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Growth paths and routes to exit: 'shadow of death' effects for new firms in Japan

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Abstract

Research has recently emphasized that the non-survival of entrepreneurial firms can be disaggregated into distinct exit routes such as merger and acquisition (M&A), voluntary closure, and failure. Firm performance is an alleged determinant of exit route. However, there is a lack of evidence linking exit routes to their previous growth performance. We contribute to this gap by analyzing a cohort of incorporated firms in Japan and find some puzzles for the standard view. Our empirical analysis suggests that sales growth generally reduces the probability of exit by merger, voluntary liquidation, and also bankruptcy. However, the relationship is U-shaped—such that rapid growth actually increases the probability of exit. More generally, each of the three exit routes can occur all across the growth rate distribution. Large firms are more likely to exit via merger or bankruptcy, while small firms are more likely to exit via voluntary liquidation.

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Notes

  1. Closely related to our current research is the work that has briefly investigated the performance of Japanese firms in the 2 years before a merger event (Kubo and Saito 2012, see their Tables 2 and 3 and Figure 1).

  2. The literature has even invented the concept of an “involuntary exit strategy,” although we doubt that something truly strategic can also be involuntary.

  3. Given the scope of this paper, however, we do not investigate the determinants of startup size, but take startup size as given, and focus on post-entry growth and exit routes.

  4. To be fair, this idea has been hinted at in the previous literature, e.g. Wennberg and DeTienne (2014, p9): “the type of exit routes available and the willingness to exit may differ significantly between lifestyle entrepreneurs and growth entrepreneurs.”

  5. Moreover, we have another advantage to use COSMOS2 that firms’ status can be traced after firms’ relocation. In contrast, firms’ relocation is often regarded as exit from a region and entry into another region in government statistics, partly because the surveys are done by prefecture.

  6. The credit investigation company asks the managers about the numbers for total annual sales, number of employees, profits etc., although the managers do not necessarily disclose the exact amount. So, the investigators usually attempt to obtain such information by a number of means, for example, by asking whether the number is same as the previous year. This explains why the number for sales is sometimes identical to the previous year (i.e. change of zero yen from one year to the next), and why we have a likely over-representation of annual growth rates of sales of exactly zero.

  7. Note that the earliest years are not included in the regressions because these observations are lost due to the inclusion of lagged growth as independent variable.

  8. Figure A3 in the Appendix shows (parametric) quadratic fits of the non-parametric patterns in Figure 4, including confidence intervals. Figure A3 therefore helps to establish that the observed nonlinearity is statistically significant.

  9. For discussion of advantages of a discrete-time survival model, see Wiklund et al. (2010).

  10. Regarding the effect size: Table 3 column (2) shows that if lagged growth increases by one standard deviation, then the change in the odds of exit via voluntary liquidation (compared to the benchmark case of survival) is 0.052 x (exp(−0.359) = 0.0363.

  11. See Haans et al. (2016) for critical issues in theorizing and testing of quadratic relationships.

  12. There is no clear cut-off point to distinguish between small and large firms because the firm size distribution in our sample is a continuous and approximately lognormal distribution (see Figure A1 in the Appendix). Therefore, we distinguish between small and large size subsamples by referring to the median size.

  13. This effect is only found in the specification without quadratic terms for the second lag of growth. When quadratic terms are added, the coefficient is no longer statistically significant.

  14. One potential drawback, however, of this alternative independent variable is that growth is measured over different growth periods across firms (e.g. time from startup to exit could be 2 years for one firm, and 6 years for another), and averaging over periods of different lengths could introduce bias. This could make it problematic to compare firms whose growth unfolds over different timescales (e.g. if rapid growth is harder to sustain over longer periods). This possible measurement error should be kept in mind.

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Acknowledgements

We are grateful to Giulio Bottazzi, Elena Cefis, Masaru Karube, Francesco Lamperti, Sadao Nagaoka, Alessandro Nuvolari, and seminar participants at the Sant’Anna School of Advanced Studies (Pisa, Italy), the Innovation Economics Workshop, Hitotsubashi University (Tokyo, Japan), and University of Bergamo (Bergamo, Italy) for many helpful comments and discussions. Any remaining errors are ours alone.

Funding

Grant-in-Aid for Scientific Research (B) (No. 26285060) and (C) (No.18K01639), Japan Society for the Promotion of Science.

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Authors and Affiliations

  1. CENTRUM Católica Graduate Business School (CCGBS), Lima, Peru

    Alex Coad

  2. Pontificia Universidad Católica del Perú (PUCP), Lima, Peru

    Alex Coad

  3. School of Economics, Kwansei Gakuin University, Hyogo, Japan

    Masatoshi Kato

  4. Research Center for Entrepreneurship, Kwansei Gakuin University, Hyogo, Japan

    Masatoshi Kato

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Appendix

Appendix

Fig. A1
figure 5

Distribution of log sales

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Fig. A2
figure 6

Lagged growth distribution (kernel density)

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Fig. A3
figure 7

Exit rates for each exit route across the growth rates distribution with confidence intervals (95%)

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Table A1 Definition of variables
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Table A2 Summary statistics for variables used in the regressions
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Table A3 Correlation matrix of variables (Number of observations is 20,238)
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Table A4 Summary statistics for independent variables by status: survival, merger, voluntary liquidation, and bankruptcy
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Table A5 Summary statistics for independent variables for below- and above-median subsamples in terms of the number of employees at the first year of observation
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Table A6 Complimentary log-log regression results
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Coad, A., Kato, M. Growth paths and routes to exit: 'shadow of death' effects for new firms in Japan. Small Bus Econ 57, 1145–1173 (2021). https://doi.org/10.1007/s11187-020-00341-z

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