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Economics for CED

Economics for CED. Noémi Giszpenc Spring 2004 Lecture 5: Micro: Markets and Information Investment and Insurance March 30, 2004. What is investment?. Investment means to apply resources in ways that you hope will produce more resources later. “Wealth creation”

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Economics for CED

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  1. Economics for CED Noémi GiszpencSpring 2004Lecture 5: Micro: Markets and InformationInvestment and Insurance March 30, 2004

  2. What is investment? • Investment means to apply resources in ways that you hope will produce more resources later. • “Wealth creation” • Also necessary to shore up used-up resources--replacement & maintenance • Does not add to “net” investment Economics for CED: Lecture 5, Noémi Giszpenc

  3. How do firms decide to invest? • Based on calculation: “By the book”--will expected returns exceed expected costs by an acceptable margin? • A great deal of uncertainty exists about the future: a lot of guesswork involved • Based on confidence: leap in the dark • Expectations about what other investors are doing Economics for CED: Lecture 5, Noémi Giszpenc

  4. A detour into accounting • Basic accounting equation:Assets = Liabilities + Equity • Can be seen as a description of capital’s Uses and Sources • Different (combos of) uses bring different returns • Different sources have different costs Economics for CED: Lecture 5, Noémi Giszpenc

  5. Structure of a balance sheet Economics for CED: Lecture 5, Noémi Giszpenc

  6. Uses & sources: returns & costs Annual costs/returns per $100 Cost of capital funds Investment 1 Investment 2 Investment 3 Investment 4 Investment projects 0 $ Quantity of funds Economics for CED: Lecture 5, Noémi Giszpenc

  7. 4 sources of capital • Equity: creating & selling new shares • Pays dividends dependent on performance • “Dilutes” stock of existing shareholders • Retained earnings: “internal funds” • Cheapest & most common source • Bonds: promises to pay interest & principal • Buyers of bonds can trade these in markets • Bank debt: easier to obtain than bond-buyers • Must pay market rate of interest, meet conditions Economics for CED: Lecture 5, Noémi Giszpenc

  8. Calculating return (5 ways) • Total return: good for one-off, immediate & definite return projects • Compare percent difference between returns and costs with market interest rate • Payback: useful for comparing similar investments with similar lifetimes • How long will it take for project to cover costs and start earning? • What will assets be worth and what will they earn after the payback period? • Ex: Farm, office building, bus Economics for CED: Lecture 5, Noémi Giszpenc

  9. Calculating return: 5 ways (cont.) • Accounting rate of return • Good for productive investments with regular returns, analogous to interest rates • Discounted present value of cash flow • For investments with different patterns of earning over time • The amount of money that would need to be invested now, at compound interest at current or expected interest rates, to generate the future asset or income. Economics for CED: Lecture 5, Noémi Giszpenc

  10. Calculating return: 5 ways (cont.) • Internal rate of return • The rate of compound interest that would yield the expected return to an investment • Discounts returns in the future because tied-up capital could be used & earning elsewhere • Can be used to compare alternative investments; compare expected returns w/market returns; estimate present value of future returns Economics for CED: Lecture 5, Noémi Giszpenc

  11. Example: Bonds vs. Pine trees Economics for CED: Lecture 5, Noémi Giszpenc

  12. Effects of different tax regimes • Net profit split between dividends to shareholders and retained earnings • Retained earnings lead to investment, growth in share value --> capital gains for shareholders • Different taxation of dividends & K gains: can encourage or discourage retention • Chosen policy depends on beliefs about how firms, investors choose to invest funds Economics for CED: Lecture 5, Noémi Giszpenc

  13. Why does investment fluctuate? • Lumpy capital • Much productive building & equipment can be paid for over time but must be acquired all at once • Innovation • New product to be produced or new process • Expectations • Better to invest when strong demand expected • Firms tend to invest when others are investing • Acceleration and deceleration • Intensifies booms and slumps Economics for CED: Lecture 5, Noémi Giszpenc

  14. Portfolios of investments • “hedge”: reduce overall risk by spreading investment over many independent projects • The word risk from sailors’ word for steep rock: merchants could lose all their investment in one cataclysm • So they invented insurance Economics for CED: Lecture 5, Noémi Giszpenc

