Making Gravity Great Again

No 9391, Policy Research Working Paper Series from The World Bank

Abstract: The gravity model is now widely used for policy analysis and hypothesis testing, but different estimators give sharply different parameter estimates and popular estimators are likely biased because dependent variables are limited-dependent, error variances are nonconstant and missing data frequently reported as zeros. Monte Carlo analysis based on real-world parameters for aggregate trade shows that the traditional Ordinary Least Squares estimator in logarithms is strongly biased downwards. The popular Poisson Pseudo Maximum Likelihood model also suffers from downward bias. An Eaton-Kortum maximum-likelihood approach dealing with the identified sources of bias provides unbiased parameter estimates.

Keywords: International Trade and Trade Rules; Trade and Services; Economic Conditions and Volatility; Financial Sector Policy; Transport Services (search for similar items in EconPapers)
Date: 2020-09-09
New Economics Papers: this item is included in nep-ecm and nep-int
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Citations: View citations in EconPapers (3)

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Working Paper: Making Gravity Great Again (2020)
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