This paper studies the nonparametric identification of a contract model with adverse selection and moral hazard. Specifically, we consider the false moral hazard model developed by Laffont and Tirole (1986). We first extend this model to allow for general random demand and cost functions. We establish the nonparametric identification of the demand, cost, deterministic transfer, and effort disutility functions as well as the joint distribution of the random elements of the model, which are the firm's type and the demand, cost, and transfer shocks. The cost of public funds is identified with the help of an instrument. Testable restrictions of the model are characterized.

Identification and Estimation of Bidders' Risk Aversion in First-Price Auctions by Isabelle Perrigne and Quang Vuong. Published in volume 97, issue 2, pages 444-448 of American Economic Review, May 2007

In this paper, we conduct a structural analysis of multi-attribute auctions of contracts with a general allocation rule when private information is multidimensional. Upon modeling bidders’ contract value that accounts for their endogenous ex post actions, we nonparametrically identify bidders’ private information from their bids and estimate their joint distribution. Analyzing cash-royalty auctions of Louisiana oil leases, we find government revenue worse and development rates no better than in a cash auction with a fixed royalty in view of adverse selection and moral hazard. Our findings revise conventional wisdom on the optimality of multi-attribute auctions. (JEL D44, D82, D86, H82, Q35)

This paper analyzes first-price sealed-bid auctions of standing timber organized by the French forest service, Office National des Forêts (ONF). A feature of these auctions is that they are held with random reserve prices. We consider an auction model with a random reserve price within the independent-private-value paradigm. After establishing the identification of the model, we estimate the underlying bidders' private-value distribution by using a simple two-step nonparametric procedure. This procedure allows the computation of the winners' informational rents as well as the optimal reserve price. We then simulate a first-price sealed-bid auction with the optimal announced reserve price. Empirical results show that the optimal reserve price allows the ONF to extract more of bidders' willingnesses to pay. Moreover, our results show that, though sales do not vary much, profits for the ONF would significantly increase and less timber would be sold.

This paper studies the nonparametric identification of the first-price auction model with risk averse bidders within the private value paradigm. First, we show that the benchmark model is nonindentified from observed bids. We also derive the restrictions imposed by the model on observables and show that these restrictions are weak. Second, we establish the nonparametric identification of the bidders' utility function under exclusion restrictions. Our primary exclusion restriction takes the form of an exogenous bidders' participation, leading to a latent distribution of private values that is independent of the number of bidders. The key idea is to exploit the property that the bid distribution varies with the number of bidders while the private value distribution does not. We then extend these results to endogenous bidders' participation when the exclusion restriction takes the form of instruments that do not affect the bidders' private value distribution. Though derived for a benchmark model, our results extend to more general cases such as a binding reserve price, affiliated private values, and asymmetric bidders. Last, possible estimation methods are proposed.

This paper proposes a general approach and a computationally convenient estimation procedure for the structural analysis of auction data. Considering first-price sealed-bid auction models within the independent private value paradigm, we show that the underlying distribution of bidders' private values is identified from observed bids and the number of actual bidders without any parametric assumptions. Using the theory of minimax, we establish the best rate of uniform convergence at which the latent density of private values can be estimated nonparametrically from available data. We then propose a two-step kernel-based estimator that converges at the optimal rate.

This paper proposes a new methodology for analyzing nonlinear pricing data. We establish identification of the model primitives with a known tariff and characterize the model restrictions on observables. We propose a quantile-based nonparametric estimator that achieves consistency at the parametric rate. We introduce unobserved product heterogeneity with an unknown tariff and show how our identification and estimation results extend. A Monte Carlo study analyzes the robustness of our methodology to menus of two-part tariffs. Analysis of cellular service data assesses the performance of various pricing strategies. We discuss extensions to network effects, multiproduct firms, bundling, differentiated products, and oligopolies.

Water utilities are reminiscent of network industries and are characterized by important fixed costs. These factors contribute to a single firm serving an area justifying public intervention on pricing. About one fourth of U.S. water utilities is private and subject to regulation. Regulators are unlikely to be perfectly informed and regulation is unlikely to be costlessly implemented. These inherent imperfections have lead economists to consider the incentive properties of regulatory procedures using the economics of information. See David Baron (1989). The empirical literature on regulation has focused on evaluating the effects of regulation on prices, firms ’ costs, efficiency and innovation in sectors such as airline, electricity and energy as surveyed by Paul Joskow and Nancy Rose (1989). Few of these empirical studies rely on the socalled theory of regulation. Regarding the water industry, there is an abundant literature on residential water demand, firms ’ cost and their efficiency given their public versus private nature. Relying on a model with asymmetric information and a sample of California water utilities, Frank Wolak (1994) assesses the consumer welfare loss due to asymmetric information and shows that the model with asymmetric information provides a superior description of the cost and demand data than the model under perfect