Price Distortions in Agriculture and Their Effects:Arn International Comparison

SWP-359

Wol ld Bank Staff Working Paper No. 359

OctDber 1979

y: Malcolm D. Bale and Ernst LutzJ 2C * * Economic Analysis and Projections Department

HF Development Policy Staff541 6. 5 © 1979

P5 Bank2 . eet, N.W.

n, D.C. 20433, U.S.A.

* ethose of the authorsi ts aff ilIiated

ehalf.

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The views and interpretations in this document are those of the author andshould not be attributed to the World Bank, to its affiliated organizations,or to any individual acting in their behalf.

WORLD BANK ..

Staff Working Paper No. 359

October 1979 p\gG

PRICE DISTORTIONS IN AGRICULTURE AND THEIR EFFECTS:

AN INTERNATIONAL COMPARISON

The central thesis of this paper is that agricultural pricing policiespursued by developing countries produce effects which are diametricallyopposite to those produced by the pricing policies of many developed coun-tries, and that the policies of both are costly in terms of global welfare.

In general, the agricultural sector in developing countries is heavily taxedwhile that in the developed countries receives substantial price protection.The effects of agricultural price distortions on output, consumption, tradeand rural employment are estimated for nine countries. In addition, theeffects of priee distortidns on the distribution of income between producersand consumers, on goverunment revenue and foreign exchange, and the net social

losses of the policies are calculated. The results indicate that there arelarge income transfers and impacts on migration from the rural to the urbansector in developing countries and from the urban to the rural sector indeveloped economies.

To insure proper interpretation of this paper and its policy implications,attention is drawn to the following caveats: some secondary data is of question-able quality and could be improved; specific methodological questions raisedin the course of this research have been inadequately addressed; the resultsare based on only one year (1976); and some personal judgements were requiredfor determining certain data input. For these reasons the results should be

interpreted with caution. They represent orders of magnitude and should be

considered tentative. The paper is the.first phase of work in progress onthe issue of agricultural price distortions.

Prepared by: Malcolm D. Bale and Ernst LutzEconomic Analysis and Projections DepartmentDevelopment Policy Staff

Copyright 1979The World Bank1818 H Street, N.W.Washington, D.C. 20433USA

PRICE DISTORTIONS IN AGRICULTURE AND THEIR EFFECTS:AN INTERNATIONAL COMPARISON

Introduction

Agriculture is the main source of food for the world, and food

is the basic input in the daily sustenance of humans. Yet in many parts

of the world there is insufficient food which in turn implies inadequate

agricultural output. The reasons for inadequate agricultural production

are many and varied, ranging from poor distribution and poor production

techniques to political intervention at various levels in the global agri-

cultural complex. The most important reason for deficient agricultural

output is difficult to ascertain, but T.W. Schultz in the first Elmhurst

Memorial Lecture to the International Association of Agricultural Econo-

mists left no doubt as to his ranking of the causes. He suggested that

the level of agricultural production depends not so much on technical con-

siderations, but in large measure "on what governments do to agriculture." 1/

That governments intervene in the agricultural price setting

mechanism in many different ways and for assorted reasons is so obvious

as to be pedestrian. Export taxes on agricultural products provide govern-

ment revenue and keep domestic prices low, product price supports in developed

countries maintain farm incomes and provide surpluses which in turn find their

way to developing country markets to further depress domestic farm prices,

and agricultural inputs are frequently either taxed or subsidized. Yet the

magnitude of these effects on agricultural output, income distribution

between producers and consumers, efficiency and on rural employment is

often not fully appreciated.

Government alteration of market incentives in agriculture can

be classified in three ways based on the output effects of the interven-

tion (after Schultz, 1978). First, there are economic policies which

are neutral with respect to the opportunity cost of agricultural production.

Second, there are cases where agricultural production is overvalued, and

finally, there are cases where agricultural production is undervalued.

There are few countries that meet the first classification and we do not

attempt to identify them here. Typically high income developed countries

fall into the second category. In this study, we examine Japan, West Germany,

France and Britain, countries where high levies are placed on grain imports,

where sugar, meat and dairy imports are highly restricted by quotas, and

where, in the case of Japan, rice is greatly overpriced. The immediate

consequence of these policies is that there is overproduction and under-

consumption of agricultural output. The third category is typically made

up of low-income developing national. Here, as examples, we examine the

pricing policies of Thailand, Egypt, Argentina and Pakistan, where export

taxes and price controls often undervalue agricultural output resulting

in underproduction. The food situation in many of these nations is such

that they cannot afford to forego such production opportunities. Finally,

we consider the case of Yugoslavia, sometimes classified as a developing

country and sometimes classified as a centrally planned economy.

