1 Private Equity Returns and Disclosure Around the World Douglas Cumming and Uwe Walz Hofstra Conference on Private Equity May 2, 2007

2 Motivation: Worldwide Policy Debate 2002 CALPERS disclosure lawsuit – Public pension funds must disclose venture capital and private equity returns, even on unexited investments Implications for understanding determinants of, and reporting of, returns Do we need mandated disclosure standards for VC and PE funds? Biggest issue for VC/PE markets since collapse of Internet bubble Regulation of VC and PE funds one of the biggest issues in UK Financial Times last week

3 Research Questions 1. What are the determinants of VC and private equity returns across countries? 2. Are unexited investment values over-reported to institutional investors? 3. Are biases in reporting unexited investments related to legal conditions? 4. Relative merits of alternative approaches to stimulating VC markets

4 Prior Research VC / PE Returns – Cochrane (2005 Journal of Financial Economics) – Cumming and MacIntosh (2007 Cambridge Journal of Economics) – Hege, Palamino and Schwienbacher (2003 WP) – Lerner, Schoar and Wong (2006 Journal of Finance) – Ljungqvist and Richardson (2003 WP) VC Exits – Cumming and MacIntosh (2003 Journal of Banking and Finance) – Cumming, Fleming and Schwienbacher (2006 Journal of Corporate Finance) VC value-added – Cumming (2006 Journal of Business) – Gompers and Lerner (1999 MIT Press) No prior paper on disclosures of unexited VC returns

5 New Contributions 1. First look at project-specific returns to VC and private equity across countries 2. Innovative application of econometric selection methods to measure VC returns 3. First look at biases in unexited returns and relations to fundraising 4. Policy implications: Reporting Standards needed in VC?

6 I. Theory and Hypotheses II. Data III. Econometric Tests IV. Policy Implications

7 Institutional and Other Investors Venture Capital Funds Entrepreneurial Firms $ Returns $ Returns (realized vs ‘expected’) Venture Capital Cycle E.g., CALPERS California Public Pension Fund Pension Plan Members (you and I) Reporting bias of unexited returns in annual reports? Why care? Distorted asset allocations, less overall fundraising 2-7 years before exit event (IPO, Acquisition, Write-off)  This Paper  Cumming & Johan (2007 JBF)  CD Howe Institute, AEI Sciences Po, Brookings, PWC, EVCA, NVCA, etc. They all care a lot!

8 1. Advice, Monitoring & Returns Monitoring/advice activities of VC are responsible for return of VC Main focus on VC characteristic Model with asymmetric information Advice is not contractible IRR must be sufficiently large to induce VC to undertake optimal level of advice/monitoring The more productive the VC is, the higher the optimal advice/monitoring level  the lower the price of shares for the VC  the higher the VC returns

9 1. Advice, Monitoring & Returns (Continued) Hypotheses: The higher the intensity of monitoring and advice the higher the expected IRR of the VC – Convertible securities, syndication  higher expected rate of return – Co-investment:  lower returns – Smaller portfolios (# investments) / manager  lower returns Better legal environment  more efficient advice and less information asymmetries upon exit  the higher expected returns

10 2. Biases in Reporting Un-Exited Investments Valuation take place against trade-off between  Fundraising concerns (higher valuations potentially facilitate fundraising in next round)  Reputational concerns (overvaluation damages long-run reputation) Simple set-up: two projects, two VC types Pooling equilibria may emerge (bad projects are overstated)

11 2. Biases in Reporting Un-Exited Investments (Continued) Hypotheses: Expected Fundraising Benefit > Expected Reputation Cost – Inexperienced VCs: overstate – Earlier stage and high tech: overstate – Syndicated investment: less likely to overstate – Co-investment: more likely to overstate Legal environment increases costs of overstatement – Less stringent accounting rules: overstate – Sarbanes Oxley: less likely to overstate

12 I. Theory and Hypotheses II. Data III. Econometric Tests IV. Policy Implications

13 CEPRES Dataset 221 venture capital and private equity funds 72 venture capital and private equity firms 5117 entrepreneurial firms (3826 venture capital and 1214 private equity) 32 years (1971 – 2003) 39 countries (North and South America, Europe and Asia) Table 1 (see paper) defines the variables

