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A control group study of incubators’ impact to promote firm survival

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Abstract

It is widely unclear as to whether start-up firms supported by publicly-initiated incubator initiatives have higher survival rates than comparable start-up firms that have not received support by such initiatives. This paper contributes to the underlying discussion by performing a large-scale matched-pairs analysis of the long-term survival of 371 incubator firms (after their graduation) from five German incubators and a control group of 371 comparable non-incubated firms. The analysis covers a 10-year time span. To account for the problem of selection bias, a non-parametric matching approach is applied to identify an appropriate control group. For neither of the five incubator locations, we find statistically significant higher survival probabilities for firms located in incubators compared to firms located outside those incubator organizations. For three incubator locations the analysis reveals statistically significant lower chances of survival for those start-ups receiving support by an incubator. The empirical results, therefore, raise some doubts regarding the impacts of incubation on long-term firm survival.

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Notes

  1. In fact, such an initiative to implement routinely conducted outcome reviews to gather graduate performance data has been demanded for decades (e.g., Bearse 1998; Sherman and Chappell 1998).

  2. NBIA argues that direct comparisons of separate data sets on firm survival in general and statistics on incubators’ graduate survival are widely inappropriate.

  3. It should not be concealed that contrasting ‘liability-hypotheses’ have been developed that presume different relationships between firm age and hazard development. For instance, Brüderl and Schüssler (1990) assume (and verify) an inversed u-shaped ‘liability of adolescence’, where there is a low risk of exit in an early phase of development, which increases afterwards and decreases monotonically after a peak. They explain such patterns by a ‘(…) certain amount of initial resources and endowments (…)’ that all new organizations have. Until this individual starting-package (e.g. financial resources) is not completely depleted, the founder will do everything to preserve. In fact, results of prior studies trying to justify or reject one of these hypotheses vary considerably according to diverging regional, sectoral or temporal foci and heterogeneous sample populations (see Strotmann 2007 for an overview).

  4. In practice, there exists a broad range of terminologies for business incubators and/or technology centers. This heterogeneity, which is a well-known problem in incubator-incubation research (Hackett and Dilts 2004), makes it difficult to distinguish between both types of German incubator facilities. Sometimes, a specific name for an incubator is chosen by its stakeholders primarily for marketing issues.

  5. Not to forget that market exit is a central element within an efficient economy as well (Strotmann 2007), since new firms may induce improvements (e.g. on regional employment, improved competitiveness, acceleration of structural change), even if they fail (Fritsch and Mueller 2004).

  6. In contrast to firm survival as dependent variable, other indicators of incubators’ effectiveness are much more frequently studied in control group based analyses. Among the criteria that are most frequently applied are different measures referring to innovativeness of firms, such as R&D intensity, patent activity or R&D expenditures (Colombo and Delmastro 2002; Lindelöf and Löfsten 2004; Radosevic and Myrzakhmet 2009; Squicciarini 2008; Westhead 1997), measures of the cooperation propensity, particularly with academic institution (Colombo and Delmastro 2002; Fukugawa 2006; Yang et al. 2009) or firm growth measured in terms of employment, sales or profitability (Colombo and Delmastro 2002; Löfsten and Lindelöf 2002; Westhead and Storey 1994).

  7. ‘Hightech-Manufacturing’ (NACE Rev. 2 codes 20–37), ‘Wholesale trade and retail trade’ (51, 52), ‘Construction’ (45), ‘Computer’ (including hard- and software, 72), ‘Research and development’ (73), ‘Consulting and business-related services (BRS)’ (including engineering consultants, 74), ‘Education’ (80) and ‘Recreation/sports/culture/others’ (including also non-knowledge based services like, for example, call-center and facility management 90–93).

  8. This would happen if incubated firms are kept alive at the expense of firms located in the respective city that have not been supported by the incubator and do not survive. This question has been raised by scholars in the past, who argue that firms might kept alive through incubation that would otherwise not have survived under market conditions (Sternberg 1992). However, to date there is no empirical evidence for such crowding-out in the context of business incubation.

  9. Firms that ended up in liquidation after the reference date (between January 1, 2007 and December 31, 2009) were explicitly not considered as closures.

  10. Regarding these M&A-cases, there are different ways how to classify them. First, assuming that those firms were successful, they may be count as survivors (Rothaermel and Thursby 2005), implying a narrow definition of a firm closure/failure. Second, and certainly more exact, looking at the details of the respective deals/merger contracts (e.g. price or post-deal strategic changes) might create a solid rationale for classifying the M&A cases. Unfortunately, Creditreform does not report details about the deals, and an additional search (internet, business registers) did not yield any results.

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  1. Department of Urban Economics, Halle Institute for Economic Research, P.O. Box 11 03 61, 06017, Halle (Saale), Germany

    Michael Schwartz

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Appendices

Appendix 1

See Table 6.

Table 6 Correlation matrix; N = 43,467
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Appendix 2

See Table 7.

Table 7 Results of probit estimations for the probability of receiving public support by an incubator organization (standard errors in parentheses)
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Appendix 3

See Table 8.

Table 8 Comparison of the distribution of main matching variables for ‘On-incubator’ firms, potential controls before matching, and ‘Control group’ after matching; comparison per incubator location
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Schwartz, M. A control group study of incubators’ impact to promote firm survival. J Technol Transf 38, 302–331 (2013). https://doi.org/10.1007/s10961-012-9254-y

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