2001Palgrave Macmillan UK eBooksRequires access

Welfare and the Strategies of Preference Revelation

Alex Coram

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Abstract

The purpose of this chapter is to consider the case where the state acts as a benevolent dictator and attempts to maximize the welfare of the population. The problem of finding the maximizing set of transfers would be easy to solve if the utilities of each individual and the device for aggregating these utilities, were known. All that would then be required is to specify the welfare operator and to pick the outcomes that maximized the specified measure of aggregate utilities. This may all seem straightforward. Why not simply ask each individual how much each outcome is worth? The values they report could then be aggregated and the outcome selected accordingly. It should be obvious from the previous analysis, however, that the strategies of the individuals reporting their values are unlikely to bring about an outcome on the Pareto frontier. This is because a strategy of lying cannot be prohibited and the optimum strategy for each player will be to report whatever gives the best chance of a favourable outcome. An outcome based on these reports is not necessarily optimal. An example is a game where the prize is given to the individual who reports the highest utility for some desirable outcome. Since it is optimal for everyone to give the maximum number allowable the information content of the reports is zero. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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What this paper is about

The purpose of this chapter is to consider the case where the state acts as a benevolent dictator and attempts to maximize the welfare of the population. The problem of finding the maximizing set of transfers would be easy to solve if the utilities of each individual and the device for aggregating these utilities, were known. All that would then be required is to specify the welfare operator and to pick the outcomes that maximized the specified measure of aggregate utilities. This may all seem straightforward. Why not simply ask each individual how much each outcome is worth? The values they report could then be aggregated and the outcome selected accordingly. It should be obvious from the previous analysis, however, that the strategies of the individuals reporting their values are unlikely to bring about an outcome on the Pareto frontier. This is because a strategy of lying cannot be prohibited and the optimum strategy for each player will be to report whatever gives the best chance of a favourable outcome. An outcome based on these reports is not necessarily optimal. An example is a game where the prize is given to the individual who reports the highest utility for some desirable outcome. Since it is optimal for everyone to give the maximum number allowable the information content of the reports is zero. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Available abstract

The purpose of this chapter is to consider the case where the state acts as a benevolent dictator and attempts to maximize the welfare of the population. The problem of finding the maximizing set of transfers would be easy to solve if the utilities of each individual and the device for aggregating these utilities, were known. All that would then be required is to specify the welfare operator and to pick the outcomes that maximized the specified measure of aggregate utilities. This may all seem straightforward. Why not simply ask each individual how much each outcome is worth? The values they report could then be aggregated and the outcome selected accordingly. It should be obvious from the previous analysis, however, that the strategies of the individuals reporting their values are unlikely to bring about an outcome on the Pareto frontier. This is because a strategy of lying cannot be prohibited and the optimum strategy for each player will be to report whatever gives the best chance of a favourable outcome. An outcome based on these reports is not necessarily optimal. An example is a game where the prize is given to the individual who reports the highest utility for some desirable outcome. Since it is optimal for everyone to give the maximum number allowable the information content of the reports is zero. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Key concepts: Outcome (game theory), Population, Pareto principle, Economics, Ask price, Set (abstract data type), Dictator, Microeconomics

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