Download The Transfer Efficiency and Trade Effects of

The Transfer Efficiency and Trade
Effects of Direct Payments
Joe Dewbre, Jesús Antón, and Wyatt Thompson
All the different ways governments use to
provide financial support to farmers can
potentially distort trade and reduce net economic welfare. However, there are some
types of support that are less trade distorting and more efficient than others. This article reports the results of an analysis that
examined different policy measures providing support to crop producers to rank them
in terms of their effects on a selection of indicators, with a particular focus on trade distortion and income transfer efficiency.1 We
begin with an analysis of the differences in
policy impacts among the three main categories of support provided to crop producers in OECD countries: market price support,
payments based on land use, and payments
based on use of purchased inputs (OECD
2001c). That analysis is based on a two-region
model of equilibrium in the world market
for a representative crop. Analytical solutions
to this model are developed to compare the
production, trade, and income effects of the
different support measures. Following procedures used in Cahill and in Moro and
Sckokai, comparisons are of “impact ratios”
using market price support as the reference
category. These ratios measure the effect on
production, trade or farm income of a given
Joe Dewbre, Jesús Antón, and Wyatt Thompson are economists
in the Agricultural Directorate of the Organization for Economic
Cooperation and Development, where the underlying analysis
was undertaken. The views expressed are our own and not necessarily those of the OECD Secretariat or its Member countries.
We thank our Secretariat colleagues Ken Ash, Carmel Cahill,
Wilfrid Legg, and Michèle Patterson for helpful comments on an
earlier draft and Stèphane Guillot for computer programming
assistance.
This article was presented in a principal paper session at the
AAEA annual meeting (Chicago, IL, August 2001). The articles
in these sessions are not subjected to the Journal’s standard refereeing process.
1
Transfer efficiency is usually defined as the ratio of income
gain of the targeted beneficiaries, assumed to be farm households
in this article, and the sum of the associated government expenditures and consumer costs (OECD 1995). The gain in farm household income is the sum of gains in quasi-rents earned by farm
households in supplying factors they own—mainly land and farm
household labour. We use a closely related definition of transfer
efficiency—the ratio of the gain in farm household income to the
monetary value of consumer and taxpayer transfers to support
farmers.
change in support provided by any one of the
three categories of direct payments, relative
to the estimated impact on production, trade
or farm income of the same monetary change
in market price support.2 We then turn to
a policy simulation analysis with an empirical version of the model using data from
two base years—1987 and 1998—and parameter estimates derived mainly from reviews of
published studies.
The crucial distinction among the support
measures studied is initial price incidence.
Measures providing market price support
have their first incidence on both the price
producers receive and the price consumers
pay. Direct payments based on output (e.g.,
deficiency payments) initially impact only the
producer price of that crop, whereas those
based on use of purchased inputs or on the
land area have their initial incidence on the
prices in the associated factor markets.
Analytical Results
The framework for the model developed is
that of the farm sector elaborated in Gardner
and in Hertel. Our version and application closely follow that developed in Gunter,
Jeong, and White. Table 1 defines the variables and main equations of the model.
Most of the variables are measured in
terms of rates of change, conveniently yielding equations that are linear in the logarithms
of the variables. The four equilibrium equations presented in table 1 constitute a compact representation of the entire model.
The four endogenous variables are percent
changes in world quantity (produced and
consumed), world market price, the market
rental rate for land, and the market price
of an aggregated nonland factor. The four
2
The article focuses exclusively on the effects of support measures produced through their incidence on relative prices. Other
possible channels of incidence, risk, and wealth effects, for example, are ignored (OECD 2001b and Hennessey).
