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The effects of firms’ R&D and innovation activities on their survival: a competing risks analysis

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Abstract

Using a data set of Norwegian firms, an examination is made of the relationship between firms’ R&D activities and their survival. A firm may exit the market through closure, or merger and acquisition (M&A). The analysis is based on a discrete time competing risks model with unobserved heterogeneity. We find that product-innovative firms have a higher probability of exit due to M&A, but only if they also introduce new products into their market. This highlights the importance of differentiating between different groups of product-innovative firms. None of the R&D and innovation activities considered has significant effects on the probability of firm closure.

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Notes

  1. Audretsch (1991, 1995) and Audretsch and Mahmood (1994, 1995) have found that innovation activities are important determinants of firm survival, but these studies focus on innovation activities at the industrial level and not those within each firm.

  2. An introduction to the literature which focuses on the relationship between firm survival and innovation is given in Dalglish and Newton (2001).

  3. Fernandes and Paunov (2012, footnote 4) refer to the article by Mairesse and Mohnen (2010), which points out that ‘what exactly is defined as a new or improved product is not always clear anyway, certainly not to the respondents... The distinction between “new to the firm” and “new to the market” is also subject to a great deal of subjective judgement. To give a correct answer to this question presupposes a very good knowledge of one’s market’ (Mairesse and Mohnen 2010, p. 1137). Although the authors raise a valid concern, this is probably a widespread problem regarding subjective answers to survey questions on the relative performance of firms that the quality ‘can be very different depending on the judgment and knowledge of the respondents’ (Mairesse and Mohnen 2010, p. 1137).

  4. Jensen et al. (2008), Buddelmeyer et al. (2010), and Helmers and Rogers (2010) also use data for firms from different industrial sectors.

  5. See Lieberman and Montgomery (1988) and Kopel and Löffler (2008) for a discussion of first-mover advantages.

  6. For a discussion of cost competition, see Pries (2006).

  7. Mañez et al. (2009) find that large firms and/or firms operating in high-tech industries have significantly higher sunk R&D costs compared with small firms and/or firms in low- and medium-tech industries.

  8. Innovative firms may include firms that had innovation activities during the period 1999–2001 that did not result in a product or process innovation because the activities were abandoned before completion, or not completed by the end of 2001.

  9. Hazard models are also used in Jensen et al. (2008), Fontana and Nesta (2009), Buddelmeyer et al. (2010), Giovannetti et al. (2011), Fernandes and Paunov (2012), and Colombelli et al. (2013). Fontana and Nesta (2009, p. 296) emphasise that they apply a hazard model with two destinations, but treat the destinations as independent in their analysis.

  10. Buddelmeyer et al. (2010, p. 262) claim that Cefis and Marsili (2005) examine the effect in survival time due to ‘successful’ innovation.

  11. The share of R&D personnel among all employees is 4 % (0.126) for all manufacturing firms and 7 % (0.248) for manufacturing firms that are closed down, while from Table 1 we see that this share is 6 % (0.170) for all firms in our sample and 7 % (0.201) for all firms that are closed down (standard deviation in parenthesis). Thus, the ratio between the standard deviations is 197 % (=0.248/0.126) for manufacturing firms and 118 % (=0.201/0.170) for all firms.

  12. The Kendall’s rank correlation coefficients between the share of R&D personnel among all employees and total gross wages per employee are 15.6 % for the manufacturing sector and 14.6 % for all industrial sectors as a whole, while the Spearman’s rank correlation coefficients between the same variables are 20.4 % for the manufacturing sector and 19.0 % for all industrial sectors (all correlation coefficients are significant at the 1 % level).

  13. This result holds even at the 10 % level for manufacturing firms, but only at the 5 % level for all firms in our sample.

  14. Related to the ‘shadow of death’ phenomenon, Carreira and Teixeira (2011) explain that ‘the empirical literature... suggests that exiting firms do not face a ‘sudden death”. On the contrary, firms tend to reveal a steady decrease in their productivity level relative to survivors well before closure’ (p. 340).

  15. We have no obvious instruments for the R&D and innovation indicators either, although we are aware that some studies have used instruments for innovation (Lachenmaier and Woessmann 2006). Furthermore, although IV estimators are consistent given valid instruments, ‘IV estimators can be much less efficient than the OLS estimator and can have a finite-sample distribution that for usual finite-sample sizes differs greatly from the asymptotic distribution. These problems are greatly magnified if instruments are weakly correlated with the variables being instrumented’ (Cameron and Trivedi 2005, p. 103).

  16. From (R4) for the model in Table 4, we also find that manufacturing firms that are both product- and process-innovative have a relatively higher probability of exit due to M&A, but the result is only significant at the 10 % level.

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Acknowledgments

Many thanks to Editor Bernd Fitzenberger and three anonymous referees for valuable comments on earlier drafts of this paper. The paper has also benefited from discussions with my colleagues Olav R. Spilling and Tore Sandven, and my former colleagues Aris Kaloudis and Øyvind Wiborg. Also, many thanks to my former colleague Rachel Sweetman and language consultant John G. Taylor for valuable contributions during proof editing. All remaining errors are my own responsibility.

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    Pål Børing

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Børing, P. The effects of firms’ R&D and innovation activities on their survival: a competing risks analysis. Empir Econ 49, 1045–1069 (2015). https://doi.org/10.1007/s00181-014-0901-z

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