2. Lecture one © copyright ： qinwang 2013 Qinwang@mail.shufe.edu.cn SHUFE school of international business

3. Outline What is managerial economics Objectives of the firm Analysis methods Risk and uncertainty Agency Problems & Solutions

4. Resource allocation Organization activity The nature of managerial economics Economics Management

5. Economic Theory  Economic theory helps managers understand real-world business problems Uses simplifying assumptions to turn complexity into relative simplicity  The Main Problem in Economy Limited resources Unlimited wants

6.  Limit personal wants ?  Get more resources? Resource allocation: How to use limited resources to satisfy unlimited wants. What would you do?

7. Economics What ？ How much ？ For who ？ When Where How

8. Resource scarcity---Economic-cost and revenue ---Decision What Does “ Managerial Economics ” Do? Help manager to make business decision on the economic perspective and use micro- economic theory to make your decision effectively.

9. Managerial Economics Integrates the use of economics, math, and financial analysis to make good business decisions Managerial economics Economic Management Decision technique Business decision

10. Objectives of the firm The Nature of the Firm Division of labor advantage theory Transaction cost theory The boundary of the firm Case: GM and Fisher (auto-parts producer ) Knowledge theory

11. Objectives of the firm  Profit maximization: Short-term profit? Long-term profit?

12.  Shareholder wealth maximization The value of the firm =V 0 (shares outstanding), is the present value of expected future profits  or cash flows, discounted at the shareholders required rate of return, Ke, ignoring taxes.  V 0 (shares outstanding) =   t /(1+Ke) t t=1

13.  Profit: = TR - TC = P Q - TC  Economic Cost (or opportunity cost) is the highest valued benefit that must be sacrificed as a result of choosing an alternative.  Economic profit is the difference between revenues and total economic cost (including the economic or opportunity cost of owner supplied resources such as time and capital.

14. Why Profit Varies Across Industries?  Risk-bearing theory  Dynamics equilibrium (or frictional, temporary disequilibrium) theory of profit  Monopoly theory of profit  Innovation theory of profit  Managerial efficiency theory of profit

15. Analysis methods : 1.Marginal perspective :“It is valuable ？ ” The flight is traveling from city A to city B, Total cost of every seat is $250. When there are still some seats available (vacancies) ， would you like sell them to students for $150 ？

16. 2. Maximum perspective: The more the better? P fertilizer = wheat Wheat plant and fertilizer: P fertilizer =30, P wheat =15, How much fertilizer per Mu to get profit maximum for the farmer ？ Quantity of fertilizer/mu Production (unit) Marginal production 020-- 13010 2388 3435 4463 5482 6491 7 0

17. Marginal Revenue = Marginal Cost profit=TR-TC=15×48-30 ×5=570 Quantity of fertilizer Marginal revenue ( ￥ ) Marginal costMarginal profit 0-- 115030120 2 3080 3753045 4 3015 530 0 61530-15 7030-30

18. 3. Game Analysis Prisoner dilemma

19. Two Auto’s Price Decision Products of Auto Firm I and Firm II have no difference ， Price is the main factor in competition Profit ： Million Firm II High priceLow price Firm I High price 500 ， 500100 ， 700 Low price 700 ， 100300 ， 300

20. Risk, uncertainty and information  Risk and uncertainty  Risk reference  Information asymmetry and decision Economic Decisions CONSTRAINTS INFORMATION GOALS & OBJECTIVES

21. Risk vs. Uncertainty  Risk Must make a decision for which the outcome is not known with certainty Can list all possible outcomes & assign probabilities to the outcomes  Uncertainty Cannot list all possible outcomes Cannot assign probabilities to the outcomes

22. Expected Value  Expected value (or mean) of a probability distribution is: Where X i is the i th outcome of a decision, p i is the probability of the i th outcome, and n is the total number of possible outcomes

23. Economic situation ProbabilityROI: rate of return on investment(%) Case one （ Treasury bonds ） Case two （ Corporate bond ) Case three (Stock market) Depression0.28.010.0-2.0 Normal0.58.09.011.0 Prosperous0.38.0 19.0 Expected value 18.08.910.8 The person has one million to invest for one year.

