Skip to main content
SpringerLink
Log in

Economic failure and the role of plant age and size

  • Published:
Small Business Economics Aims and scope Submit manuscript

Abstract

This paper introduces a large-scale administrative panel data set on corporate bankruptcy in Germany that allows for an econometric analysis of involuntary exits where previous studies mixed voluntary and involuntary exits. Approximately 83 % of all bankruptcies occur in plants with not more than 10 employees, and 61 % of all bankrupt plants are not older than 5 years. The descriptive statistics and regression analysis indicate substantial negative age dependence with respect to bankruptcy risk but confirm negative size dependence for mature plants only. Our results corroborate hypotheses stressing increasing capabilities and positional advantage, both predicting negative age dependence with respect to bankruptcy risk due to productivity improvements. The results are not consistent with the theories explaining age dependence via imprinting or structural inertia.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Notes

  1. Fackler et al. (2013a) provide evidence for the reasons for plant closure in Germany. They do not use bankruptcy information and do not distinguish between voluntary and involuntary closure.

  2. A similar argumentation can, e.g., be found in Honjo (2000:560).

  3. Coad (2013) proposes to use the term ‘death’ instead of ‘failure.’ As ‘death’ summarizes voluntary and involuntary closures, however, this term is not very useful for our discussion.

  4. German bankruptcy law distinguishes between consumer bankruptcy and regular bankruptcy, the latter accounting for corporate bankruptcy. According to these regulations, local district courts are responsible for the implementation of bankruptcy proceedings. Bankruptcy proceedings are initiated at the request of creditors or debtors and require illiquidity or over-indebtedness on the part of the firm. The court will not initiate the process if these conditions are not met. The two most important decisions in the course of the process are whether to formally begin the bankruptcy proceeding and whether to reject claims because the remaining assets are insufficient to cover the expenses of the bankruptcy proceedings. Both decisions also underlie the official figures and are part of our data.

  5. For a case in point, see Jirjahn et al. (2011). They provide a theoretical discussion of how the relationship between management and a formal employee representation evolves over time and how it may increase firm productivity.

  6. This includes, for instance, the IAB Establishment Panel, the Linked-Employer-Employee Data (LIAB), and individual-level data (SIAB and IEB) provided by the Institute for Employment Research of the BA (IAB).

  7. The BHP is described in Hethey-Maier and Seth (2010).

  8. Because we intend to measure involuntary closures, our definition of bankruptcy risk deliberately assigns plants that survive the bankruptcy process to the denominator.

  9. Throughout the paper, we will use the same age and size categories as presented in the figures. The categories are chosen such that there are a sufficient number of observations per category interaction, e.g., plants being small and old. Note that we do not opt for continuous age and size variables as it turns out that restrictions such as linearity or log-linearity in the interaction effects are not supported by our multivariate results.

  10. Computing plant age from the first appearance of a plant ID in the data can lead to underestimation of true plant age, as a new plant ID may, e.g., reflect a change in ownership instead of the true date of plant foundation. Note that all our results concerning age dependence hold if we use worker flows to indicate and exclude ambiguous entries (see Hethey and Schmieder 2010). However, using worker flows to exclude ambiguous entries yields somewhat more pronounced negative size dependence. See the corresponding results in Figs. 5 and 6. We do not employ the restricted sample in subsequent analysis, as a considerable number of plants are dropped due to missing values in the entry classification scheme.

  11. As discussed previously, all results of the cross-tabulation remain qualitatively unchanged when excluding ambiguous entries.

  12. As described in Sect. 2, however, we include bankruptcies where the court refuses to open a formal bankruptcy trial because assets are too low to pay the liquidator. We therefore capture the vast majority of cases.

  13. We do not disaggregate exits according to the classifications in Hethey and Schmieder (2010) as it is necessarily arbitrary how to define the exit classes and to decide with which class our data should be compared. What is more, we think that using all vanishing IDs is more instructive for researchers who do not have linked employer–employee data necessary to apply the worker flow measures in Hethey and Schmieder (2010).

  14. The number of observations in Table 5 is higher than in Table 1 because, as described in the text, in Table 1 all observations with vanishing ID but without bankruptcy filing are excluded from the denominator, while in Appendix Table 5 we exclude the much smaller number of exits with bankruptcy.

