAP together with national price-support policies and provides yearly estimates of the costs for the 1971–83 period. In Table 37 in Appendix I estimates are reported for 1978, when, according to the study, the costs of agricultural support peaked, and 1983. Their results imply significant costs from the operation of price-support mechanisms: around 0.3 percent of total GDP for the EC-10, equivalent to roughly one third of Greece’s GDP, was wasted in 1983. In per capita terms, this is approximately $25.

Probably the most often quoted study of the effects of the CAP is the monograph by Buckwell and others (1982). As with the previous two studies, they model explicitly many countries and markets, with the interaction between commodities captured by cross-elasticities. An important advantage of this paper is that it takes into account intra-EC transfers resulting from Community preference schemes, the common financing of the CAP, and MCAs. Their estimate of the consumers’ loss is comparable to that of the Bureau of Agricultural Economics, but that of the taxpayers is smaller, possibly because of the inclusion of the aforementioned intra-EC transfers. The total cost estimate, however, is larger than that of the Bureau. The reason for this is probably the fact that Buckwell and others model the structure of the agricultural sector in greater detail and, therefore, are more accurate in their estimation of the producers’ benefit.

Tyers (1985) and Tyers and Anderson (1986a, 1986b, and 1987) use different versions of the same model to estimate the costs of the CAP alone and of the CAP plus domestic policies. The basic model is discussed in the first part of this appendix. In comparison to the previous studies, there seem to be several advantages in the analytical framework used by Tyers and Anderson. First, the international policy interactions are better captured, because the degree of disaggregation is higher (24 countries and country groups in the Tyers (1985) paper and 30 in the 1986a Tyers and Anderson paper). Second, government behavior is incorporated in the model and assumed to be different in the short and the long run. Third, stockholding behavior is modeled explicitly.

The estimates presented in the studies are for different years (1980 for the Tyers study and 1980–82 and 1985 for the Tyers and Anderson studies)82 and country groups (EC-9 to EC-12) and for varying degrees of disaggregation of the rest of the world. In the two earlier studies, the total cost estimate is significantly higher than in any other partial equilibrium study: it is 1.1 percent of the GDP of the EC-9 in 1980 in the Tyers study and 1.3 percent of the GDP of the EC-10 in 1985 in the Tyers and Anderson paper. The implied transfer ratio in the latter study is 1.88. In their 1987 study, however, the authors estimate total costs at only 0.3 percent of the GDP of the EC-12 and the transfer ratio at 1.2. The discrepancy with the earlier studies seems to reflect in part a change in the measurement of the welfare effects. While the model used in this and earlier studies by the same authors is nonlinear, in the earlier studies linear approximations to supply and compensated demand curves were used to measure the welfare effects. The areas that emerge from such approximations are accurate only for small changes in domestic prices—in the case of the EC, however, the price changes were in fact very large. In the 1987 studies, the areas under nonlinear curves were measured, which in some cases resulted in substantially smaller welfare effects. In addition, the 1987 study assumes a much lower degree of transmission of world market price changes to domestic price changes. The long-run transmission elasticities for the EC, for example, range between zero and 0.76 depending on the particular commodity.83 As a consequence of the higher degree of insulation of prices in the EC and other countries and geographical regions, trade liberalization in the EC has a larger impact on world market prices. This is reflected in the significantly larger increases in agricultural world market prices as a result of trade liberalization in industrial countries in the 1987 study compared with the earlier studies (see below). Consequently, the gains from liberalization, which depend on the counterfactual world market prices, are much smaller.

The studies by Spencer (1985) and Burniaux and Waelbroeck (1985) are general equilibrium models. Spencer has a very simple CGE model with nine countries (eight in the EC, with Belgium and Luxembourg lumped together, and the rest of the world) and two goods (agriculture and non-agriculture) produced with two factors of production. He calculates that 0.9 percent of the GDP of the EC-9 is lost as a result of the CAP.

Burniaux and Waelbroeck use a more sophisticated CGE framework, which includes nine regions and models separately production and consumption in the urban and rural areas of each (see Burniaux and Waelbroeck, 1985). As in the Tyers and Anderson (1986a) model, different degrees of insulation of the domestic market are captured by price transmission equations. The paper distinguishes between more and less “flexible” regions; the United States and Latin America, for example, are assumed to insulate their domestic markets less than oil exporting countries and Europe.

The Burniaux and Waelbroeck model calculates the long-run effects of a policy change today, subject to growth rate forecasts for the regions under consideration. Dismantling the CAP today (that is, in 1985), according to the model, generates a gain in real income equal to 2.7 percent of GDP of the EC in 1995. This result is somewhat surprising, compared with the other studies presented here, but can be explained by the assumptions fed into the model. Burniaux and Waelbroeck, unlike other studies, assume that international commodity prices, even if nothing else changes, will be decreasing continuously until 1995. Agricultural protection in the EC with variable import levies, which maintain domestic commodity prices unchanged, is obviously bound to look increasingly expensive against this background. Nevertheless, this scenario is not unreasonable, especially if the commodity price trends of the last 30 years continue in the future.

Finally, the results from a recently released OECD study (1987) can be construed to be based on a simple partial equilibrium approach, which implicitly assumes inelastic demand for agricultural products in the EC for estimating costs to the consumers. The expenditures incurred by both the national and the EC authorities on agriculture, on the other hand, are taken in the study to represent the costs to the taxpayer. The OECD study estimates the cost of agricultural policy in the EC to the consumers at about $28 billion in 1980 prices (or about 1.8 percent of GDP of the EC-9). The total cost (to the consumers and taxpayers) of this policy is estimated at 2.8 percent of GDP; the annual average costs are estimated at ECU 11,437 per holding and ECU 7,465 per agricultural worker during the period 1979–81.84

The diversity of the methodologies used makes it difficult to summarize the evidence presented in Table 37. In general, though, the estimates of the welfare costs of the CAP seem to fall into two zones: a “low” one, with net losses ranging from 0.32 percent to 0.55 percent of Community GDP (Morris (1980), Australia, Bureau of Agricultural Economics (1985), Buckwell and others (1982), and Tyers and Anderson (1987)), and a “high” one, with net losses at around 1 percent or more of Community GDP (Tyers (1985), Tyers and Anderson (1986a), Spencer (1985). and Burniaux and Waelbroeck (1985)). The Thomson and Harvey (1981) Study also belongs to the latter group by virtue of their estimate of the transfer ratio, which is comparable to that of Tyers and Anderson (1986a).

Although it is impossible to judge the validity of these figures without some idea of the true costs, it is worth noting that the studies that produce estimates in the high zone use generally superior methodology and a higher level of disaggregation. To the extent that this is a valid criterion for evaluating empirical work, it can be concluded that these studies are probably more accurate in estimating the welfare costs of the CAP.

The remaining part of this section discusses briefly a few studies that focus on different, distributional or country-specific, effects of the CAP and are not included in Table 37. Harling and Thompson (1985) use a partial equilibrium model to estimate the costs of intervention in the poultry industry for, among other countries, the Federal Republic of Germany and the United Kingdom. They find that in 1975–77 the resulting deadweight losses were on the order of $ 10.5 million for these two countries together.

Bale and Lutz (1979b and 1981) calculate the costs of price support for wheat, maize, sugar, and beef in selected countries. They use a very simple partial equilibrium model and report a net welfare loss of $737.3 million for France, $1,112.4 million for the Federal Republic of Germany, and SI 12.4 million for the United Kingdom.

The paper by Buckwell and others provides estimates of the welfare costs by country. They are summarized in Table 38. The transfer ratio, which can be thought of as a broad measure of policy efficiency, is 1.50 for the Community as a whole. It is the highest in the United Kingdom (2.07), Italy (1.87), and the Federal Republic of Germany (1.8). It is less than unity in the Netherlands, Ireland, and Denmark, indicating that these countries benefit from the intercountry redistribution of income caused by the CAP (see Buckwell and others (1982); also, Koester and Tangermann (1986)).

This ranking of the gainers from the CAP is similar to the one in Spencer (1986). He uses a general equilibrium model to evaluate which countries would do better outside the CAP, and by how much. It turns out that Ireland would be the only clear loser, with Denmark gaining the least. The only notable difference between Buckwell and others and Spencer is the Netherlands: in the former study the less-than-unity transfer ratio indicates that the country is benefiting, whereas in the latter the Netherlands appears to be losing from the operation of the CAP.

