Presentation is loading. Please wait.

Presentation is loading. Please wait.

New Firm Performance and the Replacement of Founders Jing Chen Copenhagen Business School Peter Thompson Emory University 12th Roundtable for Engineering.

Similar presentations


Presentation on theme: "New Firm Performance and the Replacement of Founders Jing Chen Copenhagen Business School Peter Thompson Emory University 12th Roundtable for Engineering."— Presentation transcript:

1 New Firm Performance and the Replacement of Founders Jing Chen Copenhagen Business School Peter Thompson Emory University 12th Roundtable for Engineering Entrepreneurship Research Georgia Institute of Technology November 10, 2012

2 Motivation Thoery on founder turnover (Holmes and Schmitz 1990) Distinct comparative advantage embodied by entrepreneurs and CEOs Entrepreneurs specialize in new business creation Professional managers specialize in managing existing ventures Research gap in the empirical literature Literature on leadership (CEO)change in established firms (Carroll 1984, Haveman and Khaire 2004) Not exactly an entrepreneurial (startup) context Literature on founder turnover in startups with transformational growth VC-financed (Hellmann and Puri 2002) Small samples of high-tech startups (Wasserman 2003, Boeker and Wilbank 2005) No framework to understand founder turnover in a broader population of firms 2

3 This Paper Purpose/contribution a large representative sample of startups little involvement of VC Research questions Initial / prior startup performance Subsequent performance after founder turnover Labor market outcome of departing founders The matching model Individual level: U-shaped relationship between founder ability and turnover Firm level: mismatching between founder ability and quality of business idea Can the U-shaped relationship be carried over for startup preformance and founder turnover What is the correlation between the first and second-period performance with/without turnover 3

4 A Two-Period Model (I) 4

5 A Two-Period Model (II) 5

6 Payoff with an outside CEO Payoff with the founder Figure 1. Second period payoffs; c > 0. A startup with a very low-quality idea exits the market in the 2nd period The founder stays if his ability is matched with the quality of business idea. Mismatch arises because the founders abiltiy is relatively lower than the quality of business idea. The founde is replaced with a CEO with higher ability. Mismatch arises because the founders abiltiy is relatively higher than the quality of business idea. The founde is replaced with a CEO with lower ability. 6

7 Figure 2. Founder Ability vs. Second-Period Idea Quality, by Outcome Baseline Simulations, 5000 observations 7

8 8 Figure 3. First-Period vs. Second-Period Performance among Surviving Firms, by Outcome VC story

9 Data Entrepreneurship in Denmark Business start-up rate in 2000: 2.99% (13/21 countries in GEM) Venture capital investment in 1999: 0.04% of GDP (Denmark) vs. 0.52% of GDP (US) Three databases maintained by Statistics Denmark The Entrepreneur Database ( ) New businesses created in Denmark Unique identifiers (firm, plant, and one individual) the focus on 1999 and 2000 cohorts due to availability of accounting data The Firm Database ( ) Employment information for all workers at all firms in Denmark Identify possible co-founders The Integrated Database for Labor Market Research ( ) Employer-employee matched panel Labor market information at firm, plant, and individual level Demographic information of employees 9

10 Data Original founder Formed a startup in 1999 or 2000 as a sole proprietor Currently working at the new business At least one employee working at the business as his/her primary occupation (minimum economic activities) Firm outcomes Survival : same firm ID from previous year appears in the current year Ownership change : Different firm ID, same establisment (plant) ID Exit : All establishments of the firm are no longer found in the data Founder status at the original startup Stay : as employee or employer Exit : due to turnover, business exit or ownership change 10

11 1999 cohort (1,588 startups)2000 cohort (2,584 startups) Figure 5. Status Change of Startups by Year 11

12 The Samples Subsample 1: Startup performance and founder turnover 1,784 startups survived during the observation window between founding year and 2005 Subsample 2: Founder turnover and startup future performance Turnover by 2002 Turnover after 2002 No Turnover Exited or acquired by 2002 ×× Exited or acquired after 2002 × Survived to 2004 × 12 2,349 startups remain in subsample 2

13 Dept Var: = 1 if founder replaced in year t Using sales in year t-1Using sales in founding year (1)(2)(3)(4) Log of sales *** *** *** *** (-5.08)(-5.10)(-3.30)(-3.43) (Log of sales) *** *** *** *** (5.71)(5.87)(3.36)(3.61) Founder characteristics Founder age __ *** __ *** (-3.05)(-3.40) College educated = 1 __ * __ (-1.38)(-0.54) Male = 1 __ __ (-1.28)(-0.86) Married = 1 __ *** __ *** (-3.25)(-2.98) Firm characteristics Firm age *** *** *** *** (-10.39)(-9.47)(-9.68)(-8.46) Cohort dummy (= 1 if founding year = 2000) (1.34)(1.04)(0.96)(0.69) Controls for industryNoYesNoYes Ave Log Likelihood No. of observations7,3577,3487,305 Table 1. The Effect of Startup Performance on the Probability of Founder Turnover Sales in thousand DKK. z-scores are in parentheses. Significance levels: *** 0.01, ** 0.05, *

14 14 Figure 3. First-Period vs. Second-Period Performance among Surviving Firms, by Outcome