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16 Table 2. Summary Statistics and Difference Tests Unrealized / Partially realized Ent Firm Investments Fully Realized Ent Firm InvestmentsDifference Tests PE Fund Characteristics # Ent Firms Average IRR Median IRR # Ent Firms Average IRR Median IRRMeansMedians All Funds All Funds in the Data p <= 0.00*** Market and Legal Factors MSCI Return > 3.5% p <= 0.000*** MSCI Return < 3.5% p <= 0.000*** Risk Free Return > 3.5% p <= 0.000*** Risk Free Return < 3.5% p <= 0.000*** Legality Index > p <= 0.000*** Legality Index < p <= 0.000*** Country Earnings Aggressiveness Index > p <= 0.000*** Country Earnings Aggressiveness Index < p <= 0.000*** Country Disclosure Level Index > p <= 0.000*** Country Disclosure Level Index < p <= 0.000***

17 Table 2. Summary Statistics and Difference Tests (Continued) Unrealized / Partially realized Ent Firm Investments Fully Realized Ent Firm InvestmentsDifference Tests PE Fund Characteristics # Ent Firms Average IRR Median IRR # Ent Firms Average IRR Median IRRMeansMedians Fund Characteristics Fund Number in the PE Firm > p <= 0.000*** Fund Number in the PE Firm < p <= 0.000*** Age of Specific PE Fund > 1795 days p <= 0.000*** Age of Specific PE Fund < 1795 days p <= 0.000*** Portfolio Size (# Investees) / # General Partners > **p <= 0.000*** Portfolio Size (# Investees) / # General Partners < p <= 0.000*** Entrepreneurial Firm Characteristics Seed Stage p <= 0.097* Start-up Stage *p <= Early Stage ***p <= 0.000*** Expansion Stage p <= 0.000*** Unknown Seed, Early or Expansion Stage p <= 0.000*** Late Stage p <= 0.000*** MBO/MBI p <= 0.000*** LBO p <= 0.052* Other Type of Private Equity p <= 0.006*** Publicly Listed Firm p <= Industry Market / Book > p <= 0.000*** Industry Market / Book < **p <= 0.000***

18 Table 2. Summary Statistics and Difference Tests (Continued) Unrealized / Partially realized Ent Firm Investments Fully Realized Ent Firm InvestmentsDifference Tests PE Fund Characteristics # Ent Firms Average IRR Median IRR # Ent Firms Average IRR Median IRRMeansMedians Investment Characteristics Lead Investment p <= 0.000*** Syndicated Investment p <= 0.000*** Co-Investment p <= 0.000*** PE Board Seat(s) p <= 0.000*** Convertible Security with Actual Periodic Cash Flows p <= 0.000*** Standard Deviation of Cash Flows to Entrepreneur / Initial $ Invested p <= 0.000*** Standard Deviation of Cash Flows to Entrepreneur / Initial $ Invested ***p <= Initial Amount Invested > $US 2,500, p <= 0.000*** Initial Amount Invested < $US 2,500, p <= 0.000***

19 Table 3. [Condensed] Correlation Matrix (1) Log (1+IRR)1.00 (2)Log (MSCI)0.15 (3)Log (Interest)-0.06 (4)Log (Legality)0.03 (5)Log (Committed Capital)-0.06 (6)Log (Fund Number)0.04 (7)Log (Portfolio Size / Manager)0.03 (8)Seed-0.10 (9)Early-0.03 (10)Expansion0.03 (11)Late0.03 (12)Log (Industry Market / Book)0.01 (13)Lead Investor0.07 (14)Syndicated Investment0.06 (15)Co-Investment-0.06 (16)Board Seats0.00 (17)Convertible Security0.05 (18)Standard Deviation of Cash Flows0.01 (19)Log (Initial Investment)-0.04

20 I. Theory and Hypotheses II. Data III. Econometric Tests IV. Remarks

21 “Realized Returns Econometrics” Multi-step Heckman correction to measure the returns to VC and private equity investment Heckman selection corrections for 1. Unexited / Exited Investments 2. Partial / Full Exits Statistical problems associated with OLS on a subsample of fully realized IRRs

22 3-Step Heckman Correction 1. Probit: Exit / No Exit 2. Selection Corrected Probit: Full / Partial Exit, accounting for the selection effects associated with an actual exit (step 1) 3. Heckman Linear Regression IRR, accounting for both steps # 1 and 2 Contrast to Cochrane (2002): moves from step # 1 to step # 3 Contrast to Ljungqvist and Richardson (2003): OLS on restricted sample of realized returns

