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...

This paper (1) presents a general model of online price competition, (2) shows how to structurally estimate the underlying parameters of the model when the number of competing firms is unknown or in dispute, (3) estimates these parameters based on UK data for personal digital assistants, and (4)...

We consider the identification of a Markov process {Wt, Xt*} for t=1,2,...,T when only {Wt} for t=1, 2,..,T is observed. In structural dynamic models, Wt denotes the sequence of choice variables and observed state variables of an optimizing agent, while Xt* denotes the sequence of serially...

This paper proposes a new semi-nonparametric maximum likelihood estimation method for estimating production functions. The method extends the literature on structural estimation of production functions, started by the seminal work of Olley and Pakes (1996), by relaxing the scalar-unobservable...

This paper provides sufficient conditions for the nonparametric identification of the regression function m(.) in a regression model with an endogenous regressor x and an instrumental variable z. It has been shown that the identification of the regression function from the conditional...

We estimate nonparametric learning rules using data from dynamic two-armed bandit (probabilistic reversal learning) experiments, supplemented with auxiliary eye-movement measures of subjects' beliefs. We apply recent econometric developments in the estimation of dynamic models. The direct...

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...

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...

This paper presents identification and estimation results for a flexible state space model. Our modification of the canonical model allows the permanent component to follow a unit root process and the transitory component to follow a semiparametric model of a higher‐order...

<p><p><p>Consider an observed binary regressor D and an unobserved binary variable D*, both of which affect some other variable Y . This paper considers nonparametric identification and estimation of the effect of D on Y , conditioning on D* = 0. For example, suppose Y is a person's wage, the unobserved...</p></p></p>