  15. Fackler et al. (2013a) use a subset of the data on vanishing plant IDs used in our study. Looking at the years 2001–2006, they also find evidence for U-shaped age dependency. Also using the BHP data but not reporting how exit is measured, Schindele and Weyh (2011) show increasing hazard rates for older plants in their survival analysis of entry cohorts.

  16. The advantages of OLS over probit or logit estimators are the straightforward interpretation of coefficients as marginal effects and, given 7,822,643 observations, its computational efficiency. See Fackler et al. (2013a) for a detailed explanation.

  17. Note that our results for size dependence in failure risk could be influenced by what Griliches and Regev (1995) have termed the ‘shadow of death.’ A “shadow of death” in employment means that plants shrink for a considerable amount of time before they ultimately exit the market (see also Fackler et al. 2013b). In our data, plant size categories are defined by the number of employees on the last 30th of June on which the plant exists and may therefore not reflect the plant’s long-run employment level. However, a ‘shadow of death’ cannot explain why we do not find negative size dependence because any reduction in employment just prior to exit moves bankrupt plants into lower size categories and would therefore artificially produce negative size dependence.

  18. The share of part-time workers working fewer than 18 h per week may seem implausibly high at first glance, in particular within smaller plants. The figures represent means over plant-level averages, such that each plant has the same weight. Within each size category, the smallest plants constitute the highest share among all plants, and hence, employment shares at the plant level may be very different from the corresponding shares at the worker level, as is typically reported in official statistics.

  19. For comparison, Fig. 7 in Appendix presents results from a regression analysis of vanishing plant IDs instead of bankruptcies. The definition of the dependent variable is described in Sect. 5. Not surprisingly, the insights derived from the regression are also quite similar to those from the descriptive evidence and therefore differ much from the analysis of bankruptcy risk.

  20. As discussed previously, all results remain qualitatively unchanged when we exclude ambiguous entries.

  21. Comparing columns (1) and (3) of Table 4 reveals that controlling for wages reverses the sign of the East Germany dummy. Thus, conditional on the same wage structure, East German plants are, ceteris paribus, less likely to fail than their West German competitors. Because East German wages and productivity levels are on average much lower than those in West Germany, conditioning on wages implies comparing a high-wage (high-productivity) East German plant with a low wage (low productivity) West German plant. As long as the relative position in the local productivity distribution affects bankruptcy risk, the change in the sign of the East Germany regressor demonstrates that wages capture unobserved productivity differences that would otherwise be reflected in the coefficients of other regressors, whether in the region dummy or in the age or size dummies.

  22. Audretsch and Mahmood (1995:101) also report that entrants reduce failure risk by increasing start-up size.

References

  • Aldrich, H., & Auster, E. A. (1986). Even dwarfs started small: Liabilities of age and size and their strategic implications. Research in Organizational Behavior, 8, 165–198.

    Google Scholar 

  • Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of bankruptcy. Journal of Finance, 23, 589–609.

    Article  Google Scholar 

  • Arrow, K. J., & Lind, R. C. (1970). Uncertainty and the evaluation of public investment decisions. American Economic Review, 60(3), 364–378.

    Google Scholar 

  • Audretsch, D. B. (1991). New-firm survival and the technological regime. The Review of Economics and Statistics, 73(3), 441–450.

    Article  Google Scholar 

  • Audretsch, D. B., & Mahmood, T. (1995). New firm survival: New results using a hazard function. The Review of Economics and Statistics, 77(1), 97–103.

    Article  Google Scholar 

  • Audretsch, D. B., Santarelli, E., & Vivarelli, M. (1999). Start-up size and industrial dynamics: Some evidence from Italian manufacturing. International Journal of Industrial Organization, 17, 965–983.

    Article  Google Scholar 

  • Barron, D. N., West, E., & Hannan, M. T. (1994). A time to grow and a time to die: Growth and mortality of credit unions in New York City, 1914–1990. American Journal of Sociology, 100(2), 381–421.

    Article  Google Scholar 

  • Bates, T. (2005). Analysis of young, small firms that have closed: Delineating successful from unsuccessful closures. Journal of Business Venturing, 20, 343–358.

    Article  Google Scholar 

  • Bender, S., Hilzendegen, J., Rohwer,G., & Rudolph, H. (1996). Die IAB-Beschäftigtenstichprobe 1975–1990. Beiträge zur Arbeitsmarkt- und Berufsforschung 197, Nürnberg.

  • Benedetto, G., Haltiwanger, J., Lane, J., & McKinney, K. (2007). Using worker flows to measure firm dynamics. Journal of Business and Economic Statistics, 25(3), 299–313.

