Well-Posedness of Measurement Error Models for Self-Reported Data

It is widely admitted that the inverse problem of estimating the distribution of a latent variable X* from an observed sample of X, a contaminated measurement of X*, is ill-posed. This paper shows that measurement error models for self-reporting data are well-posed, assuming the probability of reporting truthfully is nonzero, which is an observed property in validation studies. This optimistic result suggests that one should not ignore the point mass at zero in the error distribution when modeling measurement errors in self-reported data. We also illustrate that the classical measurement error models may in fact be conditionally well-posed given prior information on the distribution of the latent variable X*.

Private Monitoring and Communication in Cartels: Explaining Recent Collusive Practices

Motivated by recent cartel practices, a stable collusive agreement is characterized when firms' prices and quantities are private information. Conditions are derived whereby an equilibrium exists in which firms truthfully report their sales and then make transfers within the cartel based on these reports. The properties of this equilibrium fit well with the cartel agreements used in a number of markets including citric acid, lysine, and vitamins.

Estimation of Nonlinear Models with Mismeasured Regressors Using Marginal Information

We consider the estimation of nonlinear models with mismeasured explanatory variables, when information on the marginal distribution of the true values of these variables is available. We derive a semi-parametric MLE that is shown to be $\sqrt{n}$ consistent and asymptotically normally distributed. In a simulation experiment we find that the finite sample distribution of the estimator is close to the asymptotic approximation. The semi-parametric MLE is applied to a duration model for AFDC welfare spells with misreported welfare benefits. The marginal distribution of the correctly measured welfare benefits is obtained from an administrative source.

Nonparametric Identification of Auction Models with Non-Separable Unobserved Heterogeneity

We propose a novel methodology for nonparametric identification of first-price auction models with independent private values, which accommodates auction-specific unobserved heterogeneity and bidder asymmetries, based on recent results from the econometric literature on nonclassical measurement error in Hu and Schennach (2008). Unlike Krasnokutskaya (2009), we do not require that equilibrium bids scale with the unobserved heterogeneity. Our approach accommodates a wide variety of applications, including settings in which there is an unobserved reserve price, an unobserved cost of bidding, or an unobserved number of bidders, as well as those in which the econometrician fails to observe some factor with a non-multiplicative effect on bidder values.

On the Conjunction Fallacy in Probability Judgment: New Experimental Evidence Regarding Linda

This paper reports the results of a series of experiments designed to test whether and to what extent individuals succumb to the conjunction fallacy. Using an experimental design of Kahneman and Tversky (1983), it finds that given mild incentives, the proportion of individuals who violate the conjunction principle is significantly lower than that reported by Kahneman and Tversky. Moreover, when subjects are allowed to consult with other subjects, these proportions fall dramatically, particularly when the size of the group rises from two to three. These findings cast serious doubts about the importance and robustness of such violations for the understanding of real-life economic decisions.

A Mechanism for Thawing the Credit Markets

This paper describes a mechanism designed to induce commercial banks to increase their willingness to extend loans in an economic environment characterized by increased uncertainty and diminished expectations. This mechanism is a new tool for the conduct of monetary policy to combat recessions.

A Theory of Bayesian Decision Making

This paper presents a complete, choice-based, axiomatic Bayesian decision theory. It introduces a new choice set consisting of information-contingent plans for choosing actions and bets and subjective expected utility model with effect-dependent utility functions and action-dependent subjective probabilities which, in conjunction with the updating of the probabilities using Bayes' rule, gives rise to a unique prior and a set of action-dependent posterior probabilities representing the decision maker's prior and posterior beliefs.