BACKGROUND PAPERS
2 INTERNATIONAL MONETARY FUND
THE EFFECT OF TRADE ON INCOME AND INEQUALITY:
A CROSS-SECTIONAL APPROACH
1
This background note is a short summary of the main results in a forthcoming working paper. We use countries’
exogenous geographic characteristics to construct an instrument for trade openness, and examine the cross-
country relationship between trade, income and inequality.
A. Motivation and Methodology
1. There is a strong correlation between trade and income, and trade and inequality in
the cross section of countries, but inferring causality is complicated due to endogeneity
problems. Countries with higher trade openness (exports plus imports as a share of GDP) tend to
have higher living standards and lower income
inequality. The gap between more open and less
open economies in terms of their GDP per capita
and income Gini coefficient is persistent, and if
anything it has widened in the last two decades
(Figure 1). However, trade openness is arguably
endogenous in these simple bivariate
relationships as many variables that affect income
and inequality directly may also be correlated
with trade itself. For example, countries that
adopt open trade policies may also pursue other
market-friendly domestic policies and conduct
stable fiscal and monetary policies. Since these
policies are likely to affect income and inequality, trade openness is likely to be correlated with
important factors that are omitted from the naïve approach.
2. Countries’ exogenous geographic characteristics can be exploited to achieve causal
identification. As the literature on the gravity model of trade demonstrates, geography is a
powerful determinant of bilateral trade (e.g. Head and Mayer, 2014). A seminal paper by Frankel and
Romer (1999, henceforth FR) showed that one can use this insight to construct a valid instrument for
countries’ overall trade openness. In particular, they estimate a gravity equation that includes only
geographical variables such as bilateral distance, area, and whether the countries are landlocked,
and they aggregate the fitted values to obtain the predicted trade openness of each country. The
included geographic characteristics are unlikely to have important effects on countries’ income
except through their impact on trade. Thus, the constructed trade openness can be used to obtain
1
Prepared by Diego Cerdeiro and Andras Komaromi. This paper was prepared as a background study for the
Western Hemisphere Department’s Cluster Report on Trade Integration in Latin America and the Caribbean. This
paper describes research in progress by the authors and is published to elicit comments and to encourage debate.
The views expressed in this paper are those of the authors and do not necessarily represent the views of the IMF, its
Executive Board, or IMF management.
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9
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1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
GDP per capita - Bottom tertile GDP per capita - Top tertile
Gini coef. - Bottom tertile Gini coef. - Top tertile
Figure 1: Income and inequality by level of openness
(average of countries in bottom and top tertile)