Firm survival: methods and evidence

Abstract

This paper surveys the Industrial Organization literature on firm survival. We find that, in retrospect, the econometric specifications used in this area have progressively become more sophisticated, addressing issues such as discrete time, unobserved heterogeneity and competing risks. We also identify a number of firm- and industry-specific covariates that provide largely consistent results across samples, countries and periods. On the other hand, the evidence is less clear-cut with regard to ownership and spatial factors.

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

Notes

  1. 1.

    It is worth stressing that we restrict our attention to those investigations that discuss inferences obtained from duration models using an Industrial Organisation perspective (broadly defined). This selection criterion allows us to keep the number of analysed references within reasonable limits and, more importantly, make the studies involved in this survey largely comparable. In practice this means that we have excluded papers that merely report descriptive statistics and/or univariate estimates, that use econometric specifications different from duration models and that focus on the particular case of self-employment. On the other hand, we did include some references from the Organizational Ecology. We found that, although these papers adopt a “distinctly sociological perspective” (Hannan 2005: 53), this exception was necessary for a comprehensive treatment of the effects of age and size on firm survival (see Sect. 3.1).

  2. 2.

    Time-variant covariates and alternative sampling schemes raise a number of technical problems in duration models (Lancaster 1990; van den Berg 2001). However, we have judged it unnecessary to address them because they are not frequent in firm survival studies and, in any case, under certain conditions they can be easily handled in the simple models described here (Jenkins 2005).

  3. 3.

    There is no general agreement on the definition of business failure. Some studies associate failure with bankruptcy, while others argue that failure occurs if the firm fails to meet its responsibilities to its stakeholders. In practice, the definition of exit largely depends on the available information. For example, if there is information on mergers and acquisitions, the larger firm is judged to continue and the smaller to exit. It is also common to judge that the firm has exited if it does not appear in the database for two (or more) consecutive periods.

  4. 4.

    For example, for right censored observations T = min{T*, C}, being T* the latent failure time and C the (latent) censoring time.

  5. 5.

    In fact, we could not find any investigation on firm survival using alternative specifications such as e.g., additive and log-linear hazards (Lancaster 1990; Linton et al. 2003). It is also interesting to note that, despite their popularity, neither the PH model nor the AFT model “can be (…) justified on economic-theoretical grounds” (van den Berg 2001: 3403).

  6. 6.

    The PH model in regression form corresponds to the following expression: \( {{ - }}\ln {\int_{{0}}^t {{\mathop \theta \nolimits_0 }} }{{(}}u{{) }}du \, = \,\beta^{\prime} {{x + }}\varepsilon \), with the error term following the Type 1 Extreme Value distribution. “Thus, the two specifications are general in different ways. The proportional hazard model restricts the distribution of the additive error but allows fairly general transformations of the duration variable to achieve linearity in regressors. The accelerated lifetime model restricts the transformation for duration but allows fairly general error distributions” (Kiefer 1988: 669).

  7. 7.

    Alternative distributions include e.g., the Inverse Gaussian, which was originally proposed by Lancaster (1972) in his analysis of strike durations. However, in general these distributions do not generate conditional hazard functions within the PH-ATF frameworks and to our knowledge have not been used in the analysis of firm survival.

  8. 8.

    Other firm survival studies that explore competing risks specifications are, for example, Wheelock and Wilson (2000) and Mata and Portugal (2000). The former analyse acquisition and bankruptcy in the US banking sector and the latter distinguish between liquidation and divestiture in a sample of new foreign manufacturing firms. Unfortunately, none of them provide comparative results from single-spell models.

  9. 9.

    See Table 2 for a list of IO studies analysing the effects of size and age. In Organizational Ecology (see Hannan 2005), the fact that smaller firms have a higher risk of failure is known as the “liability of smallness” (Freeman et al. 1983). Similarly, the “liability of newness” refers to the higher risk of failure faced by younger firms (Stinchcombe 1965). See also Brüderl and Schussler (1990) and Fichman and Levinthal (1991) on the so-called “liability of adolescence” and Barron et al. (1996) on the “liability of senescence”.

  10. 10.

    Other strategic activities that have been investigated are advertising (Segarra and Callejón 2002; Kimura and Fujii 2003; Esteve and Mañez 2007) and exporting (Kimura and Fujii 2003; Esteve et al. 2004; Esteve and Mañez 2007). The overall conclusion is that firms engaging in these activities seem to have lower hazard rates.