Amer. J. Agr. Econ. 83 (Number 5, 2001): 1204–1214
Copyright 2001 American Agricultural Economics Association
Dewbre, Antón, and Thompson
Transfer Efficiency and Trade Effects of Direct Payments
1205
Table 1. Representative Country Module of PEM Crop Model (one output and two inputs):
Definitions and Equations
Price and quantities:
qd , qs
pd , ps , pw
xjd , xjs
rjd , rjs
qrd , qrs
Qd , Qs , Qrd , Qrs
Policy variable symbol:
m
o
a
s
M O A S
First incidence of policy:
pd = pw + m
ps = pd + o
rfs = rfd + a
rps = rpd + s
Parameter symbol:
d
kj
d , s
j
Structural equations:
q d = d p d
xjd = −ki rjd + ki rid + q s
xjs = ej rjs
qrd = d pw ; qrs = s pw
Equilibrium
equations:
ps = j=f p kj rjd
xjs = xjd
Qs q s − Qd q d = Qrd qrd − Qrs qrs
Stands for:
Percentage change in crop demand and supply quantities
Percentage change in domestic demand and supply prices and
in world price of crops
Percentage change in input demand and supply quantities, j = f p,
for farm owned and purchased inputs
Percentage change in input demand and supply prices
Percentage changes in crop demand and supply quantities in the
rest of the world
Levels of domestic crops demand and supply and level of demand
and supply in the rest of the world, in the initial equilibrium
Stands for:
Percentage change in rate of Market price support
Percentage change in rate of Output price support
Percentage change in rate of Area payment
Percentage change in rate of Subsidy to purchased inputs
Initial level in the rates of the four kinds of support, all assumed to
be nonnegative
Price gap between:
Crop demand price and world price
Crop supply and demand prices
Farm owned input (land) supply and demand prices
Purchased input supply and demand prices
Stands for:
Elasticity of demand for the crop in the domestic country assumed
negative
Cost share of input j used in producing the crop, with j = f p
Elasticity of substitution between factor f and p, assumed to be
positive
Elasticity of demand and supply for the crop in the rest of the world
Elasticity of supply of input j = f p , assumed to be positive
Explanation
Domestic consumption demands for i = 1 to 4 crops
Input demands for j i = f p and i = j
Input supplies for j = f p
Consumption demand and production supply in the rest of the world
Economic meaning
Zero profit conditions (crop supply price equals unit average cost of
production)
Input market clearing for j = f p
World market equilibrium
exogenous variables are the percentage rates
of market price support, output payments,
area payments, and input subsidies (payments based on nonland factor use). Solving this system of equations would yield algebraic expressions that show the relationships
between each of the solving variables and the
various support rates. However, our purpose
is to compare the effects of equal changes,
not in the rate, but in the level of support provided by the different measures. We do this in
four steps, always starting with the basic fourequation system described above but adding
at each step a fifth equation to make one or
the other of the rates of support endogenous
and making the level change in the amount of
that kind of support exogenous. These four
models are then solved one by one to obtain
the algebraic expressions showing the relationships of interest—the changes in production, trade, and farm household income as
functions of postulated changes in the levels
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Number 5, 2001
of the various support measures. Finally, we
show the ratios of the market effects (production, trade, and farm income) of output
support, area payments, and input subsidies
as compared to the corresponding market
impacts resulting from market price support.
Results are presented in the left-hand side
of tables A1, A2, and A3. Table A1 contains production impact ratios, table A2, the
trade impact ratios, and table A3, the farm
income impact ratios. The ranges of theoretically possible values that the associated
ratios can take on are indicated under each
formula. The theoretical production impact
ratios, applying equally to all three categories of direct payments, are unambiguously
greater than zero, irrespective of the initial
conditions. That is to say, all the different
kinds of direct payments would be expected
to have some impact on production. Regardless of the category of support, the marginal
impact on production is smaller the larger
the initial rate of support applying to that
category. If we start with a large rate of
support, then a part of any increase in that
rate is spent paying that preexisting rate on
all new resources brought into production.
