Testing the trade credit and trade link: evidence from data on export credit insurance


Trade finance has received special attention during the financial crisis as one of the potential culprits for the great trade collapse. Several researchers have used micro level data to establish the link between trade finance and trade, especially so during the financial crisis, and have found diverting results. This paper analyses the effect of trade credit on trade on a macro level through a whole cycle. We employ Berne Union data on export credit insurance, the most extensive dataset on trade credits available at the moment, for the period of 2005–2011. Using an instrumentation strategy we can identify a significantly positive effect of insured trade credit, as a proxy for trade credits, on trade. The effect of insured trade credit on trade is very strong and remains stable over the cycle, not varying between crisis and non-crisis periods.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2


  1. 1.


  2. 2.

    Eaton et al. (2011) find that demand shocks can explain 80 % of the decline in trade and for some countries, like China and Japan, this share is a lot smaller. Hence, a significant share of the trade collapse remains to be explained.

  3. 3.

    See the Bankers Association of Finance and Trade (BAFT) website's for an expansion of such definition (www.baft-ifsa.org).

  4. 4.

    Note that we use the term trade credit for credit extended to finance international transactions (not for domestic transactions).

  5. 5.

    80 % of total credit insured is short-term, only 20 % is long-term (over a year) (IMF-BAFT 2009).

  6. 6.

    See Van der Veer (2010), Felbermayr and Yalcin (2013), Felbermayr et al. (2012), Moser et al. (2008) and Egger and Url (2006).

  7. 7.

    Berne Union website, at www.berneunion.org.

  8. 8.

    Documents from the G-20 in Cannes (2011) refer to the need to improve statistical information on trade finance (see report of the Development Working Group 2011).

  9. 9.

    Commercial services such as marketing, design, engineering, maintenance, transportation, telecommunications and computer services are often part of contracts related to the movement of merchandises. For example, the sale of machinery for outward processing manufactures is often associated to installation, maintenance, computer software design, etc. In industries such as natural resource exploration or satellite launching, the service can even hardly be separated from the merchandise itself. Therefore, it seems to make sense to add statistics of commercial service to imports to merchandise. We have nonetheless excluded services for robustness checks purposes, with little change in results.

  10. 10.

    Note that the data does not include public services.

  11. 11.

    It can be argued that financial institutions, through the process of "transformation" use short-term resources for long-term loans. This is a fair argument, However, this possibility is limited by prudential ratios, in particular the liquidity and stable funding ratios, from the Basel international framework.

  12. 12.

    Countries are classified according to their gross national income (GNI). See http://data.worldbank.org/about/country-classifications/country-and-lending-groups Accessed 03.09.2012.

  13. 13.

    One may argue that the financial crisis already started earlier. However, the real crisis began with the crash of Lehman Brothers in the third quarter of 2008. Nevertheless, in the robustness checks we also use a different definition of the crisis period beginning in the first quarter of 2008. Our results remain basically unchanged.

  14. 14.

    We do not use the standard gravity equation as we think it is less suited for addressing the endogeneity concerns we have regarding insured trade credits. Furthermore, we do not have bilateral trade credit data but data on short-term insured trade credits by destination countries only. Therefore, we rely with our specification on the classical import estimation equation adding trade finance as an explanatory variable.

  15. 15.

    Indeed, other fixed effects could have been included to account for such "institutional factors" such as changes in monetary policy in reaction to the financial crisis, which certainly affected liquidity and other variables. The large number of potential fixed effects is linked to the fact that the estimation equations do not derive from a theoretical model, that would have isolated trade finance from the LM (money) function, and discussed its impact on the (income) IS function. We acknowledge that this would have been a very different paper in scope and ambition.

  16. 16.

    The short-term claims per credit variable has been rescaled to be on similar scales as the rest of the regressors.

  17. 17.

    To instrument the interaction term we have regressed the endogenous variables insured trade credits on our instruments and the other explanatory variables in the first stage. The predicted value has then been interacted with the crisis dummy.

  18. 18.

    This is also why we do not take the logarithm of the share of short-term claims paid, as we would lose a large part of our observations otherwise.