  15. What is insurance? • To make sure. To remove uncertainty and protect against risk. • People prefer certainty: they have an aversion to risk. • In particular people would not like to see income (or rather consumption) dip below a certain minimum. • Willing to pay to “smooth” consumption Economics for CED: Lecture 5, Noémi Giszpenc

  16. Risk, uncertainty, and insurance • Economists use lotteries to think about uncertain situations: • Example 1: say you pay $10 to get: • 10% chance of winning $100 • 90% chance of losing (winning 0) • Example 2: (real life uncertainty --- no charge) • 5% chance of losing $1,000 in a burglary • 95% chance of no burglary, so loss = 0 • Example 3: Plaintiff is injured in an accident and files a lawsuit. She has a • 70% chance of winning damages of $10,000. Economics for CED: Lecture 5, Noémi Giszpenc

  17. Expected Value • Example 1: EV = .10(100) + .90(0) = $10 • Note: this lottery is “fair,” because the cost of the lottery ticket equals the EV of what the buyer will get. • Example 2: EV = .05(-1,000) + .95(0) = -$50. • Example 3: EV = .70(10,000) = $7,000 Economics for CED: Lecture 5, Noémi Giszpenc

  18. Attitudes toward risk • Risk neutral: a risk neutral person is indifferent about “fair” bets. She doesn’t care how much uncertainty she bears. So s/he gets equal utility from having $10 or having a 10% chance of receiving $100 and a 90% chance of receiving 0 (the winnings in example 1). • Risk averse: a risk averse person prefers certainty over “fair” bets. So s/he prefers to have $10 over having the lottery in example 1. • Risk loving: a risk loving person prefers “fair” bets over certainty. So s/he prefers having the lottery in example 1 to having $10. Economics for CED: Lecture 5, Noémi Giszpenc

  19. Utility and Uncertainty: EU • Utility in each state is weighted by its probability of occurring; EU is weighted sum. • Example 2 • Suppose the person’s initial wealth is W. • She faces two possible outcomes: • If the burglary occurs, her wealth falls from W to W-1000, and her utility is U(W-1000), which is lower than... • If no burglary occurs, and her utility is U(W). • Situation (1) occurs with probability .05 and (2) occurs with probability .95. • So her expected utility (the expected value of her U) is:EU = .05 U(W-1000) + .95 U(W) Economics for CED: Lecture 5, Noémi Giszpenc

  20. Expected Wealth • Still Example 2: • The person’s expected wealth (or the expected value of her wealth) is:EW = .05(W-1000) + .95 (W) = W – 50 • Risk neutral people act as though they are maximizing their expected wealth. • They are indifferent to more/less uncertainty and only care about the expected value of their wealth. Economics for CED: Lecture 5, Noémi Giszpenc

  21. Relationship of wealth to utility The slope is the additional utility that individuals receive from an extra dollar of (expected) wealth. Economics for CED: Lecture 5, Noémi Giszpenc

  22. Relationship of wealth to utility • Utility from wealth leads to risk preferences • For risk neutral people, the slope is constant. • This means that they get the same increase in happiness/utility from an additional dollar, regardless of whether they are poor or rich. • For risk averse people, the slope declines as W rises. • Therefore they get a larger increase in happiness/utility from an additional dollar when they are poor than when they are rich. • Because of this, they don’t like uncertainty. Economics for CED: Lecture 5, Noémi Giszpenc

  23. Relationship of wealth to utility: risk averse people • Suppose that instead of W, they have either W+100 or W-100, each with .5 probability. • The value of the extra $100 in additional utility is less than the cost in lost utility of losing $100. • So they gain less from having an additional $100 than they lose from having $100 fewer dollars. • Their utility level when they have W with certainty is U(W), and their expected utility level if they have W+100 or W-100, each with equal probability, is .5U(W+100) + .5U(W-100). • So U(W) > .5U(W+100) + .5U(W-100). • So if they face uncertainty, they will want insurance. Economics for CED: Lecture 5, Noémi Giszpenc

  24. Relationship of wealth to utility • Risk loving people are the opposite of risk averse people. • They get a larger increase in happiness/utility from an additional dollar if they are rich than if they are poor. • As a result, they prefer having W+1 or W-1, each with the same probability, to always having W. • So U(W) < .5U(W+100) + .5U(W-100). • Most people are risk averse. Economics for CED: Lecture 5, Noémi Giszpenc

