Chapter 36
LARGE SAMPLE ESTIMATION AND HYPOTHESIS
TESTING*
WHITNEY K. NEWEY
Massachusetts Institute of Technology
DANIEL MCFADDEN
University of California, Berkeley
Contents
Abstract
1. Introduction
2. Consistency
2.1. The basic consistency theorem
2.2. Identification
2.2.1. The maximum likelihood estimator
2.2.2. Nonlinear least squares
2.2.3. Generalized method of moments
2.2.4. Classical minimum distance
2.3. Uniform convergence and continuity
2.4. Consistency of maximum likelihood
2.5. Consistency of GMM
2.6. Consistency without compactness
2.1. Stochastic equicontinuity and uniform convergence
2.8. Least absolute deviations examples
2.8.1. Maximum score
2.8.2. Censored least absolute deviations
3. Asymptotic normality
3.1. The basic results
3.2. Asymptotic normality for MLE
3.3. Asymptotic normality for GMM
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