Greece also appears to gain a very small amount, around ECU 5–10 million a year, from participating in the CAP (see Georgakopoulos (1986) and Georgakopoulos and Paschos (1985)). This result, however, should be interpreted with care, since it is not derived from a full counterfactual analysis.

Breckling, Thorpe, and Stoeckel (1987) use a simple general equilibrium model to appraise the economy-wide effects of the CAP for four EC members: France, the Federal Republic of Germany, Italy, and the United Kingdom. They conclude that the costs of agricultural price support extend beyond the traditional welfare losses. Specifically, for all countries taken together, manufacturing industries (excluding food processing) lose between 1.1 and 2.5 percent of potential gross output and between 4.4 and 6.2 percent of exports, and total employment is reduced by around 1 percent (or 860,000 jobs). Unemployment increases universally in these countries as nonagricultural sectors are relatively intensive employers of labor. The job loss is more in the United Kingdom and the Federal Republic of Germany followed by Italy and France. This is the result of slower growth of labor-intensive nonagricultural sectors in the former countries. The results, however, suggest that despite the emerging unemployment, France is a net beneficiary of the CAP in view of its large rural sector and EC transfers under the applicable common policy. These results are broadly confirmed in a later study by Stoeckel and Breckling (1988), which uses the same model. The authors find that national and supranational protection of the agricultural sector in the four countries under investigation, reduce real aggregate income by 1.5 percent and cause a loss of about four million jobs.

Despite the budgetary and welfare burden of the CAP, the agricultural lobby has resisted attempts to liberalize and is, instead, stepping up pressure to reinforce the CAP (Koester (1985), Gerken (1986), and von Witzke (1986)). This movement away from liberalization is apparently accelerated by demands for more equal distribution of the CAP benefits between member states. Josling (1979) discusses the CAP in the light of the expansion of the EC in southern Europe and concludes that the wider range of commodities and the shifting political balance within the Community will increase the domestic costs, exacerbate the budgetary problems, and amplify the international effects of agricultural protection. In the same vein, Koester (1977) argues that as long as it is possible for member countries to supranationalize costs of national agricultural support, the prospects for a CAP reform are poor. This argument may be questionable at a time of acute budgetary crisis.

Effects of the CAP on International Trade

This section discusses the evidence on the effects the CAP has on the level of prices and the volume and pattern of world trade in agricultural commodities. Since the policies that apply to different products vary widely, the estimated effects for each of the most important commodities covered by the CAP are presented separately. These commodities are wheat, coarse grains (barley, maize, rye, oats, millet, and sorghum), rice, ruminant meat (beef and veal), nonruminant meat (pork, poultry, etc.), sugar, and dairy products. Table 43 presents the estimated effects of a hypothetical abolition of the CAP on the international prices of the above commodities. Each of the studies reviewed calculates a counterfactual world trade equilibrium with a completely liberalized EC market for the commodities in question and then compares the resulting counterfactual prices with the actual world prices.

The estimates show that abolition of the CAP would significantly increase the world prices of all the commodities examined. In other words, the CAP exerts a powerful downward pressure on the actual price level. Roughly speaking, the effect is stronger on dairy products, grains, and ruminant meat and weaker on sugar and rice. This result is to be expected, since the former category of products is afforded greater effective protection than the latter (see Sampson and Yeats (1977), Koester and Tangermann (1986)).

All the estimates reported in Table 43 come from partial equilibrium models. There are considerable differences between the estimated price effects for each commodity, which can be, to a large extent, traced back to the differences in the methodology and the data used in each study. First of all, models that cover only a few commodities or do not take into account market interaction tend to predict higher counterfactual prices and, therefore, overestimate the effects on world markets of price support in the CAP. If only a few isolated markets are liberalized, then the pressure from the other, still protected, markets will spill over via commodity substitution, and the observed effects will be amplified. The first four studies listed in Table 43 share this characteristic. The Koester and Valdes (1984) paper in particular, although it examines many products, does not take into account cross-effects and uses, essentially, a single-commodity approach.85

A second element that accounts for differences between estimated effects, even if the methodology is similar, is the data used. This explains partially why the results of the four other papers (Anderson and Tyers (1984), Tyers and Anderson (1986a and 1987), and Matthews (1985b)), which are all multicommodity models and examine the effects of a generalized liberalization on individual commodity prices, are so diverse. Anderson and Tyers (1984) probably overestimate the degree of protection in the Community by using the official intervention prices as the appropriate domestic market prices (Koester and Tangermann (1986)). Owing to the existing surplus stocks, however, EC market prices are generally lower than the intervention prices (see the information provided in Commission of the European Communities (1987a, Statistical Information)). Matthews, on the other hand, underestimates the degree of protection in the Community, because he uses the EC c.i.f. price as the appropriate world price. As the Community is a net exporter of many of these commodities, however, the f.o.b. price or the price in major foreign ports should be used.

A third factor that affects crucially the outcome of counterfactual experiments is the values of the parameters used. For example, the higher the domestic demand elasticity is, the stronger the domestic reaction to liberalization and the larger the final effect on the world price will be. Tyers (1985) and Anderson and Tyers (1984) use EC demand elasticities between -0.5 and -0.7 (Tyers (1985)). whereas Matthews postulates a value of -0.4 for all commodities (Matthews (1985b). The former range of values is based on a more detailed survey of the relevant empirical literature. Also, as mentioned above, the difference in “transmission elasticities” between the more recent Tyers and Anderson studies influences the results.

Finally, the last significant cause of deviations between the estimates of different models is the varying degree of country and commodity coverage and differences in the base period. The Tyers and Anderson papers (1986a and 1987) are by far the most detailed in that respect, modeling 7 commodity and 30 country groups. Unfortunately it is impossible to tell a priori whether a greater degree of disaggregation tends to generate larger or smaller effects.

The OECD (1987) has produced a comprehensive partial equilibrium study on the effects of agricultural protection in the world. Although the emphasis is on multilateral liberalization, they report some estimates of the effect on world prices of a unilateral liberalization in the Community. Their counterfactual, however, is not the free trade equilibrium but a 10 percent across-the-board reduction in nominal protection of all commodities. They calculate that this partial liberalization in the EC increases the world prices of most commodities from 0.55 percent, in the case of sugar, to 2.81 percent, in the case of milk. In the case of grains, however, prices actually fall a little following the hypothetical CAP reform, owing to decreased demand for grains by livestock producers.

The calculated counterfactual prices are important, first, because they give some idea of the degree of distortion in world agricultural markets that is due to the CAP and, second, because they provide the basis for the estimation of the effects of liberalization on the pattern and volume of world trade. Changes in the pattern and volume of trade, of course, have little importance in and of themselves. Calculating them, however, is a necessary step in assessing the effects the CAP has on the real income of Europe’s trading partners. For that reason we present and discuss some of the empirical work on this issue very briefly.

Table 44 highlights the main results. Abolition of the CAP increases total commodity trade by a considerable amount. This is caused basically by a large increase in EC net imports, prompted by lower consumer and higher producer prices. The effect is stronger in the most heavily protected sectors, such as wheat, grains, and dairy products. The reported effects would be much larger if they were expressed in value, rather than volume, terms.

The results of studies cited in Table 44 are influenced by the estimated post-liberalization counterfactual prices and the coverage and grouping of countries. Koester (1982), for example, includes in the developed countries group all the centrally planned economies, which form a separate group in Tyers and Anderson (1986a). The only surprising result, which cannot be explained by these factors, is the negative change in EC net imports of wheat that Tyers and Anderson report. Given that the Community is a net exporter of wheat, this means that abolishing the CAP will lead to an increase in net wheat exports. Unfortunately the authors do not comment on this counterintuitive conclusion.

The net trade effects of the CAP on other trading partners are also discussed in other studies, which are not comparable to the ones reported in Table 44 because in those, authors conduct a different counterfactual experiment, or use a different taxonomy for reporting their quantitative results, or do not provide quantitative results at all. Sarris (1983) calculates the effects of EC enlargement in southern Europe on international trade in fruit and vegetables. He estimates that including Greece, Spain, and Portugal under the CAP umbrella increases the value of net imports (or reduces the value of net exports) of the other major producing countries by approximately $116.6 million (in 1980 prices). Tangermann (1978 and 1981) discusses the possible effects of reforming the CAP on the trade flows between developed and less developed countries. He concludes that, since the CAP protects mostly temperate products, EC imports from other temperate/developed countries will increase as a result of reducing price support. The effect on trade with developing countries, however, is ambiguous. The producers of such commodities there will have an incentive to increase their production but, on the other hand, they will also have to compete with other exporters. The final outcome depends crucially on the supply elasticities. Finally, Mackel and Marsch (1984) focus on, among other things, the effect of the CAP on trade in commodities that are not protected in the EC. They argue that the CAP has increased imports of substitute products to the EC, like manioc and soya and that, therefore, a liberalization will harm producers of such commodities.