  1. Amiti, M., & Weinstein, D. E. (2011). Exports and financial shocks. The Quarterly Journal of Economics, 126(4), 1841–1877.

    Article  Google Scholar 

  2. Baldwin, R. (2009). The great trade collapse: Causes, consequences and prospects, VoxEU.org ebook.

  3. Behrens, K., Corcos, G., & Mion, G. (2011). Trade Crisis? What Trade Crisis? (CEPR Discussion Paper 7956). London: Centre for Economic Policy Research.

  4. Berne Union (2010). Credit insurance in support of international trade: Observations throughout the crisis. Export Credit Insurance Report, Berne Union 2010.

  5. Bricongne, J.-C., Fontagné, L., Gaulier, G., Taglioni, D., & Vicard, V. (2012). Firms and the global crisis: French exports in the turmoil. Journal of International Economics, 87(1), 134–146.

    Article  Google Scholar 

  6. Bruegel. (2012). Real effective exchange rates for 178 countries: A new database (Bruegel Working Paper 2012/06).

  7. Chor, D., & Manova, K. (2012). Off the cliff and back? Credit conditions and international trade during the global financial crisis. Journal of International Economics, 87(1), 117–133.

    Article  Google Scholar 

  8. Development Working Group (2011). 2011 Report of the Development Working Group for the G20 Summit in Cannes. Accessible at: http://www.g20.utoronto.ca/summits/2011cannes.html.

  9. Eaton, J., Kortum, S., Neiman, B., & Romalis, J. (2011). Trade and the Global Recession (NBER Working Paper 16666). Cambridge, MA: National Bureau of Economic Research.

  10. Egger, P., & Url, T. (2006). Public export credit guarantees and foreign trade structure: Evidence from Austria. The World Economy, 29(4), 399–418.

    Article  Google Scholar 

  11. Eichengreen, B., & O’Rourke, K. H. (2010). What do the new data tell us, VoxEU.org, 8 March.

  12. Emran, M. S., & Shilpi, F. (2010). Estimating an import demand function in developing countries: A structural econometric approach with applications to India and Sri Lanka. Review of International Economics, 18(2), 307–319.

    Article  Google Scholar 

  13. Felbermayr, G., Heiland, I., & Yalcin, E. (2012). Mitigating liquidity constraints: Public export credit guarantees in Germany (CESifo Working Paper no. 3908).

  14. Felbermayr, G., & Yalcin, E. (2013). Export credit guarantees and export performance: An empirical analysis for Germany. The World Economy, 36(8), 967–999.

    Article  Google Scholar 

  15. Goldstein, M., & Khan M. S. (1985). Income and price effects in foreign trade. In Handbook of International Economics (pp. 1041–1105) Amsterdam: Elsevier.

  16. Hasselblad, V., Stead, A. G., & Galke, W. (1980). Analysis of coarsely grouped data from the lognormal distribution. Journal of the American Statistical Association, 75(372), 771–778.

    Article  Google Scholar 

  17. Hausman, J. A. (1978). Specification tests in econometrics. Econometrica, 46(6), 1251–1271.

    Article  Google Scholar 

  18. Hausman, J. A. (1983). Specification and estimation of simultaneous equation models. In Z. Griliches & M. D. Intriligato (Eds.), Handbook of econometrics (Vol. 1, pp. 391–448). Amsterdam: North-Holland.

    Google Scholar 

  19. Heitjan, D. F., & Rubin, D. B. (1990). Inference from coarse data via multiple imputation with application to age heaping. Journal of the American Statistical Association, 85(410), 304–314.

    Article  Google Scholar 

  20. Houthakker, H. S., & Magee, S. P. (1969). Income and price elasticities in world trade. Review of Economics and Statistics, 51(2), 111–125.

    Article  Google Scholar 

  21. ICC (2009). Rethinking Trade Finance 2009: An ICC Global Survey. ICC Banking Commission Market Intelligence Report, Document No. 470-1120 TS/WJ 31 March 09, International Chamber of Commerce, Paris.