A consequence of this diminishing marginal
impact is that the ratio comparing the effects
of any form of support to market price support has, in principle, no upper bound—the
denominator can take on values increasingly
close to zero. Thus, irrespective of the type
of direct payments, the larger the initial rates
of market price support, the larger the ratio
becomes. The third column of table A1 contains the formulas for production ratios for
the case of zero rates of initial support. Even
when initial rates of support are zero, we
still cannot put a finite upper bound on,
and therefore cannot rank, the production
impact ratios for any one of the categories of
payments. In theory, these ratios could also
become very large if the quantity response of
domestic demand to a world price change is
large compared to the quantity response to
that change in the rest of the world. However, note that, a theoretical lower bound
greater than zero exists for the case of zero
initial support. This same lower bound for all
categories of payments is obtained under the
“small-country” assumption3 as shown in the
fourth column in table A1. Moreover, in this
3
We define a small country as one for which, in response to
a 1% change in world price, the ratio of the quantity change in
its excess supply to the quantity change in rest-of-world’s excess
demand approaches zero.
Amer. J. Agr. Econ.
special case, and only in this case, the production ratios for all three types of direct payments depend just on the parameters determining domestic supply. Payments based on
output have exactly the same impact on production as market price support, in other
words, an impact ratio equal to one. Conversely, payments based on either of the two
categories of inputs (land and nonland) will
have a production ratio that is, in general,
different from one. It can be proven that the
production effects of payments based on a
category of input use will be less than the
production effects of market price support if
the targeted input is the one with the lower
elasticity of supply; on the contrary, the production ratio will be larger than 1 for the
other input. In this special case, if the elasticity of supply of land is smaller than the
elasticity of the nonland inputs, then the payments based on area will have a smaller
impact on production than market price support.
Numerically, as shown in table A2, trade
ratios will always be either equal or smaller
than the corresponding production ratios.
Market price support increases producer and
consumer prices, simultaneously increasing
both supply and reducing demand. Payments
directly affect only the supply part of the
trade equation. If they affect the demand part
of that equation at all, then it is through feedback effects of induced supply increases on
world market prices, an effect in the opposite direction to that of market price support.
Accordingly, the trade ratio will be smaller
than the production ratio the larger is the
size of the country and the more responsive is domestic demand. In the extreme case
in which domestic demand or its elasticity
is zero, trade ratios are equal to production ratios. For the same reason that we cannot put a finite upper bound on the production ratios for the general case (column 2,
table A1), we also cannot put a finite upper
bound on the trade ratios for this case (column 2, table A2). Conversely, we can do
so both for the case of zero initial support
and for the case that combines zero initial
support and the small country assumption.
Indeed, the trade ratios are identical for the
two cases (i.e., size of country does not matter). If initial support levels are zero, then
the trade effects of payments based on output
are unambiguously less than those of market price support. Likewise, the trade effects
of payments based on area are smaller than
Dewbre, Antón, and Thompson
Transfer Efficiency and Trade Effects of Direct Payments
those of payments based on output under the
assumption that the elasticity of land supply is smaller than that for nonland inputs.
Symmetrically, the trade effects of payments
based on nonland factor use are greater than
the trade effects of area payments and those
of market price support.
To measure the farm income ratios, we
assumed that the only farm owned factor
is land. Moreover, estimated farm income
ratios of the various support measures
were calculated using first-order (linear)
approximations to the induced change in
quasirents earned by landowners. Note that,
mathematically, ratios of the second-order
approximations of farm income effects of
the various direct payments to those of market price support will be smaller, equal, or
larger than one only if the corresponding
ratios of first-order approximations are also
smaller, equal, or larger than one. In other
words, for the purpose of ordering the farm
income impacts of two kinds of payments, the
second-order approximation will serve just
as well as the first-order approximation. The
expressions for these ratios are presented in
table A3.
The farm income impacts of changes in
support measures also exhibit decreasing
marginal impact, yielding a range of theoretically possible ratios between zero and infinity for the general case. Indeed, the farm
income ratio for payments based on purchased inputs can, if the elasticity of substitution between land and nonland factors is
high enough, become negative. The third column in table A3 contains results for the case
of zero initial support. Under this assumption the payments based on area have the
largest impact on farm income, followed by
output support and market price support. In
addition, for the small country case, the farm
income impacts of payments based on purchased inputs are smaller (making the transfer less efficient) than those of payments
based on output.
