1. High-Growth Entrepreneurship David B. Audretsch Prepared for the OECD Copenhagen, March 2012 3/23/2012

2. Research Questions What constitutes a “high-growth firm”? How prevalent are high-growth firms? What is their (economic) impact? What are determinants of high growth firms? Firm-specific Locational What are policy implications? 3/23/2012

3. What Constitutes a High Growth Firm? “All enterprises with average annualized growth greater than twenty percent per annum, over a three-year period, and with ten or more employees at the beginning of the observation period. Growth is thus measured by the number of employees and by turnover.” the OECD-Eurostat Manual on Business Demography Statistics (2007) 3/23/2012

4. Gazelle Firms “All enterprises up to five years old with average annualized growth greater than twenty percent per annum over a three-year period, and with ten or more employees at the beginning of the observation period.” OECD-Eurostat Manual on Business Demography Statistics (2007) 3/23/2012

5. Prevalence Less than 5 percent of firms in U.S. (Birch and Medoff, 1994) Between 2-4 percent of firms in U.K. (BERR, 2008) Less than one percent of enterprises in most countries (OECD, 2007) Less than two percent of turnover in most countries (OECD, 2007) 3/23/2012

6. Economic Impact Birch and Medoff (1994 )1988-1992, around 70 percent of all new jobs in the United States created by existing firms (rather than new startups) were accounted for by only four percent of the firms. This same four percent of the firms accounted of 60 percent of all new jobs in the entire U.S. economy. U.K. government study finds between two to four percent of all firms account for most of the growth in employment (BERR, 2008) Account for high share of employment created in any time period OECD (2007) 3/23/2012

7. Determinants Theoretical Framework Empirical Evidence Firm Specific Locational Specific 3/23/2012

8. Theoretical Framework – Gibrat’s Law Underlying Assumption: Opportunities are randomly distributed Size it = (1 +e t ) Size it-1 Prediction – Firm growth is unpredictable, randomly distributed and not specific to firm or locational characteristics 3/23/2012

9. Framework of Knowledge Spillover Theory of Entrepreneurship Knowledge created in one organizational context but not fully commercialized triggers entrepreneurial startups Entrepreneurship provides conduit for spillover of knowledge from organization creating knowledge to new firm commercializing it 3/23/2012

10. Framework of Knowledge Spillover Theory of Entrepreneurship New & firms account for high share of employment created Prediction that high growth should be systematically related to High knowledge contexts (firm & locational specific) Negatively related to firm age (firm specific) Negatively related to firm size (firm specific) (Contrary to Gibrat’s Law) 3/23/2012

11. Empirical Evidence on Firm Growth For largest firms, Gibrat’s Law holds Not systematically related to firm-specific characteristics of size and age For broader distribution of firm size, Growth rates are higher for younger enterprises Growth rates are higher for smaller enterprises Growth rates are even higher for small and young enterprises in knowledge-intensive industries Caves, Journal of Economic Literature (1998) Sutton, Journal of Economic Literature (1997) 3/23/2012

12. Empirical Evidence Consistent with Jovanovic’s theory of noisy selection (1982) and the knowledge spillover theory of entrepreneurship Robust across countries Caves, Journal of Economic Literature (1998) Sutton, Journal of Economic Literature (1997) 3/23/2012

14. Temporal Impact of Entrepreneurship on Employment Growth in the United States (Source: Acs and Mueller, 2007) 3/23/2012

15. Determinants of High-Growth Firms Firm-Specific Determinants High Growth Firms Young High Growth Firms Small Birch and Medoff (1994), Henrekson and Johansson (2010), Storey (1994) 3/23/2012

16. Firm-Specific Determinants Henrekson and Johansson (2010, p. 1), “net employment growth rather is generated by a few rapidly growing firms—so-called gazelles—that are not necessarily small and young. Gazelles are found to be outstanding job creators. They create all or a large share of net new jobs. On average, gazelles are younger and smaller than other firms, but it is young age more than small size that is associated with rapid growth.” 3/23/2012