  22. ICC (2011). Global Risks—Trade Finance 2011. International Chamber of Commerce, Paris: An initiative of the ICC Banking Commission.

    Google Scholar 

  23. IMF-BAFT Trade Finance Survey (2009). Survey among banks assessing current trade finance environment. Washington: IMF.

    Google Scholar 

  24. Korinek, J., Le Cocguic, J., & Sourdin, P. (2010). The availability and cost of short-term trade finance and its impact on trade (OECD Trade Policy Working Paper 98). Paris: Organisation for Economic Co-operation and Development.

  25. Krugman, P. R., & Obstfeld, M. (2009). International economics: Theory and policy. Boston: Pearson Education.

    Google Scholar 

  26. Levchenko, A. A., Lewis L. T., & Tesar L. L. (2010). The collapse of international trade during the 2008–2009 Crisis: In Search of the Smoking Gun (NBER Working Paper 16006). Cambridge, MA: National Bureau of Economic Research.

  27. Manova, K. (2012). Credit constraints, heterogeneous firms, and international trade. Mimeo: Stanford University.

    Google Scholar 

  28. Marquez, J. R. (2002). Estimating trade elasticities. Dordrecht: Kluwer.

    Google Scholar 

  29. Moser, C., Nestmann, T., & Wedow, M. (2008). Political risk and export promotion: Evidence from Germany. The World Economy, 31(6), 781–803.

    Article  Google Scholar 

  30. Paravisini, D., Rappoport, V., Schnabl, P., & Wolfenzon, D. (2011). Dissecting the effect of credit supply on trade: Evidence from matched credit-export data (NBER Working Paper 16975). Cambridge, MA: National Bureau of Economic Research.

  31. Petersen, M. A., & Rajan, R. (1997). Trade credit: Theories and evidence. Review of Financial Studies, 10(3), 661–691.

    Article  Google Scholar 

  32. Rubin, D. B. (1987). Multiple imputation for nonresponse in surveys. New York: Wiley.

    Google Scholar 

  33. Senhadji, A. (1998). Time-series estimation of structural import demand equations: A cross-country analysis. IMF Staff Papers, 45(2), 236–268.

    Article  Google Scholar 

  34. Staiger, D., & Stock, J. H. (1997). Instrumental variables regression with weak instruments. Econometrica, 65(3), 557–586.

    Article  Google Scholar 

  35. Van der Veer, K. (2010). The private credit insurance effect on trade (De Nederlandsche Bank Working Paper No. 264). SSRN: http://ssrn.com/abstract=1950076 or doi: 10.2139/ssrn.1950076.

Download references


We would like to thank the Berne Union for providing the data on export credit insurance and especially Fabrice Morel for his assistance with the data. Thanks are also due to Patrick Low for his support.

Author information



Corresponding author

Correspondence to Martina Engemann.



See Fig. 3; Tables 2, 3, 4, 5, 6, 7, 8, 9 and 10.

Table 2 List of countries included in the estimation sample
Table 3 Descriptive statistics
Table 4 Hausman (1978, 1983) test for endogeneity of insured trade credits
Table 5 Testing whether the instruments have a direct effect on real imports
Table 6 Estimation results without instrumenting short-term insured trade credits
Table 7 Second-stage results of import estimation controlling for a special crisis effect
Table 8 Second-stage results of import estimation using multiply imputed short-term claims data
Table 9 Second-stage results of import estimation using only merchandise imports
Table 10 Second-stage results of import estimation using a different definition of the crisis period
Fig. 3

Histogram of the ratio of insured trade credits scaled by real imports. Figure shows the distribution of insured trade credit over real imports in our estimation sample

About this article

Verify currency and authenticity via CrossMark

Cite this article

Auboin, M., Engemann, M. Testing the trade credit and trade link: evidence from data on export credit insurance. Rev World Econ 150, 715–743 (2014). https://doi.org/10.1007/s10290-014-0195-4

Download citation


  • Trade credit
  • Financial crisis
  • Import estimation

JEL Classification

  • F13
  • F34
  • G21
  • G23