  11. 11.

    In contrast, capital intensity (Audretsch and Mahmood 1995; Tveterås and Eide 2000; Agarwal and Gort 2002), price-cost margin (Audretsch and Mahmood 1995; Honjo 2000; Segarra and Callejón 2002) and market concentration (Mata and Portugal 1994, 2002; Görg and Strobl 2003; López and Puente 2007; Strotmann 2007) are industry-specific characteristics that do not seem to provide consistent results.

  12. 12.

    Another study worth mentioning is that of Fritsch et al. (2006), who have recently shown that the survival rates of West German establishments depend not only on regional and sectorial characteristics but also on the number of start-ups in neighbouring regions. In other words, they provide indirect evidence of spatial autocorrelation in the survival rates using a linear specification (robustly) estimated by OLS.

  13. 13.

    This does not mean that the conditions at entry do not matter (Hannan 2005). A good financial structure, for example, may be critical for the future prospects of the new firm (Honjo 2000; López-García and Puente 2007).

References

  1. Addison JT, Portugal P (1998) Some specification issues in unemployment duration analysis. Labour Econ 5:53–66

    Article  Google Scholar 

  2. Agarwal R, Audretsch DB (2001) Does entry size matter? The impact of the life cycle and technology on firm survival. J Ind Econ 49:21–43

    Article  Google Scholar 

  3. Agarwal R, Gort M (2002) Technological change. Firm and product life cycle and firm survival. Am Econ Rev 92:184–190

    Article  Google Scholar 

  4. Agarwal R, Sarkar M, Echambadi R (2002) The conditioning effect of time on firm survival: an industry life cycle approach. Acad Manage J 45:971–994

    Google Scholar 

  5. Allison PD (1995) Survival analysis using the SAS system: a practical guide. SAS Institute Inc., Cary, NC

    Google Scholar 

  6. Andersen PK, Borgan O, Gill RD, Keiding N (1993) Statistical models based on counting processes. Springer, New York

    Google Scholar 

  7. Audretsch DB (1991) New firm survival and the technological regime. Rev Econ Stat 73:441–450

    Article  Google Scholar 

  8. Audretsch DB (1995) Innovation and industry evolution. The MIT Press, Cambridge, MA

    Google Scholar 

  9. Audretsch DB, Mahmood T (1991) The hazard rate of new establishments: a first report. Econ Lett 36:409–412

    Article  Google Scholar 

  10. Audretsch DB, Mahmood T (1994) The rate of hazard confronting new firms and plants in U.S. manufacturing. Rev Ind Organ 9:41–56

    Article  Google Scholar 

  11. Audretsch DB, Mahmood T (1995) New firm survival: new results using a hazard function. Rev Econ Stat 77:97–103

    Article  Google Scholar 

  12. Barron DN, West E, Hannan MT (1996) A time to grow and a time to die: growth and mortality of credit unions in New York City, 1914–1990. Am J Sociol 100:381–421

    Article  Google Scholar 

  13. Brüderl J, Schussler R (1990) Organizational mortality: the liabilities of newness and adolescence. Adm Sci Q 35:530–547

    Article  Google Scholar 

  14. Caves RE (1998) Industrial organization and new findings on the turnover and mobility of firms. J Econ Lit 36:1947–1982

    Google Scholar 

  15. Cefis E, Marsili O (2005) A matter of life and death: innovation and firm survival. Ind Corp Change 14:1–26

    Article  Google Scholar 

  16. Cleves MA, Gould WW, Gutierrez RG (2004) An introduction to survival analysis using Stata, Revised edn. Stata Press, College Station, TX

  17. Cox DR (1972) Regression models and life tables. J R Stat Soc (Ser B) 34:187–202

    Google Scholar 

  18. Disney R, Haskel J, Heden Y (2003) Entry, exit and establishment survival in UK manufacturing. J Ind Econ 51:91–112

    Article  Google Scholar 

  19. Dolton PJ, van der Klaauw W (1995) Leaving teaching in the UK: a duration analysis. Econ J 105:431–444

    Article  Google Scholar 

  20. Ericson R, Pakes A (1995) Markov-perfect industry dynamics: a framework for empirical work. Rev Econ Stud 62:53–82

    Article  Google Scholar 

  21. Esteve S, Mañez J (2007) The resource-based theory of the firm and firm survival. Small Business Economics, forthcoming

