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Informationen zum Autor G.S.Maddala was one of the leading figures in field of econometrics for more than 30 years until he passed away in 1999. At the time of his death, he held the University Eminent Scholar Professorship in the Department of Economics at Ohio State University. His previous affiliations include Stanford University, University of Rochester and University of Florida. Kajal Lahiri is Distinguished Professor of Economics, and Health Policy, and Management and Behaviour at the State University of New York, Albany where he is also Director of the Econometric Research Institute. Professor Lahiri is an Honorary Fellow of the International Institute of Forecasters. Klappentext Maintaining G.S. Maddala's brilliant expository style of cutting through the technical superstructure to reveal only essential details, while retaining the nerve centre of the subject matter, Professor Kajal Lahiri has brought forward this new edition of one of the most important textbooks in its field. The new edition continues to provide a large number of worked examples, and some shorter data sets. Further data sets and additional supplementary material to assist both the student and lecturer are available on the companion website www.wileyeurope.com/college/maddala New features for the fourth edition: Chapters 5 and 6, on Heteroscedasticity and Autocorrelation, now reflect the latest professional practice in dealing with these common variations of the basic regression model. Chapter 10 includes extensive discussion on diagnostic checking in linear models, various nested and non-nested model selection procedures, specification testing, data transformations, and tests for non-normality. The first three chapters of Part III cover an introduction to time-series analysis, including the Box-Jenkins approach, forecasting and seasonality, models of expectations and distributed lag models, and vector auto-regressions, unit roots, and cointegration. Chapters 15 and 16 cover, respectively, the latest developments in panel data analysis and various re-sampling methods for use in small sample inference. Zusammenfassung Now in its fourth edition, this landmark text provides a fresh, accessible and well-written introduction to the subject. With a rigorous pedagogical framework, which sets it apart from comparable texts, the latest edition features an expanded website providing numerous real life data sets and examples. Inhaltsverzeichnis Foreword xvii Preface to the Fourth Edition xix Part I Introduction and the Linear Regression Model 1 CHAPTER 1 What is Econometrics? 3 1.1 What is econometrics? 3 1.2 Economic and econometric models 4 1.3 The aims and methodology of econometrics 6 1.4 What constitutes a test of an economic theory? 8 CHAPTER 2 Statistical Background and Matrix Algebra 11 2.1 Introduction 11 2.2 Probability 12 2.3 Random variables and probability distributions 17 2.4 The normal probability distribution and related distributions 18 2.5 Classical statistical inference 21 2.6 Properties of estimators 22 2.7 Sampling distributions for samples from a normal population 26 2.8 Interval estimation 26 2.9 Testing of hypotheses 28 2.10 Relationship between confidence interval procedures and tests of hypotheses 31 2.11 Combining independent tests 32 CHAPTER 3 Simple Regression 59 3.1 Introduction 59 3.2 Specification of the relationships 61 3.3 The method of moments 65 3.4 The method of least squares 68 3.5 Statistical inference in the linear regression model 76 3.6 Analysis of variance for the simple regression model 83 3.7 Prediction with the simple regression model 85 3.8 Outliers 88 3.9 Alternative functional forms for regression equati...
