Publication: Estimating the Gravity Model When Zero Trade Flows are Frequent and Economically Determined
Date
2015-06
ISSN
Published
2015-06
Author(s)
Abstract
This paper evaluates the performance of
alternative estimators of the gravity equation when zero
trade flows result from economically-based data-generating
processes with heteroscedastic residuals and
potentially-omitted variables. In a standard Monte Carlo
analysis, the paper finds that this combination can create
seriously biased estimates in gravity models with
frequencies of zero frequently observed in real-world data,
and that Poisson Pseudo-Maximum-Likelihood models can be
important in solving this problem. Standard threshold–Tobit
estimators perform well in a Tobit-based data-generating
process only if the analysis deals with the
heteroscedasticity problem. When the data are generated by a
Heckman sample selection model, the Zero-Inflated Poisson
model appears to have the lowest bias. When the data are
generated by a Helpman, Melitz, and Rubinstein-type model
with heterogeneous firms, a Zero-Inflated Poisson estimator
including firm numbers appears to provide the best results.
Testing on real-world data for total trade throws up
additional puzzles with truncated Poisson
Pseudo-Maximum-Likelihood and Poisson
Pseudo-Maximum-Likelihood estimators being very similar, and
Zero-Inflated Poisson and truncated Poisson
Pseudo-Maximum-Likelihood identical. Repeating the Monte
Carlo analysis taking into account the high frequency of
very small predicted trade flows in real-world data
reconciles these findings and leads to specific
recommendations for estimators.
Citation
“Martin, Will; Pham, Cong S.. 2015. Estimating the Gravity Model When Zero Trade Flows are Frequent and Economically Determined. Policy Research Working Paper;No. 7308. © World Bank, Washington, DC. http://openknowledge.worldbank.org/handle/10986/22182 License: CC BY 3.0 IGO.”
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