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The Economic Contribution of High-Growth Firms: Do Policy Implications Depend on the Choice of Growth Indicator?

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Abstract

Prior studies have defined high-growth firms (HGFs) in terms of growth in firm employment or firm sales, and primarily analyzed their contribution to overall employment growth. In this paper we define HGFs using the commonly applied growth indicators (employment and sales), but also add definitions based on growth in value added and productivity. Our results indicate that HGFs in terms of employment are not the same firms as HGFs in terms of productivity, and that their economic contributions differ significantly. Economic policy promoting fast growth in employment may therefore come at the cost of reduced productivity growth. Although HGFs of different definitions may not be the same firms, young firms are more likely to be HGFs irrespective of definition. This suggests that economic policy should focus on the conditions for new firm formation and early growth of firms, rather than target a particular type of HGFs.

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Notes

  1. Recently, endogenous growth theory has emerged arguing that new knowledge drives economic growth (Romer 1986). This literature was preceded by Hayek who early on forcefully emphasized the role of knowledge (e.g. 1937, 1945, 1984).

  2. Audretsch and Fritsch (2002) and Fritsch and Mueller (2006) have extended the use of the regimes concept to geographical units, notably regions, the idea being that the mode of production in a certain region may be distinct from the dominant modes of production in other regions.

  3. The measures of ambitious entrepreneurship, provided by the Global Entrepreneurship Monitor, echo this. Stam et al. (2008) find that ambitious entrepreneurship contributes more strongly to country-scale economic growth than entrepreneurship in general. According to Wong et al. (2005), high-growth potential Total Entrepreneurial Activity (TEA) is the sole form of entrepreneurship that has any explanatory effect on differing rates of economic growth across nations. Based on this and similar studies, Sternberg and Wennekers (2005, p.200) conclude: “These findings may have important implications for entrepreneurship policy in highly developed economies. At least from an economic growth perspective, policy should focus primarily on potentially fast-growing new firms and not on new enterprises in general.”

  4. Organic growth is growth through new appointments in a firm, while acquired growth is growth through acquisitions and/or mergers. Organic growth and acquired growth may also be denoted internal growth and external growth, respectively. McKelvie and Wiklund (2010) also suggest that different hybrids of organic and acquired growth should be considered.

  5. Stam et al. (2011) investigate whether the rate of HGFs has an effect on subsequent macroeconomic performance in a sample of low- and high-income countries during the period 2002–2005. Teruel and de Wit (2011) analyze the determinants of HGFs in different countries. As they do not concern themselves directly with the contribution of HGFs, we do not include their studies in our overview.

  6. López-Garcia and Puente (2012) use growth in value added to identify HGFs. However, this is only as a test of robustness of their regression model with HGFs defined by growth in employment. As their study does not consider the contribution of HGFs defined by value added, we do not include their use of value added as a growth indicator in our survey of the previous literature.

  7. Although they do not directly focus on HGFs, this is supported by Coad and Broekel (2012). Their results indicate that the relationship between employment and productivity growth is dependent on where the firm is located at the firm growth rate distribution. An increase in productivity growth seems to be associated with a decrease in employment growth for most firms, while it stimulates further employment growth for fast growing firms.

  8. The report investigates the growth dynamics of firms in 11 countries for the period 2002 to 2005. It covers the non-agricultural business sector, ISIC Rev3 Sectors 10–74. In general, firms with ten or more employees are analyzed.

  9. Shepherd and Wiklund (2009) investigate correlations between firm growth measured over one- and three-year time spans, finding them to be rather high in the case of employment and sales growth. They see average correlations of 0.582 for absolute employment growth measured over these two time spans, and 0.580 for absolute sales growth, while correlations for relative employment growth were 0.556 and for relative sales growth 0.678.

  10. We also identified HGFs as the firms with the 3 % highest growth rates during the studied periods in order to test whether our results are sensitive to the chosen cut-off level. All results remain qualitatively similar, and are available from the authors upon request.

  11. A descriptive analysis also shows that HGFs are significantly larger and older when the Eurostat-OECD definition of HGFs is used (see Table A1 in the Appendix).

  12. Absolute employment HGFs are defined measuring the growth in employment in absolute numbers; relative employment HGFs are defined measuring the growth in employment in relative numbers; composite employment HGFs are defined measuring the growth in employment using a combination of relative and absolute numbers; absolute sales HGFs are defined measuring the growth in sales in absolute numbers; relative sales HGFs are defined measuring the growth in sales in relative numbers; absolute value added HGFs are defined measuring the growth in value added in absolute numbers; relative value added HGFs are defined measuring the growth in value added in relative numbers; absolute productivity HGFs are defined measuring the growth in labor productivity in absolute numbers; relative productivity HGFs are defined measuring the growth in labor productivity in relative numbers.

  13. How the Eurostat-OECD definition and the choice of growth cut-offs influence the average size and age of different types of HGFs are presented in Table 13 in the appendix.

  14. Firm size is lagged two periods to avoid endogeneity problems.

  15. All the firms in the database are denoted by five-digit SNI codes. Based on these, the firms have been sorted using three-digit SNI codes into 213 different industries to control for industry-specific heterogeneity in the presence of HGFs. The estimated coefficients for each of these industry dummies are not presented in this paper in order to save space, but are available from the authors upon request.

  16. Note that the variables D72 and DGROUP are not presented in Table 7 in order to save space, but are available from the authors upon request. The enterprise group dummy is always positive and significant (in line with previous research), except in the regressions where HGFs based on productivity function as a basis for the dependent variable, where it is insignificant. The dummy for being registered as a startup in 1972 is only occasionally significant.

  17. All estimations were also done with a 3 % cut-off point to test the robustness of our results. The results are qualitatively very similar to the results we obtain when we use the 1 % cut-off point, and they are available from the authors upon request.

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Acknowledgments

We are grateful for useful comments from Niclas Berggren, David Granlund, seminar participants at Dalarna University, the 2010 HUI Workshop on Research in Retailing, the Research Institute of Industrial Economics (IFN), the Ratio Institute, and two anonymous referees. We are also grateful for financial support from Ragnar Söderberg’s Foundation.

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Authors and Affiliations

  1. Dalarna University, Falun, Sweden

    Sven-Olov Daunfeldt & Niklas Elert

  2. HUI Research, SE-103 29, Stockholm, Sweden

    Sven-Olov Daunfeldt & Dan Johansson

  3. Örebro University School of Business, Örebro,, SE-701 82, Sweden

    Dan Johansson

  4. The Ratio Institute, P.O. Box 3203, SE-103 64, Stockholm, Sweden

    Niklas Elert

  5. Örebro University, Örebro, Sweden

    Niklas Elert

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  1. Sven-Olov Daunfeldt
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Correspondence to Dan Johansson.

Appendix

Appendix

Table 13 Average age and size of HGFs for different growth cut-offs and the Eurostat-OECD definition, growth calculated over a 3-year period
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Daunfeldt, SO., Elert, N. & Johansson, D. The Economic Contribution of High-Growth Firms: Do Policy Implications Depend on the Choice of Growth Indicator?. J Ind Compet Trade 14, 337–365 (2014). https://doi.org/10.1007/s10842-013-0168-7

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