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Risk, Uncertainty, and Sensitivity Analysis How economics can help understand, analyze, and cope with limited information

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Generic Group Project Land Use Habitat conservation plan calls for acquisition of 100 acres of land in coastal area. Cost uncertain. Maybe $1,000,000 (30% chance), maybe $3,000,000 (70% chance). NPV of benefits are $2,000,000 (for sure!). Good idea? Marine Reserves Proposal to add 10 km 2 to the CIMR at cost (reduced harvest) of $2 million (NPV); ecological benefits uncertain: $4 million with probability 0.7; $0 with probability 0.3

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What is “risk”? Can be loosely defined as the “possibility of loss or injury”. Should be accounted for in social projects (and regulations) and private decisions. Think of there being different “states of nature” that can emerge, and we are uncertain about which we will end up with. We want to develop a way to describe risk quantitatively by evaluating the probability of all possible outcomes.

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Attitude toward risk Problem: Dean Haston likes to ride her bike to school. If it is raining when she gets up, she can take the bus. If it isn’t, she can ride, but runs the risk of it raining on the way home. Value of riding bike (no rain) = $4 each way Value of riding bike in rain = -$4 (each way) Value of taking bus = $1 (each way)

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Dean Haston’s options & the “states of nature” The Asst. Dean can either ride her bike or take the bus. Bus: She gains $1 each way: $2 Bike: Depends on the “state of nature” Rain (on way home): $4 - $4 = 0. No rain: $4 + $4 = $8.

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Which does she prefer? If the Asst. Dean takes the bus, she knows she’ll gain $2 (no uncertainty). If the Dean rides her bike: If it rains, she gains 0. If it doesn’t rain, she gains $8. Whether she is better taking the bike or bus depends on 2 things: The probability of rain Her attitude toward risk

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The probability of rain Suppose Pr(rain) =.5……Pr(no rain) =.5 Bus: $2 (certain) Bike:.5(8) -.5(0) = $4 (risky) If she is risk neutral, she takes her bike ($4 > $2) If she is a risk lover, she takes her bike If she is sufficiently risk averse, she may bus Suppose Pr(rain) =.8….Pr(no rain) =.2 Bus: $2 Bike:.2(8) +.8(0) = $1.60 (risky) If she is risk neutral, she rides the bus ($2 > 1.60)

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Risk more generally Coin toss pays $10 or $20 Utility Some good (or $) Q: Would this person rather get 15 for sure or play coin toss? U(15).5*U(10) +.5*U(20) This person is RISK AVERSE

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Risk attitudes in general Generally speaking, most people risk averse. Diversification can reduce risk. Since gov’t can pool risk across all taxpayers, there is an argument that society is essentially risk neutral. Most economic analyses assume risk neutrality. Note: may get unequal distribution of costs and benefits.

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Expected payoff more generally Suppose n “states of nature”. V i = payoff under state of nature i. P i = probability of state of nature i. Expected payoff is: V 1 p 1 +V 2 p 2 +… Or V i P i

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Example: Air quality regulations New air quality regulations in Santa Barbara County will reduce ground level ozone. Reduce probability of lung cancer by.001%; affected population: 100,000. How many fewer cases of lung cancer can we expect?…about *100,000 = 1. We don’t know who will get sick but this is our expectation of the number of cases

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Example: Climate change policy 2 states of nature High damage (probability = 1%) Cost = $10 13 /year forever, starting in 100 yrs. Low damage (probability = 99%) Cost = $0 Cost of control = $10 11 Should we engage in control now?

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Control vs. no control (r=2%) Control now: high cost, no future loss Cost = $10 11 Don’t control now: no cost, maybe high future loss: If high damage = [1/( ) + 1/( ) + 1/( ) + … ] = (10 13 /(.02))/( ) = $7 x If no damage = $0.

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Overall evaluation Expected cost if control = $10 11 Expected cost if no control = (.01)(7 x ) + (.99)(0) = $7 x By this analysis, should control even though high loss is low probability event.

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Value of Information The real question is not: Should we engage in control or not? The question is: Should we act now or postpone the decision until later? So there is a value to knowing whether the high damage state of nature will occur. We can calculate that value…this is “Value of information”

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Sensitivity Analysis A method for determining how “sensitive” your model results are to parameter values. Sensitivity of NPV, sensitivity of policy choice. Simplest version: change a parameter, re-do analysis (“Partial Sensitivity Analysis”)

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Climate change: sensitivity to r

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Sensitivity to Uncertainty on the probability of high damage

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More sophisticated sensitivity The more nonlinear your model, the more interesting your sensitivity analysis. Should examine different combinations. Monte Carlo Sensitivity Analysis: Choose distributions for parameters. Let computer “draw” values from distn’s Plot results

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Managing Risk Risk is a problem of its own Several tools available to reduce risk Insurance Liability

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Insurance—fire insurance example Probability of loss: 0.001; Loss=$100,000 Expected annual loss: $100 No insurance Most years: no loss; some years $100,000 loss 1000 houses pool $100 each/yr ($100,000/yr) Most years—one loss Sometimes no losses, sometimes 2-3 losses Much less variability in annual losses Fire is amenable to risk pooling Risks uncorrelated Earthquake insurance in Cal NOT amenable to risk pooling Most years no loss; some years enormous loss

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Conditions for insurability of risks Loss must be amenable to risk pooling There must be a clear loss Loss must be in well-defined period of time Frequency of loss must allow a premium calculation Moral hazard must not be severe (eg, hazardous waste insurance causes folks to be sloppy) Adverse selection must not be severe (eg, only high risk folks take out insurance)

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Liability – a way of regulating risk For firms/individuals engaged in risky activities Rather than regulate risk, hold parties responsbible for negative outcomes Eg, Oil Tanker Regs Some regs apply to nature of tankers Other protection achieved through liability Threat of liability reduces risky activities Bankruptcy can be a problem

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