Empirical research on the impact of the CAP on international commodity trade, far from being in unequivocal agreement, has reached some common conclusions regarding at least the direction of the effects. First, the CAP has a significant depressing effect on world prices. Second, as a result of this, trade flows are severely distorted: EC exports are artificially boosted at the expense of net exports of other countries. Third, this distortion keeps the volume of world trade at a lower level than it would otherwise be. Fourth, these effects are generally more significant for the products that are heavily protected in the Community, such as wheat, coarse grains, ruminant meat, and dairy products.

Effects of the CAP on the Welfare of Non-EC Countries

The influence the CAP exerts on international trade means that the real incomes of all trading partners are eventually affected. The conventional view, popular with Community officials, is that a unilateral liberalization in the EC will benefit the exporters and harm the importers of temperate zone products by increasing their prices. Consequently, given that most developing countries import temperate zone commodities, the CAP actually constitutes a transfer of income from EC consumers and taxpayers to poor countries via cheaper international food prices. Furthermore, the concessionary character of the Lomé Convention means that a liberalization, which would imply an abolition of those agreements as well, would be even more detrimental to the developing countries. The data in Table 45 seem to support this view. The table presents the effects that a hypothetical complete liberalization has on the welfare of two broad groups: the non-EC developed countries and the developing countries.

The models reviewed in Table 45 are all partial equilibrium, and the degree of commodity and country coverage varies, but two facts stand out. First, the size of the total effect on each of the two country groups is not large compared to GDP or total export earnings. Second, developing countries as a group stand to lose from an abolition of the CAP, while the effect on developed countries is ambiguous.

Differences in the estimated size of the effects can be generally traced back to commodity coverage or the data used. The figures reported by Koester (1982) and Koester and Schmitz (1982) are expectedly lower than the rest, since these studies cover only cereals and sugar, respectively. Therefore, although the estimated effect on the world price of the individual commodities may be higher, as discussed in the previous section, the total welfare effect is small. Matthews (1985b) also reports a small estimated loss for the developing countries for two reasons. One, which was mentioned earlier, because he underestimates the degree of protection in the Community. Two, because he uses smaller domestic supply elasticities than other studies. The higher the supply elasticity assumed for the developing countries, the stronger is the supply response to increasing world prices and the more likely is the realization of gains from increased exports. Matthews (1985b) uses a supply elasticity of 0.4 for all countries, whereas Koester (1982), Anderson and Tyers (1984), and Tyers (1985) use elasticities in the neighborhood of unity. Extensive empirical research has shown that long-run supply elasticities in developing countries vary widely according to the specific product but are generally rather low, fluctuating between 0.1 and 0.3 for grains and 0.2 and 0.5 for rice (see Bale and Lutz (1979b), Scandizzo and Bruce (1980), and the references therein).

Anderson and Tyers (1984) conduct a different counter-factual experiment. They calculate the impact of a 2 percent annual reduction in EC support prices from 1981 to 1990. Their results are difficult to interpret because, although the final effect of the phased reduction of the support prices will be significant, it is unclear how close it will be to that of a complete liberalization.

Tyers and Anderson (1986a and 1987) have the highest degree of disaggregation, and the most detailed model among the ones in the table, and report in both studies the highest welfare loss for developing countries from abolishing the CAP.86 In their 1986 study, Tyers and Anderson found that even non-EC developed countries lose because the increase in grain prices as a result of liberalization diminishes the welfare of producers of livestock as they have to pay higher input prices.

Table 45 may lead one to believe that, no matter what the sign is for each group, the effect of the CAP is essentially small. Reporting only net effects for two large country groups, however, conceals the distribution of gains or losses among individual countries. The information that can be pieced together about this is quite interesting. First of all, the small net gain (or the net loss) in the developed countries group is entirely due to the heavy losses of Japan. The rest of the countries in the group all register gains or very small losses (see Tyers (1985), and Tyers and Anderson (1986a)). Second, the distribution of the effect within the developing country group is also very varied, depending basically on whether the country is a net exporter or importer of temperate zone commodities. For some of the countries, the gains or losses are significant. Argentina, for example, appears to gain around $200 million a year, while Korea and Pakistan each lose $300 million (Tyers and Anderson (1986a)) from a liberalization of the EC agriculture. Moreover, if liberalization implies abolition of the Lomé Convention it is possible that the developing country signatories will lose even more than the rest of the group. Given, however, that agricultural commodities and, in particular, temperate zone products are a very small portion of the goods that get preferential treatment under the convention, the effects of abolishing the Lomé agreements is likely to be small compared with the effect of a CAP liberalization.

The evidence supporting the conventional view that most developing countries actually benefit from the operation of the CAP tends to be discounted by some researchers. They argue that the fact that developing countries are net importers of temperate zone commodities is due to protectionist policies such as the CAP in developed countries, which depress international prices and make agricultural exports unprofitable. Abolishing such policies, therefore, may imply costs for developing countries in the short run, but in the long run increased prices will stimulate agricultural production and exports, the pattern of trade will change, and developing countries will realize important gains. Counterfactual analysis, which uses econometrically estimated supply elasticities, fails to capture this potential “switching” effect and, consequently, measures only the short-run losses. This argument is very appealing to the proponents of unilateral liberalization, who also point out that it is only under the CAP regime that the Community has turned into a net exporter of many temperate commodities (Australia, Bureau of Agricultural Economics (1985)). It has, however, two important drawbacks. First, the lack of reliable long-run supply elasticity estimates makes it impossible to measure the potential switching effect accurately. Second, it is not supported by the existing evidence on agricultural policies in developing countries. If they actually believed in the harmful effects of the present low level of international prices and in their dynamic comparative advantage as commodity producers, they would subsidize agriculture to stimulate domestic production. Many developing countries, however, especially in Africa, actually tax agriculture (Koester and Tangermann (1986)).

Another argument that has been voiced against the estimates in Table 45 has to do with the limitations of the partial equilibrium methodology. A unilateral liberalization in the Community will affect nonagricultural sectors and factor markets and have repercussions on commodity trade. To capture these secondary effects, a general equilibrium model must be used.

Burniaux and Waelbroeck (1985) use a CGE to calculate how a liberalization of trade in agricultural commodities in the Community in 1985 would affect the welfare of developing countries in 1995; the results are quite striking. They estimate that total real income of the developing countries would be higher by 2.9 percent if the CAP were abolished. This is explained by the strong assumption that, even with no change in the CAP, foreign exchange shortages in developing countries will oblige them to rely more and more on agricultural exports. Thus the switching occurs even with no policy change in the Community. It is obvious then that an abolition of the CAP, which raises world prices, benefits the developing countries.

Loo and Tower (1988) use a four-sector general equilibrium model, which they calibrate for six typical developing countries, to investigate the effects of a 10 percent increase in agricultural prices on world markets assumed to result from trade liberalization in industrial countries. They find that developing countries would gain about $26 billion in 1985 prices as a result of the assumed increase in world market prices for agricultural commodities.87 This gain could be split between the developing and industrial countries in various ways. With developing country real income unchanged, the benefit to the industrial countries from agricultural liberalization in terms of a reduction in the amount of aid they need to supply would amount to a real income gain of over $16 billion. Alternatively, the developing countries could reduce their external public debt by 2.8 percent on average, with reductions for the poorest countries of up to 4.8 percent.

These results basically reflect three effects of higher agricultural world market prices on developing countries. First, there is a change in the terms of trade, which affects real incomes. This effect is positive for countries that are net exporters of agricultural products but negative for others that are net importers. Second, there is a gain in efficiency for most developing countries as resources are shifted from relatively inefficient nonagricultural sectors to agriculture. Third, as a result of resource allocation in favor of agriculture, there is an increase in government tax revenue (which allows a reduction in average tax rates) since many developing countries tax agriculture and subsidize certain nonagricultural sectors. The paper by Loo and Tower suggests that the second and third effects may well dominate any terms-of-trade losses that developing countries may incur as a result of a liberalization of agricultural trade in industrial countries.

