Estimation, inference, and specification analysis

  title={Estimation, inference, and specification analysis},
  author={Halbert L. White},
  • H. White
  • Published 1 September 1996
  • Economics
This book examines the consequences of misspecifications ranging from the fundamental to the nonexistent for the interpretation of likelihood-based methods of statistical estimation and interference. Professor White first explores the underlying motivation for maximum-likelihood estimation, treats the interpretation of the maximum-likelihood estimator (MLE) for misspecified probability models, and gives the conditions under which parameters of interest can be consistently estimated despite… 
Inference for Iterated GMM Under Misspecification
This paper develops inference methods for the iterated overidentified Generalized Method of Moments (GMM) estimator. We provide conditions for the existence of the iterated estimator and an
Penalized Indirect Inference
Parameter estimates of structural economic models are often difficult to interpret at the light of the underlying economic theory. Bayesian methods have become increasingly popular as a tool for
On the Power of Bootstrapped Specification Tests
Abstract Decisions based on econometric model estimates may not have the expected effect if the model is misspecified. Thus, specification tests should precede any analysis. Bierens' specification
Parameter Estimation With Out-of-Sample Objective
We study parameter estimation from the sample X, when the objective is to maximize the expected value of a criterion function, Q, for a distinct sample, Y. This is the situation that arises when a
Testing for the mixture hypothesis of geometric distributions
Use of the likelihood ratio (LR) statistic is examined to test for the mixture assumption of geometric distributions. As the asymptotic null distribution of the LR statistic is not a standard
Bootstrap Conditional Distribution Tests in the Presence of Dynamic Misspecification
In this paper, we show the first order validity of the block bootstrap in the context of Kolmogorov type conditional distribution tests when there is dynamic misspecification and parameter estimation
An Information Theoretic Approach to Econometrics
This book is intended to provide the reader with a firm conceptual and empirical understanding of basic information-theoretic econometric models and methods. Because most data are observational,
Specification Tests for Non-Gaussian Maximum Likelihood Estimators
We propose generalized DWH specification tests which simultaneously compare three or more likelihood‐based estimators in multivariate conditionally heteroskedastic dynamic regression models. Our
Distributions of Maximum Likelihood Estimators and Model Comparisons
  • P. Hingley
  • Mathematics
    World Congress on Engineering
  • 2007
If the model is known, simulations, normal approximations and p*‐formula methods can be used, however, exact analytic methods for describing the estimator density are recommended.