Knowledge Networks, Venture Investment Flows and Localized New Firm Formation

Knowledge Networks, Venture Investment Flows and Localized New Firm Formation Presentation by D.A. Hicks & C. Xiao School of Economic, Political and Policy Sciences The University of Texas at Dallas ICTPI 09 Porto, Portugal July 13-14, 2009

Outline Background Research Objectives Summary of Relevant Literature Research Design Empirical Results and Interpretation Conclusions Contributions Policy Recommendations

Background - U.S. Economy Venture capital-backed companies employed more than 10 million American workers and generated $2.1 trillion in revenues in 2005. This represents 16.6% of GDP and 9.0% of private sector employment. Source: National Venture Capital Association (2007)

U.S. Venture Capital Investment (Total Investment, $ current) 100,000 90,000 80,000 Total Investment ($) by Source Total Investment ($) by Target 70,000 60,000 50,000 40,000 30,000 20,000 10,000 0 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003

U.S. Venture Capital Investment (Total Deals, $ current) 14,000 12,000 Total Deals by Source Total Deals by Target 10,000 8,000 6,000 4,000 2,000 0 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003

U.S. Venture Capital Investment (Average Value of Investment, $ current) 10,000 9,000 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000 0 1961 1963 1965 Average Value of Investment ($000s) by Source Average Value of Investment ($000s) by Target 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003

VCI Ecosystem Development (Venture Source Metros, #) 130 120 110 100 90 80 70 60 50 40 30 20 10 0 1960 1962 1964 Cumulative Venture Source Metros Venture Source Metros 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002

VCI Ecosystem Development (1960s Venture Source Metros, #) 60 55 50 45 40 35 30 25 20 15 10 5 0 1960 1962 61 Boston, Dallas-Fort Worth, Kansas City, Los Angeles, New York, Providence 62 Austin, Mpls., New Orleans, St. Louis, Washington, D.C. 63 Chicago, San Francisco 64 Springfield (MA) 65 San Jose 67 San Antonio 68 Bridgeport (CT), Cleveland, Columbus (OH), Des Moines, Las Vegas, Milwaukee, Philadelphia, Trenton, Tulsa, Wichita (KS) 69 Atlanta, Buffalo, Hartford, Oxnard 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002

VCI Ecosystem Development (1970s Venture Source Metros, #) 60 55 50 45 40 35 30 25 20 15 10 5 0 1960 1962 1964 70 Baton Rouge, Denver, Jacksonville (FL), 71 Pittsburgh, San Diego, Sheboygan 72 Baltimore, Cedar Rapids, Houston, Miami, Phoenix, 73 Rochester (NY) 75 Charlotte 76 Albuquerque, Detroit, Duluth, 77 Anderson (IN), Cincinnati, Memphis, Nashville 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 79 Indianapolis, Portland (OR), Seattle 1986 1988 1990 1992 1994 1996 1998 2000 2002

VCI Ecosystem Development (1980s Venture Source Metros, #) 60 55 50 45 40 35 30 25 20 15 10 5 0 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 80 Chattanooga, Salt Lake City, Tampa 81 Boulder, Champaign, Greenville (SC), Louisville, Mobile, Richmond, Sacramento 82 Lansing, Madison, Santa Cruz, Santa Fe, Toledo, Winston-Salem 83 Albany, Ann Arbor, Columbia (SC), Durham, Manchester, New Haven, Oklahoma City, Portland (ME) 84 Birmingham, Honolulu, Huntsville, Johnstown, Little Rock, Palm Bay, South Bend, Virginia Beach 85 Allentown, Anchorage, Beaumont, Fort Wayne, Peoria, Provo, Waco 87 Dayton, Santa Rosa 88 Lincoln 89 Tucson 1994 1996 1998 2000 2002

VCI Ecosystem Development (1990s Venture Source Metros, #) 60 55 50 45 40 35 30 25 20 15 10 5 0 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 90 Ithaca, Topeka 92 Raleigh 93 Salinas 94 Harrisburg, Syracuse 95 Macon, Midland 96 Greensboro, Omaha, Stockton 97 Barnstable, Colorado Springs, Sioux Falls, Spokane 98 Bellingha Charleston (S 99 Cape C Orlando, R Barbara, W

