The agglomeration of exporters by destination

Abstract

Precise characterization of informational trade barriers is neither well documented nor understood. Using Russian customs data, we document that regional destination-specific export spillovers exist for developing countries, extending a result that was only known for developed countries. This result suggests behavior responding to a destination barrier. To account for this fact, we build on a monopolistic competition model of trade by postulating an externality in the international transaction of goods. We test the model’s prediction on region-level exports using Russian data and find improvement over gravity-type models without agglomeration. This finding has important development implications in that export policy that considers current trade partners may be more effective than policy that focuses only on the exporting country’s industries. Furthermore, our findings can be considered in the burgeoning literature refining transaction costs beyond the traditional iceberg cost.

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Fig. 1
Fig. 2

Notes

  1. 1.

    Cassey (2009) shows that for the United States, manufacturing data are the only data that can be reliably used for the state of production of the export instead of the state where the export began its journey abroad, whereas agriculture and mining data are not reliable.

  2. 2.

    Le Gallo and Dall’erba (2008) find no significant difference in results if they use great circle distances or travel time by road from the most populous town.

  3. 3.

    Russia’s federal regions are somewhat similar in geographic scope to US states. The number of regions has decreased since 2003 because of mergers. It is common to study Russia at this level of geographic disaggregation. See Broadman and Recanatini (2001) for example.

  4. 4.

    These results are robust to using export volume instead of the number of exporting firms.

  5. 5.

    Korinek and Sourdin (2010) show that shipping companies quote transportation rates in cost per container.

  6. 6.

    Martin et al. (2008) find that agglomeration positively affects firm productivity. To address this issue, Koenig et al. (2010) introduce a total factor productivity (TFP) variable to prevent overestimation of spillovers. In our data, we are unable to construct such a variable; however, Koenig et al. show that including productivity, while significant, does not affect the coefficient on the spillover.

  7. 7.

    Koenig et al. (2010) write, “Results are coherent with a linear specification since the effect on starting to export of having one neighbor exporting the same product to the same destination compared to zero (0.072) is very similar to the effect of having two neighbors instead of one, and of having three neighbors instead of two.”

  8. 8.

    We do, however, acknowledge that there other are bilateral variables such as immigration. But we believe that these are of secondary importance because the patterns of regional Russian immigrants (or the 185 identified ethnic groups in Russia) to the 175 countries in the world are unlikely to be empirically relevant compared to the product of GDPs.

  9. 9.

    The estimates for a “naive” gravity equation are

    $$\begin{aligned} \log X_{ij}&= -\underset{(0.580)}{0.84}+\underset{(0.043)^{*}}{0.56}\log Y_i+\underset{(0.020)^{*}}{0.29}\log Y_j-\underset{(0.065)^{*}}{1.17}\log D_{ij}\\&N=2,\!985, \quad \hat{R^2}=0.15, \; \text{ RMSE}=2.45 \end{aligned}$$
    Table 2 OLS estimates on Russian data
  10. 10.

    A logistic regression similar to (2) except replacing the number of exporting firms with aggregate weight yields:

    $$\begin{aligned} E_{ij}&= \underset{(0.074)^{}}{0.567}+\underset{(0.002)^{*}}{0.230}\log W_{ij}-\underset{(0.008)^{*}}{0.764}\log D_{ij}-\underset{(0.004)^{*}}{0.329}\log Y_i+\underset{(0.003)^{*}}{0.076}\log Y_j\\&N=3{,}979{,}007\nonumber \end{aligned}$$
    (5)

References

  1. Anderson JE, van Wincoop E (2003) Gravity with gravitas: a solution to the border puzzle. Am Econ Rev 93(1):170–192

    Article  Google Scholar 

  2. Armenter R, Koren M (2010) A balls-and-bins model of trade, unpublished

  3. Axtell RL (2001) Zipf distribution of US firm sizes. Science 293(5536):1818–1820

    Article  Google Scholar 

  4. Bernard AB, Jensen JB (2004) Why some firms export. Rev Econ Stat 86(2):561–569

    Article  Google Scholar 

  5. Besedeš T, Prusa TJ (2006) Product differentiation and duration of US import trade. J Int Econ 70(2): 339–358

    Article  Google Scholar 

  6. Bradshaw M (2008) The geography of Russia’s new political economy. New Polit Econ 13(2):193–201

    Article  Google Scholar 

  7. Broadman HG, Recanatini F (2001) Where has all the foreign investment gone in Russia? World Bank Policy Research working paper no. 2640

  8. Cassey AJ (2009) State export data: origin of movement vs. origin of production. J Econ Soc Meas 34(4):241–268. doi:10.3233/JEM-2009-0323

    Google Scholar 

  9. Cassey AJ (2012) An application of the Ricardian trade model with trade costs. Appl Econ Lett 19(13): 1227–1230

    Article  Google Scholar 

  10. Cassey AJ, Schmeiser KN (2013) Six comparisons of firm-level and product-level data. Appl Econ Lett 20(4):382–385

    Article  Google Scholar 

  11. Chaney T (2008) Distorted gravity: the intensive and extensive margins of international trade. Am Econ Rev 98(4):1707–1721

