1. Boom and Bust in the Venture Capital Industry and the Impact on Innovation Josh Lerner Harvard University and NBER

2. Extraordinary drop in venture activity…

3. … has triggered worries about consequences “Most venture capitalists are shelving the expensive change-the-world bets of the past few years.. The danger is that cutbacks will go too fast and too deep.” Business Week, 2001.

4. Agenda u Seeks to understand implications of venture investment collapse for innovation:  Demystifying booms and busts in venture capital.  Understanding implications for public policy.  Exploring public policy consequences.

5. Basic elements u Not different from any other markets:  Supply and demand! u Supply is willingness of investors to provide capital.  Likely to increase with expected rate of return.

6. Supply Curve for Venture Capital Return Quantity

7. Basic elements (2) u Demand is supply of acceptable businesses. u Varies with return demanded by investors:  The higher the return expectation, the fewer firms satisfy the test. u Together supply, demand will determine quantity Q, return R.  Crude but useful!  Can illustrate historical shifts from U.S.

8. Steady-State Level of Venture Capital Return Quantity S D R Q

9. Example 1: 1995-98 u Expansion of opportunity associated with diffusion of the Internet. u Can be seen as shift of demand curve outward. u Increase in VC funding, and rising returns:  Predictions of inevitable decline misguided.

10. Impact of Demand Shock Return Quantity S D2D2 R2R2 Q1Q1 R1R1 D1D1 Q2Q2

11. Example 2: 1979 u Prior to 1979, pension funds essentially prohibited from VC investing. u Policy shift allowed these investments, shifted demand curve out. u Led to decline in considerable growth, but decline in returns.

12. Impact of a Supply Shock Quantity Return R1R1 Q1Q1 R2R2 Q2Q2 S1S1 S2S2 D

13. Example 3: 1957 u Sputnik launch led to two policy shifts:  SBIC program, which made it easier to raise venture pools (supply).  Boost in government high-tech procurement, which increased demand for VC. u Led to substantial increase in quantity, but little impact on returns.

14. Quantity Return R2R2 Q1Q1 R1R1 Q2Q2 Impact of a Supply and Demand Shock S1S1 S2S2 D2D2 D1D1

15. Painful adjustments u So far, assumed smooth adjustment. u In actuality, may see under- or over- reaction:  Dramatic swings in fundraising levels and returns. u How do these effects come about?

16. Level of fundraising

17. Level of returns

18. Rationales for stickiness u VC funds are raised for extended periods. u Investors shift targets only on occasion. u VC groups often limit rate of growth to avoid adjustment problems. u Even after decision is made, draw-downs and liquidations take many years. u Funds “self-liquidate”: must run faster in hot periods to stay even.

19. Consequences of stickiness u In long run, supply curve may be upward- sloping. u But in short run, may be nearly vertical. u Immediate consequence of demand shocks may be spike in returns, not volume.

20. Quantity Return R2R2 Q1Q1 R1R1 Q2Q2 Impact on Quantity of a Demand Shock R3R3 D2D2 D1D1 SS SL

21. Rationales for overshooting u Hard to assess promise of new technologies:  Uncertainty is what created opportunity in first place! u Public markets provide very noisy--but highly visible--signals of industry promised:  “Irrational exuberance.”

22. Consequences of overshooting u Public market, other signals may lead VCs to conclude that major demand shift:  Actual shift may be far more modest. u Supply may swing out to perceived value, leading to:  Surge in funding of investments.  Poor returns.

23. Quantity Return R1R1 Q1Q1 R3R3 Q3Q3 Misleading Public Market Signals SS 1 SL SS 3 D2D2 D1D1 D3D3

24. Venture capital appears to spur innovation u Venture capital is well suited for funding high-risk innovative projects:  Intensive scrutiny of business plans.  Restrictions in preferred stock agreements.  Staged financing.  Board service and monitoring.  Informal advice. Not surprising that dominant funding source.

25. Supporting evidence u Hellmann and Puri [2000]:  Look at 170 Silicon Valley firms.  Venture capital-backed firms seem more innovative on several measures.  Unfortunately, hard to control for causality: Does VC spur innovation or does innovation spur VC?

26. Supporting evidence (2) u Kortum and Lerner [2000] look at industry level:  VC appears to have a strong positive effect: Even after controlling for corporate and government R&D spending.  Use 1979 ERISA shift to address causality issues.  In 1983-95 period, while VC <3% of corporate R&D, accounted for ~10% of innovation.

27. But is impact of market cycles as bad as it seems? u During “overshooting” periods, too similar companies funded at too high valuations:  Biotech financing surge in early 1990s led to dozens of similar firms pursuing same approach to same disease. Mean pre-money value of VC-funded biotech firms in mid-1992 was $70MM.  By 12/93, only 42 of 262 public biotechnology companies had a market capitalization above $70MM.  Financial and social returns modest.  Similar stories form Internet boom.

28. But is impact of market cycles as bad as it seems? (2) u Supporting evidence from regression analyses:  Look at impact of venture capital on innovation in boom periods and others.  Coefficient is about 15% lower during the years and industries with venture investments : Effect is strongly statistically significant.  Effect widens when add controls for causality.

29. But is impact of market cycles as bad as it seems? (3) u Thus, while cycles in activity are dramatic, impact on innovation may be more modest. u Quality of companies funded during booms is often lower.  Caution: if complete melt-down in fundraising, investments, could be very harmful.

30. Policy implications u “Public venture capital” programs have far too often added “fuel to the fire”:  Concentrating on “hot sectors” in boom periods: May lead to “success stories,” but unlikely to boost innovation much. u Much better strategy is to focus on “out of favor” sectors and technologies:  In-Q-Tel, SBIR provide models.

31. Policy implications (2) u More generally, may be best to focus on boosting demand for funds:  Less emphasis on supply of capital.  Possible efforts: Easing access to early-stage federally funded research. Tax incentives. u Less direct efforts likely to enjoy greatest success!