  25. A role for insurance • Insurance helps reduce or eliminate uncertainty. • Example 2 with burglary insurance: • Suppose there are 20 people who face the same risk of losing $1000 with 5% probability. • They each put $50 into a cigar box, so $1000 is collected in total. • Over the next year, one of them has a burglary and the $1000 is paid to her. • So the insurance provides coverage of $1000 for losses in return for a premium of $50/year. Economics for CED: Lecture 5, Noémi Giszpenc

  26. “Fair insurance” • “Fair insurance” if the insurance premium ($50) just equals the expected value of each insured person’s loss, which is ($1000)(.05) = $50. • So the insurance company makes zero profit. • With the insurance, the person no longer faces uncertainty. She has wealth of • W – 50 if no burglary occurs or • W- 50 –1000 + 1000 = W - 50 if a burglary occurs. • So her utility is U(W-50), regardless of whether a burglary occurs or not. • Suppose the fair insurance premium is called f. Economics for CED: Lecture 5, Noémi Giszpenc

  27. Risk preferences and premiums • risk neutral: indifferent between certainty or uncertain situation with same expected wealth, as in the burglary example. • Indifferent to fair insurance against the risk: expected wealth EW is W-50, regardless • risk averse: prefer certainty over uncertain situation with same expected wealth. • Better off buying fair insurance. • Means that they would be willing to pay more than the fair insurance premium of $50 to get the insurance. Economics for CED: Lecture 5, Noémi Giszpenc

  28. Risk preferences and premiums • risk loving: prefer uncertainty over facing an uncertain situation with same expected wealth. • If offered fair insurance, better off not buying it. • Means they would be willing to pay less than the fair insurance premium of $50 to get the insurance. Economics for CED: Lecture 5, Noémi Giszpenc

  29. Risk aversion and willingness to pay • Assume U= √W • Risk from example 2: 5% chance of a burglary and loss of $1000. • If no insurance, then EU = .05 U(W-1000) + .95 U(W) • Initial wealth, W, is $2,000. • EU = .05*(√ 1000) + .95*(√ 2000) = 44.066 utils • Say person buys fair insurance for a premium of f = $50 • then her wealth is always $1950 and her utility is: • U = √(1950) = 44.159 utils (higher) Economics for CED: Lecture 5, Noémi Giszpenc

  30. Maximum premium • Utility if no insurance is U = 44.06. • The maximum insurance premium that she would be willing to pay would leave her with same utility as no insurance: 44.06 utils. • Suppose the max insurance premium is denoted m. • If she buys insurance for m, then she always will have wealth of 2000 – m and her utility will be U = √(2000 – m) with certainty. • So U = √(2000 – m) = 44.06 and m = $58.15. • This is more than the fair insurance premium of $50. Economics for CED: Lecture 5, Noémi Giszpenc

  31. Conclusions on premiums • a risk averse person is better off if she can buy full insurance for a fair premium than if she goes uninsured. • a risk averse person is willing to pay more than the fair premium to obtain insurance, so m > f. • Note: People can be more/less risk averse. The closer their utility functions are to straight lines, the less risk averse they are and the closer m is to f. Economics for CED: Lecture 5, Noémi Giszpenc

  32. Who buys insurance? Who sells? • Risk averse people: willing to buy insurance for more than the fair insurance premium. • So selling insurance is profitable. (Selling fair insurance means making zero profit.) • So risk neutrals sell insurance to risk averses. • Risk neutral people absorb risk • but are made better off: they receive premiums that are higher than the fair level. • Risk averse people pay more than the fair insurance premium • but are better off because they get rid of risk. Economics for CED: Lecture 5, Noémi Giszpenc

  33. Problems w/ story’s assumptions • Many insurance buyers w/ identical risks. • In our example, all have a 5% chance/year of losing $1000 in a burglary. • The “law of large numbers” allows the insurance company to predict risks very accurately. • Insured persons’ risks of loss independent: • one person’s probability of a loss unaffected by whether another person has a burglary. • Examples of non-independent risks: • Burglars who steal from several apartments in a building. Hurricane or earthquake insurance. • These risks are positively correlated. Economics for CED: Lecture 5, Noémi Giszpenc

  34. Problems w/assumptions (cont.) • No moral hazard. • Refers to increases in the probability of an event occurring if it is insured against. • Example of moral hazard: people with burglary insurance may become careless about locking their doors. • Or, if there is moral hazard, then insurance companies have perfect information. • Example: an insured person doesn’t lock his door. So his probability of loss rises from 5% to 20%. • The insurer observes this and raises the premium from $50 to $200. Economics for CED: Lecture 5, Noémi Giszpenc

