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Small Business Economics

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15-01-2021

One swallow does not make a summer: episodes and persistence in high growth

Authors: Silviano Esteve-Pérez, Fabio Pieri, Diego Rodriguez

Published in: Small Business Economics | Issue 3/2022

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Abstract

This paper analyzes firms’ episodes (spells) of high growth (HG) using a sample of Spanish manufacturing firms observed over two decades. The use of duration models allows us to investigate the following: (i) the probability of experiencing HG episodes, (ii) persistence in HG, and (iii) the determinants of the transitions in and out of the HG state and whether their impact varies over the business cycle. We find that about half of the firms experience at least one HG episode, but they seldom experience more than one. Moreover, high-growth status is rarely repeated due to high first-year selection. Yet, in subsequent years beyond the first one, the hazard rate from HG status falls substantially. These results suggest an “episodic” nature of HG and further allow us to identify two groups of firms characterized by the following: (i) (relatively) long HG spells and short no high-growth (NHG) spells and (ii) short HG spells and long NHG spells. In addition, some firm and market (demand) characteristics increase the probability of becoming an HG firm and enhancing HG persistence. Finally, during the downturn, the role of younger age and smaller size in explaining HG decreases.

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Empirical papers have shown that the distribution of firm growth rates is tent-shaped (e.g., Bottazzi and Secchi 2006; Bottazzi et al. 2011). Its “heavy” tails reveal the existence of a reduced group of episodes of fast growth (and other few ones of fast contraction).

Throughout the paper, we use the terms spell and episode interchangeably.

The definition of (what constitutes) an HGF is not a trivial issue (Coad et al. 2014); indeed, the choice of the growth metric may well affect the results of the analyses (Delmar et al. 2003; Daunfeldt et al. 2013). The reader is cross-referred to Section 3, in which we introduce the definition of HG employed in this work.

We also jointly estimate the equations modeling the two types of transitions, allowing for non-zero correlation across the firm-level unobserved variables that affect both transitions.

See Erhardt (2019, Table 1) for a classification of recent studies along these dimensions.

The sampling procedure of the ESEE is the following: firms with fewer than 10 employees are excluded from the survey. Firms with 10–200 employees are randomly sampled by two-digit NACE industry and size strata, holding around 4% of the population in 1990. All firms with more than 200 employees were requested to participate, resulting in a participation rate of around 60% in 1990. Important efforts have been made to minimize attrition and annually incorporate new firms with the same sampling criteria as in the base year so that the sample of firms is representative of the Spanish manufacturing sector over time. See https://www.fundacionsepi.es/investigacion/esee/en/spresentacion.asp for comprehensive information about the ESEE.

The ESEE does not provide the number of hours worked by part-time employees, but they are merely 3% of permanent workers.

In the words of Sutton (1997, p. 40), “Size can be measured in a number of ways […] annual sales, […] current employment, and […] total assets. Though we might in principle expect systematic differences between the several measures, such differences have not been a focus of interest in the literature.”

Firms in the sample grow either organically or via M&As. For the purpose of this work and to avoid losing the information provided by firms that go through M&As or spin-off procedures, we identify episodes of non-organic growth at the moment in time in which they happen (year t). We consider the pre-episode (up to year t − 1) and post-episode (from year t + 1 onward) units of analysis as two separate spells.

Admittedly, while our definition resembles Birch’s (1981) definition, an absolute definition may also be used, such as the one proposed by the Eurostat–OECD Manual on Business Demography Statistics (2007). The manual defines an HGF as one with the following attributes: (i) it initially possesses 10 or more employees or has at least four times the national per capita income in annual revenues, and (ii) it experiences average annualized employment or revenue growth of greater than 20% over a 3-year period. While the debate about what constitutes an HGF is nontrivial (Coad et al. 2014), it is beyond the scope of this work. Only for comparison purposes with the definition advocated by the Eurostat–OECD manual, we report that about 3% of firms fulfill the criterion of having a cumulative average growth rate larger than 20% for 3 consecutive years.