Taken together, results from this section of
the article lead to a ranking of production,
trade and farm income effects of direct payments relative to market price support that
is definitive for all indicators for only one
special case. It requires four assumptions: (1)
zero initial support, (2) a small country, (3)
an elasticity of substitution between land and
nonland factors of production that is greater
than zero, and (4) an elasticity of land supply
that is less than that of the nonland factors
1207
of production. In this case, the production
effects of market price support and output
payments are equal, but greater than those
of payments based on area and less than
those of nonland input subsidies. The ranking of trade effects under the assumptions is
exactly the same as that of production effects
with one exception: the trade effects of output price support will generally always be less
that those of market price support. Meanwhile, the ranking of farm income effects is
just the reverse of that applying to production effects (i.e., payments based on land use
are the most efficient, followed by payments
based on output, market price support, and
then payments based on nonland factor use).
The ranking of support measures for the
more general cases of a large country or some
initial support or both could be different for
different initial conditions and parameter values; empirical questions we address in the following section.
Empirical Results
The policy simulation model of the world
market for crops employed in this analysis
is called the policy evaluation matrix (PEM)
model, used to support ongoing monitoring
and evaluation of Member country agricultural policies using the PSE (OECD 2001a).
It comprises of six individual country modules: Canada, the European Union (treated
as one country), Mexico, Switzerland, and the
United States, and one for the rest of the
world. The basic equation structure of each
of the country modules is shown in table 1.
In the rest-of-world module, crop demand is
modeled in the same way as in the individual country modules but crop supply is represented using simple aggregate supply equations.
There are four crops: wheat, rice, coarse
grains, and oilseeds; and three types of factors of production: land, nonland farm owned
factors, and purchased factors represented in
each country module. An important consideration in modeling the demand and supply
of factors, especially cropland, is the degree
to which they are specific to a particular crop.
The aggregated factor “other farm owned” is
assumed to be completely crop-specific. That
is, we defined a unique category of this factor
for each crop and allowed no substitution in
its use among crops. Conversely, we did not
distinguish purchased factors on a crop basis,
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Number 5, 2001
thereby assuming a perfect substitutability in
their use among crops in response to changes
in relative prices. In modeling demand and
supply of cropland, we defined a unique category of land for each crop in the same
way as for the other-farm-owned aggregate.
However, we assumed that the supply of
land to each crop depends not only on the
rental rate for that category of cropland but
on the rental rates for all other categories
of land use as well. The latter included all
the study crops plus a residual category of
land use—other arable land. Following Abler
and Shortle, this approach recognizes that
although some land may be better suited
for one crop than for another, there can be
some substitution among uses in response to
changes in land rental rates.4
Given the modeling framework, simulation results are sensitive to numerical values
chosen for any and all supply and demand
parameters in the model. The most important parameters in the present application
are those characterizing the aggregate production technology—the elasticities of factor substitution and supply.5 These were all
based on two reviews of published studies
of agricultural supply, one (Abler) covering
studies that contained estimates of supply
response in the NAFTA countries and the
other (Salhofer) covering studies that contained estimates of supply response in European countries. Findings from these reviews
provided upper and lower bounds of ranges
of plausible values for supply and substitution elasticities (table 2) but provided no
strong basis for choosing any particular value
falling within those bounds. Accordingly, for
the analysis, we assumed these parameters to
be random variables, belonging to uniform
distributions over their respective ranges.
(We followed procedures similar to those
4
The elasticities of land supply response were calibrated to
guarantee, as far as possible, consistency with available empirical
estimates as well as cross-equation restrictions applying to systems of equations derived from a cost function. Specifically, all
own elasticities are positive and greater in absolute value than
the sum of all (negative) cross-elasticities ensuring that a uniform increase in rental rates for included crops would result in
a net increase in total area planted. The cross-elasticities for all
pairwise combinations of type of cropland and rental rate except
those relating to rice, are negative reflecting the assumption that
the study crops (excepting rice) compete for the same land. The
rental rate for rice land does not appear in any but the rice land
equation, and it is the only variable in that equation. Finally, the
cross-elasticities were calibrated to ensure symmetry in the associated cross-derivatives.
5
Results are less sensitive to the numerical values of crop
demand elasticities and the ranges of “plausible values” for these
parameters is relatively much narrower than for the production
function parameters.