  35. Real world insurance • In actuality, the assumptions for fair insurance aren’t met. • So insurance companies use deductibles and co-insurance to reduce moral hazard. • Deductibles: if a loss occurs, the insured person pays the first $100. • Co-insurance: if a loss occurs, the insured person pays 10%. • Sometimes insurance isn’t available, particularly when risks are positively correlated. • Example is earthquake insurance, which is only available as a government program. Why? Economics for CED: Lecture 5, Noémi Giszpenc

  36. Adverse selection • Imperfect information sometimes leads to good risks dropping their insurance coverage. • Example: there are healthy people with 1% chance of getting a disease and unhealthy people with 5% chance of getting the same disease. • People know their types, but insurance companies can’t observe individuals’ types. • So it charges all insureds the same premium of .03L, where L is the cost of treating the disease. • So the healthy subsidize the unhealthy and this causes some healthy people to drop the coverage. Economics for CED: Lecture 5, Noémi Giszpenc

  37. Adverse selection (cont.) • The proportion of unhealthy people in the group of people buying insurance rises. • So the insurance company must raise the price of insurance in order to avoid losing money. • But the unhealthy people may not be willing to pay the high premium. • If so then the insurance disappears completely. Economics for CED: Lecture 5, Noémi Giszpenc

  38. Breakdowns in the system • If buyer of insurance knows more than seller of insurance, there could be adverse selection or moral hazard • If buyer of labor knows less than sellers, could be group-based discrimination • Works the same way in deciding loans • Among results: redlining (not selling insurance or awarding loans in particular areas or for particular populations) Economics for CED: Lecture 5, Noémi Giszpenc

  39. “Lemons” example: used car market • Two types of used cars: good cars and lemons • Sellers know if their used cars are lemons or not. • Value of a lemon is L, and value of a good used car is G: G > L. • Buyers can’t find out if individual used cars are lemons or not. • They only know the overall probability of used cars being lemons = p. • Buyers’ willingness-to-pay for used cars is the expected value of a used car:EV = pL + (1-p)G Economics for CED: Lecture 5, Noémi Giszpenc

  40. “Lemons” example continued • Sellers’ incentives: • keep good cars because G > EV • sell lemons because L < EV. • Adverse selection makes good used cars disappear. • Buyers eventually learn this • so p rises and EV falls. • This makes sellers’ incentives to keep good cars even stronger. • The market for used cars turns into a market for lemons only. Economics for CED: Lecture 5, Noémi Giszpenc

  41. Bankruptcy example • Suppose a person borrows an amount B and promises to repay B(1+r) next year. • Next year, with probability p she will lose her job. In this case, her income falls from Y to Y’. • Her expected utility without bankruptcy isEU = (1-p)U(Y-B(1+r)) + pU(Y’-B(1+r)) • Introduce bankruptcy: If she files for bankruptcy her debt will be discharged. • No obligation to repay from future earnings. • Now her expected utility with bankruptcy isEU = (1-p)U(Y-B(1+r)) + pU(Y’) Economics for CED: Lecture 5, Noémi Giszpenc

  42. Bankruptcy example continued • Bankruptcy makes borrower better off by partially insuring against job loss. • Bankruptcy may cause problems: • lenders raise the interest rate on loans, since borrowers who lose their jobs don’t repay. This makes those who repay their debts worse off. • Bankruptcy is estimated to cost the average debtor who repays $400/yr in extra interest payments. • borrowers may work less hard and become more likely to lose their jobs, since the bad outcome isn’t so bad (moral hazard). • What problems caused w/no bankruptcy laws? Economics for CED: Lecture 5, Noémi Giszpenc

  43. Workarounds the breakdowns • Signaling (costly) • Pay to reveal your type or • Undertake activity that is less costly for your type of person • Examples: university degrees, “resume” paper • Social capital • Investments in reciprocal relationships • Form of insurance, loan guarantees Economics for CED: Lecture 5, Noémi Giszpenc

  44. More workarounds • Conditionality • Often imposed by banks • (doesn’t change underlying motivations) • Loan sharks • Loan to populations thought to be bad risks and charge high premiums • Often use inside knowledge; sometimes threat of violence Economics for CED: Lecture 5, Noémi Giszpenc

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