This paper discusses government intervention in agricultural

price determination, drawing on welfare theory to quantify the economic

impacts on output, income distribution, efficiency and employment. The

general theme is that the agricultural policies pursued by developing

countries produce effects which are diametrically opposite to those pro-

duced by the policies of many developed countries, and that the policies

of both are costly in terms of global welfare. 2/ The paper begins with

a description of the theoretical model on which the analysis is based then

continues by detailing the data sources. The results are presented in

Section 4, followed by some concluding thoughts.

Method and Theoretical Basis

The results of the paper are derived using standard partial equi-

librium analysis in the Marshallian economic surplus framework. The method

is well known for both its usefulness and limitations. Details are not

presented here, but the reader is referred to Currie, et al for an excellent

review of the concept, to Bale and Greenshields for an application of the

method, and to Lutz and Scandizzo for a review of other studies. In this

paper the real and pecuniary effects of agricultural price distortions in

a small country case are analyzed using nominal protection coefficients to

measure the disparity between domestic prices and border prices. Typical causes of

price distortions are producer price supports, tariffs, quotas, export taxes,

input subsidies, etc. In each case, the distortion drives a wedge between

the domestic price and the world or "border" price. Domestic prices are

defined as the prices at farm and consumer levels, and border prices are

the existing "world" price at the same point in the marketing chain. Border

prices are used as the point of reference for the evaluation because they

represent the opportunity cost of the traded commodities. 3/ They are also

conveniently available as they are observed in the international market-

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place. Nominal protection coefficients (NPCs) prgvide a metric of the

disparity between domestic prices and international prices, and are defined

as:

NPC = 1 + -drPrPw

where Pd = domestic price, P = border price, and r = the official exchange

rate (Balassa). The basic analytic structure of the model is represented

by equations 1 through 7.

Net social loss in production, NSL . . . . . . (1)

=1/2 (Qw % Q) (Pw - P ) = 1/2 t n Vw p p s

Net social loss in conumption, NSL .. . . . . (2)

1/2 (C - C) (P -P p) 1/2 t n Ww c w c d

Welfare gain of producers, Gp . . . . . . (3)

= Q (P -P) - NSL

Welfare gain of consumer, G . . . . . . (4)

=C (P -P) -NSLw c c

Change in foreign exchange earnings, dF . . . . .(5)

-w (Qw - Q + C - Cw)

Change in government revenue, dG .. . . . (6)

= (NSL +NSLc) - Gp- Gc = -(1) - (2) - (3) - (4)

Change in rural employment, dL = dQ. L/Q . . . . (7)

where: Qw production at world prices, Q = production at domestic prices,

Pw = border prices, P = price faced by domestic producers, P = price faced

by domestic consumers, t , tp = proportion of tariff in domestic price at

the consumer (t c) or the producer (t p) level, n = elasticity of domestic

supply, nd = elasticity of domestic demand, V = value of production at Pp,

W = value of consumption at P c, C = consumption at world prices, C = con-

sumption at domestic prices and L/Q = labor/output coefficient.

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Data Sources

The FAO Production Yearbook is used as a source of production

levels, and imports and exports are obtained from the FAO Trade Yearbook.

Supply and demand elasticities are from Rojko et. al. with the exception

of those for rubber in Thailand that are from Behrman. Since elasticity

estimates differ widely from researcher to researcher, and because we wish

to demonstrate the sensitivity of the results to changes in elasticities,

the supply and demand elasticities presented in Table 1 are + 0.5 times

the point estimates given by Rojko et. al. and Behrman. Nominal protectior

coefficients for developing countries are based on coefficients from detailed

country case studies by Bertrand (Thailand), Cuddihy (Egypt), Gotsch and

Brown (Pakistan), Reca (Argentina), and ULG Consultants Limited (Yugoslavia).

Since some coefficients had only been estimated to 1975, adjustments were

made to obtain the nominal protection coefficients that were used in this study.

The nominal protection coefficients for developed countries were

calculated from the International Wheat Council, International Sugar

Organization, U.S. Department of Agriculture, 1979, and the World Bank, 1978a.

Note that despite the Common Agricultural Policy of the EC, NPC's of members

are not identical. This is due to the "Monetary Compensatory Amounts" (MCAs)

and "green" currencies where internal EC exchange rates in agriculture differ

from official exchange rates.

Labor/Output Coefficients are constructed from Bartsch, Palacpac,

International Cotton Advisory Committee, U.S. Department of Agriculture, 1978a,,b,

U.K. Ministry of Agriculture, Forestry and Fisheries, European Communities

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Commission, and the World Bank, 1978b. In the case of developing countries,

marginal labor/output coefficients are derived from a labor-

intensive technology such as hand-harvesting with a bullock-drawn cart

and hand threshing. Average coefficients are simply the average of coefficients

taken from two or three different production techniques on irrigated and

non-irrigated farms. In developed countries, only average coefficients

are available. Marginal coefficients are arbitrarily calculated as 1.5

average coefficients. The conversion rates of man-hours to full-time

worker equivalents, in hours per year, are: France, 1964; West Germany, 2315;

United Kingdom, 2269; Japan, 2450; Yugoslavia, 2450; and developing countries,

2980.