Amer. J. Agr. Econ.
described in Griffiths and Zhao and in Davis
and Espinoza.)
To have a more complete coverage of
area payments used in the study countries,
we need to distinguish between two subcategories: (1) those requiring a producer to
plant one or more of the study crops versus (2) those requiring merely that the land
remain in arable uses.6 These are labeled in
the annex tables as AP1 and AP2, respectively.
A policy simulation experiment comprised
solving the model after introducing an
increase, set at 1% of the initial value of total
crop production,7 in one category of support
in one of the study countries. We did policy
simulation experiments for every pairing of
study country and support measure, ignoring
whether the corresponding category of support actually features in the policy mix used
in a country. All simulation experiments were
repeated once using 1987 quantity, price, and
support data as the base, and once using
1998 data. Moreover, for each combination
of base year, type of support, and country,
the simulation experiment was repeated 100
times. Each simulation experiment was based
on a new, complete set of factor substitution and supply elasticities for every crop and
every country in the model; each elasticity
was drawn randomly and independently from
its own distribution.8
Tables A1–A3 contain key empirical
results presented on a country-by-country
basis and summarized in terms of means
and standard deviations of the distributions
of estimated impact ratios generated in the
6
In the real world, area payments are frequently accompanied by planting restrictions as well as voluntary and mandatory
set-aside requirements—features that may mitigate their impacts
on crop production. Moreover, some program of payments may
not require land to be kept in agricultural uses. These features
of policy implementation, ignored in this analysis, would further
reduce the production and trade effects of area payments as
compared to market price support, payments based on output or
payments based on variable input use.
7
One per cent was an arbitrary choice. During the preliminary
phases of the analysis, we tested a number of alternatives in the
range one to ten per cent of the initial value of production. We
found that results, when expressed in relative terms as described,
did not change appreciably with differences in the magnitude of
the shock over that range.
8
As explained, the supply of cropland in the model is represented via a system of crop-specific land supply equations.
Consequently, the own and cross-elasticities in these equations
are not independent of each other. Any combination of values
chosen for them must satisfy symmetry in cross-price derivatives and the adding up restrictions. Accordingly, at each turn
of step one in the procedure a check was performed to verify
whether these two restrictions were satisfied. If not, that step was
repeated as many times as necessary until a set of land supply
elasticities satisfying the two restrictions was obtained.
Dewbre, Antón, and Thompson
Table 2.
Transfer Efficiency and Trade Effects of Direct Payments
1209
Factor Supply and Substitution Elasticities
Elasticity of Supply
Nonland Factors
Purchased
Land
Farm owned
Own Price
NAFTA Countries
European Countries
Minimum
Maximum
Minimum
Maximum
050
450
050
450
010
070
010
090
Own Price
Average Crossa
020
060
010
040
−010
−020
−004
−015
Elasticity of Substitution
NAFTA Countries
European Countries
a Specific
Minimum
Maximum
Minimum
Maximum
Purchased
Factors
Land & Farm
Owned
Land &
Purchased
Purchased &
Farm Owned
000
020
000
100
000
020
000
080
000
100
000
100
000
180
030
150
values of cross-elasticities were calculated using these averages, the base period area shares and imposing the adding up and symmetry restrictions.
simulation experiments. Figure 1 shows histograms of the distributions of estimated
results for the net trade ratio.
The histograms of estimated trade ratios
for payments based on area are markedly
to the left of the histograms of estimated
trade ratios for all the other categories of
support. Thus, these forms of support are
found to be less trade distorting than market price support, output payments, and input
payments. Not surprisingly, estimated trade
600
ratios for area payments not requiring planting of study crops (AP2) are smaller than
estimated trade ratios for area payments that
do require planting (AP1). The average ratio
of the trade impact of a given amount of support provided in the form of area payments
not requiring planting is about one-tenth that
of the same amount of support provided
as market price support. The corresponding average for payments requiring planting is about one-fourth of the market price
Area
Payments 2
Market
Price
Support
500
Output
Support
Frequency
400
Area
Payments 1
300
Input
Support
200
100
0
-0.1
0
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
1
1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9
2
2.1 2.2 2.3
Trade ratio
Note: The distribution of impact ratios of each category of support cover 100 simulations for each of the five countries and for
each of the two years (e.g. 1000 simulations).