For example, in 2009 (the worst year for employment in Spain), the 90th percentile was 0.0453, which contrasts sharply with the 1998 value of 0.198.

The NHG state comprises a heterogeneous set of growth episodes (from mildly positive to very negative), gathering a lot of heterogeneity. Some of these episodes may be interesting per se (e.g., the high-decline firms, as suggested by Coad et al. 2014), but exploitation of the heterogeneity within the NHG state is beyond the scope of this work.

Briefly, we start with an unbalanced panel of firms over 1991–2016. The definition of HGF involves comparing a firm’s annual growth rate with the sample annual growth rate obtained using a 3-year moving average. Therefore, we define HG/NHG states from 1993 to 2015. Furthermore, in the survival analysis, (i) the information in 2015 is only used to determine whether ongoing spells in 2014 end or are right-censored (i.e., continue in 2015); (ii) we focus on “fresh” spells, so ongoing spells in 1993 are dropped. Thus, we end up with 24,947 observations.

This corresponds to the simple mean of observed durations both for complete and right-censored spells.

To avoid an odd behavior in the estimated baseline hazard functions due to scarcity of observations spanning longer durations, we right-censor spells of HG longer than 3 years. Likewise, to make the results comparable for the two transitions, we apply the same right-censoring to NHG spells, which is also supported by piecewise estimates of the baseline (not reported, but available from the authors upon request) that suggest no significant differences in hazards across different spell ages.

However, if unmeasured factors that affect the error term were correlated with our lagged covariates over time, then biased estimators would be obtained. We partly deal with this issue both using a relatively large set of explanatory variables and estimating frailty duration models that account for firm-level unobserved heterogeneity.

We are grateful to a reviewer for raising this point.

In the model for the transitions NHG to HG, we cannot reject the existence of unobserved heterogeneity (col. 1 in Tables 3 and 4). Hence, the regression coefficients for this model are defined conditional on the unobserved heterogeneity. Hence, the impact of each covariate holds valid for two spells with an identical frailty term.

Table C1 in an online appendix reports the full estimates of the columns labeled “Total” for NHG and HG hazards.

Indeed, while no industry shows a statistically significant difference in explaining persistence in HG, “Leather, fur, and footwear” and “Timber” show, for firms belonging to them, higher probabilities of experiencing an HGE than the reference industry does (“Meat related products”). Conversely, “Printing and publishing,” “Chemicals,” and “Basic metal products” all show lower probabilities of their firms experiencing an HGE in relation to the reference industry.

The taxonomy followed is a more aggregated version of that provided by Eurostat (http://ec.europa.eu/eurostat/statistics-explained/index.php/Glossary:High-tech_classification_of_manufacturing_industries). See Table 2 for further details.

In all the following specifications, we include both year and industry dummies, but we avoid reporting their (consistent) coefficients to save space. Complete tables are available from the authors upon request.

Indeed, in Section 4.4, we replicate the analysis by measuring firm size with (real) sales and we do find a significant positive association between being and exporter and the probability of shifting from NHG to HG.

For instance, the decrease in the impact of SP_REP3 on the transition NHG to HG takes place because firms with high hazard rate HG to NHG are selected into repeated NHG spells. The negative correlation between the two transitions leads to a disproportionate presence of firms with low hazard rate NHG to HG in repeated spell category. These firms push down the odds of NHG to HG in SP_REP3 increasing the negative impact (i.e., lower odds ratio) when residual correlation is uncontrolled.

As previously explained, the duration analysis includes right-censored spells and treats them properly. However, in this complementary analysis, a 1-year HG spell that is right censored could be inadequately assigned to a duration length of 1, while its true duration could be longer than that.

Column 1 of Table A1, in the Online Appendix, shows the β estimated parameters for a partial proportional odds model with spell length as the dependent variable. Only the dummy variable that measures “high-productivity” firms (PRODUCTIVITY_H) fails to meet the proportional odds assumption. Accordingly, the results for both unconstrained coefficients are shown in that case.