Results

A. Production, Consumption and Trade Effects

Agricultural pricing policies in developed and developing countries

show significant differences. While agricultural commodity prices in developed

countries generally have positive rates of protection, the agricultural sector

in developing countries is being taxed through price intervention measures.

As a result, the levels of agricultural production in industrialized nations

are higher than without intervention whereas agricultural output in less

developed countries are significantly smaller than what it would be in the

absence of distortions. In the high elasticity case, for example, France

and Germany are producing an increment of 4.3 and 2.8 million tons of wheat

respectively due to the price protection, whereas the production in Argentina

and Pakistan is discouraged with a resulting estimated decrease of 7.0 and

1.3 million tons, respectively (Table 2).

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On the other hand with consumption the picture is reversed;

developing countries consume more and developed'countries less than they

would in the absence of price intervention measures. Thus the pricing

policies clearly have a beneficial effect in providing more food for the

malnourished non-agricultural population in LDCs. If this is one of the

policy objectives of price intervention, it is achieved at the expense of

the agricultural sector.

Trade effects are merely the combination of production and

consumption effects. For the general case we find that through the pricing

policies, exports of developing countries are reduced (for exported

commodities with NPC's smaller than 1) and that for the industrialized

nations their imports are curtailed (for imported commodities with NPC's

larger than 1). In the case of imports of developing countries with NPC's

of less than 1, imports are increased by the sum of the absolute values of

the production and consumption effects. This case implies government sub-

sidies; for example for wheat and maize in Egypt. 4/ On the other hand,

export commodities with NPC's larger than 1 imply that dumping is taking

place with export subsidies necessary to bridge the gap between the internal

price and world market price. All five commodities analyzed for France

are examples of this policy.

On the basis of a small sample of countries, it is difficult to

determine what the aggregate effects of the agricultural policies are at

the world market-level. Even for a standard case where developing countries

are exporters using export taxes and where developed countries are importers

with positive rates of protection, the sign of the price impact on the world

market cannot be determined a priori since both net exports adid net imports

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are being reduced simultaneously. Hence, it would be necessary to analyze

the policies of all trading countries of a particular commodity before the

world market price impact could be estimated.

B. Employment/Migration Effects

The process of economic development is typically associated

with internal migration from the primary sector in rural areas, to industrial

and service sectors in urban centers (Kuznets, p. 48). Economic theories

of internal human migration conceive the process as a response to differences

in employment opportunities between regions where potential migrants evaluate

costs and benefits associated with relocation and make their decision

accordingly. A primary determinant in such a decision is the relative income

opportunities in rural versus urban locations (Sjaastad, Falario). In spite

of (or because of) 5/ massive development efforts over the last decade, rural

poverty persists in many parts of the world and recent work has demonstrated

that low real income levels of farm households have in some cases declined

(Rajaraman), while various price-support measures to maintain farm incomes

are prevelant in other parts of the world. A common explanation for

rural poverty is that agricultural productivity is low because of tenancy

arrangements and limited access to modern inputs such as controlled irrigation,

chemical fertilizers, pesticides, mechanization, new varieties, credit,

extension services, etc. (Mellor). Yet such explanations avoid the issue of

the effect that product prices have on agricultural productivity and therefore

on employment and migration. Here we attempt to quantify the extent to which

product prices that are undervalued contribute to a sub-optimal rural pop-

ulation and the extent to which product prices that are overvalued contribute

to a larger-than-optimal rural population.

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We present four estimates of the agricultural employment impacts

of price distortions in Table 2. Two are based on average labor/output

coefficients using production changes calculated from high and low supply

elasticity estimates. The other two employment changes are calculated using

marginal labor/output coefficients where production changes are based on

high and low supply elasticities. There are three reasons for presenting

the results in this manner. First, we wish to demonstrate the sensitivity

of the employment effects to changes in assumptions. Second, labor coefficients

tend to be rather gross estimates from numerous secondary sources using

different assumptions and typically vary by more than 100 percent within

developing countries for different production techniques of the same crop.

Our results may be regarded as capturing the upper and lower bounds of employ-

ment changes. Third, it can be argued that under a regime of distorted prices,

the marginal operators will be displaced or expanded in response to price

changes. Thus, marginal labor/output coefficients are more appropriate in

estimating agricultural employment impacts.

Referring to the developed countries in Table 2, we see that

existing agricultural pricing policies retain significant numbers of workers

in agriculture. Japanese rice pricing policies are particularly significant,

retaining from between one half of a million workers (low supply elasticity,

average coefficient) to 2 million workers (high supply elasticity, marginal

coefficient). As a proportion of farm population, these numbers are large

(2.1 to 9.6%), and even expressed as a proportion of total population (0.4 to

1.9%) the numbers are significant. In the European countries presented here,

workers retained in agriculture are somewhat smaller both absolutely and relatively.

