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733 kr
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This book represents a first course in econometrics, assuming only some knowledge of elementary probability theory and statistics on the part of the student. Its rigorous and comprehensive discussion concentrates on the general linear model, treating the standard case as well as the consequences resulting from violation of the underlying assumptions. Extensively documented chapters also cover the misspecification problem and errors in the variable model, simultaneous equations models and, uniquely, Multiple Comparison Test, Durbin- Watson Theory, Power Functions and Bayesian Analysis. Each chapter concludes with carefully selected exercises.
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This book has taken form over several years as a result of a number of courses taught at the University of Pennsylvania and at Columbia University and a series of lectures I have given at the International Monetary Fund. Indeed, I began writing down my notes systematically during the academic year 1972-1973 while at the University of California, Los Angeles. The diverse character of the audience, as well as my own conception of what an introductory and often terminal acquaintance with formal econometrics ought to encompass, have determined the style and content of this volume. The selection of topics and the level of discourse give sufficient variety so that the book can serve as the basis for several types of courses. As an example, a relatively elementary one-semester course can be based on Chapters one through five, omitting the appendices to these chapters and a few sections in some of the chapters so indicated. This would acquaint the student with the basic theory of the general linear model, some of the prob lems often encountered in empirical research, and some proposed solutions. For such a course, I should also recommend a brief excursion into Chapter seven (logit and pro bit analysis) in view of the increasing availability of data sets for which this type of analysis is more suitable than that based on the general linear model.