VCI Ecosystem Development (2000-0101 Venture Source Metros, #) 60 55 50 45 40 35 30 25 20 15 10 5 0 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 Jackson (MS), Ogden, Pittsfield, Sarasota, Vero Beach 2001 Augusta (GA) 2000 2002

VCI Ecosystem Development (1969-2001 Venture Source Metros, #) 60 55 50 45 40 35 30 25 20 15 10 5 0 61 Boston, Dallas-Fort Worth, Kansas City, Los Angeles, New York, Providence 62 Austin, Mpls., New Orleans, St. Louis, Washington, D.C. 68 Bridgeport (CT), Cleveland, Columbus (OH), Des Moines, Las Vegas, Milwaukee, Philadelphia, Trenton, Tulsa, Wichita (KS) 1960 1962 1964 63 Chicago, San Francisco 64 Springfield (MA) 65 San Jose 67 San Antonio 1966 1968 1970 1972 1974 70 Baton Rouge, Denver, Jacksonville (FL), 71 Pittsburgh, San Diego, Sheboygan 72 Baltimore, Cedar Rapids, Houston, Miami, Phoenix, 73 Rochester (NY) 77 Anderson (IN), Cincinnati, Memphis, Nashville 69 Atlanta, Buffalo, Hartford, Oxnard 75 Charlotte 76 Albuquerque, Detroit, Duluth, 80 Chattanooga, Salt Lake City, Tampa 81 Boulder, Champaign, Greenville (SC), Louisville, Mobile, Richmond, Sacramento 79 Indianapolis, Portland (OR), Seattle 88 Lincoln 1976 1978 1980 1982 1984 1986 82 Lansing, Madison, Santa Cruz, Santa Fe, Toledo, Winston-Salem 83 Albany, Ann Arbor, Columbia (SC), Durham, Manchester, New Haven, Oklahoma City, Portland (ME) 89 Tucson 90 Ithaca, Topeka 92 Raleigh 84 Birmingham, Honolulu, Huntsville, Johnstown, Little Rock, Palm Bay, South Bend, Virginia Beach 85 Allentown, Anchorage, Beaumont, Fort Wayne, Peoria, Provo, Waco 87 Dayton, Santa Rosa 93 Salinas 94 Harrisburg, Syracuse 95 Macon, Midland 1988 1990 1992 1994 1996 1998 96 Greensboro, Omaha, Stockton 97 Barnstable, Colorado Springs, Sioux Falls, Spokane 98 Bellingham, Charleston (SC), El Paso 99 Cape Coral, G Rapids, Kingspo Orlando, Reno, Rockford, St. Cloud, Santa Barbara, Worces Youngstown 2000 Jacks Ogden, Pit Sarasota, V 2000 2002 2001 A

1960s Inward Investment DFW-Received VCI ($1000)

1970s Inward Investment DFW-Received VCI ($1000)

1980s Inward Investment DFW-Received VCI ($1000)

1990s+ Inward Investment DFW-Received VCI ($1000)

1960s Outward Investment DFW-Sourced VCI ($1000)

1970s Outward Investment DFW-Sourced VCI ($1000)

1980s Outward Investment DFW-Sourced VCI ($1000)

1990s+ Outward Investment DFW-Sourced VCI ($1000)

Background - Metro-scale Economies New firm births generated more than 6.7 million jobs in 2002, which accounted for 6.8% of total employment in U.S. metroregions.

Research Objectives: To test for a link between targeted venture capital investment (VCI) and localized new firm formation (NF 2 ) VCI NF 2 To identify patterned variations in NF 2 across U.S. metro-regions To elaborate the original relationship in a multivariate model (1990-2001).

