Summary and Info
This book provides the tools and concepts necessary to study the behavior of econometric estimators and test statistics in large samples. An econometric estimator is a solution to an optimization problem; that is, a problem that requires a body of techniques to determine a specific solution in a defined set of possible alternatives that best satisfies a selected object function or set of constraints. Thus, this highly mathematical book investigates situations concerning large numbers, in which the assumptions of the classical linear model fail. Economists, of course, face these situations often. Key Features * Completely revised Chapter Seven on functional central limit theory and its applications, specifically unit root regression, spurious regression, and regression with cointegrated processes * Updated material on: * Central limit theory * Asymptotically efficient instrumental variables estimation * Estimation of asymptotic covariance matrices * Efficient estimation with estimated error covariance matrices * Efficient IV estimation
More About the Author
Halbert Lynn White, Jr. (November 19, 1950 – March 31, 2012) was the Chancellor’s Associates Distinguished Professor of Economics at the University of California, San Diego, and a Fellow of the Econometric Society and the American Academy of Arts and Sciences.
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