The geographic determinants of bankruptcy: evidence from Switzerland
- 576 Downloads
This paper examines the geographic determinants of firm bankruptcy. We employ hazard rate models to study the bankruptcy risk of a firm, allowing for time-varying covariates. Based on a large sample from all geographic areas and the major sectors of the Swiss economy, we find the following main results: (1) Bankruptcy rates tend to be lower in the central municipalities of agglomerations; (2) bankruptcy rates are lower in regions with favorable business conditions (where corporate taxes and unemployment are low and public investment is high); (3) private taxes and public spending at the local level have little impact on bankruptcy rates.
KeywordsBankruptcy Geography Agglomeration Religion Language Exit
JEL ClassificationsC41 R10 Z10
We are grateful to the associate editor, Philipp Koellinger, and three anonymous referees for many detailed comments. We also thank Dirk Burghardt, Manfred Fischer, Bruno Frey, Dennis Gärtner, Luigi Guiso, Daniel Halbheer, Ulrich Kaiser, Mariko Klasing, Rico Maggi, Gianmarco Ottaviano, Dieter Pennerstorfer, Armin Schmutzler, Enrique Schroth, Christoph Weiss, and seminar participants at Arlington (IIOC 2008), Berne (Swiss IO Day 2006), Brussels (EcoMod), Lugano, Milan (EEA 2008), Munich (VfS 2007), Valencia (EARIE 2007), and Zurich for helpful discussions and suggestions. Support from the Swiss National Science Foundation (through grant no. PP0012-114754), the Swiss Federal Statistical Office, and the Cantonal Bank of St. Gallen is gratefully acknowledged. The usual disclaimer applies. In particular, the opinions expressed in this paper are those of the authors and are not attributable to HSBC. The authors are solely responsible for the contents.
- Audretsch, D. B. (1995). Innovation and industry evolution. Cambridge, MA: MIT Press.Google Scholar
- Audretsch, D. B., Bönte, W., & Tamvada, J. P. (2007). Religion and entrepreneurship. CEPR Discussion Paper No. 6378.Google Scholar
- Buehler, S., Kaiser, C., & Jaeger, F. (2005). Competition policy and exit rates: Evidence from Switzerland. Contributions to Economic Analysis & Policy, 4, Article 15. Available at: http://www.bepress.com/bejeap/contributions/vol4/iss1/art15.
- Caves, R. E. (1998). Industrial organization and new findings on the turnover and mobility of firms. Journal of Economic Literature, 36, 1947–1982.Google Scholar
- Combes, P. P., Duranton, G., Gobillon, L., & Puga, D. (2009). The productivity advantages of large cities: Distinguishing agglomeration from firm selection. Mimeo.Google Scholar
- Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society, Series, B34, 187–220.Google Scholar
- Dahl, M. S., & Sorenson, O. (2010). Home sweet home: entrepreneurs’ location choices and the performance of their ventures. Available at: http://www.ssrn.com/abstract=1596810. Accessed 27 Apr 2010.
- Duranton, G., & Puga, D. (2004). Micro-foundations of urban agglomeration economies. In J. V. Henderson & J. F. Thisse (Eds.), Handbook of regional and urban economics (Vol. 4, pp. 2063–2117). Amsterdam: North-Holland.Google Scholar
- Fujita, M., Krugman, P., & Venables, A. J. (1999). The spatial economy: Cities, regions, and international trade. Cambridge, MA: MIT Press.Google Scholar
- Gottmann, J. (1980). Center and periphery. London: Sage.Google Scholar
- Hardin, J., & Hilbe, J. (2007). Generalized linear models and extensions (2nd ed.). College Station, TX: Stata Press.Google Scholar
- Hudson, J. (1989). The birth and death of firm. Quarterly Review of Economics and Business, 29, 68–86.Google Scholar
- Jacobs, J. (1969). The economics of cities. New York: Vintage.Google Scholar
- Kalbfleisch, J. D., & Prentice, R. L. (1980). The statistical analysis of failure time data. New York: Wiley.Google Scholar
- Kiefer, N. M. (1988). Economic duration data and hazard functions. Journal of Economic Literature, 26, 646–679.Google Scholar
- Rosenthal, S. S., & Strange, W. C. (2004). Evidence on the nature and sources of agglomeration economies. In V. Henderson & J. F. Thisse (Eds.), Handbook of regional and urban economics (Vol. 4, pp. 2119–2171). Amsterdam: North-Holland.Google Scholar
- Swiss Federal Statistical Office. (2004). Religionslandschaft in der Schweiz (The religious landscape of Switzerland). Neuchâtel: Swiss Federal Statistical Office.Google Scholar
- Swiss Federal Statistical Office. (2005). Die Raumgliederung der Schweiz (The spatial structures of Switzerland). Neuchâtel: Swiss Federal Statistical Office.Google Scholar
- Symeonidis, G. (2002). The effects of competition. Cambridge, MA: MIT Press.Google Scholar
- Van den Berg, G. J. (2001). Duration models: Specification, identification, and multiple durations. In J. J. Heckman & E. Leamer (Eds.), Handbook of econometrics (Vol. V, pp. 3381–3460). Amsterdam: North Holland.Google Scholar