Literature Review - Determinants of NF 2 Extant literature reports that the regional attributes influencing NF 2 can be grouped into six (6) categories: 1) Macro-economy infrastructures 2) Market-demand conditions 3) Industry structure and dynamics 4) Infrastructure supporting innovation potential 5) Human capital 6) Unemployment rate/level

Literature Review- Determinants of NF 2, (Cont d) Macro-Economy Activity Economic Growth (GDP Δ --Fritsch & Falck, 2003; real GDP p.c. --Johnson & Parker,1996) Government Spending (Sutaria & Hicks, 2004; Kirchhoff, et. al. 2002) Market Demand Conditions : Population (Sutaria & Hicks, 2004; Lee, Florida & Acs, 2004; Audretsch & Fritsch, 1994) Income Growth (Sutaria & Hicks 2004; Armington & Acs, 2002)

Literature Review- Determinants of NF 2, (Cont d) Industry Structure Establishment Size (Sutaria & Hicks, 2004; Armington & Acs, 2002) Establishment Density (Armington & Acs,2002; Kirchhoff et. al., 2002) Lagged Entry and Exit Rates (Sutaria & Hicks, 2004; Fritsch & Falck, 2003; Johnson & Parker, 1996) Services Employment Share (Johnson & Parker, 1996)

Literature Review- Determinants of NF2, (Cont d) Infrastructure for Innovation Potential Patent (Lee, Florida & Acs, 2004; Fritsch & Falck, 2003) R&D Expenditures (Kirchhoff, et. al., 2002) Human Capital College Graduate Share (Armington & Acs, 2002; Kirchhoff, et. al., 2002) Skilled Worker Share (Fritsch,1992)

Literature Review- Determinants of NF 2, (Cont d) Unemployment Unemployment Rate (Sutaria & Hicks, 2004; Reynolds, 1994) Unemployment Δ Rate (Sutaria & Hicks, 2004; Reynolds, 1994)

Research Design Research Questions original relationship Variables and Model Research Hypotheses elaborated model Data Development Steps Analysis Methods

Research Questions In general, what are determinants of NF 2 across U.S. metro-regions? Specifically, does local access to venture capital influence NF 2? If so, how?

Variables & Basic Model Metro-Regional Factors 1. Macroeconomic Factors 2. Market Demand 3. Industrial Structure 4. Human Capital 5. Innovation Infrastructure* Rate of NF 2 *Venture Capital Investment

Modeling NF 2 NF 2 it = ƒ(vciit/it-5,gdpit-1,mdcit-1,isit-1,hcit-1,innoit-1,εit ) where I = region, t = time period NF 2 = New firm formation/entry VCI = Venture capital investment activity GDP = Gross domestic product MDC = Market demand conditions IS = Industrial structure HC = Human capital INNO= Innovative characters ε = Other unmeasured influences

Measuring DV NF 2 NF 2 - The number of new start-up firms per 100,000 workers (Labor market approach)

Category Venture Capital Macro-Econ. Factors Market Demand Condition Industrial Structure Human Capital Innovation Indicators Independent Variables Venture Capital Investment GDP Growth Rate Population Growth Rate Code Operationalization Expected Sign LNVCI Dollar value of venture capital investment in a region ln + GDPGR The rate of growth of domestic product % + POPGR The rate of population growth % + Population Level LNPOP The logarithm of population size ln + HT Share of Employment Mean Establish. Size Exit Rate Entry Rate S&E PhDs SS PhDs College education Total PhDs Academic R&D Expenditures HTS MES EXR ENR PHDSE PHDSS High-tech employment in a region, divided by its total employment. % + Total employment in a region, divided by total number of +/- establishments The ratio of died firms to total firms operating at the end of previous year. The ratio of new start-ups to total establishments operating at the end of previous year. The number of science and engineering doctorates awarded The number of science and engineering doctorates awarded % + % + ln + ln + CES The percentage of adults with at least a bachelor degree % + PHD The number of doctorates awarded ln + RDE Academic R&D expenditures ln + Patent PAT The number of patent issued per 1,000,000 employees +

Identifying VCI Lag Structure Variable Dependent Variable = NF 2 Rate in Year t 0 Standardized Coefficients VCI (ln) t 0.098*** VCI (ln) t-1 0.096** VCI (ln) t-2 0.0969** VCI (ln) t-3 0.1041** VCI (ln) t-4 0.1072** VCI (ln) t-5 0.1172** VCI (ln) t-6 0.1154** Adjusted R-Square 0.0459 0.0428 0.0413 0.0449 0.0549 0.0638 0.0605 Number of Observations 3505 3505 3226 2974 2668 2376 2084

Research Hypotheses A region s H1: level of VCI is positively related to its NF 2 rate. H2: GDP growth rate is positively related to its NF 2 rate. H3: population growth rate is positively related to its NF 2 rate. H4: population size is positively related to its NF 2 rate.