    Article  Google Scholar 

  • Benmelech, E., & Bergman, N. (2011). Bankruptcy and the collateral channel. Journal of Finance, 56(2), 337–378.

    Article  Google Scholar 

  • Blossfeld, H.-P. (1987). Labor market entry and the sexual segregation of careers in the Federal Republic of Germany. The American Journal of Sociology, 93(1), 89–118.

    Article  Google Scholar 

  • Bottazzi, G., & Tamagni, F. (2011). Big and fragile: When size does not shield from default. Applied Economics Letters, 18(14), 1401–1404.

    Article  Google Scholar 

  • Brüderl, J., & Schüssler, R. (1990). Organizational mortality: The liabilities of newness and adolescence. Administrative Science Quarterly, 35(3), 530–547.

    Article  Google Scholar 

  • Carreira, C., & Silva, F. (2010). No deep pockets: Some stylized empirical results on firms’ financial constraints. Journal of Economic Surveys, 24(4), 731–753.

    Article  Google Scholar 

  • Coad, A. (2013). Death is not a success: Reflections on business exit. International Small Business Journal,. doi:10.1177/0266242612475104.

    Google Scholar 

  • Egeln, J., Falk, U., Heger, D., Höwer, D., & Metzger, G. (2010). Ursachen für das Scheitern junger Unternehmen in den ersten fünf Jahren ihres Bestehens. Mannheim/Neuss: ZEW.

    Google Scholar 

  • Esteve-Perez, S., & Manez-Castillejo, J. A. (2008). The resource-based theory of the firm and firm survival. Small Business Economics, 30, 231–249.

    Article  Google Scholar 

  • Fackler, D., Schnabel, C., & Wagner, J. (2013a). Establishment exits in Germany: The role of size and age. Small Business Economics, 41(3), 683–700.

    Article  Google Scholar 

  • Fackler, D., Schnabel, C., & Wagner, J. (2013b). Lingering illness or sudden death? Pre-exit employment developments in German establishments. Industrial and Corporate Change. doi: 10.1093/icc/dtt041.

  • Geroski, P. A., Mata, J., & Portugal, P. (2010). Founding conditions and the survival of new firms. Strategic Management Journal, 31, 510–529.

    Google Scholar 

  • Griliches, Z., & Regev, H. (1995). Firm productivity in Israeli industry 1979–1988. Journal of Econometrics, 65, 175–203.

    Article  Google Scholar 

  • Hannan, M. T., Carroll, G. R., Dobrev, S. D., & Han, J. (1998). Organizational mortality in European and American automobile industries Part I: Revisiting the effects of age and size. European Sociological Review, 14(3), 279–302.

    Article  Google Scholar 

  • Hannan, M. T., & Freeman, J. (1977). The population ecology of organizations. American Journal of Sociology, 82(5), 929–964.

    Article  Google Scholar 

  • Harhoff, D., Stahl, K., & Woywode, M. (1998). Legal form, growth and exit of West German Firms—Empirical results for manufacturing, construction, trade and service industries. The Journal Of Industrial Economics, 46(4), 453–488.

    Article  Google Scholar 

  • Headd, B. (2003). Redefining business success: Distinguishing between closure and failure. Small Business Economics, 21(1), 51–61.

    Article  Google Scholar 

  • Hethey, T., & Schmieder, J. F. (2010). Using worker flows in the analysis of establishment turnover—Evidence from German Administrative Data. FDZ Methodenreport 06/2010. Nürnberg.

  • Hethey-Maier, T. & Seth, D. (2010). The Establishment History Panel (BHP) 1975–2008. FDZ-Datenreport, 04/2010, Nürnberg.

  • Honjo, Y. (2000). Business failure of new firms: An empirical analysis using a multiplicative hazards model. International Journal of Industrial Organization, 18, 557–574.

    Article  Google Scholar 

  • Hudson, J. (1986). An analysis of company liquidation. Applied Economics, 18(2), 219–235.

    Article  Google Scholar 

  • Jirjahn, U., Mohrenweiser, J., & Backes-Gellner, U. (2011). Works councils and learning: On the dynamic dimension of codetermination. Kyklos, 64(3), 427–447.

    Article  Google Scholar 

  • Jovanovic, B. (1982). Selection and the evolution of industry. Econometrica, 50(3), 649–670.