Matthews (1985a) makes an additional argument in favor of substantial gains by developing countries from a unilateral liberalization in the EC. If, for example, EC real income rose as a result of a more efficient allocation of resources after a liberalization, the developing countries would gain indirectly from the increased demand for their exports by the Community and by other developed countries whose agricultural export earnings would also have risen. This argument is convincing in qualitative terms. Many past studies do not take account of these secondary effects on global welfare and, therefore, probably underestimate the gains from liberalization. It is far from clear, however, that these secondary effects would be quantitatively significant.

The empirical literature surveyed in this section seems to point to a few unambiguous conclusions. First, agricultural price support in the Community is not necessarily harmful to all, or even most, non-EC countries. A unilateral liberalization would benefit some of Europe’s trading partners and harm others. In particular, current net importers of temperate zone commodities would lose, whereas current or potential net exporters would gain. Since most developing countries are current net importers, they stand to lose as a group from an abolition of the CAP, at least in the short run. The important issue is who will be able to adjust domestic production and consumption patterns so as to take advantage of the higher world prices in the longer run.

Second, although the size of the effect on broad groups of countries is small, the distribution of gains and losses is far from uniform. Countries that are heavily dependent on temperate zone commodity imports because of climate and geography (e.g., Japan) or because they are poor appear to benefit significantly from the operation of the CAP.

Finally, the above results should be interpreted with some caution, it is important to keep in mind that the gains from unilateral liberalization predicted with partial equilibrium models probably have some degree of downward bias built in, because they do not take into account secondary repercussions in nonagricultural sectors.

Effects of the CAP on International Price Stability

Conventional wisdom holds that countries or regions that insulate their domestic markets increase world price instability. As discussed in the theoretical part of this appendix, this is not necessarily true. The question is essentially an empirical one. Empirical research on the effects of the CAP on price stability has given an affirmative answer: all the studies reviewed here agree that the CAP exerts a significant destabilizing influence on world commodity prices. Table 46 summarizes some of the evidence.

The impact of policies on price stability is estimated with the help of counterfactual analysis. A measure of variability is defined first and then the price variability at the counter-factual non-CAP equilibrium is calculated and compared with actual price variability. Most studies introduce random supply and demand shocks, calculate the corresponding counterfactual equilibria, and then use either the standard deviation or the coefficient of variation of the resulting distribution of prices to measure variability.88 Table 46 presents the calculated share of world price variability owing to the CAP; in other words, the decrease in variability that would obtain if the CAP were abolished. The destabilizing effect is strongest in the wheat, coarse grains, and dairy products sectors.

Comparing the EC agricultural policies with price-support schemes in other countries reveals that the CAP is the most important destabilizing factor in the world markets. Sarris and Freebairn (1983) estimate that the CAP alone accounts for more than half of the excess variability of the price of wheat over its global free trade level. Blandford (1983) calculates “transmission coefficients” that show the extent to which changes in trade rather than in domestic consumption are used to stabilize the domestic market and concludes that the Community transmits a larger absolute amount of domestic variability in grain to the world market than any other group of countries. Of all the ways in which price support can affect world price stability mentioned earlier, two are most important for the destabilizing effect of the CAP. First, the CAP relies heavily on variable tariffs, which not only protect the domestic agricultural sector but also insulate domestic consumers from world price variations (Matthews (1985b)). Second, protection reduces the incentive for private stockbuilding, which implies wider price fluctuations. The latter effect could be avoided by government-sponsored stockpiling. Koester, however, finds evidence that in some years EC stocks increased when world market prices were extremely high, thereby actually amplifying world price variability (Koester (1982)).

The last half of this section discussed briefly why price stability is considered important from a welfare point of view, especially for developing countries. Unfortunately, there are no empirical estimates of the welfare losses caused by the destabilizing effects of the CAP. Given the size of the effects, though, it may well be the case that a liberalization would benefit Europe’s trading partners significantly by reducing world price variability.

Concluding Remarks

This appendix has been concerned with two different but related aspects of the CAP: the domestic effects on the welfare of EC members, and the effects on international commodity trade and, consequently, on the welfare of the rest of the world.

Recent empirical literature that has been surveyed addresses these two issues by means of various tools, ranging from single-sector partial equilibrium models to general equilibrium models of the global economy. The differences in methodology, data used, country and commodity coverage, and degree of disaggregation are considerable, and so are the differences in the quantitative estimates. Therefore, if one is to put the reported results in perspective and compare them, it is necessary to have a good understanding of the theoretical premises and the modeling details of each study.

Each approach has its relative merits. The attraction of partial equilibrium models is their simplicity, which means that greater effort can be devoted to collecting data and capturing the peculiarities of the sector(s) represented. On the other hand, intersectoral links are ignored, which in turn means that not all of the effects of agricultural policies are covered. General equilibrium models are more comprehensive in that sense, but they are more demanding both analytically and in terms of data requirements. Overall, however, general equilibrium models are preferable in that they reveal the effects of agricultural price support on other sectors and on the macroeconomy. These effects are both important for policy purposes and, in the case of the CAP, significant in size. Without a general equilibrium model it is difficult to capture the secondary repercussions that liberalization has on the world economy via factor and other product markets. Ignoring these effects may cause systematic underestimation of the gains from liberalization.

Empirical research on the domestic effects of the CAP has reached some unequivocal conclusions. First, the CAP redistributes large amounts of income to farmers, primarily from consumers and secondarily from taxpayers. This transfer is economically inefficient, in that it incurs a deadweight loss. The mean estimate of this loss is around 1 percent of the Community’s GDP.

Second, the distribution of this loss among countries is not uniform. Most countries, however, stand to lose. The heaviest loser appears to be the United Kingdom, followed by Italy and the Federal Republic of Germany. France probably also registers small losses. The clear gainer is Ireland. The evidence on Denmark and the Netherlands is ambiguous.

Third, other than the deadweight loss that the whole economy suffers, other sectors incur costs because of the CAP as well. In particular, subsidizing agricultural production means discriminating against industry and services, diverting resources away from them and reducing their exports. This kind of cost has not attracted enough attention, mainly because it requires general equilibrium modeling. Quantification of intersectoral effects is, therefore, an important area for future research.

The economy-wide and sectoral losses are by no means the only costs of the CAP. Agricultural price support, especially of such magnitude, generates wasteful rent-seeking and lobbying and distorts investment. These costs are difficult to estimate, but they mean that the traditional welfare calculations, even if they include intersectoral repercussions, underestimate the true social costs of operating the CAP.

With regard to the international effects of the CAP, empirical research has come to some interesting conclusions. By encouraging domestic production and raising consumer prices, especially in products with low income elasticity, the CAP has artificially reduced EC consumption and boosted production, turning Europe into a net exporter of most temperate zone commodities. This increase in the EC commodity surplus depresses and destabilizes world prices and makes production in other countries less profitable. The pattern of world trade is, in this way, severely distorted. This effect is more evident in the sectors that are relatively more heavily protected, like wheat, coarse grains, ruminant meat and dairy products.

The distortionary effects of the CAP affect the welfare of the Community’s trading partners. Generally speaking, net exporters of temperate zone commodities lose, while net importers gain. Since most developing countries are net importers, less developed countries as a group appear to benefit from the operation of the CAP, at least in the short run, through an improvement in their terms of trade.

This result, although it is confirmed by most existing studies, should be treated with caution. First of all, it conceals the distribution of losses and gains across countries, which is far from uniform. Second, it is derived mostly from partial equilibrium models, which ignore secondary repercussions on welfare via the nonagricultural markets; the available general equilibrium studies show that ignoring these repercussions leads to systematic underestimation of the costs of the distortion. Third, it may be relevant only in the short run; if many developing countries were able to take advantage of higher commodity prices and switch from being net importers to net exporters, the result would prove incorrect over the longer run. Fourth, it ignores the cost of increased price instability, which is probably more detrimental to poor than to rich countries.

It is hard to express these qualifications quantitatively; however, even if the majority of developing countries actually gained from the CAP this gain would be very small compared with the welfare losses in the EC. It would be easy for the Community to compensate the losers from a unilateral liberalization and still realize substantial benefits.89 From a world welfare point of view, of course, there is an even better alternative than a unilateral liberalization-cum-compensation scheme: that of a multilateral reduction of protection in agricultural markets. All existing evidence strongly suggests that moves toward freer trade that involve more, rather than fewer, trading partners would spread the benefits more uniformly. In other words, the optimal response of the losers from a unilateral liberalization is to liberalize their markets as well.90

Appendix IV Economic Costs of the CAP: An Illustrative Exercise for the Federal Republic of Germany

There is by now a sizable body of empirical literature on the effects of the CAP on the domestic economies of member countries.91 Most of this literature is based on models of the partial equilibrium type—that is, models that focus on the markets for agricultural products and assume that prices and quantities of other goods and services are unaffected by changes in agricultural policy. Fewer attempts have been made at estimating the effects of the CAP by means of so-called computable general equilibrium models, which take account of intersectoral linkages. Those computable general equilibrium experiments that have been carried out, however, indicate that intersectoral dependencies are important, and that without taking explicit account of them it is not possible to calculate the full effect of agricultural policies on macroeconomic variables, such as growth, employment, and prices.

