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.
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