Controlling for the effects of information in a public goods discrete choice model

This paper develops a reduced form method of controlling for differences in information sets of subjects in public good discrete choice models, using stated preference data. The main contribution of our method comes from accounting for the effect of information provided during a survey on the mean and the variance of individual-specific scale parameters. In this way we incorporate both scale heterogeneity as well as observed and unobserved preference heterogeneity to investigate differences across and within information treatments. Our approach will also be useful to researchers who want to combine stated preference data sets while controlling for scale differences. We illustrate our approach using the data from a discrete choice experiment study of a biodiversity conservation program and find that the mean of individual-specific scale parameters and its variance in the sample is sensitive to the information set provided to the respondents

The Power of the Little Blue Pill: Innovations and Implications of Life Style Drugs in an Aging Population 1

Abstract The launch of Viagra in April 199

The Effects of Experience on Preference Uncertainty: Theory and Empirics for Public and Quasi-Public Goods

This paper develops a model of demand estimation in which consumers learn about their true preferences through consumption experiences. We develop a theoretical model of Bayesian updating, perform comparative statics over the model, and show how the theoretical model can be consistently incorporated into a reduced form econometric model. We then estimate the model using data collected for two quasi experience with a good will make consumers more certain over their preferences in both mean and variance are supported in each case.‐public goods. We find that the predictions of the theoretical exercise that additiona

Profit Sharing in Renewable Resource industries: Implications and Optimal Management

In renewable resource industries, labor is commonly paid with a share of the harvested resource rather than with a per unit-of-effort wage. Share cropping in agriculture is one well-known example and entitlement of the crew to a share of the revenue from the sale of the catch is almost universal among commercial fishing fleets. This paper shows that sharing arrangements have substantial implications for the industry's profits, optimal resource management, and the resource's ecological state. Effectively, sharing agreements can interact with fluctuations in natural capital to cause inefficient investment levels and skew industry rents toward labor. As a consequence, optimal regulatory policy for such industries must account for the implications of such sharing arrangements. The model demonstrates why management tools like individual transferable quotas in fisheries, have had unexpected ecological benefits in terms of increasing and stabilizing fishery stocks. Finally, the paper provides an illustrative example using the US Pacific albacore fishery

What is the causal impact of information and knowledge in stated preference studies?

This paper reports the results of a stated preference experiment designed to test how information about a good’s attributes provided in a survey affects knowledge, and how knowledge affects preferences for that good. A novel experimental design allows us to elicit subjects’ ex ante knowledge levels about a public good’s attributes, exogenously vary how much new objective information about these attributes we provide to subjects, elicit subjects’ valuation for the good, and elicit posterior knowledge states about the same attributes. We find evidence of incomplete learning and fatigue: as subjects are told more information, their marginal learning rates decrease. Consistent with previous work, ex ante knowledge does affect stated willingness to pay. However, we find no significant marginal impact of knowledge on the mean nor the variance of willingness to pay for changes in the environmental good conditional on ex ante knowledge. Our results are consistent with a number of conceptual models of information processing and preferences, including confirmation bias, costly search, and timing differences in learning and preference formation

SEDP-2014-05

In this study we elicit agents' prior information set regarding a public good, exogenously give information treatments to survey respondents and subsequently elicit willingness to pay for the good and posterior information sets. The design of this field experiment allows us to perform theoretically motivated hypothesis testing between different updating rules: non-informative updating, Bayesian updating, and incomplete updating. We find causal evidence that agents imperfectly update their information sets. We also field causal evidence that the amount of additional information provided to subjects relative to their pre-existing information levels can affect stated WTP in ways consistent overload from too much learning. This result raises important (though familiar) issues for the use of stated preference methods in policy analysis

SEDP-2014-04

This paper compares how increases in experience versus increases in knowledge about a public good affect willingness to pay (WTP) for its provision. This is challenging because while consumers are often certain about their previous experiences with a good, they may be uncertain about the accuracy of their knowledge. We therefore design and conduct a field experiment in which treated subjects receive a precise and objective signal regarding their knowledge about a public good before estimating their WTP for it. Using data for two different public goods, we show qualitative equivalence of the effect of knowledge and experience on valuation for a public good. Surprisingly, though, we find that the causal effect of objective signals about the accuracy of a subject's knowledge for a public good can dramatically affect their valuation for it: treatment causes an increase of $150-$200 in WTP for well-informed individuals. We find no such effect for less informed subjects. Our results imply that WTP estimates for public goods are not only a function of true information states of the respondents but beliefs about those information states

What is the Causal Effect of Information and Learning about a Public Good on Willingness to Pay?

In this study we elicit agents' prior information set regarding a public good, exogenously give information treatments to survey respondents and subsequently elicit willingness to pay for the good and posterior information sets. The design of this field experiment allows us to perform theoretically motivated hypothesis testing between different updating rules: non-informative updating, Bayesian updating, and incomplete updating. We find causal evidence that agents imperfectly update their information sets. We also field causal evidence that the amount of additional information provided to subjects relative to their pre-existing information levels can affect stated WTP in ways consistent overload from too much learning. This result raises important (though familiar) issues for the use of stated preference methods in policy analysis

Social Networks and Non-market Valuations *

Abstract This paper considers the role of social networks in the non-market valuation of public goods. In the model individuals derive utility from both their own direct enjoyment of the public good as well as from the enjoyment of those in their network. We find that network structure almost always matters, both for utility and for valuation. The network increases aggregate valuation when it assigns higher importance, that is, greater total weight, to individuals with higher private values for the public good. The model provides a theoretical foundation for the idea of opinion leaders who have disproportionate influence over their communities. Specifically, opinion leaders are individuals assigned high importance by the network, and projects favored by opinion leaders tend to be favored by the network as a whole. The model can also guide future empirical studies by enabling a more structural approach to non-market valuation in a socially-connected group