Asymptotic Theory for Econometricians.

Peter M. Robinson; Hannah J. White

doi:10.2307/2554258

February 1, 1988Economica

Asymptotic Theory for Econometricians.

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Establish a unified mathematical framework for the large-sample behavior of estimators used in linear models and instrumental variables analysis.
Analyzes linear model and instrumental variables estimators using probability limit theory.
Applies laws of large numbers alongside classical and functional central limit theorems.
Derives analytical methods for estimating asymptotic covariance matrices under general data-generating conditions.
Demonstrates explicit regularity conditions required for estimator consistency and asymptotic normality in econometric settings.
Provides valid covariance matrix estimation techniques to enable robust asymptotic hypothesis testing.
Extends foundational limit theory to functional central limit processes for dynamic and nonstationary econometric applications.

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Abstract

The Linear Model and Instrumental Variables Estimators. Consistency. Laws of Large Numbers. Asymptotic Normality. Central Limit Theory. Estimating Asymptotic Covariance Matrices. Functional Central Limit Theory and Applications. Directions for Further Study. Solution Set. References. Index.

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Robinson et al. (1988) studied this question.

synapsesocial.com/papers/6a08fd6474a93f402dd39483 https://doi.org/10.2307/2554258

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Asymptotic Theory for Econometricians.

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Asymptotic Theory for Econometricians.

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