    Article  Google Scholar 

  • Lennox, C. (1999). Identifying failing companies: A reevaluation of the logit, probit and DA approaches. Journal of Economics and Business, 51, 347–364.

    Article  Google Scholar 

  • Levinthal, D. A. (1991). Random walks and organizational mortality. Administrative Science Quarterly, 36(3), 397–420.

    Article  Google Scholar 

  • Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7, 77–91.

    Google Scholar 

  • Mata, J., Antunes, A., & Portugal, P. (2011). Borrowing patterns, bankruptcy, and voluntary liquidation. Working paper, Banque de France.

  • Mata, J., & Portugal, P. (1994). Life duration of new firms. The Journal of Industrial Economics, 42(3), 227–245.

    Article  Google Scholar 

  • Mata, J., Portugal, P., & Guimaraes, P. (1995). The survival of new plants: Start-up conditions and post-entry evolution. International Journal of Industrial Organization, 13, 459–481.

    Article  Google Scholar 

  • Sarasvathy, S. D., Menon, A. R., & Kuechle, G. (2013). Failing firms and successful entrepreneurs: Serial entrepreneurship as a temporal portfolio. Small Business Economics, 40, 417–434.

    Article  Google Scholar 

  • Schary, M. A. (1991). The probability of exit. The Rand Journal of Economics, 22(3), 339–353.

    Article  Google Scholar 

  • Schindele, Y., & Weyh, A. (2011). The direct employment effects of new businesses in Germany revisited: An empirical investigation for 1976–2004. Small Business Economics, 36(3), 353–363.

    Article  Google Scholar 

  • Stinchcombe, A. L. (1965). Social structure and organization. In J. G. March (Ed.), Handbook of organizations (pp. 142–193). Chicago: Rand McNally.

    Google Scholar 

  • Strotmann, H. (2007). Entrepreneurial survival. Small Business Economics, 28, 87–104.

    Article  Google Scholar 

  • Taylor, M. P. (1999). Survival of the fittest? An analysis of selfemployment duration in Britain. Economic Journal, 109, C140–C155.

    Article  Google Scholar 

  • Van Praag, C. M. (2003). Business survival and success of young small business owners. Small Business Economics, 21(1), 1–17.

    Article  Google Scholar 

  • Wheelock, D. C., & Wilson, P. W. (2000). Why do banks disappear? The determinants of U.S. bank failures and acquisitions. The Review of Economics and Statistics, 82(1), 127–138.

    Article  Google Scholar 

  • Woywode, M. (1998). Determinanten der Überlebenswahrscheinlichkeit von Unternehmen. Eine empirische Überprüfung organisationstheoretischer und industrieökonomischer Erklärungsansätze. Nomos, Baden-Baden.

Download references

Acknowledgments

The authors thank Daniel Fackler, Claus Schnabel, Till von Wachter, and two anonymous referees for helpful comments. This study is based on customized data. We therefore thank Cerstin Rauscher, other IAB staff members, and staff members of the German Federal Employment Agency for their indispensable support concerning data provision.

Author information

Authors and Affiliations

  1. Halle Institute for Economic Research (IWH), Halle (Saale), Germany

    Steffen Mueller

  2. University of Magdeburg, Magdeburg, Germany

    Steffen Mueller

  3. Institute for Employment Research (IAB), Nuremberg, Germany

    Jens Stegmaier

Authors
  1. Steffen Mueller
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jens Stegmaier
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Steffen Mueller.

Appendix

Appendix

See Figs. 5, 6, 7 and Table 5.

Fig. 5
figure 5

Bankruptcy risk by plant age and year (years 2007–2010), w/o ambiguous entries

Full size image
Fig. 6
figure 6

Bankruptcy risk by plant size and year (years 2007–2010), w/o ambiguous entries

Full size image
Fig. 7
figure 7

Effects on exit probability (w/o bankruptcies), OLS coefficients for interaction terms of plant age and size (years 2007–2010). Notes: The figures illustrates the results from a regression as presented in Panel B of Table 3 but where the dependent variable indicates exit for all plants that closed without bankruptcy filing

Full size image
Table 5 Exit probability (w/o bankruptcies) by age and size (in  %), years 2007–2010
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mueller, S., Stegmaier, J. Economic failure and the role of plant age and size. Small Bus Econ 44, 621–638 (2015). https://doi.org/10.1007/s11187-014-9616-y

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11187-014-9616-y

Keywords

JEL Classifications

Search

Navigation