We must bear in mind that this table shows a sizeable reduction in sample size (about 10%) compared with Table 4 due to information requirements associated with calculating the total factor productivity variable. However, as pointed out by one reviewer, the non-linear effect of total factor productivity on the likelihood of experiencing HG (also found when we include both continuous total factor productivity and its square -estimates are not reported for brevity) could suggest the existence of an “optimal level” of productivity. Beyond that level, further growth may destabilize a firm’s organization.

Sales have been deflated using price variations defined at the firm level. Specifically, the surveyed firms give annual information about markets served (up to five), identifying their relative importance (in percentage) for total sales of the firm. This information allows us to calculate a price index for all markets and for each market, using the proportions with respect to total sales as weights. Average (industry/year) price variations are used for those few firms that do not provide information.

Acemoglu, D., Akcigit, U., Alp, H., Bloom, N., & Kerr, W. (2018). Innovation, reallocation and growth. American Economic Review, 108(11), 3450–3491. https://doi.org/10.1257/aer.20130470.CrossRef

Acs, Z. J., & Mueller, P. (2008). Employment effects of business dynamics: mice, gazelles and elephants. Small Business Economics, 30, 85–100. https://doi.org/10.1007/s11187-007-9052-3.CrossRef

Anyadike-Danes, M., Bonner, K., Hart, M. & Mason, C. (2009). Measuring Business Growth. High-growth firms and their contribution to employment in the UK. NESTA Research report.

Arnold, J., Nicoletti, G., & Scarpetta, S. (2011). Regulation, resource reallocation and productivity growth. EIB Papers, 16(1), 90–115.

Audretsch, D. B. (2012). Determinants of high-growth entrepreneurship, OECD/DBA International Workshop, Copenhagen, 28 March 2012.

Audretsch, D. B., Coad, A., & Segarra, A. (2014). Firm growth and innovation. Small Business Economics, 43(4), 743–749. https://doi.org/10.1007/s11187-014-9560-x.CrossRef

Barba Navaretti, G., Castellani, D., & Pieri, F. (2014). Age and firm growth: evidence from three European countries. Small Business Economics, 43(4), 823–837. https://doi.org/10.1007/s11187-014-9564-6.CrossRef

Belenzon, S., Berkovitz, T., & Rios, L. A. (2013). Capital markets and firm organization: how financial development shapes European corporate groups. Management Science, 59(6), 1326–1343. https://doi.org/10.1287/mnsc.1120.1655.CrossRef

Bianchini, S., Bottazzi, G., & Tamagni, F. (2017). What does (not) characterize persistent corporate high growth? Small Business Economics, 48(3), 633–656. https://doi.org/10.1007/s11187-016-9790-1.CrossRef

Bianchini, S., & Pellegrino, G. (2019). Innovation persistence and employment dynamics. Research Policy, 48(5), 1171–1186. https://doi.org/10.1016/j.respol.2018.12.008.CrossRef

Birch, D. (1981). Who creates jobs? The Public Interest, 65.

Bottazzi, G., Coad, A., Jacoby, N., & Secchi, A. (2011). Corporate growth and industrial dynamics: evidence from French manufacturing. Applied Economics, 43, 103–116. https://doi.org/10.1080/00036840802400454.CrossRef

Bottazzi, G., & Secchi, A. (2006). Explaining the distribution of firm growth rates. RAND Journal of Economics, 37(2), 235–256. https://doi.org/10.1111/j.1756-2171.2006.tb00014.x.CrossRef

Bravo-Biosca, A. (2011). A look at business growth and contraction in Europe. NESTA Working Paper no. 11/02, London.

