1. Fair Prices Adverse Selection Moral Hazard Contract Design : Costly State Verification Jeffrey H. Nilsen http://video.ft.com/4051985681001/Impact-of-negative- yields/editorschoice

2. Share Return and “Fair Price”  Common stock promises share of firm’s future profits (residual since creditors repaid first) 1 st term: expected dividend yield 2 nd term: expected capital gain At t 0 : uncertain dividend & sale P Rearrange equation for simplest estimate of security’s “fair price” Use return on similar shares as discount rate (required rate of return) indicating share’s risk Expected return for holding equity for 1 period NB: similar to coupon bond held for 1 period

3. Gordon Dividend Growth Model estimates “fair” share P True value of share is PV (expected future cash flows) Assume constant dividend growth (at rate g): Next slide manipulates eqn (*) to derive Gordon’s model (as n gets large, influence of P n evaporates)

4. Gordon (equation manipulation) Multiply both sides by eqn (**) - (*) => “Gordon’s Model” Assume r > g so last term disappears Simplify

5. Gordon Model’s Macro Implication  Monetary Policy Easing (rise in M S ): P 0 rises for 2 reasons:  r eq falls (investors earn less on bonds)  g rises as GDP rises  If recession (slower GDP growth), g falls => P 0 falls  Shiller uses Gordon model to argue share prices are not rational since are more volatile than their (Gordon-determined) fundamentals (assume r > g)

6. Direct Finance Subject to Adverse Selection (Lemons)  Saver can’t evaluate asset quality, will pay only avg. P for asset  Firm selling good asset knows savers pay only avg. market P  Won’t sell its good asset on market since asset undervalued  => few good assets in market, so market quality declines and few transactions  So few firms with good assets issue shares & bonds (direct finance is not frequently utilized)

7. Mitigating Adverse Selection in Direct Finance: Provide Info ?  Free-riding & mimicking => info under-provided  S&P e.g. charges for info on issuing firms: but savers pass it on to friends who “free ride”. S&P can’t profit from publishing info  If gov’t requires issuing firms to publish info, bad firms will copy info to look good (e.g. Enron)  Borrowers always better informed than savers  Bank’s specialty to find good borrowers.  Traditionally kept loan on balance sheet so no saver could free ride on bank’s info

8. Mitigating Adverse Selection in Direct Finance: Other Mechanisms?  Collateral is something of value given to bank if borrower defaults  Borrower’s NW => borrower also suffers loss if project fails => aligns her incentives with those of lender

9. Moral Hazard in Equity (Principal – Agent problem)  Managers (agents) are hired by owners (principals) but may not act to maximize owner’s profits.  E.g. managers exert low effort contributing to low profits suffered by owner  Extreme case e.g. Enron: corrupt managers receive lavish pay, “cooked the books” to avoid detection

10. Principal – Agent Problem With Costly Monitoring (MON)  Owner or lender pays costs (attention & hired expertise) to MON borrower  Lender designs loan contract to cover cost of MON:  Bank takes share of residual profits, entrepreneur can easily cheat by reporting smaller amount, so bank must always MON  Bank takes fixed payment, MON only when don’t receive it  If MON costs high gives reason for “standard debt contract” SDC) to be optimal contract  Known in economic literature as “costly state verification”

11. Townsend (1979): Costly State Verification (CSV) Model  Risk-neutral entrepreneur has project but no funds  Costlessly observes project outcome  Project outcome depends on SON  Only resources are from project (can’t give collateral)  Risk-neutral bank (lends)  Can’t directly observe outcome  Verify entrepreneur’s claimed SON by paying fixed cost γ  Lends if E(return)= I (cost of funds)  First choose which SON to MON & which SON to NOT Eichenberger & Harper 6.2

12. Bank Wants Contract that’s Incentive Compatible (IC)  An IC contract doesn’t give borrower incentive to lie about SON (bank learns SON from borrower’s claim)  Z is return paid to bank  z NOT = R (a constant); otherwise entrepreneur would always claim lowest repayment SON  z MON < z NOT : IF borrower pays bank more when MON, borrower would always claim NOT

13.  Assign to MON state if project return < bank’s cost of funds  (this is approximately correct)  If project fails, entrepreneur must give whatever remains of project to bank (has no other resources) Example Preliminaries

14. MON costs are passed from lender to entrepreneur !! E(project return) – (repay in MON) – (repay in NOT) SONLMH Probability0.250.500.25 f(SON)½23 I = 1 Mon Cost Bank’s cost of funds Project outcomes in all SON Borrower gives bank project outcome if can’t pay promised R Repay bank if project succeeds

15. The Bank’s Profits E(return in NOT) + (repay in MON) - (MON costs) SONABC Probability.25.50.25 f(s)½23 I = 1 Specific MON costs cut bank profits

16. The Bank’s Participation Constraint (PC) E(return) + (repaid in MON) = cost of funds + E(MON cost) SONABC Probability.25.50.25 f(s)½23 PC determines value for R !! Motivate entrepreneur’s high finance costs: to compensate bank for risk of bad SON + MON costs

17. Assign Bank MON costs but it passes them on to Entrepreneur So Entrepreneur pays bank’s cost of funds + MON costs

18. Optimal Contract  R > I => must compensate bank for SON where f(s) < I  (with higher γ, need higher R) MON NOT (constant R) I is cost of funds z return to bank

19. Lessons from Costly State Verification (CSV)  If Mon costs zero, R > I compensates bank only for SON when outcome lower than fixed payment  If MON costs > 0, asymmetric info raises cost of funds to entrepreneur, dampens investment  SDC is real-world loan contract: bank asks for R, if it receives less, it declares entrepreneur bankrupt to recover as much as possible

20. Moral Hazard if Debt  If lender buys debt, riskier project tempts entrepreneur  Entrepreneur likes: earns more if win  Lender dislikes: less likely to be repaid  Example $10 loan: If succeed If failEntrepreneur expects Probability of non- payment to lender Planned Project 90% $20 10% $0 Risky Project 50% $50 50% $0 Expected value = prob win * (amt win) + prob lose * (amt lose)

21. Moral Hazard if Debt  If a lender buys debt, riskier project can tempt entrepreneur  Entrepreneur likes: earns more if win  Lender dislikes: less likely to be repaid  Example $10 loan: If succeed If failEntrepreneur expects Probability of non- payment to lender Planned Project 90% $20 10% $0$18 10% Risky Project 50% $50 50% $0$2550% Expected value = prob win * (amt win) + prob lose * (amt lose)

22. Solving Moral Hazard in Debt  Include Restrictive Covenant in Contract to ensure entrepreneur uses funds in specific project  NW or Collateral aligns borrower’s incentives with lender’s  Lender seizes NW or collateral if borrower defaults  Bank specializes in loan monitoring and enforcement