The analysis in this appendix is based on a simple computable general equilibrium model for the Federal Republic of Germany. A change in protection of agricultural production in the EC is simulated and the domestic effects on the German economy are explored.

The Model

The model that serves as the basis for the simulation is a “small” computable general equilibrium model, which closely follows Dixon and others (1982). It is small in the sense that only four productive sectors are represented: agriculture (which includes food processing), industry, traded services, and nontraded services. Each sector is assumed to produce one good. Final demands and demands for intermediate inputs are satisfied by a combination of imports and domestic production. The model distinguishes three types of imports (agricultural goods, industrial goods, and traded services); each constitutes an imperfect substitute for the corresponding type of domestic production. There are four kinds of final demand (investment, government consumption, private consumption, and exports) and three types of primary inputs (labor, capital, and land). All tariff and subsidy changes in agriculture are assumed to apply at the EC border and all EC countries are assumed to act in an identical way. The model assumes that each sector’s capital stock, as well as real wages, the external position, and the nominal exchange rate, are unaffected by the simulated change in policies.92

The aggregation level of the model is reflected in the following input-output table. Table 49 describes which sources satisfy each type of demand in the base period: In the model, changes of input-output structures are represented by equations for input demand, final demand, supplier behavior, and market equilibrium. These equations are discussed in the following paragraphs.

Input Demand

Producers are assumed to minimize the cost of production, and to be confronted with a two-level production function. The first level imposes constant returns to scale and Leontieff complementarity between different types of intermediate inputs and between intermediate and primary inputs. The second level allows for constant elasticity (CES) substitution between imported and domestically produced intermediate inputs and between different types of primary factors. The mode) describes the solution to the optimization problem in a set of equations for producers’ factor demand. Thus, in a given sector (sector j) demand for both domestically produced and imported intermediate inputs depends on the activity level [Zij)] and the relative prices of imports and domestic production:

INTERINPUT(DOM,i,j)=F1[Z(j),P(DOM,i),P(IMP,i)];i=1,2,3;j=1,2,3,4.(1)
Table 49.

Input-Output Structure for the Base Year1

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The capitalized names in the table represent variables of the computable general equilibrium model. The notation is fully documented in Table 52.

INTERINPUT(IMP,i,j)=F2[Z⁡(j),P⁡(DOM,i),P⁡(IMP,i)];i=1,2,3;j=1,2,3.(2)
INTERINPUT(4,j)=F3[Z⁡(j)];j=1,2,3,4.(3)

Here equation (3) states that input-demand for nontraded services (which are produced by sector 4) only depends on activity levels in the demanding industries, as there are no imports to substitute for domestic deliveries.

The equations for primary input-demand state that each sector’s demand is determined by its activity level and the relative prices of labor, capital, and land:

LAB(j)=F4[Z⁡(j),P⁡(LAB),P⁡(CAP),P⁡(LAND)];j=1,..,4(4)
CAP(j)=F5[Z⁡(j),P⁡(LAB),P⁡(CAP),P⁡(LAND)];j=1,..,4(5)
LAND(j)=F6[Z⁡(j),P⁡(LAB),P⁡(CAP),P⁡(LAND)];j=1.93(6)

Final Domestic Demand

Investment

By assumption, the simulated policy shock leaves the share of aggregate real investment in real domestic absorption unchanged, but the model allows for substitution between imports and domestically produced investment goods, when relative prices change:

INV(DOM,i)=F7[INV(TOTAL),P⁡(DOM,i),P⁡(IMP,i)];i=1,..,4(7)
INV(IMP,i)=F8[INV(TOTAL),P⁡(DOM,i),P⁡(IMP,i)];i=1,..,3(8)
INV(TOTAL)=F9(ABS)(9)
Household Consumption

Consumers are assumed to maximize their utility by substituting between different goods in response to relative price changes (in a linear expenditure system). The model fixes the share of total consumption, however, in real domestic absorption:

CONS(DOM,i)=F10[CONS(TOTAL),P(DOM,1),P(DOM,2),P(DOM,3),P(DOM,4),P(IMP,1),P(IMP,2),P(IMP,3)];i=1,…,4(10)
CONS(IMP,i)=F11[CONS(TOTAL),P(DOM,1),P(DOM,2),P(DOM,3),P(DOM,4),P(IMP,1),P(IMP,2),P(IMP,3)];i=1,2,3(11)
CONS(TOTAL)=F12(ABS)(12)
Government Consumption

Like private consumption, government consumption is assumed to maintain its share in real domestic absorption. Since government services are solely provided by the “non-traded services sector” (sector 4),94 this relationship can be expressed as follows:

GOV(DOM,4)=F13(ABS)(13)

Domestic Supply

A constant-retums-to-scale technology is assumed for all productive sectors. Marginal costs of production increase with output, however, since the supply of two of the primary factors (capital and land) is fixed. The individual producer chooses the output level that equates marginal cost with output price:

P(DOM,i)=F16[P(DOM,j),P(IMP,w),P(LAB),P(CAP),P(LAND);j=1,…4but j≠i,w=1,…,3];i=1,…4(14)

Here, F16 is the marginal cost of production.

Domestic Prices and World Market Prices

The markups in foreign trade (for transport, wholesale, retail services, etc.) are assumed to remain constant in the wake of the simulated policy change. Similarly the nominal exchange rate is assumed to be unaffected. Thus, the relationship between world market prices (in foreign currency) and domestic prices of traded goods only changes if the duty ratio (defined as 1 plus the ad valorem rate of import protection) or the subsidy ratio (defined as 1 plus the ad valorem rate of export protection) moves:

P(DOM,i)=FCP(EX,i)*XRATE¯*SUBSIDYRATIO(i)*1/MARKUP; i¯=1,…,3(15)
P(IMP,i)=FCP(IMP,i)*XRATE¯*DUTYRATIO(i)*MARKUP¯;i=1,…,3(16)

In the following experiment it was assumed that the subsidy and duty ratios in the agricultural sector would decline by 20 percent as a result of liberalization of the CAP.95 In line with the studies surveyed in Appendix III (see also Table 43), it was further assumed that world market prices for agricultural products would increase by about 8 percent relative to prices for manufactures and traded services; thus, domestic prices for agricultural products by implication were assumed to decline by 12 percent in relative terms. These assumptions are reflected in the following equations:

FCP(EX,i)=FCP(EX,i)¯,i=1,…3(17)
FCP(IMP,i)=FCP(IMP,i)¯,i=1,…,3(18)
SUBSIDYRATIO(i)=SUBSIDY¯RATIO(i),i=1,…,3(19)
DUTYRATIO(i)=DUTYRA¯TIO(i),i=1,…,3(20)

Equations (17)–(20) allow for the exogenous setting of the foreign currency prices of exports and imports, as well as the subsidy and duty ratios in the traded goods’ sectors of the model.

Market Closure

The model is closed by a set of equations that link demand and supply by imposing market clearing on all markets except the labor market.

Markets for Primary Factors

By assumption there is a slack in the labor market as wage-earners keep real wages fixed at a rate above the market-clearing level. Capital and land are assumed not to move between sectors and equilibrium in the markets for these factors is attained by adaption of demand:

P(LAB)=CONSUMERPRICEINDEX [P(DOM,1),P(DOM,2),P(DOM,3),P(DOM,4),P(IMP,1),P(IMP,2),P(IMP,3)].(21)
CAP(j)=CAP(j);¯j=1,…,4.(22)
LAND(j)=LAND;j¯=1.(23)
Domestic Production

Equilibrium in the markets for output from the four sectors requires that total domestic production satisfy aggregate demand:

Z(i)=ΣjINTERINPUT(DOM,i,j)+INV(DOM,i)+CONS(DOM,i)+GOV(DOM,i)+EX(i);i=1,…,4.(24)
External Balance

By assumption, the foreign currency value of the exports equals the foreign currency value of imports so that domestic absorption is determined by aggregate output, with traded goods inflated by their terms of trade:

ABS=ΣiZ(i)*FCP(EX,i)/FCP(IMP,i)+Z⁡(4),i=1,2,3.(25)

Mathematical Structure

In practice, all equations described above are formulated in a log-linear form and the model constitutes a linear equation system that can be solved for percentage changes in all endogenous variables.96

Parameter Settings

The model is numerically specified for the Federal Republic of Germany, and the initial demand and supply structure is represented by a German input-output table for 1980.97 The key parameter settings are shown in Table 50.