    Article  Google Scholar 

  12. Choquette E, Meinen P (2011) Export spillovers and the extensive and intensive margins of trade, http://www.etnpconferences.net/sea/sea2011/PaperSubmissions/Submissions2011/S-F-22.pdf, unpublished

  13. Crozet M, Koenig P (2010) Structural gravity equations with intensive and extensive margins. Can J Econ 43(1):41–62

    Article  Google Scholar 

  14. Eaton J, Eslava M, Kugler M, Tybout JE (2008) Export growth in Colombia: firm-level evidence. In: Helpman E, Marin D, Verdier T (eds) The organization of firms in a global economy. Harvard University Press, Cambridge, pp 231–272

    Google Scholar 

  15. Eaton J, Kortum S, Kramarz F (2011) An anatomy of international trade: evidence from French firms. Econometrica 79(5):1453–1498

    Article  Google Scholar 

  16. Fujita M, Thisse JF (1996) Economics of agglomeration. J Jpn Int Econ 10(4):339–378

    Article  Google Scholar 

  17. Glejser H, Jacquemin A, Petit J (1980) Exports in an imperfect competition framework: an analysis of 1,446 exporters. Q J Econ 94(3):507–524

    Article  Google Scholar 

  18. Head K, Ries J, Swenson D (1995) Agglomeration benefits and location choice: evidence from Japanese manufacturing investments in the United States. J Int Econ 38(3–4):223–247

    Article  Google Scholar 

  19. Hummels D (2001) Toward a geography of trade costs. Center for Global Trade Analysis, Purdue University GTAP working paper no. 1162

  20. IMF (2006) World economic outlook database. international monetary fund, Washington, DC, http://www.imf.org/external/pubs/ft/weo/2006/01/data/index.htm. Accessed Dec 15, 2006

  21. Koenig P (2009) Agglomeration and the export decisions of French firms. J Urban Econ 66(3):186–195

    Article  Google Scholar 

  22. Koenig P, Mayneris F, Poncet S (2010) Local export spillovers in France. Eur Econ Rev 54(4):622–641

    Article  Google Scholar 

  23. Korinek J, Sourdin P (2010) Maritime transport costs and their impact on trade. Appl Econ Perspect Policy 32(3):417–435

    Article  Google Scholar 

  24. Krautheim S (2012) Heterogenous firms, exporter networks and the effect of distance on international trade. J Inter Econ 87(1):27–35

    Article  Google Scholar 

  25. Le Gallo J, Dall’erba S (2008) Spatial and sectoral productivity convergence between european regions, 1975–2000. Pap Reg Sci 87(4):505–525

    Article  Google Scholar 

  26. Lovely ME, Rosenthal SS, Sharma S (2005) Information, agglomeration, and the headquarters of US exporters. Reg Sci Urban Econ 35(2):167–191

    Article  Google Scholar 

  27. Marshall A (1920) Principles of economics, Revised edn. Macmillan, London

  28. Martin P, Mayer T, Mayneris F (2008) Spatial concentration and firm-level productivity in France. CEPR discussion paper no. 6858

  29. Melitz MJ (2003) The impact of trade on intra-industry reallocations and aggregate industry productivity. Econometrica 71(6):1695–1725

    Article  Google Scholar 

  30. Micco A, Pérez N (2002) Determinants of maritime transport costs. http://www.iadb.org/res/publications/pubfiles/pubWP-441.pdf, Inter-American Development Bank working paper no. 441

  31. Nuadé W, Matthee M (2007) The geographical location of manufacturing exporters in South Africa, United Nations University-World Institute for Development Economics Research working paper no. 2007/09

  32. Ottaviano G, Tabuchi T, Thisse JF (2002) Agglomeration and trade revisited. Int Econ Rev 43(2):409–436

    Article  Google Scholar 

  33. Rauch J (1999) Networks versus markets in international trade. J Int Econ 48(1):7–35

    Article  Google Scholar 

  34. Russia (2004, 2006) All regions trade and investment guide. CTEC Publishing LLC, Moscow

  35. Schmeiser K (2012) Learning to export: Export growth and the destination decision of firms. J Int Econ 87(1):89–97

    Article  Google Scholar 

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Acknowledgments

The authors thank Thomas Holmes, Yelena Tuzova, Anton Cheremukhin, and seminar participants at Amherst College, Vasser College, Washington State University, Kansas State University, University of Scranton, University of Richmond, and the Midwest International Trade Conference and New York Economics Association annual meetings. Cassey thanks Qianqian Wang and Pavan Dhanireddy for research assistance, and Jeremy Sage for help with ArcGIS. Cassey also thanks the Western Regional Science Association and the editors of the Annals of Regional Science. Portions of this research are supported by the Agricultural Research Center Project #0540 at Washington State University. This manuscript received the Springer Award for best paper by an early career scholar at the 51st Annual WRSA Meeting, Kaui HI, February 2012.

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Cassey, A.J., Schmeiser, K.N. The agglomeration of exporters by destination. Ann Reg Sci 51, 495–513 (2013). https://doi.org/10.1007/s00168-012-0538-9

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JEL Classification

  • D23
  • F12
  • L29