Bravo-Biosca, A., Criscuolo, C., & Menon, C. (2016). What drives the dynamics of business growth? Economic Policy, 31(88), 703–742. https://doi.org/10.1093/epolic/eiw013.CrossRef

Brenner, T., & Schimke, A. (2015). Growth development paths of firms - a study of smaller businesses. Journal of Small Business Management, 53(2), 539–557. https://doi.org/10.1111/jsbm.12081.CrossRef

Capasso, M., Cefis, E., & Frenken, K. (2014). On the existence of persistently outperforming firms. Industrial and Corporate Change, 23(4), 997–1036. https://doi.org/10.1093/icc/dtt034.CrossRef

Carpenter, R. E., & Petersen, B. C. (2002). Is the growth of small firms constrained by internal finance? The Review of Economics and Statistics, 84(2), 298–309. https://doi.org/10.1162/003465302317411541.CrossRef

Clarke, R. G., Cull, R., & Kisunko, G. (2012). External finance and firm survival in the aftermath of the crisis: evidence from eastern Europe and central Asia. Journal of Comparative Economics, 40(3), 372–392. https://doi.org/10.1016/j.jce.2012.01.003.CrossRef

Coad, A. (2007a). Firm growth: a survey, Papers on Economics and Evolution, 0703. Jena: Max Planck Institute of Economics.

Coad, A. (2007b). A closer look at serial growth rate correlation. Review of Industrial Organization, 31(1), 69–82. https://doi.org/10.1007/s11151-007-9135-y.CrossRef

Coad, A., Daunfeldt, S. O., & Halvarsson, D. (2018). Bursting into life: firm growth and growth persistence by age. Small Business Economics, 50(1), 55–75. https://doi.org/10.1007/s11187-017-9872-8.CrossRef

Coad, A., Daunfeldt, S. O., Hölzl, W., Johansson, D., & Nightingale, P. (2014). High-growth firms: introduction to the special section. Industrial and Corporate Change, 23(1), 91–112. https://doi.org/10.1093/icc/dtt052.CrossRef

Coad, A., & Hölzl, W. (2009). On the autocorrelation of growth rates evidence for micro, small and large firms from the Austrian Service Industries, 1975-2004. Journal of Industry, Competition and Trade, 9(2), 139–166. https://doi.org/10.1007/s10842-009-0048-3.CrossRef

Coad, A., & Rao, R. (2008). Innovation and firm growth in high-tech sectors: a quantile regression approach. Research Policy, 37, 633–648. https://doi.org/10.1016/j.respol.2008.01.003.CrossRef

Coad, A., & Srhoj, S. (2019). Catching gazelles with a lasso: big data techniques for the prediction of high-growth firms. Small Business Economics, 1–25. https://doi.org/10.1007/s11187-019-00203-3.

Criscuolo, C., Gal, P. & Menon, C. (2014). The dynamics of employment growth: new evidence from 18 countries, OECD Science, Technology, and Industry Policy Papers, no. 14, OECD publishing, Paris.

Daunfeldt, S.-O., & Halvarsson, D. (2015). Are high-growth firms one-hit wonders? Evidence from Sweden. Small Business Economics, 44(2), 361–383. https://doi.org/10.1007/s11187-014-9599-8.CrossRef

Daunfeldt, S. O., Halvarsson, D., & Johansson, D. (2013). The economic contribution of high-growth firms: do policy implications depend on the choice of growth indicator? Journal of Industry, Competition and Trade, 14(3), 337–365. https://doi.org/10.1007/s10842-013-0168-7.CrossRef

Delmar, F., Davidsson, P., & Gartner, W. (2003). Arriving at the high-growth firm. Journal of Business Venturing, 18(2), 189–216. https://doi.org/10.1016/S0883-9026(02)00080-0.CrossRef

Dosi, G., Grazzi, M., Moschella, D., Pisano, G., & Tamagni, F. (2020). Long-term firm growth: an empirical analysis of US manufacturers 1959-2015. Industrial and Corporate Change, 29(2), 309–332. https://doi.org/10.1093/icc/dtz044.CrossRef

Dosi, G., Marsili, O., Orsenigo, L., & Salvatore, R. (1995). Learning, market selection and evolution of industrial structures. Small Business Economics, 7(6), 411–436. https://doi.org/10.1007/BF01112463.CrossRef

Erhardt, E. C. (2019). Measuring the persistence of high firm growth: choices and consequences. Small Business Economics, 1–28. https://doi.org/10.1007/s11187-019-00229-7.

