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*Rose is B.T. Rocca Jr. Professor of International Trade and Economic Analysis and Policy in the Haas School of Business at the University of California, Berkeley, NBER research associate, and CEPR Research Fellow. Spiegel is Senior Research Advisor, Economic Research Department, Federal Reserve Bank of San Francisco. We thank Rob Feenstra for a comment that helped inspire this paper; Rose thanks INSEAD for hospitality while part of this paper was written. We also thank Gerd Haeusler, Phillip Lane, Nancy Marion, Paulo Mauro, Michael Mussa, and participants at the IMF's Fourth Annual Research Conference, and especially Mark Wright, for comments. A current (PDF) version of this paper and the STATA data set used in the paper are available via the Internet at: http://faculty.haas.berkeley.edu/arose.
While the Kehoe and Levine model allows for asset seizure, it does not consider interruptions of trade in spot markets, which might be considered analogous to the direct trade sanctions in our model below.
See Wright's (2003) comments on our paper below. Wright argues that the assumption of superior information sets held by primary trading partners may give those partners comparative advantages in lending in pure reputation models with the additional assumption of continuous trade in goods to avoid the “excessive gross flows” problem.
In the limiting case where the εij 's are distributed uniformly, the equilibrium borrowing allocation results in the debtor defaulting on both creditors or none.
If bank lending reflects trade credits, coefficient estimates from our IV estimation may be biased upwards. As our estimated effect is large, however, it is unlikely that correction for this bias would eliminate our results.
Our measurement of cross-border obligations may contain errors from a number of sources. First, the use of consolidated data may not correctly assign the risk of banks' foreign branches. Second, “outward risk transfers” are sometimes used to transfer risks to residents of other countries, and our data set would not pick these up. Still, as these errors fall in the regressand of our model they only make the effect of trade harder to find and do not appear to introduce any bias issues.
These data are available via the Internet at: http://www.bis.org/publ/qcsv0206/hanx9b.csv and are part of the International Banking Statistics published regularly in the BIS Quarterly Review. For technical reasons we usually ignore a few observations from Ireland and Spain; adding these makes little difference in general to our results.
Bilateral trade on FOB exports and CIF imports is recorded in U.S. dollars; we deflate trade by the U.S. CPI. We create an average value of bilateral trade between a pair of countries by averaging all of the four possible measures potentially available.
Wherever possible, we use World Development Indicators (taken from the World Bank's WDI 2000 CD-ROM) data. When the data are unavailable from the World Bank, we fill in missing observations with comparables from the Penn World Table Mark 5.6, and (when all else fails) from the IMF's International Financial Statistics. The series have been checked and corrected for errors.
Box-Cox tests imply that the natural logarithmic transformation is quite reasonable, and that the level transformation is rejected in favor of the log transform.
Though if we include only developing country borrowers, our estimate remains significant at 0.53 (standard error of 0.04).
Again, if we include only developing country borrowers, our estimate remains significant at 0.38 (standard error of 0.08).
If we use lags (e.g., of the GDP terms) as instrumental variables, our key result of a positive effect of trade on borrowing is not changed.
Lending may be motivated by servicing FDI, rather than the sovereign risk issues considered in the theory above. To test this, we add a control in the form of the natural logarithm of FDI sourced from the creditor country. We obtained the bilateral FDI data from the OECD's International Direct Investments Yearbook 1980–2000. This data set is annual and unavailable for many countries in our sample, containing only some 2,600 observations. When we add this control to our default IV regression (in logs, with controls) its coefficient is indeed positive and significant. Still, the log of trade retains an economically and statistically significant coefficient of 0.62 (with a robust standard error of 0.11).