  22. Esteve S, Sanchis A, Sanchis JA (2004) The determinants of survival of Spanish manufacturing firms. Rev Ind Organ 25:251–273

    Article  Google Scholar 

  23. Fichman M, Levinthal DA (1991) Honeymoons and the liability of adolescence: a new perspective on duration dependence in social and organizational relationships. Acad Manage Rev 16:442–468

    Article  Google Scholar 

  24. Fotopoulos G, Louri H (2000) Location and survival of new entry. Small Bus Econ 14:311–321

    Article  Google Scholar 

  25. Freeman J, Carroll G, Hannan M (1983) The liability of newness: age dependence in organizational death rates. Am Sociol Rev 48:692–710

    Article  Google Scholar 

  26. Fritsch M, Brixy U, Falck O (2006) The effect of industry, region, and time on new business survival––a multi-dimensional analysis. Rev Ind Organ 28:285–306

    Article  Google Scholar 

  27. Fujita M, Krugman P, Venables AJ (1999) The spatial economy. MIT Press, Cambridge

    Google Scholar 

  28. Geroski PA (1995) What do we know about entry? Int J Ind Organ 13:421–440

    Article  Google Scholar 

  29. Görg H, Strobl E (2003) Footlose multinationals? Manchester Sch 71:1–19

    Article  Google Scholar 

  30. Han A, Hausman JA (1990) Flexible parametric estimation of duration and competing risk models. J Appl Econom 5:1–28

    Article  Google Scholar 

  31. Hannan MT (2005) Ecologies of organizations: diversity and identity. J Econ Perspect 19:51–70

    Article  Google Scholar 

  32. Hannan MT, Carrol GR, Dobrev SD, Han J (1998) Organizational mortality in European and American automobile industries. Part I: revisiting the effects of age and size. Eur Sociol Rev 14:279–302

    Google Scholar 

  33. Harhoff D, Stahl K, Woywode M (1998) Legal form, growth and exit of West German firms. J Ind Econ 46:453–488

    Article  Google Scholar 

  34. Heckman JJ, Singer B (1984) A method for minimising the impact of distributional assumptions in econometric models for duration data. Econometrica 52:271–320

    Article  Google Scholar 

  35. Honjo Y (2000) Business failure of new firms: an empirical analysis using a multiplicative hazards model. Int J Ind Organ 18:557–574

    Article  Google Scholar 

  36. Hougaard P (2000) Analysis of multivariate survival data. Springer, New York

    Google Scholar 

  37. Hutton JL, Monaghan PF (2002) Choice of parametric accelerated life and proportional hazard models for survival data: asymptotic results. Lifetime Data Anal 8:375–393

    Article  Google Scholar 

  38. Jenkins SP (2005) Survival analysis. Institute for Social and Economic Research, University of Essex (Unpublished manuscript)

  39. Jofre J (2007) Agglomeration economies and firm survival. In: Arauzo JM, Manjón MC (eds) Entrepreneurship, industrial location and economic growth. Edward Elgar, Cheltenham, forthcoming

  40. Jovanovic B (1982) Selection and evolution of industry. Econometrica 50:649–670

    Article  Google Scholar 

  41. Kiefer NM (1988) Economic duration data and hazard functions. J Econ Lit 26: 646–679

    Google Scholar 

  42. Kimura F, Fujii T (2003) Globalizing activities and the rate of survival: panel data analysis on Japanese firms. J Jpn Int Econ 17:538–560

    Article  Google Scholar 

  43. Lancaster T (1972) A stochastic model for the duration of a strike. J R Stat Soc (Ser A, General) 135:257–271

    Article  Google Scholar 

  44. Lancaster T (1990) The econometric analysis of transition data. Cambridge University Press, Cambridge

    Google Scholar 

  45. Linton OB, Nielsen JP, van de Geer S (2003) Estimating multiplicative and additive hazard functions by Kernel methods. Ann Stat 31:464–492

    Article  Google Scholar 

  46. López-García P, Puente S (2007) A comparison of the determinants of survival of Spanish firms across economic sectors. In: Arauzo JM, Manjón MC (eds) Entrepreneurship, industrial location and economic growth. Edward Elgar, Cheltenham, forthcoming

  47. Mata J, Portugal P (1994) Life duration of new firms. J Ind Econ 42:227–246

    Article  Google Scholar 

  48. Mata J, Portugal P (2000) Closure and divestiture by foreign entrants: the impact of entry and post-entry strategies. Strateg Manage J 21:549–562