For example, in France, if free market prices prevailed for the five

- 10 -

commodities, between 52,987 and 241,200 workers in an agricultural labor

force of 8.6 million would be displaced. 6/ In terms of absorption into

the total work force, the numbers amount to 0.16 to 0.75%. While this may seem

to be a rather small percentage it is, nonetheless, significant. In a period

of high general unemployment even one or two points change in the unemployment

rate can involve heavy social and political costs.

In developing countries, agricultural price distortions have

the effect of reducing farm employment from that which would exist under

free market prices. In general, the absolute value of the employment effects

are larger for developing countries than for developed countries, partly

because of the labor-intensive production methods used in developing countries.

The numbers suggest the extent to which price distortions create unemployment

and stimulate migration. Using the high supply elasticity and marginal labor

coefficients in Egypt, for example, the total reduction in agricultural employment

for the four commodities is 1.15 million workers or around five percent of

the rural population. Employment in rice production accounts for a large por-

tion of this. No doubt the numbers would be considerably larger if secondary

(multiplier) effects were considered and if all commodities were covered.

Unemployment and rates of rural to urban migration that exceed

rates of urban job creation are serious problems in developing countries.

While overt unemployment is pronounced in urban centers, disguised

unemployment is prevalent in rural areas (Todaro, Wonnacott). Thus,

any policies that contribute to the problem, such as agricultural product

pricing policies, need to be carefully examined. The conventional lay

wisdom that if farm product prices were to increase in developing countries

poor people would be hurt needs to be scrutinized. Many of the poor are

rural poor or former-rural residents who have migrated to urban areas in

search of better employment opportunities. Higher agricultural prices

could only assist them as farmers, landless laborers, or farm-related

workers. Viewed in a longer run dynamic context, as farmers and farm

laborers realize higher incomes their demand for urban-produced goods

and services will increase, so stimulating employment in urban areas. 7/

C. Welfare Effects

Our results indicate that the economies of the countries analyzed

incur large annual welfare losses due to a misallocation of resources

resulting from the existing agricultural pricing policies (Table 3). The

losses depend linearly on the assumed elasticities and quadratically on

the size of the price distortion as measured by a proportional tariff rate.

Total net social losses are the sum of net social losses in production and

in consumption. They range from $26 million (US) for the United Kingdom

(the low elasticity assumption) to $4,119 million for Japan (the high elasticity

case). Even though the sample of commodities used in this analysis is

small, it is interesting to compare the estimated welfare losses to the GNP

of the countries. The results show that compared to economic output,

distortions are generally more costly in developing countries than in

industrialized nations (Table 4). 8/ Further, the results are obtained from

a partial equilibrium model. Using a general equilibrium analysis that

takes long-run consequences of the price distortions into account, the

estimated social costs would typically be considerably larger.

As our results in Table 5 indicate, the most sizeable effects

of the different agricultural policies are the welfare transfers between

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consumers and producers. While the farm sector of the developing countries

studied was taxed from about $700 million to about $2 billion annually,

the producers in developed countries receive large transfers due to

protection. In Japan, where the average rate of protection is the highest,

farmers gain between $2.6 and $5.1 billion for the total of the five major

commodities analyzed. 9/ Consumers in the developed countries incur

large welfare losses due to price protection whereas the consumers in

developing countries generally gain from this type of price intervention.

With the exception of France , all countries acquire increased

government revenues from their interventionist policies. Thus, the fact

that most governments gain from price distortions confirms that government

revenue generation is an objective of price intervention.

The effects on foreign exchange earnings are again clearly

divided along different levels of development. While industrialized nations

gain foreign exchange through protectionist policies, developing countries

lose foreign exchange earnings. This is particularly serious in that foreign

exchange availabilities represent a major bottleneck for developing countries

in their efforts to increase growth and alleviate poverty.

Conclusions

What emerges from this paper is the vital role that farm product

prices play in achieving optimum output and productivity growth. Because

"incorrect" price signals are being given to farmers, allocative, production,

and consumption potentials are not being realized. In many cases, the estimated

changes in production greatly alter trade patterns, in some cases causing

importing countries to become self-sufficient, and in other cases causing

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"would-be exporters" to become importers. The magnitude of income transfers

and efficiency losses (net social losses) is also impressive, both as an

absolute number and as a proportion of national income. The rural employment

effects of price distortions, while perhaps less impressive than the welfare

losses, are nonetheless serious, given the high unemployment rates in

developing countries and the political sensitivity of agricultural

employment in developed countries.

The ultimate question about agricultural pricing policies is their

dynamic effects. Here we have seen the size of the static effects but our

model (and the state of technology of our profession) does not allow us to

estimate accurately price distorting effects on income and industrial growth,

adoption of technology, investment in agriculture, social consequences, etc.

While decision-making at the public level is not by agricultural economists,

but by politicians, our profession plays a vital role in defining and

quantifying the issues involved, and in extending these findings to appropriate

officials. Our hope is that this paper is in that tradition.