The underlying household utility function is assumed to be additive; thus the uncompensated own price elasticities (nij) and cross-price elasticities (nij for i ≠ j) can be derived as follows:98

nii = (ξi/w) - ξi αi [1 + (ξi/w)]

nij = - ξi αi [1 + (ξj/w)] for i ≠ j.

Here ξi represents the expenditure elasticity for product i. while w is the Frisch parameter and αi is the household budget share for product i. The Frisch parameter was set at -1.83.99

Table 50.

Federal Republic of Germany: Key Parameter Settings

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Based on Lluch, Powell, and Williams (1977, p. 54).

Based on Lächler (1985, p. 85) and Fund staff calculations. These elasticities are assumed to be the same for all uses.

A simple Cobb-Douglas production function was assumed to characterize industry and the service sectors, while the substitution elasticity for primary factors in agriculture was set at a level, which brought the output supply price elasticity in line with estimates from the literature.

Numerical Results

The effects of an ending of agricultural price support under the CAP on the German economy are simulated by lowering the rates of subsidization/import protection by 26 percentage points100 and increasing the world market price for agricultural products by 8 percent relative to that for manufactures. The macroeconomic consequences are substantial (Table 51). Aggregate output increases by 3.6 percent and employment by 5.5 percent as the reduction in output and employment in the agricultural sector is more than compensated for by increases in other sectors. The consumer price level falls by 1.7 percent and the terms of trade worsen by 0.7 percent. As a result of the latter change, real income and domestic demand increase by slightly less than aggregate output. These results are, of course, dependent upon the numerous model assumptions. In particular, with real consumption wages, that is, the nominal wage deflated by the consumer price level, assumed constant, real output wages, that is, the nominal wage deflated by the product price level, decline, and employment and output increase. To the extent that the reduction in the consumer price level would give rise to an increase in real consumption wages, employment, and output, and real income gains owing to liberalization of agricultural policies would be smaller.

Table 51.

Federal Republic of Germany: Changes Elicited by the Abolition of Agricultural Protection Through the CAP

(In percent)

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Source: Fund staff calculations.

Sectoral Effects on Output

The elimination of agricultural price support reduces domestic currency prices for agricultural goods to the level of world market prices. Consequently, farmers reduce output and employment until marginal costs meet the new output price. Wages decline relative to output prices in the nonagricultural sectors, reflecting the assumption of fixed real consumption wages, so that producers in these sectors increase employment and output. The expansion is most pronounced in industry and in the nontraded services’ sector, where production is more labor intensive than in the traded services’ sector. The net effect of these sectoral output changes is a significant increase in aggregate output and employment.

Domestic Demand and Trade Flows

The decline in domestic agricultural prices reduces production and increases consumption of agricultural goods; consequently, exports decline.101 Exports of the industrial sector, on the other hand, increase as the expansion in output, elicited by the drop in wages relative to output prices, exceeds the increase in domestic demand. The relatively small rise in domestic demand for manufactures reflects low growth in consumption, which is due chiefly to the relatively small expenditure elasticity of households for this product group. Reflecting a moderate increase in output (owing to a relatively low labor intensity of production) and a strong increase in domestic demand (owing to a substantial increase in consumption),102 exports of services decline. Consumption of nontraded services rises strongly owing to the high expenditure elasticity of households for this product group. Domestic demand, however, increases by somewhat less because of a smaller rise in government demand.

Table 52.

Federal Republic of Germany: Notation of Variables

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The development of imports depends upon the changes in final domestic demand and in the demand for intermediate goods. In agriculture, higher consumption demand for imports is partly offset by lower input demand so that imports of agricultural goods increase only little. In industry, on the other hand, strong input demand boosts imports despite a relatively small increase in final domestic demand (particularly consumption). Imports of traded services increase substantially because the rise of final domestic demand exceeds output growth. Owing to the assumption of external balance in foreign currency terms and a deterioration in the terms of trade, aggregate import volumes increase by somewhat less than the volume of aggregate exports.

Concluding Remarks

The model simulation shows that intersectoral dependencies are important in the debate on the consequences of the CAP. Strong effects on nonagricultural production, prices, and trade are likely to be transmitted through factor markets. Thus, an assessment of the CAP cannot be made solely by judging the CAP’s ability to live up to its own stated objectives but has to take account of its influence on other variables. The simulation indicates that the influence of the CAP on EC countries’ GDP, employment, inflation, and balance of payments is significantly negative.

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Recent Occasional Papers of the International Monetary Fund

42. Global Effects of Fund-Supported Adjustment Programs, by Morris Goldstein. 1986.

43. International Capital Markets: Developments and Prospects, by Maxwell Watson, David Mathieson, Russell Kincaid, and Eliot Kalter, 1986

44. A Review of the Fiscal Impulse Measure, by Peter S. Heller, Richard D. Haas, and Ahsan H. Mansur. 1986.

45. Switzerland’s Role as an International Financial Center, by Benedicte Vibe Christensen. 1986.

46. Fund-Supported Programs, Fiscal Policy, and Income Distribution: A Study by the Fiscal Affairs Department of the International Monetary Fund. 1986.

47. Aging and Social Expenditure in the Major Industrial Countries, 1980–2025, by Peter S. Heller, Richard Hemming, Peter W. Kohnert, and a Staff Team from the Fiscal Affairs Department. 1986.

48. The European Monetary System: Recent Developments, by Horst Ungerer, Owen Evans, Thomas Mayer, and Philip Young. 1986.

49. Islamic Banking, by Zubair Iqbal and Abbas Mirakhor. 1987.

50. Strengthening the International Monetary System: Exchange Rates, Surveillance, and Objective Indicators, by Andrew Crockett and Morris Goldstein. 1987.

51. The Role of the SDR in the International Monetary System, by the Research and Treasurer’s Departments of the International Monetary Fund. 1987.

52. Structural Reform, Stabilization, and Growth in Turkey, by George Kopits. 1987.

53. Floating Exchange Rates in Developing Countries: Experience with Auction and Interbank Markets, by Peter J. Quirk, Benedicte Vibe Christensen, Kyung-Mo Huh, and Toshihiko Sasaki. 1987.

54. Protection and Liberalization: A Review of Analytical Issues, by W. Max Corden. 1987.

55. Theoretical Aspects of the Design of Fund-Supported Adjustment Programs: A Study by the Research Department of the International Monetary Fund. 1987.

56. Privatization and Public Enterprises, by Richard Hemming and Ali M. Mansoor. 1988.

57. The Search for Efficiency in the Adjustment Process: Spain in the 1980s, by Augusto Lopez-Claros. 1988.

58. The Implications of Fund-Supported Adjustment Programs for Poverty: Experiences in Selected Countries, by Peter S. Heller, A. Lans Bovenberg, Thanos Catsambas, Ke-Young Chu, and Parthasarathi Shome. 1988.

59. The Measurement of Fiscal Impact: Methodological Issues, edited by Mario I. Blejer and Ke-Young Chu. 1988.

60. Policies for Developing Forward Foreign Exchange Markets, by Peter J. Quirk, Graham Hacche, Viktor Schoofs, and Lothar Weniger. 1988.

61. Policy Coordination in the European Monetary System. Part I: The European Monetary System: A Balance Between Rules and Discretion, by Manuel Guitián. Part II: Monetary Coordination Within the European Monetary System: Is There a Rule? by Massimo Russo and Giuseppe Tullio. 1988.

62. The Common Agricultural Policy of the European Community: Principles and Consequences, by Julius Rosenblatt, Thomas Mayer, Kasper Bartholdy, Dimitrios Demekas, Sanjeev Gupta, and Leslie Lipschitz. 1988.

Note: For information on the titles and availability of Occasional Papers published prior to 1986, please consult the most recent IMF Publications Catalog or contact IMF Publication Services.

