Welcome to The Log of Gravity page.
Reference (with open access):
An early version of the paper can be found at CEP/LSE (and an even earlier version at Boston Fed).
In this page you can find the data set used in the paper, codes to extend some of the results in the paper, and other useful information on the implementation of the PPML estimator. These and other issues are also discussed in this short review. If you cannot find here the answer to your question about The Log of Gravity, please do not hesitate to contact the authors; we will be only too pleased to help.
The dataset (in xls and dta formats) is available here.
Charbonneau (2012, p. 41) claimed that "a Poisson model with two fixed effects does suffer from the incidental parameter problem", and this claim has recently been echoed by other researchers. However, Charbonneau's claim is based on an example with N = T = 2, which cannot be informative about the existence of an incidental parameter problem because this problem is asymptotic in nature. In contrast, Fernández-Val and Weidner (2014, example 2, p. 16) have proved that a Poisson model with two fixed effects does not suffer from the incidental parameter problem as long as the sizes of the two sets of fixed effects grow at the same rate and the regressors are strictly exogenous or predetermined. Therefore, under very general conditions, inference based on the estimation by ppml of gravity equations including both importer and exporter fixed effects will not be affected by an incidental parameter problem. Remarkably, Martin Weidner and Tom Zylkin have shown that PPML is also largely immune to the incidental parameter problem when the model contains three sets of fixed effects.
Testing competing models for non-negative data with many zeros:
We have developed a simple test to choose between competing models for non-negative data with many zeros; the paper is available here. Stata code to implement the test is available, type "ssc install hpc"; the code and data used in the paper are available here.
We have written a crude Stata command to estimate the IV version of PPML. This estimator was originally described in Windmeijer, F. and Santos Silva, J.M.C. (1997), "Estimation of Count Data Models with Endogenous regressors: An Application to Demand for Health Care," Journal of Applied Econometrics, 12(3), pp. 281-294. Here is an example of how to use the command. This estimator is now implemented in Stata; see the ivpoisson command and the add option (the default).
Here is a sample of the code to perform the test.
If you want to compute the R-squared for a model estimated by PPML, you can use the method implemented here.
PPML performance with many zeros:
Simulation evidence on the excellent performance of the PPML estimator when the data has many zeros can be found in this Economics Letters paper.
We have written a short reply to "The log of gravity revisited".
If you want to compute 'undertrading' and 'overtrading' after fixed-effects regressions with panel data, you need to obtain a set of residuals with zero mean. Here is how to do it.
Related work by other authors: FAQs & myths about the Log of Gravity
FAQs & myths about the Log of Gravity
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Last updated on 18 August 2021