models in which standard, unconditional fixed effects do not lead to bias and inconsistency due to the "incidental parameters problem" (Greene, 2004). This is an important practical advantage in relation to the alternative empirical strategy of analyzing the extensive margin via a standard gravity model using a Heckman sample selection estimator (Helpman et al., 2007), a probit model (Debaere and Mostashari, 2005) or the Tobit estimator.'* While it may be possible to avoid this problem by using a random effects estimator (Baldwin and Harrigan, 2007), the price that must be paid is a strong assumption as to the distribution of country- or sector-specific unobserved heterogeneity. Poisson estimates of our baseline model are presented in column 1 of Table 3.!? Overall, the model provides a close fit to the data, with R? equal to 0.92.”° All coefficients carry the expected signs: entry costs, export costs, distance, and EU tariffs are negative, while own tariffs, GDP, and GDP per capita are positive. The coefficients on entry costs, export costs, distance, and GDP are all statistically significant at the 1% level, but the remaining coefficients are not significant at the 10% level. These results are broadly consistent with previous work examining the diversification impacts of GDP, per capita income, and trade costs, such as Hummels and Klenow (2005) and Feenstra and Kee (2006). Similarly, our finding that lower domestic market entry costs are associated with greater export diversification is consistent with the results of Helpman et al. (2007), who find a negative and statistically significant coefficient on market entry costs in the first stage of a sample selection gravity model.”!

In terms of the magnitudes of the estimated coefficients on the trade and entry cost variables, Table 3 indicates that EU tariffs have the largest elasticity in absolute value terms (-0.6), followed '8Based on the evidence in Greene (2004), Debaere and Mostashari (2005) argue that the bias or inconsistency of their results is likely to be relatively minor in practice. '°We estimate the model cross-sectionally, using data for a single year (2005) only. While it would be desirable to estimate over multiple time periods, this is not currently possible given limited availability of our explanatory variables. °We follow Wooldridge (1997) in using R? = 1— ES'S/T S'S as a convenient summary measure of fit. We prefer it to the more common (for count data) pseudo-R? measures due to its ease of interpretation. We are conscious, however, that it should be used with caution since the Poisson model does not contain a residual as such. *1Our results in respect of domestic market entry costs might appear at first glance to contrast with those of Klinger and Lederman (2004, 2006). However, those authors use a different dependent variable, namely a count of the number of 3-digit SITC categories in which a country exports for the first time over a given period. Thus, they view diversification through the lens of export "discoveries", rather than as an increase in the proportion of nationally produced varieties that make it to the international market. Their explanatory variable set is also different, including a wider set of entry cost data such as labor market rigidity and contract enforceability indicators, but they do not consider trade costs.

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