Evaluating the Expected Welfare Gain from Insurance

By Harrison, Glenn W.; Ng, Jia Min | Journal of Risk and Insurance, March 2016 | Go to article overview

Evaluating the Expected Welfare Gain from Insurance


Harrison, Glenn W., Ng, Jia Min, Journal of Risk and Insurance


ABSTRACT

Economic theory tells us how to evaluate the expected welfare gain from insurance products on offer to individuals. If we know the risk preferences of the individual, and subjective beliefs about loss contingencies and likelihood of payout, there is a certainty equivalent of the risky insurance policy that can be compared to the certain insurance premium. This simple logic extends to nonstandard models of risk preferences, such as those in which individuals exhibit "optimism" or "pessimism" about loss contingencies in their evaluation of the risky insurance policy. We illustrate the application of these basic ideas about the welfare evaluation of insurance policies in a controlled laboratory experiment. We estimate the risk preferences of individuals from one task, and separately present the individual with a number of insurance policies in which loss contingencies are objective. We then estimate the expected consumer surplus gained or foregone from observed take-up decisions. There is striking evidence of foregone expected consumer surplus from incorrect take-up decisions. Indeed, the metric of take-up itself, widely used in welfare evaluations of insurance products, provides a qualitatively incorrect guide to the expected welfare effects of insurance.

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Consider the humble question of the welfare valuation of some new insurance product, such as the "micro-insurance" products being offered and promoted in developing countries. In general, these policies currently are evaluated by the metric of product take-up. (1) Although take-up is easy to measure, it does not automatically reflect the existence or size of the welfare gain of the insurance product to the insured. An insurance product usually involves the individual (2) giving up a certain amount of money ex ante some event in the expectation of being given some money in the future if something unfortunate occurs. Welfare evaluation, therefore, generally requires that one knows risk and time preferences of the individual, since the benefits of the product are risky, and in the future, while the costs are normally (3) certain and up front. We must also know the subjective beliefs that the individual used to evaluate possible losses. (4)

Of course, there is a "revealed preference" argument that if the product is (not) taken up it was perceived to be a positive (negative) net benefit. But that is only the starting point of any serious welfare evaluation, particularly if one wants to quantify the size of the welfare effect. What if the subjective beliefs were biased, in the sense that the individual would revise them if given certain information? What if the evaluation of the product used some criteria other that Expected Utility Theory (EUT)? What if the individual simply made a mistaken decision, given beliefs and risk preferences? Invoking this revealed preference argument implies that one could never find a negative welfare from any insurance decision!

Instead of making a priori assumptions about those preferences that are likely to be wrong, we can use controlled experiments to estimate individual preferences, valuations, and beliefs, and use those estimates in the welfare evaluation of insurance policies. Laboratory experiments provide the ideal environment to set out all of the information and behavior we need to observe in order to draw inferences about welfare. (5) Once we move to the field and consider naturally occurring data, we will then immediately realize what information is missing if we want to make interesting welfare evaluations. In this sense, laboratory and field experiments are complements (Harrison and List, 2004).

The "Theory" section presents the basic theory of insurance demand to be tested. The "Design Implications" section draws implications for the design of experimental tasks to evaluate welfare. The "Experiment" section presents the laboratory design needed to minimally address the question, and the "Results" section presents the results. …

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