Forthcoming in the American Journal of Agricultural Economics.geography, grains, trade costs, trade liberalization, Agricultural and Food Policy, Crop Production/Industries, Demand and Price Analysis, International Development, International Relations/Trade, Marketing, Research Methods/ Statistical Methods, Q17, Q54, F18,

Li, Man

Reimer, Jeffrey J.

English

Research Papers in Economics

Trade Costs and the Gains from Trade in Crop Agriculture
Jeffrey J. Reimer
Assistant Professor
Department of Agricultural and Resource Economics
213 Ballard Hall, Oregon State University, Corvallis, OR, 97331
jeff.reimer@oregonstate.edu
Man Li
Graduate Research Assistant
Department of Agricultural and Resource Economics
213 Ballard Hall, Oregon State University, Corvallis, OR, 97331
lim@onid orst edu lim@onid.orst.edu
Poster prepared for presentation at the Agricultural & Applied Economics Association 
2010 AAEA,CAES, & WAEA Joint Annual Meeting, Denver, Colorado, July 25-27, 2010.
Copyright 2010 by Jeffrey J. Reimer and Man Li. All rights reserved.
Readers may make verbatim copies of this document for non-commercial purposes by any means,
provided that this copyright notice appears on all such copies.Jeff Reimer and Man Li
Trade Costs and the Gains from Trade in Crop Agriculture
Jeff Reimer and Man Li
Department of Agricultural and Resource Economics, Oregon State University
Introduction
World crop markets are often thin and characterized by volatile prices.  
One reason is that crop yields are highly variable over time and space.  
International trade can alleviate this problem to some extent but is 
hindered by restrictive border policies.  For example, global average 
Comparison to other models
The framework provides an alternative to computable general 
equilibrium (CGE) models.  As with them, the model can be used to 
simulate the effects of trade policy changes or other types of shocks 
once it is parameterized.  The characterization of the global trading 
Transportation costs matter
The fifth and sixth counterfactual simulations examine how changes in 
supply in one country affect the welfare of other countries.  Distance in 
particular can greatly reduce the extent by which an event in one 
country is transmitted to others.  The following scatterplot shows what 
Crop markets are thin
With the model fully parameterized, we consider six counterfactual 
simulations.  The first two are not meant to emulate actual policy 
scenarios but to illustrate basic points about the world trading system.  
We compare global trade volumes that are observed with those that  ypp , g g
bound tariffs in agriculture are roughly double those in other sectors.  
Non-tariff barriers are pervasive. Furthermore, in 2007-2008 at least 
10 grain exporting countries restricted their exports so as to keep 
prices low for consumers at home; the inability of other countries to 
import this grain caused a great deal of suffering.
Not only are world crop markets highly insulated, prospects for further 
trade liberalization are uncertain.  Since countries are often quite 
hesitant to make concessions in exchange for trade liberalization in 
other countries, it may help to illuminate basic facts about the world 
crop sector, and get new perspectives on the size and distribution of 
the gains from trade, by country.
pg g
equilibrium differs in important ways from CGE models, however.  
For example, countries specialize in a subset of homogeneous crops as 
determined by their productivity distributions and the costs of trading 
with foreign markets.  By contrast, most CGE models invoke 
specialization through differentiation by country.  Relative to that 
approach, this model has greater flexibility in the extent to which trade 
patterns adjust in response to shocks to the system.
In this way the framework is more like a spatial equilibrium model, 
which allocates trade flows on the basis of lowest possible 
transportation cost.  Unlike spatial equilibrium models, however, 
bilateral trade is predicted by a gravity model, which is generally 
superiorat replicating actual trade flows
happens if there would be an expansion of  supply in Brazil, due, say, 
to an expansion of cropped area onto former rainforest.  The effect to 
which prices fall in other countries is correlated strongly with their 
physical distance to Brazil:
would occur under hypothetical zero trade cost and autarkic (infinite 
trade cost) equilibria. When compared against these extremes, the 
international crops market is surprisingly close to the extreme of 
autarky.  For example, observed trade volumes are only one-fifteenth 
of that which would occur under zero trade costs.
Another way to interpret this result is that there is far less trade than 
one might expect given how much countries differ in terms of their: (a) 
crop prices, (b) land endowments and rental rates, and (c) crop yields.  
The severity of barriers to international trade costs – whether caused 
by policy or geography – is also revealed by the sensitivity of trade 
flows to them.  A mere 1% reduction in aggregate trade costs would 
increase world trade volumes by approximately 2.5%.