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Footnotes

1/ Schultz has long been the most ardent and eloquent spokesman of this

position. See, for example, Schultz 1964, 1976 and 1978.

2/ A recent study which addresses the developing country side of this

question in a somewhat different manner is Peterson.

3/ We recognize that the general equilibrium effects of removing price

distortions on a global basis would alter border prices and therefore

alter the magnitude of the distorting effects. However, it is extremely

difficult to estimate "shadow free market prices" in a first-best

world, and we do not suppose that we will ever be operating in a

first- or even second-best environment.

4/ Parts of the imports may not be subsidized directly by the government

of Egypt but may be the result of shipments at concessionary terms.

5/ ".... the most promising attack on employment problems in developing

countries is in efforts to redress the present urban bias in development:

strategies" (Edwards).

6/ We do not wish to render the labor estimates useless by presenting

numbers which have such a large variance, but we do want to present

realistic upper and lower bounds. We invite the interested reader to

select his "most-likely" elasticity and labor/output estimates and

thereby generate a deterministic labor number.

7/ We are indebted to Willis Peterson for suggesting this point.

8/ The distortions may or may not be a larger proportion of the agricultural

sector in developing countries than in developed countries. Figures on

gross agricultural product could not be obtained.

9/ c.f. Bale, who estimates the producer gain to farmers for these products,

except sugar, as $5.29 billion in 1975/76.

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'able 1: BASIC DATA USED FOR T11E ANiAlrSIS, 1976

Country Border Range of Supply Range of DemandPrice NPC la Elasticities Elasticities Production Consumption Exports Labor Caefficieats

Commwdity US$/mt low high low high Average Marginal

------- '000 metric tons-- -- (man-hours per ton)FRANCE

Wh4eat 143 1.26 .42 1.28 .10 .30 16,150 7,785 8,365 25 37.5Maize 152 1.31 .17 .52 .20 .60 5,603 4,486 1,117 37 55.5Barley 137 1.39 .42 1.28 .10 .30 8,530 5,637 2,893 25 37.5Sugar 289 1.35 .81 2.44 .12 .36 2,974 1,957 1,017 52 78.0Beef 2,365 1.27 .20 .60 .35 1.05 1,821 1,706 115 40 60.0

GERMWNYWheat 143 1.49 .42 1.28 .10 .30 6,702 7,252 -550 25 37.5Maize 150. 1.57 .17 .53 .20 .60 480 3,776 -3,296 37 55.5Barley 137 1.51 .42 1.28 .10 .30 6,487 7,973 -1,486 25 37.5Sugar 289 1.77 .43 1.30 .08 .24 2,733 2,584 149 52 78.0Beef 1,970 1.42 .20 .60 .35 1.05 1,365 1,435 -70 40 60.0

UNITED KINGDOMWhEat 156 1.15 .47 1.42 .10 .30 4,740 8,419 -3,679 25 37.5Maize 131 1.28 .45 1.35 .20 .60 2 3,720 -3,718 37 55.5Balley 132 1.01 .47 1.42 .10 .30 7,648 8,096 -448 25 37.5SuEar 283 1.39 .22 .66 .10 .30 746 2,558 -1,812 52 78.0Beef 1,542 1.17 .20 .60 .35 1.05 1,064 1,177 -113 40 60.0

JAPAt'WhEat fb 189 2.81 .BO 2.41 .08 .24 222 6,043 -5,821 54 81.0Baleyl7b 160 3.14 .80 2.41 .08 .24 210 1,971 -1,761 54 81.0Suj,ar 306 1.36 .21 .64 .11 .33 560 2,986 -2,426 110 165.0Beef 2,252 1.30 .33 .99 .40 1.20 298 390 -92 58 87.0Ric'e 380 2.03 .08 .24 .06 .18 15,292 .15,314 -22 185 277.5

YUGOSLAVIAWhc at 177 .54 .28 .75 .12 .37 5,979 5,118 861 25 37.5Ma: ze 185 .71 .24 .72 .17 .52 9,106 8,647 459 37 55.5Beitf 1,832 1.08 .20 .60 .40 1.20 326 266 60 40 60.0

ARGEnITINAWh4!at 136 .54 .25 .75 .05 .15 11,000 7,736 3,264 25 50.0Rice 194 .81 .27 .82 .10 .30 309 222 87 78 156.0MaFze 118 .49 .22 .67 .11 .33 5,855 2,775 3,080 55 110.0Be!f 927 .72 .25 .75 .20 .60 2,811 2,410 401 18 36.0

EGYP CWh,!at 166 .48 .12 .37 .17 .52 1,960 4,878 -2,918 220 508.0Rice 375 .35 .25 .75 .12 .37 2,300 2,089 211 360 520.6MaLze 171 .52 .16 .18 .12 .37 3,047 3,506 -459 240 480.0Co:t0n 2,397 .34 .05 .15 .10 .30 396 231 165 8,440 10,000.0