Figure 1. Distribution of trade impact ratios
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Number 5, 2001
1.8
Amer. J. Agr. Econ.
Input Support
1.6
1.4
Trade ratio
1.2
Output Support
1.0
0.8
0.6
0.4
Area Payment 1
0.2
Area Payment 2
0.0
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Farm Income ratio
Note: For each category of support, the crosses intersect at the mean ratios of the impacts of that support relative to
the market price support effects. The endpoints of the crosses are at the mean plus or minus one standard deviation.
The distribution of impact ratios of each category of support cover 100 simulations for each of the five countries and
for each of the two years (e.g. 1000 simulations).
Figure 2. Trade distortion and transfer efficiency
support.9 Payments based on the use of variable inputs were found to have the greatest
simulated impact on trade with an average
estimated trade ratio of 1.3. That the trade
effect of input subsidies is greater than that of
market price support may come as a surprise
given that the higher domestic prices associated with market price support lead both
to lower consumption and higher production
whereas input subsidies directly affect only
the production side. To understand this, note
that, because such subsidies go to the factors
assumed to be most elastic in supply, the production effects of an input subsidy will always
be greater than the production effects of market price support. The finding that the trade
effects are also greater indicates that the margin of difference in their production effects is
larger than the consumption effects of market price support. The trade effects of output
price support (payments based on output) are
seen to be similar, but generally, slightly less
than those of market price support.
Estimated farm income ratios tabulated
in columns 5–9 of table A3 reveal a ranking of support measures in terms of their
estimated effects on farm household income
that is exactly the reverse of that based on
estimated trade effects, corroborating conclusions in Schmitz and Vercammen. This relationship is plotted in figure 2.
Payments based on area are relatively seen
to be the most income efficient and least
trade distorting. Payments based on purchased inputs are the least efficient, with payments based on output in the middle, though
still superior to market price support in terms
of transfer efficiency.
Conclusions
9
However, note the substantially wider range of variation of
results applying to this latter category of area payments. There
was a wide range of differences among countries and between
the two base years, in the types and levels of support provided
via area payments. A specific example may help to illustrate the
point. In annex table A2, compare the estimated results obtained
for the European Union using 1987 base data with those using
1998 data. The average estimated trade ratio for AP1 payments
is more than three times that obtained when using 1987 data.
The reason for this is that in 1987, well before the reforms to
the Common Agricultural Policy introduced in 1992, virtually all
support to EU crop producers was in the form of market price
support. Since those changes, the great majority of support has
been in the form of AP1 type area payments. This difference in
“initial conditions” explains much of the variation captured in
figure 1.
This article has demonstrated both analytically and empirically that the type of support matters when measuring its impact on
production, trade, and farm income. However, any ranking of measures must take
into account additional information relating
to initial support and demand (domestic and
export) response. The analytical results show
that there is a decreasing marginal impact on
production, trade, and farm income for all the
Dewbre, Antón, and Thompson
Transfer Efficiency and Trade Effects of Direct Payments
support measures studied. In theory, depending on the initial patterns of support and the
size of the country in trade, any ranking of
policy measures is possible. In the case of
a small country with no initial support, the
theoretical model results in a strict ordering
of policy impacts under plausible elasticity
assumptions.
Empirical results obtained in this analysis demonstrate that those support measures
causing the greatest distortion to production
and trade (per dollar transferred to farmers from consumers and taxpayers) are also
the least efficient in providing income benefits to farm households and vice versa. These
findings point to the possibility that governments could, by changing the way support is
provided, significantly reduce distortions to
trade while minimizing the negative impacts
on farm household incomes. Market price
support is often singled out for special consideration in international policy discussions
because the associated trade interventions
increase both domestic producer and consumer prices, reduce imports or increase subsidized exports and depress world market
prices (Sumner). Results obtained indicate
that, compared to area payments, market
price support is indeed a relatively inefficient and trade distorting way of supporting farm incomes. Direct payments based
on output or on variable input use, however, were also found to be highly inefficient
and trade distorting when compared to area
payments. Distinctions between programs of
area payments that require planting of eligible crops and those that require only that
land remain in agricultural use also feature
prominently in international debate on agricultural policy. Results obtained in the analysis show that area payments requiring planting of specific crops are less efficient and
more trade distorting than payments made
irrespective of the use to which the land
is put. However, these differences are not
as great as those between area payments,
in general, and the other forms of support
studied.