17. Contradictory Evidence Acs, Parsons and Tracy (2008) American Corporate Statistical Library (ACSL), from Corporate Research Board 1994-2006 Linked to DMI file from Dun & Bradstreet, the United States Bureau of Labor Statistics’ Industry Occupation Mix, and the PUMS file from the United States Census Bureau 3/23/2012

18. Key Findings of Acs, Parsons & Tracy (2008) Most high impact firms are small Large high-impact firms account for most of the employment creation High-impact firms are not young (typical high-impact firm not a startup) Mean age 25 years old Survived startup & adolescent phases prior to being classified as high impact High-impact firms found in most sectors of economy 3/23/2012

19. Table 1: U.S. Gazelles Number of EmployeesPeriod Number of Gazelles Job ChangeRevenue Change ($1,000s) 1-19 1994-1998309,1603,018,440$577,533,025 1998-2002301,2753,573,918$716,504,242 2002-2006283,3082,883,475$589,072,471 20-499 1994-199843,3423,014,683$762,963,829 1998-200242,3903,291,048$957,923,241 2002-200639,6172,130,682$1,014,653,361 500-plus 1994-19981,5475,063,517$1,195,977,664 1998-20021,6654,515,417$1,841,396,607 2002-20061,4852,514,558$1,663,635,336 Total 1994-1998354,04911,096,640$2,536,474,518 1998-2002345,33011,380,383$3,515,824,090 2002-2006324,4107,528,715$3,267,361,168 3/23/2012

20. Number of EmployeesPeriod Number of High-Impact Firms Job ChangeRevenue Change ($1,000s) 1-19 1994-1998327,3973,170,729$346,038,292 1998-2002278,1903,577,111$423,042,570 2002-2006359,2894,041,099$425,041,975 20-499 1994-199823,4642,788,969$503,059,203 1998-200220,6012,966,647$570,102,604 2002-200616,5232,001,835$549,674,434 500-plus 1994-19981,2535,501,049$1,110,073,562 1998-20021,1825,192,558$1,657,759,197 2002-20067932,966,826$1,060,128,527 Total 1994-1998352,11411,460,747$1,959,171,057 1998-2002299,97311,736,316$2,650,904,371 2002-2006376,6059,009,760$2,034,844,936 3/23/2012

21. 1994-19981998-20022002-2006 Firm Size (No. of Employees) 1-1920-499 500- plus 1-1920-499 500- plus 1-1920-499500-plus Age of Firm 0-42.830.670.564.130.91.355.550.890.38 5-716.727.944.8922.429.899.7323.2610.196.2 8-1016.8111.497.9415.4611.567.717.313.0410.63 11-1417.8516.8214.615.0813.929.9814.3413.8210.76 15-1915.2216.1913.9513.7516.0915.5711.9514.4113.04 20-2410.5111.499.229.6111.68 8.5912.449.75 25-296.759.139.36.248.436.776.098.627.72 30-396.629.9611.396.5410.7210.586.7410.9710.89 40-493.326.126.822.985.755.332.675.476.96 50-692.426.3110.672.46.38.632.275.469.49 70-990.953.910.670.943.47.020.863.27.85 100-plus0000.451.365.670.391.486.33 3/23/2012

22. Additional Evidence United Kingdom 2008 study by Department for Business Enterprise and Regulatory Reform (BERR) Broad range of sectors entrepreneurs & management teams with higher skill levels & educational attainment greater propensity to hold intellectual property and intangible assets, including trademarks 3/23/2012

23. Additional Evidence Superior access to finance (high prevalence of venture capital finance) Cultural context promoting high growth High social capital component – networks, partnerships, relationships & linkages to other firms and institutions ( supply chains, formal strategic alliances) BERR (2008) 3/23/2012

24. Characteristics of Entrepreneur High level of human capital (education) BERR (2008); Baum et al. (2001); Baum &Locke (2004); Vivek et al. (2009) Experience as entrepreneur Baum &Locke (2004) Experience as employee in high growth firm Klepper (2009 ); Agarwal et al. (2004) 3/23/2012

