By bringing together results from the growing literature in econometrics on misspecification testing, this study provides theoretical analyses and convenient methods for the implementation of tests in applied work. Although the main emphasis is on the Lagrange multiplier principle, several other approaches are discussed and the relationships among different methods are examined. The author reviews general checks of model adequacy that do not involve the formulation of an alternative hypothesis. General and specific tests are discussed in the context of multiple regression models, systems of simultaneous equations, and models with qualitative or limited dependent variables. This wide-ranging but integrated book will be useful to a wide audience of applied and theoretical researchers, graduate students, and professional economists.
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By bringing together results from the growing literature in econometrics on misspecification testing, this study provides theoretical analyses and convenient methods for the implementation of tests in applied work.
"This monograph is an admirable attempt to provide a unified picture of the issues that have been raised in the testing literature, and to guide practitioners through the maze of different tests to which they might wish to subject their models." Russell Davidson, Journal of Economic Literature
"...an extremely valuable and clearly-written guide to a rapidly growing field, that I can recommend alike to practitioners and to students." Russell Davidson, Journal of Economic Literature
"This book is a welcome addition to the Econometric Society Monograph Series and provides a comprehensive account of the Lagrange multiplier approach and other likelihood-based procedures to the problem of misspecification testing in econometrics." M.H. Pesaran, The Economic Journal
"...an excellent review of the misspecification tests, with special emphasis on the LM principle. Developoments in the area of misspecification tests are proceeding at a rapid pace as evidenced by recent publications in refereed journals in statistics, time series, biometrics, technometrics, and econometrics." Mathematical Reviews
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