23 Table 4. Heckman Corrected IRR Regressions Continued… Panel A. Seed, Start-up, Early and Expansion Stage Investments Predicted Sign for Realized Returns Model (1)Model (2) OLS on Subsample of Fully Realized IRRs 1st Step Heckman Regression: Bivariate Probit Model 2nd Step Heckman Regression (Realized IRRs) Step 1a: Determinants of Exit Step 1b: Determinants of Full Exit, conditioned on step 1a regarding an actual exit Dependent Variable = Log(1+IRR) Dependent Variable=1 if Exit Dependent Variable=1 if Full Exit Dependent Variable = Log(1+IRR) Coefficientt-statisticCoefficient t-statisticCoefficientt-statisticCoefficientt-statistic Constant *** *** Duration of VC Investment (in Days) *** ** Market and Legal Factors Log (MSCI Return) ** Log (Risk Free Rate)? *** *** Log (Legality Index) *** ** Log (Committed Capital Overall Market at Inv Date) *** *** Fund Characteristics Log (Fund Number in the VC Firm) Log (Portfolio Size (# Investees) / General Partner) ** *** Industry Dummy Variables?YesNoYes Country Dummy Variables?YesNoYes Exit Year Dummies?YesNoYes

24 Table 4. Heckman Corrected IRR Regressions (continued) Prior work: explains 1% (Cochrane, 2001) to 12% (Ljungqvist and Rihardson, 2003) of variation in VC returns Predicted Sign for Realized Returns Model (1)Model (2) OLS on Subsample of Fully Realized IRRs 1st Step Heckman Regression: Bivariate Probit Model 2nd Step Heckman Regression (Realized IRRs) Step 1a: Determinants of Exit Step 1b: Determinants of Full Exit, conditioned on step 1a regarding an actual exit Dependent Variable = Log(1+IRR) Dependent Variable=1 if Exit Dependent Variable=1 if Full Exit Dependent Variable = Log(1+IRR) Coefficientt-statisticCoefficient t-statisticCoefficientt-statisticCoefficientt-statistic Investment Characteristics Lead Investment? Syndicated Investment *** * Co-Investment * VC Board Seat(s) ** Convertible Security with Actual Periodic Cash Flows *** *** Standard Deviation of Cash Flows to Entrepreneur ?1.200E-022.0** *** Log (Amount Invested)?9.052E * Heckman Lambda A ** Heckman Lambda B *** Model Diagnostics Number of Observations Adjusted R F Statistic15.74*** 19.65*** Loglikelihood Function Akaike Information Statistic

25 Unexited Reported IRRs (2000 – 2003) versus Predicted IRRs Contrast reported unexited IRRs (as reported to the institutional investors) with predicted IRRs for unexited investments Log(1+IRR Reported)-Log(1+IRR Expected) = Log((1+Reported IRR)/(1+Predicted IRR) = 143% Regression evidence: quite remarkably(!) consistent with the proposition that more informational asymmetry is associated with more ‘lying’!

26 Table 6. Unexited Reported IRRs versus Predicted IRRs Dep Var = Unexited IRR – Predicted IRR from Respective Model # Continued… Panel A. Seed, Start-up, Early and Expansion Stage Investments Predicted Sign Model (1a)Model (1b)Model (2a)Model (2b) Dependent Variable: Unrealized Log(1+IRR) - Fitted Values from Predicted Log (1+IRR) in Model (1) of Table IV Panel A Dependent Variable: Unrealized Log(1+IRR) - Fitted Values from Predicted Log (1+IRR) in Model (2) of Table IV Panel A Coefficientt-statisticCoefficientt-statisticCoefficientt-statisticCoefficient t-statistic Constant *** *** *** *** Market and Legal Factors Log (MSCI Return) *** *** Log (Risk Free Rate)? *** *** Country Earnings Aggressiveness Index *** *** *** *** Country Disclosure Level Index *** *** *** *** Sarbanes Oxley *** *** *** *** Fund Characteristics Log (Age of VC Fund within the VC Firm) *** *** Log (Portfolio Size (# Investees) / General Partner) *** *** Industry Dummy Variables?Yes Country Dummy Variables?Yes