Research Hypotheses A region s H1: level of VCI is positively related to its NF 2 rate. H2: GDP growth rate is positively related to its NF 2 rate. H3: population growth rate is positively related to its NF 2 rate. H4: population size is positively related to its NF 2 rate.

Research Hypotheses A region s H 1 : level of VCI is positively related to its NF 2 rate. H 2 : GDP growth rate is positively related to its NF 2 rate. H 3 : population growth rate is positively related to its NF 2 rate. H 4 : population size is positively related to its NF 2 rate.

Research Hypotheses, cont d. H 5 : high-tech employment share is positively related to the region s rate of NF 2. H 6 : mean establishment size is related to the region s rate of NF 2 ; however, the direction of that relationship is indeterminate. H 7 : current firm exit rate is positively associated with the region s rate of NF 2. H 8 : NF 2 [1-yr. lag] is positively associated with the region s rate of NF 2.

Research Hypotheses, cont d. H 9 : level of PhDs production is positively related to the region s rate of NF 2. H 10 : level of science and engineering PhD production is positively related to the region s rate of NF 2. H 11 : level of social sciences PhD production is positively related to the region s rate of NF 2. H 12 : share of adults with at least a college degree is positively related to the region s rate of NF 2.

Research Hypotheses, cont d. H 13 : A region s academic research and development expenditures are positively related to the region s rate of NF 2. H 14 : A region s level of patent awards is positively related to the region s rate of NF 2.

Data Development Unit of Analysis: MSA/PMSA Time Period: 1990-2001 Coverage: > 300 U.S. metro-regions (MSAs/PMSAs) VCI Flows: county-level data aggregated to MSA/PMSA level R&D Expenditures and Doctorate awards: university-level data allocated to corresponding metro-region based on zip codes

Data Sources Variable Name Data Source Time Period Firm Dynamics Statistics of U.S. Business 1990-2002 GDP Product Bureau of Economic Analysis (BEA) 1988-2002 Population Bureau of Economic Analysis (BEA) 1988-2002 Venture Capital VentureXpert (Thompson Financial) 1961-2001 High-tech Employment Bureau of Economic Analysis (BEA) 1988-2002 Mean Establishment Size Bureau of Economic Analysis (BEA) 1988-2002 Academic R&D Expenditures National Science Foundation (NSF) 1988-2002 Patents U.S. Office of Patents and Trademarks (USPTO) 1990-1999 Human Capital (Doctorates Award) National Science Foundation (NSF) 1994-2002 Human Capital (College Education) Bureau of Economic Analysis (BEA) 1990; 2000

Analysis Methods OLS bias (heteroscedasticity, autocorrelation, endogeneity) FGLS - correction for heteroscedasticity and autocorrelation 2SLS - correction for endogeneity

