Making Gravity Great Again
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 v...
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| Format: | Working Paper |
| Language: | English |
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World Bank, Washington, DC
2020
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| Online Access: | http://documents.worldbank.org/curated/en/100241599665436997/Making-Gravity-Great-Again http://hdl.handle.net/10986/34477 |
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okr-10986-344772022-09-20T00:11:29Z Making Gravity Great Again Martin, Will GRAVITY MODEL EATON-KORTUM MAXIMUM-LIKELIHOOD TRADE STATISTICS MISSING DATA 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. 2020-09-17T20:04:34Z 2020-09-17T20:04:34Z 2020-09 Working Paper http://documents.worldbank.org/curated/en/100241599665436997/Making-Gravity-Great-Again http://hdl.handle.net/10986/34477 English Policy Research Working Paper;No. 9391 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank World Bank, Washington, DC Publications & Research Publications & Research :: Policy Research Working Paper |
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Digital Repository |
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Foreign Institution |
| institution |
Digital Repositories |
| building |
World Bank Open Knowledge Repository |
| collection |
World Bank |
| language |
English |
| topic |
GRAVITY MODEL EATON-KORTUM MAXIMUM-LIKELIHOOD TRADE STATISTICS MISSING DATA |
| spellingShingle |
GRAVITY MODEL EATON-KORTUM MAXIMUM-LIKELIHOOD TRADE STATISTICS MISSING DATA Martin, Will Making Gravity Great Again |
| relation |
Policy Research Working Paper;No. 9391 |
| description |
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. |
| format |
Working Paper |
| author |
Martin, Will |
| author_facet |
Martin, Will |
| author_sort |
Martin, Will |
| title |
Making Gravity Great Again |
| title_short |
Making Gravity Great Again |
| title_full |
Making Gravity Great Again |
| title_fullStr |
Making Gravity Great Again |
| title_full_unstemmed |
Making Gravity Great Again |
| title_sort |
making gravity great again |
| publisher |
World Bank, Washington, DC |
| publishDate |
2020 |
| url |
http://documents.worldbank.org/curated/en/100241599665436997/Making-Gravity-Great-Again http://hdl.handle.net/10986/34477 |
| _version_ |
1764480982004531200 |