Ericson, R., & Pakes, A. (1995). Markow-perfect industry dynamics: a framework for empirical work. Review of Economic Studies, 62(1), 53–82. https://doi.org/10.2307/2297841.CrossRef

Esteve, S., Pieri, F., & Rodríguez, D. (2018). Age and productivity as determinants of firm survival over the industry life cycle. Industry and Innovation, 25(2), 167–198. https://doi.org/10.1080/13662716.2017.1291329.CrossRef

Eurostat-OECD. (2007). Eurostat-OECD manual on business demography statistics. Luxembourg: Office for Official Publications of the European Communities.

Fort, T., Haltiwanger, J., Jarmin, R., & Miranda, J. (2013). How firms respond to business cycles: the role of firm age and firm size. IMF Economic Review, 61, 520–559. https://doi.org/10.1057/imfer.2013.15.CrossRef

Foster, L., Haltiwanger, J., & Syverson, C. (2016). The slow growth of new plants: learning about demand? Economica, 83, 91–129. https://doi.org/10.1111/ecca.12172.CrossRef

Grabowski, H., Vernon, J., & DiMasi, J. A. (2002). Returns on research and development for 1990s new drug introductions. Pharmacoeconomics, 20(3), 11–29. https://doi.org/10.2165/00019053-200220003-00002.CrossRef

Grazzi, M., & Moschella, D. (2018). Small, young, and exporters: new evidence on the determinants of firm growth. Journal of Evolutionary Economics, 28(1), 125–152. https://doi.org/10.1007/s00191-017-0523-7.CrossRef

Guarascio, D., & Tamagni, F. (2019). Persistence of innovation and patterns of firm growth. Research Policy, 48(6), 1493–1512. https://doi.org/10.1016/j.respol.2019.03.004.CrossRef

Hall, B. H. (1987). The relationship between firm size and firm growth in the U.S. manufacturing sector. Journal of Industrial Economics, 35(4), 583–600.CrossRef

Haltiwanger, J., Jarmin, R. S., Kulick, R. & Miranda, J. (2017). High growth young firms: contribution to job, output and productivity growth. CARRA Working Papers, no. 2017-03.

Haltiwanger, J., Jarmin, R., & Miranda, J. (2013). Who creates jobs? Small versus large versus young. The Review of Economics and Statistics, 95(2), 347–361. https://doi.org/10.1162/REST_a_00288.CrossRef

Harrison, R., Jaumandreu, J., Mairesse, J., & Peters, B. (2014). Does innovation stimulate employment? A firm-level analysis using comparable micro-data from four European countries. International Journal of Industrial Organization, 35, 29–43. https://doi.org/10.1016/j.ijindorg.2014.06.001.CrossRef

Heckman, J. (1981). The incidental parameters problem and the problem of initial conditions in estimating a discrete time-discrete data stochastic process. In C. F. Manski & D. L. McFadden (Eds.), Structural analysis of discrete data with econometric applications (pp. 179–195). London: MIT Press.

Henrekson, M., & Johansson, D. (2009). Competencies and institutions fostering high-growth firms. Foundations and Trends in Entrepreneurship, 5(1), 1–80. https://doi.org/10.1561/0300000026.CrossRef

Henrekson, M., & Johansson, D. (2010). Gazelles as job creators: a survey and interpretation of the evidence. Small Business Economics, 35(2), 227–244. https://doi.org/10.1007/s11187-009-9172-z.CrossRef

Hölzl, W. (2014). Persistence, survival and growth: a closer look at 20 years of fast-growing firms in Austria. Industrial and Corporate Change, 23(1), 199–231. https://doi.org/10.1093/icc/dtt054.CrossRef

Hutchinson, J., & Xavier, A. (2006). Comparing the impact of credit constraints on the growth of SME in a transition country with an established market economy. Small Business Economics, 27(2–3), 169–179. https://doi.org/10.1007/s11187-005-4412-3.CrossRef

Jovanovic, B. (1982). Selection and the evolution of industry. Econometrica, 50, 649–670.CrossRef

