The semiparametric local Whittle or Gaussian estimate of the long memory parameter is known to have especially nice limiting distributional properties, being asymptotically normal with a limiting variance that is completely known. However in moderate samples the normal approximation may not be...

This paper proposes a model for estimating the underlying cross-sectional dependence structure of a large panel of time series. Technical difficulties meant such a structure is usually assumed before further analysis. We propose to estimate this by penalizing the elements in the spatial weight...

This paper considers robust estimation of moment condition models with time series data. Researchers frequently use moment condition models in dynamic econometric analysis. These models are particularly useful when one wishes to avoid fully parameterizing the dynamics in the data. It is...

Abadie and Imbens (2008) showed that the standard naive bootstrap is inconsistent to estimate the distribution of the matching estimator for treatment effects with a fixed number of matches. This article proposes an asymptotically valid inference method for the matching estimators based on the...

We propose a nonparametric likelihood inference method for the integrated volatility under high frequency financial data. The nonparametric likelihood statistic, which contains the conventional statistics such as empirical likelihood and Pearson's chi-square as special cases, is not...

This paper proposes several statistical tests for finite state Markov games to examine the null hypothesis that data from distinct markets can be pooled. We formulate tests of (i) the conditional choice and state transition probabilities, (ii) the steady-state distribution, and (iii) the...

This paper is concerned with various issues related to inference in large dynamic panel data models (where both n and T increase without bound) in the presence of, possibly, strong cross-sectional dependence. Our first aim is to provide a Central Limit Theorem for estimators of the slope...

For testing lack of correlation against spatial autoregressive alternatives, Lagrange multiplier tests enjoy their usual computational advantages, but the (x squared) first-order asymptotic approximation to critical values can be poor in small samples. We develop refined tests for lack of...

This paper studies robustness of bootstrap inference methods for instrumental variable (IV)regression models. We consider test statistics for parameter hypotheses based on the IV estimatorand generalized method of trimmed moments (GMTM) estimator introduced by Cížek (2008, 2009),and compare...