    Article  Google Scholar 

  49. Mata J, Portugal P (2002) The survival of new domestic and foreign owned firms. Strateg Manage J 23:323–343

    Article  Google Scholar 

  50. Mata J, Portugal P, Guimarães P (1995) The survival of new plants: start-up conditions and post-entry evolution. Int J Ind Organ 13:459–482

    Article  Google Scholar 

  51. Mahmood T (2000) Survival of newly founded businesses: a log-logistic model approach. Small Bus Econ 14:223–237

    Article  Google Scholar 

  52. Manton KG, Stallard E, Vaupel JW (1986) Alternative models for the heterogeneity of mortality risks among the aged. J Am Stat Assoc 81:635–644

    Article  Google Scholar 

  53. Narendranathan W, Stewart MB (1993) Modelling the probability of leaving unemployment: competing risks models with flexible base-line hazards. Appl Stat 42:63–83

    Article  Google Scholar 

  54. Neumann GR (1997) Search models and duration data. In: Pesaran MH (ed) Handbook of applied econometrics: microeconometrics. Basil Blackwell, Oxford, pp 300–351

    Google Scholar 

  55. Orbe J, Ferreira E, Nuñez-Antón V (2002) Comparing proportional hazards and accelerated failure time models for survival analysis. Stat Med 21:3493–3510

    Article  Google Scholar 

  56. Ortega-Argilés R, Moreno R (2007) The survival chances of competitive businesses. In: Arauzo JM, Manjón MC (eds) Entrepreneurship, industrial location and economic growth. Edward Elgar, Cheltenham, forthcoming

  57. Pakes A, Ericson R (1998) Empirical implications of alternative models of firm dynamics. J Econ Theory 79:1–45

    Article  Google Scholar 

  58. Segarra A, Callejón M (2002) New firms’ survival and market turbulence: new evidence from Spain. Rev Ind Organ 20:1–14

    Article  Google Scholar 

  59. Stinchcombe F (1965) Social structure and organizations. In: March JG (ed) Handbook of organizations. Rand McNally, Chicago, pp 142–193

    Google Scholar 

  60. Strotmann H (2007) Entrepreneurial survival. Small Bus Econ 28:87–104

    Article  Google Scholar 

  61. Thompson P (2005) Selection and firm survival: evidence from the shipbuilding industry, 1825–1914. Rev Econ Stat 87:26–36

    Article  Google Scholar 

  62. Tveterås R, Eide GE (2000) Survival of new plants in different industry environments in Norwegian manufacturing: a semi-proportional Cox model approach. Small Bus Econ 14:65–82

    Article  Google Scholar 

  63. van den Berg G (2001) Duration models: specification, identification and multiple durations. In: Heckman JJ, Leamer E (eds) Handbook of econometrics, vol 5. Elsevier, North-Holland, Amsterdam, pp 3381–3460

    Google Scholar 

  64. Wheelock DC, Wilson PW (2000) Why do banks disappear? The determinants of U.S. bank failures and acquisitions. Rev Econ Stat 82:127–138

    Article  Google Scholar 

  65. Winter S (1984) Schumpeterian competition in alternative technological regimes. J Econ Behav Organ 5:287–320

    Article  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Miguel C. Manjón-Antolín.

Additional information

This paper has benefited from the lively discussions on the topic by participants at the workshop on “Entrepreneurship, Firm Demography and Industrial Location” held at the WIFO (Vienna) in November 2006. We are particularly grateful to S. Esteve, J. Mañez, M. Peneder and M. Pfaffermayr (the Coordinating Editor of the journal) for their useful comments. We should also like to acknowledge financial support in the form of the grants SEJ2004-05860/ECON and SEJ2004-07824/ECON as well as from the “Xarxa de Referència d’R + D + I en Economia i Polítiques Públiques” of the Catalan Government. The usual caveats apply and any errors are, of course, our own. In particular, we apologise to those authors that we may have unfairly left out of this review of the IO literature on firm survival.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Manjón-Antolín, M.C., Arauzo-Carod, J. Firm survival: methods and evidence. Empirica 35, 1–24 (2008). https://doi.org/10.1007/s10663-007-9048-x

Download citation

Keywords

  • Duration models
  • Industry dynamics
  • Survival