We consider a situation where the distribution of a random variable is being estimated by the empirical distribution of noisy measurements of that variable. This is common practice in, for example, teacher value-added models and other fixed-effect models for panel data. We use an asymptotic...

This paper estimates a structural model of private provision of public goods to provide some new empirical evidence on individuals' strategic contributing behaviors. In the model, individuals' contributing behaviors are allowed to be heterogenous and time-varying. We show that all the main...

This paper develops the identification and estimation of nonlinear semi-parametric panel data models with mismeasured variables and their corresponding average partial effects using only three periods of data. The past observables are used as instruments to control the measurement error problem,...

This paper characterizes and proposes a method to correct for errors-in-variables biases in the estimation of rank correlation coeffcients (Spearman's ρ and Kendall's τ). We first investigate a set of suffcient conditions under which measurement errors bias the sample rank correlations toward...

Berkson errors are commonplace in empirical microeconomics and occur whenever we observe an average in a specified group rather than the true individual value. In consumer demand this form of measurement error is present because the price an individual pays is often measured by the average price...

This paper studies a simple dynamic panel linear regression model with interactive fixed effects in which the variable of interest is measured with error. To estimate the dynamic coefficient, we consider the least-squares minimum distance (LS-MD) estimation method. -- dynamic panel ; interactive...

This paper develops asymptotic theory for estimated parameters in differentiated product demand systems with a fixed number of products, as the number of markets T increases, taking into account that the market shares are approximated by Monte Carlo integration. It is shown that the estimated...

Virtually all methods aimed at correcting for covariate measurement error in regressions rely on some form of additional information (e.g., validation data, known error distributions, repeated measurements or instruments). In contrast, we establish that the fully nonparametric classical...

In this paper we introduce a new approach to estimating a differentiated product demand system that allows for error in market shares as measures of choice probabilities. In particular, our approach allows for products with zero sales in the data, which is a frequent phenomenon that arises in...

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...