Semiparametric Efficiency In Gmm Models Of Nonclassical Measurement Errors Missing Data And Treatment Effects

Contains 16 chapters authored by specialists in the field, covering topics such as: Missing-Data Imputation in Nonstationary Panel Data Models; Markov Switching Models in Empirical Finance; Bayesian Analysis of Multivariate Sample Selection Models Using Gaussian Copulas; and, Consistent Estimation and Orthogonality.

The Handbook is a definitive reference source and teaching aid for econometricians. It examines models, estimation theory, data analysis and field applications in econometrics.

This volume revisits educational equality and equity issues, especially, in education finance-related topics consisting of 15 chapters and organized in two parts. The first part of the volume entitled “Education Finance”, focuses on equity aspects of resource allocation and its influence on education. The second part, entitled “Educational Equality and Equity”, focuses on the conceptualization, and the measurements of educational inequity, and inequality with special emphasis on the cost of inequality. The field of education finance has been significantly influencing policy-makers in many countries in recent years. This volume is focused on equity and equality in education finance in an international frame. This book would be of interest to (1) scholars at the fields of education finance, economics of education, and educational policy, (2) graduate students at the course of school finance or economics of education, and (3) local and global policy makers at the fields of education policy, and education finance.

We develop a practical way of addressing the Errors-In-Variables (EIV) problem in the Generalized Method of Moments (GMM) framework. We focus on the settings in which the variance of the measurement errors is a fraction of that of the mismeasured variables, which is typical for empirical applications. For any initial set of moment conditions our approach provides a “corrected” set of moment conditions that do not suffer from the EIV bias. The EIV-robust estimator is then computed as a standard GMM estimator with these corrected moment conditions. We show that our estimator is √n-consistent, and that the standard tests and confidence intervals provide valid inference. This is true even when the EIV are so large that the naive estimator (that ignores the EIV problem) may have a large bias with confidence intervals having 0% coverage. Our approach requires no nonparametric estimation, which can be particularly useful when the measurement errors are multivariate, serially correlated, or non-classical.

The award-winning The New Palgrave Dictionary of Economics, 2nd edition is now available as a dynamic online resource. Consisting of over 1,900 articles written by leading figures in the field including Nobel prize winners, this is the definitive scholarly reference work for a new generation of economists. Regularly updated! This product is a subscription based product.

This monograph provides an up-to-date discussion of analysis strategies for regression problems in which predictor variables are measured with errors. The analysis of nonlinear regression models includes generalized linear models, transform-both-sides models and quasilikelihood and variance function problems. The text concentrates on the general ideas and strategies of estimation and inference rather than being concerned with a specific problem. Measurement error occurs in many fields, such as biometry, epidemiology and economics. In particular, the book contains a large number of epidemiological examples. An outline of strategies for handling progressively more difficult problems is also provided.

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 presented at a 2005 conference in honor of Daniel L. McFadden, whose fundamental research made discrete choice analysis part of the fabric of modern economics.