The original research papers collected in this volume continue the development of discrete choice analysis, of related structural models for analysis of choice behavior, and of the statistical theory used in inference on these models. Most papers in the volume are revised versions of ones...

This chapter reviews the usefulness of the Kalman filter for parameter estimation and inference about unobserved variables in linear dynamic systems. Applications include exact maximum likelihood estimation of regressions with ARMA disturbances, time-varying parameters, missing observations,...

A semiparametric model for observational data combines a parametric form for some component of the data generating process (usually the behavioral relation between the dependent and explanatory variables) with weak nonparametric restrictions on the remainder of the model (usually the...

A brief account is given of the methodology and theory for the bootstrap. Methodology is developed in the context of the "equation" approach, which allows attention to be focussed on specific criteria for excellence, such as coverage error of a confidence interval or expected value of a...

Asymptotic distribution theory is the primary method used to examine the properties of econometric estimators and tests. We present conditions for obtaining cosistency and asymptotic normality of a very general class of estimators (extremum estimators). Consistent asymptotic variance estimators...

This chapter reviews inference about large autoregressive or moving average roots in univariate time series, and structural change in multivariate time series regression. The "problem" of unit roots is cast more broadly as determining the order of integration of a series; estimation, inference,...