Empirical Results Independent variables Intercept 513.87 (15.27) 529.23 (10.42) 414.34 (9.45) 552.41 (11.71) 542.23 (9.65) 484.28-9.17 1. Macro-economic Condition GDP GR (t-1) 1.68** (2.04) 2.05* (1.8) 1.60* (1.85) 2.35** (2.82) 2.20** (1.98) 2.28** (2.23) 2. Market Demand Population (ln) (t-l) -14.23*** (-4.73) -19.48*** (-5.14) -17.46*** (-4.72) -18.38*** (-3.71) -20.30*** (-4.16) -23.61*** (-4.46) Population Δ (t-1) 15.59*** (5.86) 13.19*** (3.36) 13.61*** (4.12) 16.73*** (6.21) 15.52*** (4.08) 14.86*** (4.87) 3. Venture Capital Investment Venture capital (ln) (t) 2.72*** (4.58) 3.44*** (4.01) 1.73** (2.3) 4.80** (2.43) 5.76*** (2.86) 4.93** (2.53) Venture capital (ln) (t-5) 1.54** (2.34) 2.84*** (3.00) 2.04** (2.48) 1.31* (1.78) 1.53** (2.43) 1.06* (1.76) 4. Industrial Structure MES (t-1) -15.74*** (-20.65) -15.01*** (-13.93) -15.54*** (-16.99) -15.75*** (-19.95) -14.57*** (-14.23) -15.52*** (-17.99) HT emp. share (ln) (t-1) 20.50*** (4.57) 9.28** (2.45) 18.92*** (4.03) 6.89* (1.72) Entry rate (t-1) 14.26*** (8.46) 8.61*** (3.51) 11.01*** (5.05) 11.66*** (6.68) 11.45*** (4.81) 12.66*** (6.05) Exit rate (t) 18.72*** (8.12) 32.53*** (10.18) 33.61*** (11.37) 20.18*** (8.68) 26.37*** (8.68) 28.97*** (10.61) 5. Innovation Assets Patents/ 1m emp. (ln) (t-1) -15.05*** (-4.74) -18.72*** (-4.09) -4.79* (-1.78) -16.95*** (-4.62) -18.50*** (-3.97) -9.81** (-2.31) Academic R&D Exp. (ln) (t-1) 2.80*** (2.73) -5.33*** (-2.75) 2.56** (2.34) -4.76** (-2.58) 6. Human Capital Assets Model 8 Model 9 Model 10 Model 11 FGLS FGLS FGLS 2SLS Model 12 Model 13 2SLS 2SLS PhDs. in SS (ln) (t-1) 3.87 (0.92) 4.32 (0.98) PhDs. in S&E (ln) (t-1) 6.25 (1.08) 2.91 (0.47) Total PhDs (ln) (t-1) 6.95*** (3.46) 5.85** (3.02) Adjusted R-Square 2157.35 (Wald chi2) 1418.88 (Wald chi2) 1682.21 (Wald chi2) 0.6299 0.7119 0.6659 Number of observations (N) 1202 550 811 1202 550 811 F-Value 186.91 104.33 160.26 Corrected autocorrelation Corrected heteroscedasticity Corrected Corrected Corrected Corrected Corrected Corrected treatment (BP/WH(3/4)-test) (4)F=1.17 P=(0.28) (4)F=0.01 P=(0.92) (4)F=1.12 P=(0.29)

Testing for the Effect of Internal VCI Market Demand Population (ln) (t -1 ) -17.26*** (-3.6) -21.07*** (-4.15) Population growth rate (t -1 ) 12.94*** (3.32) 9.27** (3.65) Venture Capital Investment Venture capital (LNVCI) (t) 2.69** (1.36) 1.88** (0.85) Venture capital (LNVCI) (t -5 ) 2.51*** (0.79) 2.71*** (0.92) Internal VCI Share (VCS) (t) 0.81*** (0.18) 0.89*** (0.21) Industrial Structure Mean establishment size (t -1 ) -14.50*** (-0.93) -14.05*** (-1.05) High-tech employment share (ln) (t -1 ) 16.25*** (5.91) Entry rate (t -1 ) 14.02*** (2.12) 9.12*** (2.45) Exit rate (t) 22.83*** (2.79) 37.33*** (3.28) Innovation Characteristics Patents per 1,000k employees (ln) (t -1 ) -8.07** (-4.14) -4.91** (-2.36) Academic R&D expenditures (ln) (t -1 ) 0.54* (0.32) Human Capital Total PhDs (ln) (t -1 ) 8.20*** (2.4) Intercept 465.43 375.45 Log Likelihood -4358.17-3263.31 Number of observations (N) 779 586 Wald Chi Square 1472.94*** 1272.56*** Notes: Standard errors are given in parentheses. *** Significant at 0.01 level, ** at 0.05 level, and * at 0.10 level.

Research Findings Venture Capital: Current VCI levels within a region have a positive independent effect on NF 2 rates. 5-year lagged VCI flows within a region have a positive independent effect on NF 2 rates. Current internal VCI have a positive independent effect on NF 2 rates.

Research Findings- Cont d Regional GDP growth rate and population growth rate have positive effects on NF 2 rates. HT employment share, prior-year NF 2, current-year firm exit rate have positive effects and MSE has a negative effect on NF 2 rates. Patent portfolio size has a negative effect on NF 2 rates. Both local production of PhDs and share of population with at least a BS degree have positive effects on NF 2 rates.

