Retrieved from https://studentshare.org/environmental-studies/1406981-microeconomic
https://studentshare.org/environmental-studies/1406981-microeconomic.
The below diagram, an Edgeworth box, is not a representation of an efficient system. Pareto optimality would be achieved by shifting further to the right and upwards. K and L can be increased for good X while maintaining quantities for Y. Both indifference curves should be achieved so that they are tangential. However, it is important to note that there are many Pareto optimal outcomes. Both X and Y isoquants can be shifted without reducing the return from the other, or there could be an adjustment for an increase in both (Dwivedi, 2002 537).
The Coase theorem describes economic efficiency in the presence of externalities. It argues that if trade in the externalized cost is possible and there are no transaction costs and no substantial barriers to competition, bargaining over the externalized costs will lead to an efficient outcome. Poorly defined property rights and obligations or poor enforcement of those rights can lead people to shirk the obligation for damaging another's goods.
Our polluting firm is harming the interests of local fishermen. Assuming a competitive market and the right of fishermen to the property either of the fish or the water being polluted, the polluting firm will have to buy the rights to pollute either as a contract or buy the river fully. This will lead to an efficient result: Either the firm can't afford it, meaning that the social value of their product was transparently less than that of the fish; or it can, in which case the fishermen will get ample compensation for their trouble and society will get good X. If property rights belong to the polluter, then it is much harder for the social optimum to be achieved, as the polluter has little incentive to cooperate with the fishermen. Nonetheless, if the value of fish is high enough, then the polluter would have an incentive to buy the fish before the pollution has gotten too bad, and pay the local fishermen; if it isn't, then society didn't want the fish anyways (Mankiw, 2008, 217).
Risk-averse preferences are preferences when faced with uncertainty to err on the side of caution. Risk-averse agents, or agents with risk-averse preferences, will choose a lower-risk scenario out of multiple scenarios, even if the outcome could be higher even after accounting for the risk. Consider a father trying to feed his family: He is not likely to tolerate an investment that has even a 5% chance of failure if that 5% chance could deprive him of feeding his family, even if the growth from that investment was in pure economic senses worth it. Risk-averse preferences stem from scenarios whose risk is more than is quantified economically: In the case of the father, the scenario where he can't feed his family has an infinite negative value.
The certainty equivalent is the guaranteed, immediately available amount of money or value that an individual would view as equally desirable as a risky asset. Take a game where someone can play for $1000 or $0 or simply choose $500. Mathematical expectation says that the scenarios are identical, but the person playing wants a guaranteed return: Thus, to make the show more interesting, it may offer only $250, meaning that $500 (or even a lower number up to $251) is a certainty equivalent.
The risk premium is the amount of added value that a risky asset must bring. If an investment has a 1% chance to fail, I am likely to want a 1.5% growth rate on the investment at a minimum so that over 100 years the failure of an individual year does not threaten my growth.
Maximum willingness to pay for insurance is determined by these factors and others. It can be quantified mathematically: E.g. if I am offering a client a $1,000,000 life insurance policy, and he won't purchase the policy for less than $1000 annually, then that is his maximum willingness to pay (Besanko et al, 2010, 590-612).
Expected Utility: EU = (.8) * £ 100,000^.5 + (.2) * £ 50,000^.5 = 252.98221281347034655991148355462 + 44.721359549995793928183473374626 = 297.70357236346614048809495692925. Round up to 297.8.
The average likely income is £ 90,000 once weighting for probabilities.
Certainty Equivalent U = 297.8.
297.8 = W^1/2.
297.8 ^ 2 = W.
W = £88684.84.
Maximum Willingness to Pay: The maximum willingness to pay is one unit less than the average likely income weighed for probabilities, or 90,000 - .01 = £ 89,999.99.
Expected Utility
297.8
Risk Premium
1315.15 (1315.16 - .1)
Certainty Equivalent
88684.84
Maximum Willingness to Pay
89,999.99
Read More