1

The Council referred to the international undertakings entered into at the Organization for Economic Cooperation and Development and to the 1987 summit meeting of heads of state or government of the seven major industrial countries in Venice.

2

The present paper does not discuss the rationale for these objectives, assuming that supporting farmers in the EC or elsewhere is a matter of social choice.

3

Market organization is the collective name of the rules and regulations adopted by the authorities to influence the supply of and demand for a particular commodity.

4

For some detail on the policies pursued by individual countries prior to the adoption of the CAP, see Services des Publications des Communautés Européennes (1958). (Hereinafter referred to as Stresa papers.)

5

Belgium, France, the Federal Republic of Germany, Italy, Luxembourg, and the Netherlands, hereinafter referred to as EC-6.

6

The OEEC was superseded by the OECD on September 30, 1961.

7

Stresa papers, p. 182 and pp. 189–92.

8

Stresa papers, p. 222. English version was taken from excerpts quoted in Commission of the European Communities (1987a), p.17.

10

Ibid., p. 26.

11

The most commonly used nonprice support instruments are storage subsidies, which are chiefly meant to soften the impact on the market of seasonal fluctuations in production; consumer subsidies; input subsidies; and deficiency payments and production premiums of various kinds. These instruments are used in a highly selective fashion. Nonprice support also includes structural measures financed by the Community, such as irrigation schemes, reafforestation projects, and research and development. These structural measures may well be important for the future development of the Community’s agricultural sector; at present, however, they account for only a small fraction of total expenditure on the CAP. For details of the arrangements in force for individual commodities covered by the CAP, see Commission of the European Communities (1985b).

12

The term “target price” is used for cereals, sugar, milk, olive oil, and grape and sunflower seeds. To reflect technical differences, “guide price” is used for bovine meat and wine, “norm price” for tobacco, and “basic price” for pork.

13

The term “threshold price” is used for cereals, sugar, dairy products, and olive oil. Essentially the same concept is referred to as “sluice-gate price” in the case of pork, eggs, and poultry meat, and “reference price” in the case of fruit, vegetables, wine, and certain fishery products.

14

The mechanisms adopted for the products covered by the CAP do not give agriculture full protection against foreign competition For example, to secure the acceptance of the CAP by its trading partners, the Community agreed that oilseeds and so-called cereal substitutes enter the EC without import duties or quantitative restrictions. The Community believes that the large and growing imports of cereal substitutes as fcedstuffs are partly responsible for the excess supply of dairy products.

15

The computation of MCAs at different stages and the changes undergone by the system are explained in Appendix II with the help of some simplified examples.

16

This still left the Federal Republic of Germany with positive MCAs, which it found impossible to dismantle because, as prices were kept roughly stable in terms of ECUs at the subsequent annual reviews, this would have called for price reductions in deutsche mark.

17

Of course, MCAs for those countries that do not participate in the Exchange Rate Mechanism of the EMS, and for Italy, which has temporarily opted for larger fluctuation margins, have to be adjusted continuously.

19

For a detailed presentation of the EAGGF, see Commission of the European Communities (1986b).

20

There has been a co-responsibility levy for milk since 1977. with a supplementary one to penalize those who exceed the production quotas introduced in 1984. A co-responsibility levy was introduced for cereals in 1986. The revenue raised by the co-responsibility levy for milk amounted to some ECU 0.7 billion in 1986, about 3 percent of total expenditures of the EAGGF.

21

Costs of intervention arise when the expenditures for intervention purchases and stockpiling are larger than the revenue from sales out of stocks.

22

Unless otherwise indicated, the analysis for the EC focuses on the Community of 10, i.e., Portugal and Spain, which joined recently, are excluded.

23

See Appendix III for a survey of existing studies.

24

A major shortcoming of the first technique is the assumption that in the period of investigation no factors other than the introduction of the CAP influenced economic developments. The second technique rests on the equally unrealistic assumption that differences between CAP member countries and the control group result only from differences in agricultural policies.

25

See Appendix III for a more detailed discussion of the measurement of economic welfare effects of the CAP, and the limitations of the partial equilibrium analysis.

26

Several attempts have been made in the literature to estimate the effects of the CAP on economic welfare in EC countries (see Appendix III for a survey of recent studies). The models used in these studies can be characterized as cither partial or general equilibrium models. While partial equilibrium models focus on demand and supply conditions in one or more sectors of the economy and assume that other sectors are not affected by changes in agricultural policy, general equilibrium models explicitly take account of sectoral interdependencies in production.

27

The model is in the tradition of so-called Johansen models and follows closely the version developed by Dixon and others (1982). A full description of the model and discussion of the simulation results are given in Appendix IV.

28

The OECD estimated the protection afforded EC farmers by means of producer subsidy equivalents, defined as PSE = Q*(Pd–Pw) + D - L + B, where Q denotes output volumes, p prices, D direct income transfers to agriculture, L fees and levies paid by agriculture, B other budgetary support, and the subscripts d and W the domestic and world market. The first term on the right-hand side of the equation measures the amount of protection given through price support.

29

Real wages are generally regarded as rigid in the short run in European countries but relatively flexible in the United States and Japan. For empirical evidence for selected European countries see Klau and Miltelstädt (1986).

30

This is, of course, a simplification and may lead to an overstatement of the effects of changes in support prices.

31

Note that exports emerge in the model as the difference between domestic output and consumption. The analysis does not take into account stockbuilding as an alternative to exporting.

32

The thrust of these results is supported by recent studies by Stoeckel and Breckling (1988) for the Federal Republic of Germany, France, Italy, and the United Kingdom, and by Dicke and others (1988) for the Federal Republic of Germany.

33

Coefficients were calculated for each product and EC member country using producer prices in ECUs (excluding value-added tax) as published in Eurostat, and international commodity prices, as published in International Financial Statistics, convened into ECUs. The following prices were taken to represent the world market (i.e.. the low-cost suppliers’) prices: for beef, prices quoted in the London market; for sugar, the average of the New York spot price and London daily price, f.o.b, Caribbean ports; for butter. London prices; for maize, the Thailand price; and for wheat, the Australian price. Prices were not adjusted for transportation costs nor for quality differences that may exist between products of different origin. The resulting coefficients of protection give therefore only a broad picture of the actual protection afforded EC producers. Coefficients for the EC as a whole are arithmetic averages of country coefficients.

35

The OECD treats the EC as a single entity for its computations, while the estimates on nominal protection presented in Table 5 are based on individual country and commodity data.

36

These results are supported in a recent study by the U.S. Department of Agriculture (see U.S. Department of Agriculture (1987)).

37

Self-sufficiency rates are calculated as the ratios of domestic production to consumption.

38

It is not clear that this was entirely due to the CAP; the timing of the United Kingdom’s entry into the CAP coincided with the adoption of higher-yielding seed varieties in cereals.

39

It is, however, worth noting that the data on developments in EC self-sufficiency between 1960 and 1985 tend to underestimate the increase, since from 1973 onward the figures include the United Kingdom, which is a major net importer of food.

40

Also, as pointed out by Jacquemin and Sapir (1988), while the Common Market led to “trade creation” in manufactures, the CAP led to “trade-diversion” and “seems to have effectively discriminated against non-partner suppliers” (pp. 137–38).

41

This reflects the book value and not the market value of stocks at resale prices, which is considerably lower.

42

The EAGCJF accounts for most of the appropriations for agriculture in the EC’s common budget. Although most receipts in the EC budget stem from contributions by the members, some revenue is collected by way of import and certain agricultural levies. In addition, co-responsibility levies on milk and cereals generate revenues to finance specific expenditures. These levies are treated as measures to regulate agricultural markets; they are not recorded as revenue receipts but are subtracted from expenditures.

44

Net social security benefits, however, represent subsidies to agriculture only to the extent that they exceed net benefits granted to persons employed in other sectors of the economy.

45

For a detailed survey on these studies, see Appendix III.

46

The results from the OECD study (1987) can be construed to be based on a simple “partial” equilibrium approach, which implicitly assumes inelastic demand for agricultural products in the EC for estimating costs to the consumers. The expenditures incurred by both the national and the EC authorities on agriculture, on the other hand, are taken in the study to represent the costs to the taxpayers.

47

This argument would be weakened if the management of stocks by the EC contributed toward stabilizing world prices. There is, however, no evidence in favor of countercyclical stock management by the EC.

48

For details, see Appendix III.

50

See. for example, Valdes (1987).

52

There was no attempt at precise quantification in the Memorandum, but it was argued that 80 percent of all holdings were too small to keep one man fully employed because modem technology would enable him to cultivate 30–40 hectares or raise at least 40 milk cows.