Conclusions Variations in the firm birth rates are substantially explained by regional differences in regional output growth, population growth, industry structure and human capital as suggested by the relevant literature. There is significant empirical evidence to indicate that access to VCI is positively related to regional NF 2 rate.

Contributions to Literature Isolating the independent effect of VCI on NF 2 at the metro-regional level. Linking the VCI and new firm formation literatures. Extending empirical generalizations across a longer period of U.S. economic history.

Policy Recommendations Policies aimed to attract VCI by cutting capital gains tax, providing innovation subsidies and increasing public R&D spending can contribute to new firm creation. Policies or programs that are to support the creation of small firms, to transform large firms into small firms, to attract high-tech employment flows, or to create an easy environment for firm entry and firm exit would benefit a region s NF 2.

Questions? Comments? Thank you!

Directions for Future Research Examine the role of VC financing in NF 2 detailed by industry sectors Conduct some further investigation of the impact of patents on regional NF 2 Investigate what is the role of regional NF 2 in venture capital investment

Appendix-1 - Descriptive Statistics, 1990-2001 Variable Obs. Mean Std. Dev. Min. Max. NFF (per 100k labor forces.) 3286 588.18 163.7 253.21 1544.92 Firm Births 3890 1786.15 3095.79 119 28637 Firm Deaths 3865 1592.97 2790.09 117 26358 GDPGR 3990 7.9 3.72-10.57 63.76 LNVCI 4022 4.5 4.94 0 16.36 LNPOP 3934 5.81 1.03 4.03 9.16 POPGR 3909 1.2 1.24-5.02 9.37 MES 3286 182.35 47.28 64.73 394.93 ENR 3865 11.7 2.26 6.3 30.49 EXR 3865 10.38 1.54 6.46 15.94 HTS 3684 4.43 4.05 0.13 31.11 RDE 2589 9.81 2.39 2.3 14.06 PAT (per 1mil. empl.) 3060 43.59 44.92 0 583.13 PHDTT 1199 4.73 1.50 0 7.52 PHDSE 855 2.91 1.25 0 5.67 PHDSS 1148 4.34 1.46 0 7.19 CES 599 22.44 7.22 9.68 52.40 UNEMPLOYMENT RATE 622 5.25 2.31 1.20 18.00 UNEMPLOYMENT RATE OF CHANGE 622 0.17 0.99-3.11 7.00

Appendix-2:Importance of Adding VCI as Predictor of NFF Dependent Variable: New-firm Formation rate (per 100k labor forces) Model 1-A Model 1-B Model 2 Independent variables FGLS FGLS FGLS Intercept 381.38 (24.56) 435.77 (14.15) 513.87 (15.27) 1. Macro-economic Condition Regional GDP growth rate (t-1) 1.59*** (2.59) 1.69** (2.04) 1.68** (2.04) 2. Market Demand Population (ln) (t-1) -4.21 ** (-2.13) -3.61 (-1.60) -14.23*** (-4.73) Population growth rate (t-1) 11.99 *** (5.63) 15.25*** (5.67) 15.59*** (5.86) 3. Venture-capital investment Venture capital (LNVCI) (t) 2.72*** (4.58) Venture capital (LNVCI) (t-5) 1.54** (2.34) 4. Industrial Structure Mean establishment size (t-1) -13.18*** (-22.23) -15.97*** (-20.75) -15.74*** (-20.65) High-tech emp. share (ln) (t-1) 22.16*** (6.5) 24.33*** (5.44) 20.50*** (4.57) Entry rate (t-1) 12.78*** (10.27) 14.95*** (8.78) 14.26*** (8.46) Exit rate (t) 22.97*** (12.44) 19.13*** (8.2) 18.72*** (8.12) 5. Innovation Assets Patents per 1m emp. (ln) (t-1) -8.80*** (-3.27) -11.20** (-3.57) -15.05*** (-4.74) Academic R&D exp. (ln) (t-1) 2.86*** (3.31) 3.77*** (3.69) 2.80*** (2.73) Pseudo R-Square 0.5895 0.6283 0.6422 Number of observations (N) 1737 1202 1202