24. Variance  Variance is a measure of absolute risk Measures dispersion of the outcomes about the mean or expected outcome The higher the variance, the greater the risk associated with a probability distribution

25. Identical Means but Different Variances

26. Decisions Under Risk  No single decision rule guarantees profits will actually be maximized  Decision rules do not eliminate risk Provide a method to systematically include risk in the decision making process

27. Expected value rule Mean- variance rules Coefficient of variation rule Summary of Decision Rules Under Conditions of Risk Choose decision with highest expected value Given two risky decisions A & B: If A has higher expected outcome & lower variance than B, choose decision A If A & B have identical variances (or standard deviations), choose decision with higher expected value If A & B have identical expected values, choose decision with lower variance (standard deviation) Choose decision with smallest coefficient of variation

28. Which Rule is Best?  For a repeated decision, with identical probabilities each time Expected value rule is most reliable to maximizing (expected) profit Average return of a given risky course of action repeated many times approaches the expected value of that action  For a one-time decision under risk No repetitions to “ average out ” a bad outcome No best rule to follow  Rules should be used to help analyze & guide decision making process As much art as science

29. Decisions Under Uncertainty  With uncertainty, decision science provides little guidance Four basic decision rules are provided to aid managers in analysis of uncertain situations

30. Maximax rule Maximin rule Minimax regret rule Equal probability rule Summary of Decision Rules Under Conditions of Uncertainty Identify best outcome for each possible decision & choose decision with maximum payoff. Determine worst potential regret associated with each decision, where potential regret with any decision & state of nature is the improvement in payoff the manager could have received had the decision been the best one when the state of nature actually occurred. Manager chooses decision with minimum worst potential regret. Assume each state of nature is equally likely to occur & compute average payoff for each. Choose decision with highest average payoff. Identify worst outcome for each decision & choose decision with maximum worst payoff.

31.  Risk averse If faced with two risky decisions with equal expected profits, the less risky decision is chosen  Risk loving Expected profits are equal & the more risky decision is chosen  Risk neutral Indifferent between risky decisions that have equal expected profit Manager ’ s Attitude Toward Risk

32. Thrown a coin for one time, the flower is upward, you get 1000 ， the flower is downward, you loss 1000. Coin game

33.  How to reduce risk or shift risk? Search for more Information diversification Insurance

34. Information asymmetry and decision  The type of information asymmetry ：  Asymmetry before contract: adverse selection  Asymmetry after contract: moral hazard

35. Adverse Selection  You spent 200000 RMB in buying a car 3 months ago. Now you want to sell the car. (the mileage of the car is 7500 km. The car is good in quality.  How much is the car worth of? (value)  How much can it be sold in second-hand market? (price)

36.  Lemon market In markets where it is impossible to asses the quality of a product/service, where, so to say the seller of the product has more information than the buyer, the market will gradually deteriorate and maybe even eventually disappear altogether George Akerlof 2001 Nobel Memorial Prize in Economic Sciences 2001

37.  Second-hand car  The insurance market  An person's demand for insurance is positively correlated with his risk of loss, the insurer is unable to allow for this correlation in the price of insurance. This may be because of private information known only to the person himself 。

38.  Signaling model Signaling Labor-market Product–market …… What would you do when faced adverse selection Michael Spence 20012001 Nobel Memorial Prize in Economic Sciences

39. What would you do when faced with adverse selection  Screening model, Screening A technique used by one economic agent to extract otherwise private information from another. Joseph E. Stiglitz 20012001 Nobel Memorial Prize in Economic Sciences

40. Principal-agent theory  Agent ： have more information  Principal ： have less information  Example: Corporate governance: shareholder and managers Insurance market: insurer and insured

41.  The Principal-Agent Problem Shareholders (principals) want profit Managers (agents) want leisure & security  Shareholder Wealth Maximization: Conditions COMPLETE MARKETS - liquid markets for firm's inputs and by- products (including polluting by-products). NO SIGNIFICANT ASYMMETRIC INFORMATION - buyers and sellers all know the same things. KNOWN RECONTRACTING COSTS future input costs are part of the present value of expected cash flows.

42. Solutions to Agency Problems  Incentive (wages and stock option ） Extending to all workers stock options, bonuses, and grants of stock. Help make workers act as owners of firm Residual claimants: shareholder have a residual claims on the firm’s net cash flows after all expected contractual returns have been paid.  Detailed contract  Reputation (professional manager market)

43. Goals in the Public Sector and the Not-For-Profit (NFP) Enterprise Instead of profit, NFP organizations may have as their goals: 1.Maximization of the quantity of output, subject to a breakeven constraint. 2.Maximization of the utility (happiness) of NFP administrators. 3. Maximization of cash flows. 4. Maximization of the utility of contributors to the NFP organization.

44.  Questions??