PAKI 3TANWh at 152 .78 .17 .53 .20 .60 8,691 9,877 -1,186 247 533.0

Ri2e 320 .57 .15 .45 .15 .45 4,106 3,324 782 290 350.0MaLze 171 .94 .10 .30 .17 .52 764 764 0 300 480.0Co:ton 876 .58 .82 2.47 .10 .30 418 305 113 2,240 3,950.0

,HAI .ANDRi:e 218 .74 .07 .22 .03 .07 15,068 13,143 1,925 400 580.0

Maize 115 1.02 .10 .30 .05 .15 2,675 287 2,388 240 480.0Su;ar 298 1.65 .08 .24 .15 .45 1,757 633 1,124 338 507.0Ru3ber 695 .49 .09 .28 .00 .02 400 27 373 54 81.0

/a Nominal Protection Coefficient.

/b rhese coefficients represent distortions in production only; the corresponding NPCs in consumption are 1.18 for wheat and .90

for barley.

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Table 2: REAL EFFECTS OF PRICE DISTORTIONS, 1976

Country Estimated Change Estimated Change Estimated Change Estimated Change in Agricultural Employmentin Production in Consumption in Exports (average coefficients) (marginal coefficients)

Commodity low high low' high low high low high low high

… _ 000-------------- n oo metric tons--------------------- ------------- full time workers---------------FRAN(E

Wheat 1,400 4,266 -161 -482 1,560 4,748 17,821 54,302 26,731 81,454Maize 225 689 -212 -637 438 1,326 4,239 12,980 6,358 19,470Baiiley 1,005 3,063 -158 -474 1,163 3,538 12,793 38,989 19,189 58,484Suj.ar 625 1,881 -61 -183 685 2,064 16,548 49,802 24,822 74,704Becf 77 232 -127 -381 204 613 1,568 4,725 2,352 7,088

GERMJNY, F.R.Wliat 926 2,821 -238 -715 1,164 3,537 10,000 30,464 15,000 45,697Maize 30 92 -274 -823 304 915 479 1,470 719 2,206Bailey 920 2,804 -269 -808 1,189 3,612 9,935 30,281 14,903 45,421Sul,ar 511 1,546 -90 -270 601 1,815 11,478 34,727 17,217 52,090Belf 81 242 -149 -446 229 688 1,400 4,181 2,099 6,772

UNITID KINGDOMIWhvat 291 878 -110 -329 400 1,207 3,206 9,674 4,809 14,511Ma:.ze 0 1 -163 -488 163 489 0 16 0 24Ba::ley 36 108 -8 -24 44 132 397 1,190 595 1,785Su8ar 46 138 -72 -215 118 353 1.054 3,163 1,581 4,744Be,-f 31 93 -60 -180 91 272 546 1,639 820 2,459

JAP AlWha~at 114 345 -74 -221 188 566 2,513 7,604 3,769 11,406Barley 114 345 18 53 96 292 2,513 7,604 3,769 11,406Su,ar 31 95 -87 -261 118 356 1,392 4,265 2,088 6,396Beaf 23 68 -36 -108 59 17.6 544 1,610 817 2,415Ri e 6,207 18,622 -466 -1,399 7,606 20,020 468,692 1,406,151 703,038 2,109,227

YUGO3LAVIAWheat -1,273 -3,820 523 1,613 -1,796 -5,433 -12,990 -38,980 -19,485 -58,469Maize -893 -2,678 600 1,837 -1,493 -4,515 -13,486 -40,443 -20,229 -60,665Beef 5 14 -8 -24 13 38 82 229 122 343

ARGE iTINAWheat -2,343 -7,028 329 988 -2,672 -8,016 -19,525 -58,567 -39,050 -117,133Rice -20 -59 5 16 -25 -75 -520 -1,534 -1,040 -3,068

Maize -1,341 -4,083 318 953 -1,658 -5,036 -24,585 -74,855 -49,170 149,710Beef -273 -820 187 562 -461 -1,382 -1,638 -4,920 -3,276 -9,840

EGYPTWheat -255 -786 898 2,748 -1,153 -3,534 -18,700 -133,096 -43,180 -13:3,096Rice -1,068 -3,204 466 1,435 -1,533 -4,639 -128,160 -384,480 -185,120 -555,360MEize -450 -506 388 1,197 -838 -1,704 -36,000 -40,480 -72,000 -80,960Cctton -38 -115 45 135 -83 -250 -106,907 -323,533 -126,667 -383,333

PAKISTANWteat -417 -1,299 557 1,671 -974 -2,971 -34,333 -106,951 -74,087 -230,789Rice -465 -1,394 376 1,128 -841 -2,522 -44,950 -134,753 -54,250 -162,633MH.ize -5 -15 8 25 -1.3 -40 -500 -1,500 -800 -2,400Cotton -246 -748 22 66 -270 -814 -185,173 -558,507 -326,533 -984,867