Lawless, M. (2014). Age or size? Contribution to job creation. Small Business Economics, 42(4), 815–830. https://doi.org/10.1007/s11187-013-9513-9.CrossRef

Levinsohn, J., & Petrin, A. (2003). Estimating production functions using inputs to control for unobservables. Review of Economic Studies, 70(2), 317–342. https://doi.org/10.1111/1467-937X.00246.CrossRef

Lockett, L., Wiklund, J., Davidsson, P., & Girma, S. (2011). Organic and acquisitive growth: re-examining, testing and extending Penrose’s growth theory. Journal of Management Studies, 48(1), 48–74. https://doi.org/10.1111/j.1467-6486.2009.00879.x.CrossRef

López-García, P., & Puente, S. (2012). What makes a high-growth firm in Spain? A dynamic Probit analysis using firm-level data. Small Business Economics, 39(4), 1029–1041. https://doi.org/10.1007/s11187-011-9321-z.CrossRef

Lotti, F., Santarelli, E., & Vivarelli, M. (2009). Defending Gibrat’s law as a long-run regularity. Small Business Economics, 32(1), 31–44. https://doi.org/10.1007/s11187-007-9071-0.CrossRef

Manaresi F. (2015). Net employment growth by firm size and age in Italy. Bank of Italy Occasional Paper no. 298.

Moreno, F., & Coad, A. (2015). High-growth firms: stylized facts and conflicting results. In J. Katz & A. Corbett (Eds.), Entrepreneurship Growth: Individual, Firm, and Region (pp. 187–230). Emerald Group Publishing Limited.

Moschella, D., Tamagni, F., & Yu, X. (2019). Persistent high-growth firms in China’s manufacturing. Small Business Economics, 52(3), 573–594. https://doi.org/10.1007/s11187-017-9973-4.CrossRef

Nelson, R., & Winter, S. (1982). An evolutionary theory of economic change. Cambridge: Harvard University Press.

Nesta. (2009). The vital 6 per cent. Nesta: London.

Parker, S., Storey, D., & van Witteloostuijn, A. (2010). What happens to gazelles? The importance of dynamic management strategy. Small Business Economics, 35(2), 203–226. https://doi.org/10.1007/s11187-009-9250-2.CrossRef

Pozzi, A., & Schivardi, F. (2016). Demand or productivity: what determines firm growth? RAND Journal of Economics, 47, 608–630. https://doi.org/10.1111/1756-2171.12142.CrossRef

Rumelt, R. (1987). Theory, strategy and entrepreneurship. In D. Teece (Ed.), The Competitive Challenge (pp. 137–158) Ballinger Pub.

Schreyer, P. (2000). High-growth firms and employment. OECD Science, Technology and Industry Working Papers, no. 2000/03.

Sutton, J. (1997). Gibrat’s legacy. Journal of Economic Literature, 35, 40–59.

The Economist (2012). Les misérables, Jul 28^th 2012.

Vértesy, D., Del Sorbo, M., & Damioli, G. (2017). High-growth, innovative enterprises in Europe. EUR 28606 EN. Luxembourg: Publications Office of the European Union.

Vivarelli, M. (2014). Innovation, employment and skills in advanced and developing countries: a survey of economic literature. Journal of Economic Issues, 48(1), 123–154. https://doi.org/10.2753/JEI0021-3624480106.CrossRef

Williams, R. (2016). Understanding and interpreting generalized ordered logit models. The Journal of Mathematical Sociology, 40(1), 7–20. https://doi.org/10.1080/0022250X.2015.1112384.CrossRef

World Bank. (2019). High-growth firms: facts, fiction, and policy options for emerging economies. Washington, DC: World Bank.

Title: One swallow does not make a summer: episodes and persistence in high growth
Authors: Silviano Esteve-Pérez
Fabio Pieri
Diego Rodriguez
Publication date: 15-01-2021
Publisher: Springer US
Published in: Small Business Economics / Issue 3/2022
Print ISSN: 0921-898X
Electronic ISSN: 1573-0913
DOI: https://doi.org/10.1007/s11187-020-00443-8

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