Econometrics of Asymmetric Information Models with Applications to Nonlinear Pricing, Insurance and Compensation

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Since the nineties, the empirical analysis of auctions has been an active research area to which the PIs contributed with the support of previous NSF grants. Auctions are mechanisms in which buyers compete given their private willingness to pay for an object. The seller's problem is to design auction rules that secure the maximum return. Auctions are asymmetric information models. The PIs propose to analyze new data modeled similarly. As in their previous work, they begin with an economic model, study thoroughly the mapping between it and the data as well as develop quantitative methods drawing from empirical processes, kernel estimation and characteristic functions.First, price discounts (nonlinear pricing) to big buyers are studied. The PIs collect new data on yellow page advertising and cellular phone services. For the latter, they consider a firm proposing two products, namely, voice and SMS. They also address the problem of testing adverse selection by deriving the model restrictions on observables. Second, the research project analyzes insurance in which insurers are heterogeneous in both risk and in attitudes toward risk. Moreover, the PIs consider a finite number of contracts. Both lead to pooling at equilibrium, which represents new challenges. They assess deviations from contract optimality and resulting losses for the insurer. Policy questions are addressed with new data on automobile insurance. Third, this project studies executive compensation and develops models incorporating moral hazard and (i) competition among firms to attract managers and (ii) heterogeneous managers in risk attitudes; utilizing data from S&P ExecuComp.This project further advances the structural analysis of asymmetric information models while addressing fundamental questions. Several new data sets on yellow page advertising, mobile phone service and automobile insurance are collected and will be available to the research community. The methods developed by the PIs will be used by empirical researchers from industrial organization but also from other fields such as health, labor and corporate finance. The results of this project will also assist public institutions in better understanding the impact of regulatory policies on the insurance industry.