25. Characteristics of Entrepreneur High levels of experience in industry Baum et al. (2001); Baum &Locke (2004) Gender (male) BERR (2008 3/23/2012

26. Characteristics of Founding Team of Entrepreneurs Size of founding team Stability of the team members Time together as a team Heterogeneity of background Cohesiveness Eisenhardt & Schoonhoven, 1990 3/23/2012

27. Locational Characteristics No tradition in research & management Journal of Economic Literature surveys by Sutton (1997) and Caves (1998) Existence of cluster or agglomeration of complementary economic activity & supporting institutions -- Porter (1998) Empirical evidence identifying higher growth rates for entrepreneurial startups within a cluster 3/23/2012

28. Empirical Evidence Empirical evidence identifying higher growth rates for entrepreneurial startups within a cluster Gilbert et al. (2006 & 2008); Lechner and Dowling (2003) Geographic proximity facilitates accessing and absorbing localized knowledge spillovers -Jacobs (1969); Jaffe et al. (1993); Audretsch & Feldman (1996) 3/23/2012

29. Localized Spillover Conduits Worker mobility Almeida and Kogut (1999); Saxenian (1990); Lee, Miller, Hancock and Rowen (2000) Entrepreneurial startups (Audretsch, Keilbach & Lehmann, 2006) Localized networks, linkages & social capital Saxenian (1990) 3/23/2012

30. Empirical Evidence Acs, Parsons and Tracy (2008) High-impact firms found in almost every U.S. location City SMSA State Region 3/23/2012

31. Empirical Evidence Role of Geographic Proximity to Urban Area Location with close geographic proximity to urban area important High impact firms found not only in urban areas Importance of urban area decreasing over time No discernible difference in spatial location of high- and low- impact firms 3/23/2012

32. Table 4a. High-Impact Firm Geographic Location Distance from Central Business District (Miles) 1994-19981998-20022002-2006 Number PercentNumberPercentNumberPercent In CBD36,75810.4828,0859.3833,2498.84 1-531,7719.0627,5479.2033,9669.03 6-1059,27916.9050,35716.8263,45816.88 11-1535,15410.0231,47610.5239,26910.45 16-2026,3077.5023,0187.6930,1698.02 21-2527,9987.9824,1978.0830,3838.08 26-3015,5794.4413,5074.5118,0144.79 31-3510,3772.969,6613.2312,8663.42 36-4010,1802.908,9412.9911,0462.94 41 or more14,4324.1215,0045.0119,5155.19 Rural82,84023.6267,54922.5784,00822.35 3/23/2012

33. Table 4b. Low-Impact Firm Geographic Location Distance from Central Business District (Miles) 1994-19981998-20022002-2006 Number PercentNumberPercentNumberPercent In CBD983,1269.831,197,2868.241,345,9037.92 1-5879,5988.791,318,1359.071,538,3209.05 6-101,660,87516.602,461,00516.932,921,46717.19 11-15984,7869.851,513,94310.411,794,17010.55 16-20722,5897.221,122,6827.721,359,9738.00 21-25762,3617.621,180,5318.121,373,5758.08 26-30438,3484.38662,6074.56801,0964.71 31-35290,9372.91443,4643.05562,9353.31 36-40279,3592.79411,1902.83483,4022.84 41 or more434,6494.35714,8634.92877,2255.16 Rural2,566,10925.653,513,28124.163,941,50223.19 3/23/2012

34. Policy Implications Promote entrepreneurship capital Audretsch, Lehmann & Keilbach (2006) Promote access to finance Lerner & Gompers (2010) “There is strong evidence that a heavy regulatory burden negatively impacts new companies’ into the market and thereby contributes to reduced competitive pressure and less entrepreneurship.” Swedish Agency for Growth Policy Analysis (2010, p. 8) 3/23/2012

35. Conclusions High impact entrepreneurship plays key role in growth & job creation in OECD Systematic firm-specific characteristics of post- adolescent & large firms contribute the most to employment growth Entrepreneurial characteristics of human capital, experience, access to finance & social capital important Policy can facilitate high impact entrepreneurship 3/23/2012