David B Audretsch Prepared for the OECD Copenhagen March 2012 3232012 Research Questions What constitutes a highgrowth firm How prevalent are highgrowth firms What is their economic impact ID: 293792
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Slide1
High-Growth Entrepreneurship
David B. AudretschPrepared for the OECDCopenhagen, March 2012
3/23/2012Slide2
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-specificLocationalWhat are policy implications?
3/23/2012Slide3
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)
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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 Sta
tistics (2007)
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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)3/23/2012Slide6
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)
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Determinants
Theoretical Framework
Empirical Evidence
Firm Specific
Locational Specific3/23/2012Slide8
Theoretical Framework –
Gibrat’s Law
Underlying Assumption: Opportunities are randomly distributed
Size
it = (1 +et) Size
it-1
Prediction – Firm growth is unpredictable, randomly distributed and not specific to firm or locational characteristics
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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
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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)
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Empirical Evidence on
Firm Growth
For largest firms, Gibrat’s Law holds
Not systematically
related to firm-specific characteristics of size and ageFor 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)
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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)
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3/23/2012Slide14
Temporal
Impact of Entrepreneurship on Employment Growth in the United States
(
Source: Acs and Mueller, 2007)
3/23/2012Slide15
Determinants of
High-Growth Firms
Firm-Specific Determinants
High Growth Firms Young
High Growth Firms SmallBirch and Medoff (1994), Henrekson and Johansson (2010), Storey (1994)
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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.”
3/23/2012Slide17
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
3/23/2012Slide18
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 oldSurvived startup & adolescent phases prior to being classified as high impact
High-impact firms found in most sectors of economy
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Table 1: U.S. Gazelles
Number of Employees
Period
Number of
Gazelles
Job Change
Revenue Change ($1,000s)
1-19
1994-1998
309,160
3,018,440
$577,533,025
1998-2002
301,275
3,573,918
$716,504,242
2002-2006
283,308
2,883,475
$589,072,471
20-499
1994-1998
43,342
3,014,683
$762,963,829
1998-2002
42,390
3,291,048
$957,923,241
2002-2006
39,617
2,130,682
$1,014,653,361
500-plus
1994-1998
1,547
5,063,517
$1,195,977,664
1998-2002
1,665
4,515,417
$1,841,396,607
2002-2006
1,485
2,514,558
$1,663,635,336
Total1994-1998354,04911,096,640$2,536,474,5181998-2002345,33011,380,383$3,515,824,0902002-2006324,4107,528,715$3,267,361,168
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Number of Employees
Period
Number of High-Impact Firms
Job Change
Revenue Change ($1,000s)
1-19
1994-1998
327,397
3,170,729
$346,038,292
1998-2002
278,190
3,577,111
$423,042,570
2002-2006
359,289
4,041,099
$425,041,975
20-499
1994-1998
23,464
2,788,969
$503,059,203
1998-2002
20,601
2,966,647
$570,102,604
2002-2006
16,523
2,001,835
$549,674,434
500-plus
1994-1998
1,253
5,501,049
$1,110,073,562
1998-2002
1,182
5,192,558
$1,657,759,197
2002-2006
793
2,966,826
$1,060,128,527
Total
1994-1998
352,11411,460,747$1,959,171,0571998-2002299,97311,736,316$2,650,904,371
2002-2006
376,6059,009,760$2,034,844,936
3/23/2012Slide21
1994-1998
1998-2002
2002-2006
Firm Size (No. of Employees)
Firm Size (No. of Employees)
Firm Size (No. of Employees)
1-19
20-499
500-plus
1-19
20-499
500-plus
1-19
20-499
500-plus
Age of Firm
0-4
2.83
0.67
0.56
4.13
0.9
1.35
5.55
0.89
0.385-716.727.944.8922.429.899.7323.2610.196.28-1016.8111.497.94
15.46
11.567.717.313.04
10.63
11-1417.8516.8214.615.0813.929.9814.3413.8210.7615-1915.2216.1913.9513.7516.0915.5711.9514.4113.0420-2410.5111.499.229.6111.6811.688.5912.449.7525-296.759.139.36.248.436.776.098.627.7230-396.629.9611.396.5410.7210.586.7410.9710.8940-493.326.126.822.985.755.332.675.476.9650-692.426.3110.672.46.38.632.275.469.4970-990.953.910.670.943.47.020.863.27.85100-plus0000.451.365.670.391.486.33
3/23/2012Slide22
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
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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)
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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 firmKlepper (2009 ); Agarwal et al. (2004)
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Characteristics of Entrepreneur
High levels of experience in industry
Baum et al. (2001); Baum &Locke (2004)
Gender (male)
BERR (2008
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Characteristics of Founding Team of Entrepreneurs
Size of founding team
Stability of the team members
Time together as a team
Heterogeneity of backgroundCohesivenessEisenhardt & Schoonhoven, 1990
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Locational Characteristics
No tradition in research & managementJournal 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
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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)
3/23/2012Slide29
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 capitalSaxenian (1990)
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Empirical Evidence
Acs, Parsons and Tracy (2008) High-impact firms found in almost every U.S. location
City
SMSA
StateRegion3/23/2012Slide31
Empirical Evidence
Role of Geographic Proximity to Urban Area
Location with close geographic
proximity
to urban area importantHigh impact firms found not only in urban areasImportance of urban area decreasing over timeNo discernible
difference in spatial location of high- and low- impact firms
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Table 4a. High-Impact Firm Geographic Location
Distance from Central Business District (Miles)
1994-1998
1998-2002
2002-2006
Number
Percent
Number
Percent
Number
Percent
In CBD
36,758
10.48
28,085
9.38
33,249
8.84
1-5
31,771
9.06
27,547
9.20
33,966
9.03
6-10
59,279
16.90
50,357
16.82
63,458
16.88
11-15
35,154
10.02
31,476
10.52
39,269
10.45
16-20
26,307
7.50
23,018
7.69
30,169
8.02
21-25
27,998
7.98
24,197
8.08
30,383
8.08
26-30
15,579
4.4413,5074.5118,0144.7931-3510,3772.969,6613.23
12,866
3.4236-4010,1802.90
8,941
2.9911,0462.9441 or more 14,4324.1215,0045.0119,5155.19Rural82,84023.6267,54922.5784,00822.353/23/2012Slide33
Table 4b. Low-Impact Firm Geographic Location
Distance from Central Business District (Miles)
1994-1998
1998-2002
2002-2006
Number
Percent
Number
Percent
Number
Percent
In CBD
983,126
9.83
1,197,286
8.24
1,345,903
7.92
1-5
879,598
8.79
1,318,135
9.07
1,538,320
9.05
6-10
1,660,875
16.60
2,461,005
16.93
2,921,467
17.19
11-15
984,786
9.85
1,513,943
10.41
1,794,170
10.55
16-20
722,589
7.22
1,122,682
7.72
1,359,973
8.00
21-25
762,361
7.62
1,180,531
8.12
1,373,575
8.08
26-30
438,348
4.38662,6074.56801,0964.7131-35290,9372.91443,464
3.05
562,9353.3136-40279,359
2.79
411,1902.83483,4022.8441 or more 434,6494.35714,8634.92877,2255.16Rural2,566,10925.653,513,28124.163,941,50223.193/23/2012Slide34
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)
3/23/2012Slide35
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