Appendix: DV Analysis-Studies on NFF Author Country Time Period Sample Indicator Lee, Florida, & Acs U.S. 1994-96; 1994-1996 at LMAs Number of new firm births per 1 million population (2004) 1997-98 and 1997-98 at MSAs Sutaria & Hicks (2004) U.S. 1976-91 27 MSAs and PMSAs New manufacturing firms entering in a given year as a share of total manufacturing firms operating at the end of the previous year Armington & Acs U.S. 1991-96 394 U.S. LMAs;6 Number of new start-ups per 1,000 labor force (2002) industry sectors Kirchhoff et al. U.S. 1990-99 354 LMAs The number of new firms per 1,000 labor force (2002) Reynolds (1994) U.S. 1986-88 382 LMAs Number of new autonomous firms per 100 establishments Fritsch & Falck (2003) Germany 1983-97 74 Economic regions Number of new establishments per 1,000 employees Audretsch & Fritsch Germany 1986-89 75 Economic regions Number of entrants relative to the number of firms in existence (1994) Fritsch (1992) Germany 1986-87 75 Planning regions Number of start-ups per 1,000 labor force Johnson & Parker U.K. 1990 All U.K. counties Change in the number of VAT registrations (1996) Davidsson & Wiklund (1997) Sweden 1985-89 80 LMAs The average annual number of new single establishments per 1,000 inhabitants Davidsson et al. (1994) Sweden 1985-89 80 LMAs The average annual number of new single establishments per 1,000 inhabitants

Context GDP Market- demand Conditions Industrial S tructure Human Capital Innovation Unemployment Economic Infrastructures Income Growth Lee, Florida, & Acs (2004) U.S. Population (N.S.) Pop. Growth (+) % of adult pop. w/ a bachelor s degree or above (+) Patents per 100k (N.S.) The absolute income change between 1990 and 1996 (+) Sutaria & Hicks (2004) U.S. Pop. Growth Rate (+) Earning shift to services (N.S.) Mean Establishment Size (+) Lag of one year exit rate (+) Lag of one year entry rate (+) Unemployment (N.S.) Unemployment rate change (-) Local bank deposits per capita (+) ; Local government spending (N.S.) Per capita personal income change (N.S.) Armington & Acs (2002) Pop. Growth (+) Establishment size=employment / establishments (-); Share of adults having no high school degree (+) Unemployment rate (-) Personal income growth (+) U.S. Kirchhoff (2002) U.S. Reynolds (1994) U.S. Fritsch & Falck (2003) Germany Audretsch & Fritsch (1994) Germany Fritsch (1992) Germany Johnson & Parker (1996) U.K. Davidsson et al. (1994) Sweden Change of GDP (+) The real per capita GDP (N.S.) Proprietors/ Labor Force (N.S.) Pop-log (+) Pop. Change (+) % Change in Total Pop. (+) Pop. Density:Inhabitants per square mile(+) Population density (N.S.);Population growth (N.S.) Absolute Pop. (+) Pop. Density (+) Pop. Growth (+) Industry intensity= establishments / population (+) Establishment density (+); Establishment size (-) Establishment size:share of employees in establishments with <50 employees (+) (service sector) Mean establishment size (N.S.) Share of services employment (N.S.); Exit rate (N.S.);Entry rate (1 yr lag) (N.S.) share of college graduates (+) College education (+); High school education (-) % of pop over age of 15 in white-collar jobs (+);% of pop over age of 23 w / college degree (+) for business services, (-) for others University R&D expenditure (+) Share of engineers Patents per and employees with 10k pop. (+) a degree in natural sciences working in establishments with <50 employees (+) Share of unskilled and semi-skilled workers (-) share of skilled workers (+) Unemployment/labo r force (N.S.) Unemployment rate-log (+) Unemployment (+); Change in unemployment rate: (+) business services & other sectors;(-) Manufacturing Unemployment rate (-); Change in unemployment (-) (not for service sector) Unemployment rate (+);Change in unemployment rate (+) Unemployment rate (-) The number of unemployed (-) Current unemployment level (+);Previous period s unemployment trend (-) SBIR & STTR Grants (+) Local government spending (-) for all economic sectors; (+) for manufacturing sector Public business support expenditure per capita (+) Per capita income change (+) Gross value added per person (N.S.) High wage level (+)