THALLANDR:.ce -371 -1,165 139 323 -509 -1,488 -49,467 -155,333 -71,727 -225,233Mulize 5 16 0 -1 6 17 400 1,280 800 2,560Suigar 55 166 -37 -112 93 278 6,197 18,703 9,295 28,054Rutbber -37 -117 0 1 -37 -117 -666 -2,106 -999 -3,159

- 17 -

Table 3: NET SOCIAL LOSSES OF PRICE DISTORTIONS 1976

(in '000 US dollars)

Country Net Social LosE Net Social Loss Totalin Production in Consumption Net Social Loss

Conmodity low high low high low high

FRANCEWheat 26,020 79,298 2,986 8,959 29,006 88,258Maize 5,310 16,244 5,002 15,006 10,313 31,250

Barley 26,854 81,840 4,225 12,676 31,079 94,515Sugar 31,586 95,148 3,079 9,238 34,665 104,386

Beef 24,721 74,163 40,530 121,589 65,251 195,752TOTAL 113,491 346,693 55,822 167,468 160,314 514,161

GERMANY, F.R.Wheat 32,341 98,839 8,355 25,066 40,696 123,905

Maize 1,266 3,948 11,721 35,164 12,988 39,112

Barley 32,147 97,973 9,408 28,223 41,555 126,196

Sugar 56,883 171,973 10,006 30.018 66,889 201,990

Beef 33.405 100,214 61,456 184,369 94,861 284,583

TOTAL 156,042 472,947 100,946 302,840 256,989 775,786

UNITED KINGDOMWheat 3,400 10,272 1,285 3,854 4,685 14,126Maize 4 11 2,985 8,955 2,988 8,965

Barley 23 71 5 16 29 87

Sugar 2,541 7,623 3,961 11,882 6,502 19,506

Beef 4,053 12,158 7,845 23,536 11,898 35,694

TOTAL 10,021 30,135 16,081 48,243 26,102 78,378

JAPANWheat 19,567 58,946 1,254 3,763 20,821 62,709Barley 19,602 59,051 140 420 19,742 59,471Sugar 1,715 5,225 4,789 14,367 6,504 19,592

Beef 7,666 22,998 12,161 36,482 19,827 59,480

Rice 2,035,883 3,644,244 91,237 273,712 2,127,120 3,917,956

TOTAL 2,084,433 3,790,464 109,581 328,744 2,194,014 4,119,208

YUGOSLAVIAWheat 51,836 155,509 21,298 65,670 73,135 221,179Maize 23,945 71,836 16,106 49,266 40,051 121,102

Beef 354 1,062 578 1,733 931 2,794

TOTAL 76,135 228,407 37,982 116,669 114,117 345,075

ARGENTINAWheat 73,276 219,829 10,307 30,920 83,583 250,749

Rice 361 1,095 96 288 457 1,383

Maize 40,341 122,856 9,560 28,680 49,901 151,536Beef 35,468 106,403 24,327 72,980 59,794 179,383

TOTAL 149,446 450,183 44,290 132,868 193,735 583,051

EGYPTWheat 10,997 33,908 38,773 118,601 49,771 152,509

Rice 130,145 390,435 56,739 174,944 186,884 565,380

Maize 18,469 20,777 15,938 49,143 34,407 69,920

Cotton 30,403 91,208 35,470 106,409 65,873 197,618

TOTAL 190,014 536,328 146,920 449,097 336,935 985,427

PAKISTANWheat 6,968 21,723 9,316 27,947 16,283 49,670

Rice 31,966 95,899 25,878 77,635 57,845 173,534Maize 25 75 43 130 68 205

Cotton 45,660 137,536 4,063 12,189 49,723 149,725

TOTAL 84,619 255,233 39,300 117,901 123,919 373,134

THAILANDRice 10,503 33,008 3,926 9,161 14,429 42,169Maize 6 18 0 1 6 19Sugar 5,363 16,088 3,623 10,868 8,985 26,956

Rubber 6,641 20,659 0 100 6,641 20,759

TOTAL 22,513 69,773 7,549 20,130 30,061 89,903

- 18 -

Table 4: ESTIMATED TOTAL NET SOCIAL LOSSES AS A PERCENT

OF GNP FOR SELECTED COMMODITIES

Social Losses in % of GNPLow High

France 0.05 0.16

Germany 0.06 0.19

United Kingdom 0.01 0.04

Japan 0.43 0.80

Yugoslavia 0.34 1.03

Argentina 0.48 1.46

Egypt 3.62 10.58

Pakistan 1.01 3.04

Thailand 0.21 0.62

- 19 -

Table 5: MONETARY EFFECTS OF PRICE DISTORTIONS 1976

(in '000 US dollars)

Country Welfare Gain of Welfare Gain of. Change in Change in Foreigr.Producers /a Consumers la Government Exchange Earnings /a

