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Synopsis
An accessible discussion examining computationally-intensive techniques and bootstrap methods, providing ways to improve the finite-sample performance of well-known asymptotic tests for regression models. This book uses the linear regression model as a framework for introducing simulation-based tests to help perform econometric analyses.
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About the Author
LESLIE GODFREY is Professor of Econometrics at the University of York, UK and a Fellow of the Journal of Econometrics. He has served on the editorial boards of Econometric Theory and Econometric Reviews. His articles have been published in leading journals, including Econometrica, Journal of Econometrics and Review of Economics and Statistics.
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Bootstrap Tests for Regression Models (Palgrave Texts in Econometrics)
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Bootstrap Tests for Regression Models
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BOOTSTRAP TESTS FOR REGRESSION MODELS (PALGRAVE TEXTS IN ECONOMETRICS)
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BOOTSTRAP TESTS FOR REGRESSION MODELS (PALGRAVE TEXTS IN ECONOMETRICS)
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Bootstrap Tests for Regression Models
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Bootstrap Tests for Regression Models (Palgrave Texts in Econometrics)
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Bootstrap Tests for Regression Models
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Bootstrap Tests for Regression Models (Palgrave Texts in Econometrics)
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Bootstrap Tests for Regression Models (Hardcover)
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Palgrave Macmillan, Basingstoke, 2009
ISBN 10: 0230202306
ISBN 13: 9780230202306
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Hardcover. Condition: new. Hardcover. An accessible discussion examining computationally-intensive techniques and bootstrap methods, providing ways to improve the finite-sample performance of well-known asymptotic tests for regression models. This book uses the linear regression model as a framework for introducing simulation-based tests to help perform econometric analyses. An accessible discussion examining computationally-intensive techniques and bootstrap methods, providing ways to improve the finite-sample performance of well-known asymptotic tests for regression models. This book uses the linear regression model as a framework for introducing simulation-based tests to help perform econometric analyses. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780230202306
Quantity: 1 available