In this study we develop a new global simulation model of crop 
agriculture to address these questions.  The model is partial-
equilibrium and designed around the salient features of world crop 
markets: yield variability and high trade costs, the latter of which are 
caused by policy as well as geography.  The resulting framework 
provides econometric evidence about trade costs, and – since it is a 
simulation model – can be used to examine the types of questions that 
heretofore have been the domain of spatial equilibrium and 
computable general equilibrium models. 
A new model for crops trade
superior at replicating actual trade flows.
Our gravity model is different from most in the literature, in turn, in 
that it is derived from the trade model used for the simulation analysis.  
It incorporates structural parameters from the yield distributions that 
govern specialization.  Furthermore, gravity studies tend to focus only 
on what gets traded.  We allow the size of the sector to be endogenous 
and account for the amount of trade relative to overall consumption, 
that is, the extent of “home bias” in consumption.
Parameterization of model
Systematic differences between 
rich and poor countries
Many of the results differ systematically by countries’ level of 
economic development, as proxied for by per capita income.  
Countries with high average productivity are more likely to be found 
on the high end of the global income distribution.  Countries with high 
yp p y
In the third and fourth simulations we distinguish trade costs that are in 
principle reducible, such as tariffs, from those that are difficult to 
reduce, such as transportation costs.  The two simulations differ in 
terms of whether land is fixed within the crop sector.  We find that a 
modest degree of liberalization – such that each country has a level of 
openness similar to the current U.S. level – leads to big welfare gains 
in most countries, mainly because crop prices for consumers can fall a 
great deal.  Selected results are below:
A new model for crops trade
The simulation model we propose for crop agriculture is based on the 
class of Ricardian trade models developed by Eaton and Kortum 
(Econometrica, 2002).  Unlike the textbook Ricardian model, in which 
two countries each specialize in one of two goods, the goods sector is 
modeled as a continuum, with multiple countries specializing in 
sections of this continuum according to comparative advantage.
In our adaptation, specialization is determined by random productivity, 
land endowments, and the bilateral costs of trade.  Productivity is 
determined through a random draw from country-specific crop yield 
distributions Each country has a chance of being a low cost supplier
Data to estimate model parameters are primarily from the Food and
Agricultural Organization (FAO) and the Global Trade Analysis
Project (GTAP). The model corresponds to the following crops: paddy
rice, wheat, oil seeds, and cereal grains not elsewhere classified.
Nearly every model parameter is econometrically estimated. Bilateral
trade costs are calculated as an ad valorem tax equivalent and are
estimated using the structural gravity equation predicted by the model.
Parameters of the crop yield distributions are estimated by three
alternative approaches. Approach I is a Generalized Method of
Moments technique applied directly to the crop yield distributions.
Approach II proceeds in similar fashion but involves Maximum
Lik lih d Et i t i Ah III tt ith diff t ti
import trade costs, by contrast, are more likely (though not always) 
found on the low end of the global income distribution.
The insulation associated with high import trade costs may shield 
countries somewhat from adverse changes in other countries.  
However, it also means they may gain less when other countries are 
able to increase their supply.  Regardless of these tendencies, it appears 
that all countries are very far from reaping the potential gains from 
trade in international crop markets.  The framework offers a means for 
future researchers to determine the gains from trade from new policy 
directions.
distributions.  Each country has a chance of being a low cost supplier 
depending on whether it has a bumper crop or crop failure in a given 
year.
A country’s ability to trade is hampered by bilateral trade costs, 
however, which are estimated from a structural gravity model that is 
predicted by the model.
Likelihood Estimation. Approach III startsw ith a different equation
within the model and makes use of Ordinary Least Squares. The
choice of technique affects the overall parameterization of the model
since certain remaining parameters are a function of the parameters of
the crop yield distributions. A comparison of the three
parameterizations to external criteria provides evidence in favor of
Approaches I and III. We base our subsequent simulation results on
both approaches.
For further information
Please contact jeff.reimer@oregonstate.edu phone 541-737-1415

Trade Costs and the Gains from Trade in Crop Agriculture

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