55

This needs mentioning because of the long discussion on a controversial proposal to tax vegetable and marine oils and fats. This proposal has now been shelved because of the opposition of several member states, who objected to its price-raising effect, as well as of foreign suppliers. Oilseeds and vegetable oils enter the Community duty free under a regime that is bound in the GATT. In the view of its proponents, the tax would be justified inter alia because, at the time of a reduction in the support to the Community’s growers, equity would call for outlets in the Community also to be made less attractive to growers from third countries. For the arguments in favor of the tax see Commission of the European Communities (1987b, Annex II).

56

See Commission of the European Communities (1988b, Section IV, Part C).

57

For the arguments that have been put forward in favor of the adoption of the stabilizers, see Commission of the European Communities (1987e) and (1987c).

58

Real income is defined here as value added at factor cost minus rents and interest payments.

59

For a definition of the green rate, see Appendix II.

60

Commission of the European Communities (1987d, p. 3).

61

The nature and the use made of these measures through 1984 is surveyed in Commission of the European Communities (1985c), As indicated by the title, the term “guarantee threshold” is used in a very broad sense.

62

The close relationship between the two concepts is underscored by the fact that guarantee thresholds are mentioned in some reports by the Commission as instruments to implement co-responsibility.

63

See Commission of the European Communities (1987c, p. 12).

64

This decision was taken for a five-year period, but there appears to be good reason to assume that quotas will continue to be used after the end of the marketing year 1988/89. In a recent document, the Commission expressed the view that “the production cuts resulting from the suspension of the quotas must be consolidated” under the arrangements that will be applicable as of the marketing year 1989/90. See Commission of the European Communities (1987e, p. 14).

65

For a summary of the problems facing the milk sector see Commission of the European Communities (1986a, pp. 1-10).

66

See Commission of the European Communities, Bulletin, No. 12 (1986), pp. 14–15 and 85–89. and the relevant sections of Commission of the European Communities (1987b).

68

See “Council Regulation (EEC) No. 1096/88 of 25 April 1988 establishing a Community scheme to encourage the cessation of farming.” Official Journal of the European Communities, L 110 (April 29, 1988), Luxembourg, pp. 1–6.

69

See “Council Regulation (EEC) No. 1094/88 of 25 April 1988,” Official Journal of the European Communities, L 106 (April 27, 1988), Luxembourg, pp. 28–32.

71

For a recent statement of this position, see Commission of the European Communities (1988c, p. 8).

72

The Community’s position regarding the agricultural negotiations in the Uruguay Round were stated in Commission of the European Communities (1987f).

74

The equation is monetary gap=(1−centralrategreenrate)100.

75

The calculations are based on data for the week ending on Tuesday. If a change is warranted, it becomes effective on the following Monday. More frequent changes have been ruled out in order not to hamper trade.

76

Some of the secondary objectives of the CAP, such as improving the quality of food consumed, improving the distribution of income within the agricultural sector, protecting small family farms and preserving rural life styles and the natural environment, create the need for a different family of instruments that generally go under the name of guidance expenditure.

77

For a discussion of the partial equilibrium welfare analysis and its advantages see: Corden (1957) and (1971); Harberger (1959); Johnson (1960); and Currie, Murphy, and Schmitz (1971), for a discussion of its limitations, in particular with respect to analyzing agricultural price support in the EC, see Buckwell and others (1982); Valdes and Zietz (1980); Matthews (1985b); and Winters (1987).

78

See Tyers and Anderson (1986a) and also Tyers and Anderson (1987) and (1986b): earlier versions of the same model are used in Anderson and Tyers (1984), Chisholm and Tyers (1985), and Tyers (1985).

79

The basic structure of CGE models is discussed in detail in Whalley (1984) and (1985b), Ch. 3, and Winters (1987). Whalley (1985a) outline’s some of the methodological problems that applied general equilibrium analysis still faces.

80

The effect of domestic policies on international price stability is also analyzed in Bale and Lutz (1979a), Blandford (1983), and Berck and Schmitz (1984), Koester (1982) compares alternative price support policy packages against their (de)stabilizing properties.

81

Buckwell and others (1982, Ch. 3), Australia, Bureau of Agricultural Economics (1985, Ch. 6), and Whalley (1985b, Ch. 3) offer a brief discussion of the problems of counterfactual equilibrium analysis.

82

Note, however, that both in the 1986 and 1987 studies the base period for the estimates was 1980–82, The results reported for 198? are merely “scaled up” results For 1980–82 and do not take into account the major macroeconomic and supply shocks that occurred between 1980 and 1985.

83

A value of zero implies no pass-through of changes in the world prices to the domestic prices; a value of one implies complete pass-through.

84

These are the “gross” costs of (he CAP and not comparable with the “net” costs, or deadweight losses, reported in Table 37.

85

Tyers (1985) and Matthews (1985b) estimate the effects of liberalization in a multicommodity model with and without cross-effects. In both studies the models without cross-effects produce estimates 20 to 100 percent higher than the models with cross-effects. This difference is most noticeable in coarse grains, wheat, and nonruminant meat, where the removal of channels for market interaction roughly doubles the calculated effects of liberalization.

86

In line with the estimated larger price effects of liberalization, the authors report a higher loss to developing countries in their more recent study.

87

To assess the effects of the CAP alone, the results reported by Loo and Tower could be scaled using estimates of the effects of the CAP on agricultural world market prices provided in Table 43.

88

The choice of the measure is important: the standard deviation, for example, depends on the level of the mean (in this case, the price level) and, therefore, even if prices remain equally stable after liberalization, the standard deviation will be different. Koester (1982, pp. 53–54), discusses at length the different measures of variability. It turns out that even the coefficient of variation is not unbiased. Koester suggests correcting the coefficient of variation by the explanatory power of the trend regression to obtain a better measure of variability.

89

It is worth noting that, even by the most pessimistic estimate, the losses of the developing countries from a unilateral Liberalization in the EC are only around 70 percent of the official development assistance actually disbursed in 19H5 by the seven largest EC members, excluding Greece, Ireland, and Luxembourg (in 1980 U.S. dollars; see World Bank (1986, Statistical Appendix)).

90

OECD (1982) discusses the issue of multilateral liberalization in detail. There is also a large body of empirical evidence on this: Chisholm and Tyers (1985), Tyers and Anderson (1986a), Whalley (1984), Whalley (1985b), and World Bank (1986, and the references therein).

91

See Appendix III for a survey of existing studies.

92

The simulation results reported later in the appendix depend to a significant extent on the presence of classical unemployment in the economy, which seems to be the case for most European countries.

93

Note that only agriculture (sector I) uses land as a factor of production.

94

Table 48 has a “government sector” which creates the goods used by government. This sector is contained in the nontraded services sector of the mode).

95

In a recent study by the OECD (OECD (1988)) the average producer subsidy equivalent for the EC was estimated at 37 percent in 1979–81. Of this, 70 percent was accounted for by agricultural pricing policies under the CAP. Thus, abolition of the CAP was assumed to reduce the producer subsidy equivalent by about 26 percentage points, which translates into a 20 percent reduction in the average duty and subsidy ratio.

96

The model, as described above, contains 84 endogenous variables that are explained by the same number of equations. The specification of the equations ensures that the solution of the model is unique.

97

For agriculture it was assumed that 50 percent of gross value added in the base year covered labor costs, while the remainder was evenly distributed on capital and land. For all other sectors, labor costs in the base year were represented by total wage costs, while the rest of gross value added was assumed to constitute the cost of capital utilization.

99

Using the relationship between per capita GDP and w estimated by Lluch, Powell, and Williams (1977, p. 248).

100

Recall that this translates into a 20 percent reduction in the subsidy/duty ratio for agricultural products.

101

The alternative possible solution, a fall in stocks, is not incorporated into the model. The drop in exports may seem large, but in 198U exports accounted for only 7¾ percent of domestically produced agricultural goods.

102

Note that the expenditure elasticity of households for this product group is greater than one.

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Cover The Common Agricultural Policy of the European Community
The Common Agricultural Policy of the European Community
Principles and Consequences: Occa Paper No.62
ISBN:
9781557750365
ISSN:
0251-6365
Publication Date:
25 Nov 1988
Publisher:
International Monetary Fund
DOI:
https://doi.org/10.5089/9781557750365.084
Pages:
86
Chart 2.

The Economics of Price Support: The Single-Country Case

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