15 Dept Var: log of sales in 2004 Surviving Firms OLS All Firms Tobit (1)(2)(3)(4)(5)(6) Log.sale *** *** __0.724 *** *** __ (18.8)(18.6)(5.92)(6.12) Turnover0.336 *** *** __-5.00 *** __ (4.15)(2.80)(-14.4)(-0.45) Log.sale 0 *turnover__ ** __ * __ (-2.21) (-1.73) log.sale 0 percentile: <25 th (D1) __ *** __ *** (-16.6) (-5.04) log.sale 0 percentile: 25 th -75 th (D2) __ *** __ *** (-12.5) (-5.48) D1 × turnover__ *** __ *** (2.60) (-8.83) D2 × turnover__ *** __ *** (4.19) (-7.12) D3 × turnover__ __ ** (-0.29) (-9.67) 2000 cohort * * * *** (1.56)(1.49)(-1.76)(-1.80)(-1.85)(-2.76) Adj R-sq Obs.1,440 2,142 Table 2. Founder Turnover and Future Performance of Startups Columns (1) - (3): t statistics in parentheses. Columns (4) - (6): z scores in parentheses. The omitted category in columns (3) and (6) is the top quartile of the log of initial sales. All regressions include controls for industry. Significance levels: *** 0.01, ** 0.05, *

16 Logit Model Dept Var: =1 if firm survived to 2004 (1)(2)(3)(4) Log sale *** *** (3.48)(3.35) log.sale 0 percentile: <25th (D1) *** *** (-2.80)(-2.75) log.sale 0 percentile: 25th -75th (D2) *** *** (-3.83)(-3.81) D1 × turnover *** *** (-8.01)(-5.36) D2 × turnover *** (-6.90)(-1.62) D3 × turnover *** *** (-8.61)(-4.59) Turnover (-0.63)(-1.18) Log.sale 0 *turnover (-1.39)(0.21) 2000 cohort ** *** ** *** (-2.14)(-2.61)(-2.41)(-2.97) Ave. Loglikelihood Obs Z-scores in parentheses. Industry controls included. Significance levels: *** 0.01, ** 0.05, * 0.1. Table 3. Survival and Turnover 16

17 Logit Regressions Dept Var: =1 if being an employer at t+1 (1)(2)(3)(4) Log sale * __ (-0.38)(-1.92) Log sale 0 ^2__0.124 * __ (1.88) Log sale t-1 __ (-0.12)(0.35) Log sale t-1 ^2__ (-0.38) Age t (-0.52)(-0.64)(-0.32) Married t ** ** * * (2.08)(1.96)(1.92)(1.94) Male (-0.30)(-0.29)(-0.21)(-0.17) College t *** *** *** *** (-2.91)(-3.08)(-2.73)(-2.59) Ave. Loglikelihood Obs z scores are in parentheses. Significance levels: *** 0.01, ** 0.05, * 0.1. Table 4. Founders Occupational Choice after Turnover 17

18 Conclusions Summary of findings Founder turnover is more likely in the tails of the performance distribution Founder turnover has less impact on improvement of performance in starups at the upper end of the initial performance distribution (support the matching story) Future earnings of departing founders are positively correlated with the performance of their previous startups There is no evidece that they are more likely to choose entrepreneurship over other occupations after departure. (not consistent with Holmes and Schmitz theory) Future research How do owners decide between selling a business and hiring a CEO (Founder turnover vs. Business turnover) Assess whether founder-CEO paris differ across startups that is consistent with the mismatching model 18

19 Descriptive Summaries Subsample 1 1,784 startups survived during the observation window between founding year and 2005 All No TurnoverTurnover Age (mean years) Male (%) Married (%) Education (%) less than high school exact high school vocational training some college bachelor Master Phd others Obs.7,9617,

20 Descriptive Summaries Subsample 1 1,784 startups survived during the observation window between founding year and 2005 All No TurnoverTurnover Founded in 1999 (%) Initial sales (1,000 DKK)2,1492,1352,347 Initial no. of full-time employees Industry (%) Agriculture Manufacturing Construction Wholesale and retail Transport, post, telecom Low-tech businesses Public Services Personal Services Kibs High-tech Others Obs.7,9617,

21 Descriptive Summaries 1999 Cohort 2000 Cohort TurnoverNo Turnover TurnoverNo Turnover Total ,274 Survived Exited before Exited after AllNo TurnoverTurnover Obs.2,3491, Survival in 2004 (%) Founded in 1999 (%) Initial sales (1,000 DKK)2,008 1,9622,253 Sales in 2004 (1,000 DKK)5,1684,9297,639 Initial no. of full-time employees No. of full-time employees in Subsample 2 21

22 Descriptive Summaries Subsample 3 Turnover Year (t) Obs Age t Male College Married Sale 0 (1,000 DKK)2,5542,1252,3792,1932,5743,243 Gross income t+1 (1,000 DKK) Ave. gross income (1,000 DKK) Self-employed t No. Of years in SE Sales and income are all converted to 2000 prices. Descriptive Summary of Subsample 3 (Mean Values Reported) 22


Download ppt "New Firm Performance and the Replacement of Founders Jing Chen Copenhagen Business School Peter Thompson Emory University 12th Roundtable for Engineering."

Similar presentations


Ads by Google