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Gravity-Defying Trade

Authors: J. M. C. Santos Silva; Silvana Tenreyro;

Gravity-Defying Trade

Abstract

Although economists have long been aware of Jensen's inequality, many econometric applications have neglected an important implication of it: estimating economic relationships in logarithms can lead to significant biases in the presence of heteroskedasticity. This paper explains why this problem arises and proposes an appropriate estimator. Our criticism to conventional practices and the solution we propose extends to a broad range of economic applications where the equation under study is log-linearized. We develop the argument using one particular illustration, the gravity equation for trade, and use the proposed technique to provide novel estimates of this equation. Three results stand out. First, contrary to general belief, income elasticities are significantly smaller than 1. Second, standard estimators greatly exaggerate the roles of distance and colonial links. Finally, bilateral trade between countries that have signed a free-trade agreement is 30 percent larger than that between other countries, a magnitude remarkably di?erent from that predicted by conventional methods (above 100 percent).

Keywords

Free trade

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Top 10%
Average
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