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Moro, D., and P. Sckokai. “Modelling the CAP
Arable Crop Regime in Italy: Degree of
Decoupling and Impact of Agenda 2000.”
Cahiers d’économie et sociologie rurale
53(1999):50–73.
OECD (1995), Adjustment in OECD Agriculture:
Issues and Policy Response, Paris.
OECD (2001a), Market Effects of Crop Support
Measures, OECD, Paris.
OECD (2001b) “Decoupling: A Conceptual
Overview.” OECD Papers, No. 10, Paris.
OECD (2001c), Agricultural Policies in OECD
Countries, Monitoring and Evaluation 2001,
Paris.
Salhofer, K. “Elasticities of Substitution and Factor Supply Elasticities in European Agriculture: A Review of Past Studies.” Market
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Sumner, D. “Domestic Support and the WTO
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44(3)(2000):457–74.
1212
Appendix
Production Impacts: Ratios With Respect to Market Price Support
Analyticala Results
If Zero
Initial Support
Policy
and a
Simulation European
United
Small Countryc (base year) Union Switzerland States Canada Mexico
General Formulac
If Zero
Initial
Supportc
1 + M1 + s + s Qs − d Qd /Qr
1 + O1 + s + s Qs /Qr − d Qd Q r − d Q d
Qr
1
0 1 1 1
Payments
Based On:
Output
Empiricalb Results
Area
f +p f kf +p kp +f p
Qr +s Qs −d Qd
Qr −d Qd
+A
Qr +s Qs −d Qd
Qr
1+f +kf p +kf p +kp f
+
+ M1 + s 1+f p kp s Q s
Qr −d Qd f kf +p kp +f p
Qr − d Q d
f
Qr
0 f f
f f Purchased
inputs
(1987)
135
187
012
016
002 001
029
(1998)
119
004
166
010
108
100
001 000
109
002
AP1
(1987)
047
019
039
015
035
034
010 011
050
023
014
020
007
010
010 013
013
AP2
(1987)
018
008
023
010
020
009
004 004
017
008
(1998)
006
003
008
004
009
010
003 005
015
004
(1987)
152
014
227
019
151
146
007 008
083
030
(1998)
164
011
200
012
153
127
007 005
139
009
(1998)
108
030
102
038
Number 5, 2001
Table A1.
078
051
Symmetric to Area Payments
a Ranges
p p p of possible values are indicated in brackets below each formula.
empirical results are presented as the averages and the standard deviations of each ratio across 100 simulations with random sets of parameters.
are a number of meaningful expressions repeated in several formulas. To simplify the presentation we adopt the following definitions: s = f kf + p kp + f p / + kf p + kp f : the implicit elasticity of supply; Qr =
s Qrs − d Qrd : the quantity change in the net exports from the rest of the world when world prices increase by 1%; f = f + p /f kf + p kp + f p : the production ratio of area payments for a small country with no initial
support; p = p + p /p kp + f kf + p f : the production ratio of payments based on purchased inputs for a small country with no initial support (symmetric to f ).
b The
c There
Amer. J. Agr. Econ.