Commodity low high low high Revenue low high

FRANCEWheat 574,437 521,159 - 292,433 - 298,405 - 311,011 223,124 678,904Maize 258,703 247,769 - 216,382 - 226,387 - 52,633 66,533 201,615Barley 428,904 373,918 - 305,410 - 313,861 - 154,573 159,379 484,695Sugar 269,234 205,672 - 201,030 - 207,188 - 102,870 198,088 596,491Beef 1,138,079 1,088,637 -1,129,896 -1,210,955 - 73,433 483,337 1,450,011TOTAL 2,669,357 2,437,155 -2,145,151 -2,256,796 - 694,520 1,130,461 3,411,716

GERMANYWheat 437,178 370,771 - 516,503 - 533,214 38,539 166,477 505,734Maize 39,774 37,092 - 334,569 - 358,012 281,808 45,571 137,236Barley 421,099 355,273 - 566,481 - 585,296 103,827 162,961 494,886Sugar 551,291 436,202 - 585,023 - 605,035 - 33,157 173,738 524,650Beef 1,095,996 1,029,187 -1,248,775 -1,371,688 57,918 451,720 1,355,159TOTAL 2,545,338 2,228,525 -3,251,351 -3,453,245 448,935 1,000,467 3,017,665

UNITED KINGDOMWhleat 107,516 100,644 - 198,289 - 200,859 86,089 62,462 188,350Maize 70 63 - 139,434 - 145,404 136,376 21,346 64,038Barley 10,072 10,024 - 10,692 - 10,703 591 5,756 17,368Sugar 79,795 74,713 - 286,287 - 294,209 199,990 33,343 100,029Beef 274,864 266,759 316,384 - 332,075 29,622 139,976 419,928TOTAL 472,317 452,203 - 951,086 - 983,250 452,668 262,883 789,713

JAPANWheat 56,377 16,998 - 206,837 - 209,346 129,639 35,532 106,974Barley 52,302 12,853 31,396 31,116 - 103,440 15,360 46,720Sugar 59,975 56,464 - 333,727 - 343,305 267,248 36,131 108,846Beef 193,663 178,331 - 275,645 - 299,966 62,155 132,179 396,536Rice 4,770,541 2,341,044 -6,085,137 -6,267,611 8,611 2,535,894 7,607,682TOTAL 5,132,858 2,605,690 -6,869,950 -7,089,112 364,213 2,755,096 8,266,758

YUGOSLAVIAWheat - 538,646 - 642,319 395,409 351,038 70,103 - 317,977 - 961,647Maize - 512,482 - 560,372 447,805 414,645 24,625 - 276,217 - 835,184Beef 47,425 46,717 - 39,563 - 40,718 - 8,794 23,287 69,860TOTAL -1,003,703 -1,155,974 803,651 724,965 85,934 - 570,907 -1,726,971

ARGENTINAWheat - 761,436 - 907,989 473,658 453,044 204,196 - 363,404 -1,090,212Rice - 11,750 - 12,845 8,087 7,895 3,207 - 4,807 - 14,561Maize - 392,695 - 475,210 157,440 138,320 185,354 - 195,689 - 594,259Beef - 765,091 - 836,027 601,213 552,560 104,084 - 427,102 -1,281,307TOTAL -1,930,972 -2,232,071 1,240,398 1,151,819 496,841 - 991,002 -2,980,339

EGYPTWheat - 180,184 - 203,095 382,296 302,468 - 251,882 - 191,425 - 586,573Rice - 690,770 - 951,060 452,455 334,249 51,431 - 575,027 -1,739,630Maize - 268,567 - 270,875 271,834 238,630 - 37,675 - 143,362 - 291,333Cotton - 656,883 - 717,688 329,977 259,037 261,033 - 199,614 - 598,841TOTAL -1,796,404 -2,142,718 1,436,562 1,134,384 22,907 1,109,428 -3,216,377

PAKISTANWheat - 297,595 - 312,350 320,971 302,340 -39,660 - 148,031 - 451,544Rice - 596,952 - 660,884 431,504 379,748 107,603 - 269,044 - 807,133Maize - 7,864 - 7,914 7,796 7,709 0 - 2,252 - 6,838Cotton - 199,450 - 291,327 108,153 100,027 41,575 - 236,776 - 712,978TOTAL -1,101,861 -1,272,475 868,424 789,824 109,518 - 895,665 -1,978,493

THAILANDRice - 864,557 - 887,062 741,019 735,784 109,109 - 110,989 - 324,376Maize 6,146 6,134 - 660 - 661 5,492 636 1,907Sugar 334,968 324,243 - 126,235 - 133,480 - 217,719 27,647 82,942Rubber - 148,421 - 162,439 9,570 9,471 132,210 - 26,041 - 81,408TOTAL - 671,864 - 719,124 623,694 611,114 18,108 - 108,747 - 320,935

/a The "low and "high" refer to the low and high elasticity assumption and do not necessarilycorrespond to the lows or highs of the respective monetary effects.

- 20 -

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