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5.2. Estimation results Using the CPH model, we estimate the determinants of exit according to forms of exit. The definition of the variables and descriptive statistics are shown in Tables 3 and 4, respectively. Table 5 shows the estimation results by forms of exit. Column (i) of Table 5 shows the results using a pooled sample of all forms of exit, in order to compare the pooled results with each form of exit separately. In Column (i) of Table 5, the industry’s price–cost margins (P CM) and gross entry rate (ENT RY ) have significantly negative and positive effects on the hazards of the pooled exit, respectively. However, other independent industry-specific characteristics have no significant effects on the hazards of exit. Region-specific characteristics have no significant effects on the hazards of exit in Column (i) of Table 5. With respect to firm-specific characteristics, SIZE_5-9 and SIZE_10-19 have negative and significant effects on the hazards of pooled exit, although the effect of SIZE_20 is not significant. This suggests that there is a nonlinear relationship between firm size and exit. The dummy variable for joint stock companies (JST OCK) has a significantly positive effect, although this is simply included as a control variable. As for entrepreneur-specific characteristics, the variables for educational background and age have significant effects on the pooled exit results, indicating that firms whose entrepreneurs had a university education and were approaching retirement age were more likely to exit. Columns (ii)–(iv) of Table 5 show the estimation results for the determinants of exit of new firms by forms of exit. The variable for capital intensity (CAP ), as shown in Column (ii) of Table 5, has negative and significant effects on exit through bankruptcy. This result indicates that new firms tend to survive longer in capital- intensive industries. On the other hand, Columns (iii)–(iv) of Table 5 indicate that CAP has positive and significant effects on voluntary liquidation and merger, sug- gesting that new firms are more likely to exit through voluntary liquidation and 20
merger in industries characterized by large amounts of capital. These results may suggest that because firms in capital-intensive industries may have more salable re- sources, debtors and creditors prefer to dissolve businesses via voluntary liquidation or merger rather than bankruptcy using a legal procedure. R&D intensity (RD) also has negative and significant effects on the hazards of bankruptcy in Column (ii) of Table 5. This result supports the sunk-cost explana- tion, which is consistent with some previous studies, including Shapiro and Khemani (1987). On the other hand, RD has no significant effect on exit through voluntary liquidation or merger, as shown in Columns (iii) and (iv) of Table 5. Price–cost margin (P CM) has a negative effect on exit in all the models of Table 5, although the effect on bankruptcy is not significant in Column (ii). This result suggests that low profits are likely to lead to exit. This is also consistent with the result of Shapiro and Khemani (1987). Given that high price–cost margins represent the absence of competitive pressure, our result indicates that new firms are less likely to exit in industries lacking competitive pressure. As shown in Table 5, although we expected that industry growth (IG) would have significant effects on exit, we did not find any significant effects. This is, however, consistent with the result of Audretsch and Mahmood (1995). As already discussed, while higher growth is expected to give a better environment in which new firms can survive and grow, it may lead to further investments and therefore fierce competition. The risk of failure may be as high as the chance of success, and this may be one of the reasons that we do not find any significant results for industry growth. Industry’s gross entry rate (ENT RY ) indicates positive signs in all models of Table 5. Our findings suggest that higher entry rates at founding decrease the probability of survival. This is consistent with the finding of Geroski et al. (2010). With respect to region-specific characteristics, regional agglomeration (AGGLOM) has a positive and significant effect on exit through bankruptcy, as indicated in Col- 21
Page 2 and 3: DISCUSSION PAPER SERIES Discussion
Page 4 and 5: 1. Introduction Many new firms exit
Page 6 and 7: which is required to achieve econom
Page 8 and 9: how these environments shape each f
Page 10 and 11: 3. Data and method 3.1. Data source
Page 12 and 13: are regarded as bankrupt even if th
Page 14 and 15: holds for all situations. In additi
Page 16 and 17: assets to shipments in the year of
Page 18 and 19: exit of new firms of regional agglo
Page 20 and 21: cational background as a determinan
Page 24 and 25: umn (ii) of Table 5. This result su
Page 26 and 27: capital intensity does not have sig
Page 28 and 29: 6. Conclusions This paper has explo
Page 30 and 31: References Acs, Z. J., C. Armington
Page 32 and 33: Evans, D. S. (1987), ‘The relatio
Page 34 and 35: Nishimura, K. G., T. Nakajima, and
Page 36 and 37: Table 1: Summary statistics for the
Page 38 and 39: Table 3: The definitions of indepen
Page 40: Table 5: Estimation results Forms o

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