0 Trade Impacts: Ratios With Respect to Market Price Support
Analyticala Results
If Zero
Initial Support
and a
Policy European
United
Small Countryc Simulation Union Switzerland States Canada Mexico
General Formulac
If Zero
Initial
Supportc
1 + 1 + M1 + s Qr /s Qs − d Qd 1 + 1 + O1 + s Qr − d Qd /s Qs s Qs
s Q s − d Q d
s Q s
s Q s − d Q d
(1987)
0 0 1
0 1
Payments
Based On:
Output
Empiricalb Results
Area
Qr +s Qs −d Qd
s Q s
+A
Qr +s Qs −d Qd
s Qs −d Qd
+ M1 + s 1+f +kf p Qr −d Qd
+kf p +kp f
s Q s
+
Qr
s Qs −d Qd
1+f p kp f kf +p kp +f p
s Qs
s Q s
s Q s − d Q d s Q s − d Q d
0 0 f 0 f Purchased
inputs
151
090
093
030
013
018
001
003
013
(1998)
092
006
142
012
091
001
092
002
094
004
AP1
(1987)
036
015
034
013
033
009
032
009
018
012
011
015
025
035
044
006
008
008
012
011
AP2
(1987)
015
006
023
010
018
004
008
004
005
003
(1998)
004
002
008
004
007
003
009
005
014
003
(1987)
116
018
182
022
123
006
132
008
033
013
(1998)
131
013
173
014
129
006
117
006
120
011
(1998)
Symmetric to Area Payments
0 a Ranges
0 p 0 p of possible values are indicated in brackets below each formula.
empirical results are presented as the averages and the standard deviations of each ratio across 100 simulations with random sets of parameters.
footnote c in Table A1 for a definition of the variables s – implicit elasticity of supply; Qr – quantity change in the net exports from the rest of the world when world prices increase by 1%; f – production ratio of area payments
for a small country with no initial support; p – production ratio of payments based on purchased inputs for a small country with no initial support, which is symmetric to f .
b The
c See
Transfer Efficiency and Trade Effects of Direct Payments
f +p f kf +p kp +f p
106
Dewbre, Antón, and Thompson
Table A2.
1213
1214
Table A3.
Farm Income Impacts: Ratios With Respect to Market Price Support
Analyticala Results
Qr
Qr − d Qd 1 + M1 + s Qr +s Qs −d Qd
Qr −d Qd
Qr
1 + O1 + s Q +
Q − Q
Q r − d Qd
Qr
0 1 r
s
s
d
d
If Zero
Initial Support
and a
Policy
European
United
Small Countryc Simulation Union Switzerland States Canada Mexico
1
(1987)
1 1
Area
Q 1+ 1+M Q +r Q −s Q
r s s d d
Qr +kf p +Qs p kp −d Qd +kf p Qr +p kf
Qr +kf p +Qs p kp −d Qd +kf p Qr +p kf
+ k f p
0 Purchased
inputs
1+M Q
1+S Qr 1+s r +s Qs −d Qd
p Qr −Qs −d Qd
+p
Qr
Qr +kp f +Qs f kf −d Qd +kp f 1+p
Qr +s Qs −d Qd
f kp +p kf +
a Ranges
+ k f p
+ p kf
p Qr −Qs −d Qd
Qr
+p
− 109
103
078
005
016
001
001
017
(1998)
116
002
163
011
108
001
100
000
108
002
AP1
(1987)
228
033
297
044
217
029
154
020
103
023
240
265
239
144
143
042
038
028
019
015
245
034
340
046
254
023
172
022
115
028
268
285
268
158
148
045
038
024
022
016
091
137
036
076
053
015
021
016
014
015
092
122
018
068
084
015
014
018
011
011
AP2
(1987)
(1998)
(1987)
p
+ p
p
+ p
(1998)
of possible values are indicated in brackets below each formula.
empirical results are presented as the averages and the standard deviations of each ratio across 100 simulations with random sets of parameters.
c See footnote c in Table A1 for a definition of the variables – implicit elasticity of supply, Q – quantity change in the net exports from the rest of the world when world prices increase by 1%.
s
r
b The
Amer. J. Agr. Econ.
− + k f p
+ p kf
183
(1998)
+ p kf
Qr +kf p +Qs p kp −d Qd +kf p 1+f
1+A k + k +
Qr +s Qs −d Qd
f p p f
126
Number 5, 2001
General formulac
If Zero
Initial
Supportc
Payments
Based On:
Output
Empiricalb Results