In this paper we estimate the gravity model allowing for the pervasive issues of heteroscedasticity and zero bilateral trade flows identified in an influential recent paper by Santos Silva and Tenreyro. We use Monte Carlo simulations with data generated using a heteroscedastic, limited-dependent-variable process to investigate the extent to which different estimators can deal with the resulting parameter biases. While the Poisson Pseudo-Maximum Likelihood estimator recommended by Santos Silva and Tenreyro solves the heteroscedasticity-bias problem when this is the only problem, it appears to yield severely biased estimates when zero trade values are frequent. Standard threshold-Tobit estimators perform better as long as the heteroscedasticity problem is satisfactorily dealt with. The Heckman Maximum Likelihood estimators appear to perform well if true identifying restrictions are available.
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Paper provided by Deakin University, Faculty of Business and Law, School of Accounting, Economics and Finance in its series Economics Series with number
2008_03.
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Find related papers by JEL classification: C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models F10 - International Economics - - Trade - - - General F11 - International Economics - - Trade - - - Neoclassical Models of Trade F12 - International Economics - - Trade - - - Models of Trade with Imperfect Competition and Scale Economies F15 - International Economics - - Trade - - - Economic Integration
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Jones, Andrew M., 2000.
"Health econometrics,"
Handbook of Health Economics,
in: A. J. Culyer & J. P. Newhouse (ed.), Handbook of Health Economics, edition 1, volume 1, chapter 6, pages 265-344
Elsevier.
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