27 Panel A. Seed, Start-up, Early and Expansion Stage Investments Predicted Sign Model (1a)Model (1b)Model (2a)Model (2b) Dependent Variable: Unrealized Log(1+IRR) - Fitted Values from Predicted Log (1+IRR) in Model (1) of Table IV Panel A Dependent Variable: Unrealized Log(1+IRR) - Fitted Values from Predicted Log (1+IRR) in Model (2) of Table IV Panel A Coefficientt-statisticCoefficientt-statisticCoefficientt-statisticCoefficientt-statistic Investment Characteristics Lead Investment? Syndicated Investment *** *** *** *** Co-Investment *** * VC Board Seat(s)? *** *** Convertible Security with Actual Periodic Cash Flows *** *** Standard Deviation of Cash Flows to Entrepreneur ? *** ** Log (Amount Invested)? *** Model Diagnostics Number of Observations1122 Adjusted R F Statistic 37.50***102.20***28.10***91.66*** Loglikelihood Function Akaike Information Statistic

28 Subsample of 80 observations (investee firms) from 11 countries for which both the realized and unrealized reported IRR are known (Canada, Finland, France, Germany, Israel, Norway, Spain, Sweden, the Netherlands, the UK, and the US) The correlation between out-of-sample average realized IRRs and our predicted IRRs is 0.45 Appendix: Compare Actual IRR to Prior Reported Unexited IRR (This is possible now in 2006!) AverageMedian Duration Report  Exit2.6 years Unrealized reported IRR219.71%2.56% Subsequently Realized Reported IRR 98.46%8.70% Predicted IRR (Based on Table IV Model) 15.22%7.75%

29 Table VIII. Determinants of the Difference between Reported Unrealized IRRs Disclosed to Institutional Investors and Subsequently Realized IRRs Predicted Sign Model (A1)Model (A2)Model (A3)Model (A4) Dependent Variable: Unrealized Reported Log(1+IRR) - Fitted Values from Predicted Log (1+IRR) in Model (1) of Table IV Panel B Unrealized Reported Log(1+IRR) - Subsequently Realized Log (1+IRR) Coefficientt-statisticCoefficientt-statisticCoefficientt-statisticCoefficientt-statistic Constant *** *** Market and Legal Factors Log (MSCI Return Reporting Time) Log (MSCI Return Reporting Time) - Log (MSCI Return Exit Time) ? Duration from Reporting to Realization ? Country Earnings Aggressiveness Index * ** ** Country Disclosure Level Index *** Fund Characteristics Log (Age of PE Fund within the PE Firm) Log (Portfolio Size (# Investees) / General Partner) Continued…

30 Predicte d Sign Model (A1)Model (A2)Model (A3)Model (A4) Dependent Variable: Unrealized Reported Log(1+IRR) - Fitted Values from Predicted Log (1+IRR) in Model (1) of Table IV Panel B Unrealized Reported Log(1+IRR) - Subsequently Realized Log (1+IRR) Coefficientt-statisticCoefficientt-statisticCoefficientt-statisticCoefficient t-statistic Entrepreneurial Firm Characteristics Log (Industry Market / Book) *** Industry Dummy Variables? Yes Country Dummy Variables? No Yes Investment Characteristics Syndicated Investment *** Convertible Security with Actual Periodic Cash Flows *** *** *** *** Standard Deviation of Cash Flows to Entrepreneur ? Log (Amount Invested)? Model Diagnostics Number of Observations80 Adjusted R F Statistic20.97***1.90**1.74*2.35** Loglikelihood Function Akaike Information Statistic

31 Not possible to assess causality but there is evidence of positive correlations between overstatement of unexited reported IRRs and fundraising Overstatement of Unexited IRRs and Fundraising

32 Correlations: Overstatement of Unexited IRRs and Fundraising Actual Difference (Reported - Predicted IRR) Fitted Value From Difference Regression Actual Difference Fitted Values from Difference Regression Fund Size VC Firm Age Capital Under Management Capital Under Management to Date of Fundraising

33 I. Theory and Hypotheses II. Data III. Econometric Tests IV. Policy Implications

34 Measuring VC Returns Heckman selection effects are crucial  Misspecification of model without selection effects  Like Cochrane (2002), unlike Ljungqvist & Richardson (2003), unlike Brander et al. (2002)  Multidimensional selection effects are a useful new component introduced in this paper VC value-added is crucial  E.g., portfolio size / manager  Enables us to explain up to 36% of the variation in returns  Cochrane explains at most 1% using market variables only; Ljungqvist & Richardson explain up to 13% with some fund variables, but no proxies for value-added Legality is crucial for cross-country differences

35 Unexited IRRs Reported to Institutional Investors Our findings are quite remarkably(!) consistent with the proposition that more informational asymmetry is associated with more ‘lying’!  for smaller ENTs, tech companies, higher earnings aggressiveness index, lower disclosure index Positive correlation between fundraising and lying