Instead, coefficients capture the impact of trade costs on both the number of firms engaging in trade (the extensive margin) and the trade value per firm. business (the intensive margin), leading to an upward bias in the estimates. Their empirical analysis confirms that failure to control for the number of exporting firms leads to an upward bias in the estimated coefficients. The main limitation of these studies is that they only have data on the number of exporting firms for one country and therefore cannot control for the multilateral resistance terms in the gravity equation, which, as explained above, leads to biases in the estimated coefficients related to trade costs .
To overcome these problems, for the first time in the literature, we estimate the gravity equation using a new database compiled by the OECD and Eurostat that reports the value of trade and the number of firms participating in bilateral trade flows for 21 OECD reporting countries. and 36 trading partners. The main difficulty in estimating equation (10) lies in the availability of data on the number of firms participating in exports by country pair for a large sample of countries. The lowest average number of exporting firms, 42, is found in the country with the lowest GDP: Cyprus.
We also see that there is a large variation in the number of exporting companies per partner. As shown in Figure 1, there is in fact a close relationship between the value of bilateral exports and the number of exporting companies participating in the export relationship.
Econometric results
In any case, as shown by HMR, the bias introduced by selection is small compared to the bias introduced by the absence of controls for firm heterogeneity. In contrast, speaking the same language, sharing a land border and belonging to the same regional integration agreement do not have a statistically significant effect on trade. We find that, compared to the OLS coefficient, distance has a smaller negative effect on trade.
It is interesting to compare our results with recent studies that evaluated the gravity equation (Baier and Bergstrand, 2009; Head et al., 2010; Rose and Spiegel, 2011).3 It is important to emphasize that these studies use a wider sample of countries than ours. studies, and two of them use a much longer time frame. We find that our OLS-estimated distance coefficient has a larger negative effect on trade than the coefficients estimated by these studies: -1.35 in Baier and Bergstrand, -0.91 in Head et al. and -1.33 in Rose and Spiegel; relative to the Poisson estimate, our coefficient also has a larger negative effect than that reported by Head et al. Sharing a common border, speaking the same language, and having a common currency, which are not statistically significant in our OLS estimation, are positive and statistically significant in these studies.
In the Poisson estimation, as in our study, Head et al (2010) also report a positive and statistically significant coefficient for language; however, unlike our study, they also report positive and statistically significant coefficients for adjacent areas and common boundaries. These results indicate that the countries in our sample lead to estimates that are, in some cases, out of line with studies using a broader group of countries.
1) OLS (2)
OLS Reduced
5) Poisson
6) OLS with nº of
0.12) Adjacency 0.19
0.14) Common currency -0.07
5.77) Actual nº of
Conclusions
To correctly estimate the effect of variable trade costs on firms' exports, the gravity equation should control for the number of firms participating in foreign markets. Due to the absence of data, previous studies estimate this figure using an export participation model and then introduce it into a gravity equation. However, due to the strong distributional assumptions that this procedure requires, some authors cast doubt on the validity of these estimates.
To overcome these problems, this paper estimates the gravity equation using the actual number of exporting firms for a sample of 21 exporters and 36 importers. Our results show that some traditional estimates of gravity are heavily biased if they do not control for robust heterogeneity. We also find that the magnitude of the bias is much larger than reported in previous multi-country studies.
In particular, we find that the distance coefficient falls between 54% and 66% when the number of exporting firms is introduced into the gravity equation. We also find that traditional gravity estimates overestimate the impact of language and underestimate the impact of regional trade agreements on the trade-intensive margin. In particular, in 2006 and 2007, the US does not report data on the number of exporting firms.
In addition, in 2007 Poland also does not report the number of exporting companies.
0.10) Adjacency 0.44
0.12) Common currency -0.04
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