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 consistent and asymptotically normally distributed. In a...

This paper explores a semiparametric version of a time-varying regression, where a subset of the regressors have a fixed coefficient and the rest a time-varying one. We provide an estimation method and establish associated theoretical properties of the estimates and standard errors in extended...

Surveys that measure subjective states like happiness or preferences often generate discrete ordinal data. Ordered response models, which are commonly used to analyze such data, suffer from a fundamental identification problem. Their conclusions depend on unjustified assumptions about the...

This paper considers the problem of testing a finite number of moment inequalities. We propose a two-step approach. In the first step, a confidence region for the moments is constructed. In the second step, this set is used to provide information about which moments are negative. A...

Using recent results in the measurement error literature, we show that the official U.S. unemployment rate substantially underestimates the true level of unemployment, due to misclassification errors in the labor force status in the Current Population Survey. During the period from January 1996...

This paper considers the problem of testing a finite number of moment inequalities. We propose a two-step approach. In the first step, a confidence region for the moments is constructed. In the second step, this set is used to provide information about which moments are "negative." A...

In this paper we introduce the general setting of a multivariate time series autoregressive model with stochastic time-varying coefficients and time-varying conditional variance of the error process. This allows modeling VAR dynamics for non-stationary times series and estimation of time varying...

Following Giraitis, Kapetanios, and Yates (2014b), this paper uses kernel methods to estimate a seven variable time-varying (TV) vector autoregressive (VAR) model on the data set constructed by Smets and Wouters (2007). We apply an indirect inference method to map from this TV VAR to time...

In many multiple testing problems, the individual null hypotheses (i) concern univariate parameters and (ii) are one-sided. In such problems, power gains can be obtained for bootstrap multiple testing procedures in scenarios where some of the parameters are "deep in the null" by making certain...

Surveys are an important tool in economics and in the social sciences more broadly. However, methods used to analyse ordinal survey data (e.g., ordered probit) rely on strong and often unjustified distributional assumptions. In this paper, we propose using survey response times to solve that...