{"product_id":"introduction-to-econometrics-isbn-9780470032701","title":"Introduction to Econometrics","description":"\u003ci\u003eIntroduction to Econometrics\u003c\/i\u003e has been written as a core textbook for a first course in econometrics taken by undergraduate or graduate students. It is intended for students taking a single course in econometrics with a view towards doing practical data work.  It will also be highly useful for students interested in understanding the basics of econometric theory with a view towards future study of advanced econometrics. To achieve this end, it has a practical emphasis, showing how a wide variety of models can be used with the types of data sets commonly used by economists. However, it also has enough discussion of the underlying econometric theory to give the student a knowledge of the statistical tools used in advanced econometrics courses.Indem sie Modelle für die Voraussage wirtschaftlicher Entwicklungen bereitstellt, bildet die Ökonometrie heute einen Kernbereich der Wirtschaftswissenschaften - und hat sich damit zu einem zentralen Bestandteil wirtschaftswissenschaftlicher Studiengänge entwickelt. Die hier vorgelegte Einführung eröffnet Einsteigern ebenso wie fortgeschrittenen Studierenden einen Zugang, der - im Unterschied zur Lehrbuchkonkurrenz - von vornherein auf einen starken Praxisbezug setzt. Der Verfasser, ausgewiesener Ökonometrieexperte, behandelt ein breites Spektrum ökonometrischer Modelle, u. a. das einfache und das multiple Regressionsmodell. Im Mittelpunkt seiner Darstellung steht dabei nicht Theoretisches, sondern die Anwendung der Modelle auf empirische Daten. Zahlreiche Beispiele und Übungsaufgaben unter Verwendung der Standardsoftware Strata ermöglichen die Einübung in Methoden und Modelle und schaffen so die Basis für ein selbstständiges empirisches Arbeiten.\u003cbr\u003e \u003cbr\u003e \u003cp\u003ePreface ix\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1 An Overview of Econometrics 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 The importance of econometrics 1\u003c\/p\u003e \u003cp\u003e1.2 Types of economic data 2\u003c\/p\u003e \u003cp\u003e1.3 Working with data: graphical methods 6\u003c\/p\u003e \u003cp\u003e1.4 Working with data: descriptive statistics and correlation 11\u003c\/p\u003e \u003cp\u003e1.5 Chapter summary 26\u003c\/p\u003e \u003cp\u003eExercises 26\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2 A Non-technical Introduction to Regression 29\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 29\u003c\/p\u003e \u003cp\u003e2.2 The simple regression model 30\u003c\/p\u003e \u003cp\u003e2.3 The multiple regression model 42\u003c\/p\u003e \u003cp\u003e2.4 Chapter summary 55\u003c\/p\u003e \u003cp\u003eExercises 57\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3 The Econometrics of the Simple Regression Model 59\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 59\u003c\/p\u003e \u003cp\u003e3.2 A review of basic concepts in probability in the context of the regression model 60\u003c\/p\u003e \u003cp\u003e3.3 The classical assumptions for the regression model 64\u003c\/p\u003e \u003cp\u003e3.4 Properties of the ordinary least-squares estimator of \u003ci\u003eβ\u003c\/i\u003e 67\u003c\/p\u003e \u003cp\u003e3.5 Deriving a confidence interval for \u003ci\u003eβ\u003c\/i\u003e 75\u003c\/p\u003e \u003cp\u003e3.6 Hypothesis tests about \u003ci\u003eβ\u003c\/i\u003e 77\u003c\/p\u003e \u003cp\u003e3.7 Modifications to statistical procedures when \u003ci\u003eσ\u003c\/i\u003e\u003csup\u003e2\u003c\/sup\u003e is unknown 78\u003c\/p\u003e \u003cp\u003e3.8 Chapter summary 81\u003c\/p\u003e \u003cp\u003eExercises 82\u003c\/p\u003e \u003cp\u003eAppendix 1: Proof of the Gauss–Markov theorem 84\u003c\/p\u003e \u003cp\u003eAppendix 2: Using asymptotic theory in the simple regression model 85\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4 The Econometrics of the Multiple Regression Model 91\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 91\u003c\/p\u003e \u003cp\u003e4.2 Basic results for the multiple regression model 92\u003c\/p\u003e \u003cp\u003e4.3 Issues relating to the choice of explanatory variables 96\u003c\/p\u003e \u003cp\u003e4.4 Hypothesis testing in the multiple regression model 102\u003c\/p\u003e \u003cp\u003e4.5 Choice of functional form in the multiple regression model 109\u003c\/p\u003e \u003cp\u003e4.6 Chapter summary 115\u003c\/p\u003e \u003cp\u003eExercises 116\u003c\/p\u003e \u003cp\u003eAppendix: Wald and Lagrange multiplier tests 117\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5 The Multiple Regression Model: Freeing Up the Classical Assumptions 121\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 121\u003c\/p\u003e \u003cp\u003e5.2 Basic theoretical results 122\u003c\/p\u003e \u003cp\u003e5.3 Heteroskedasticity 124\u003c\/p\u003e \u003cp\u003e5.4 The regression model with autocorrelated errors 138\u003c\/p\u003e \u003cp\u003e5.5 The instrumental variables estimator 149\u003c\/p\u003e \u003cp\u003e5.6 Chapter summary 164\u003c\/p\u003e \u003cp\u003eExercises 165\u003c\/p\u003e \u003cp\u003eAppendix: Asymptotic results for the OLS and instrumental variables estimators 168\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6 Univariate Time Series Analysis 173\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 173\u003c\/p\u003e \u003cp\u003e6.2 Time series notation 175\u003c\/p\u003e \u003cp\u003e6.3 Trends in time series variables 177\u003c\/p\u003e \u003cp\u003e6.4 The autocorrelation function 179\u003c\/p\u003e \u003cp\u003e6.5 The autoregressive model 181\u003c\/p\u003e \u003cp\u003e6.6 Defining stationarity 195\u003c\/p\u003e \u003cp\u003e6.7 Modeling volatility 197\u003c\/p\u003e \u003cp\u003e6.8 Chapter summary 205\u003c\/p\u003e \u003cp\u003eExercises 207\u003c\/p\u003e \u003cp\u003eAppendix: MA and ARMA models 210\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7 Regression with Time Series Variables 213\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 213\u003c\/p\u003e \u003cp\u003e7.2 Time series regression when X and Yare stationary 214\u003c\/p\u003e \u003cp\u003e7.3 Time series regression when Y and X have unit roots 217\u003c\/p\u003e \u003cp\u003e7.4 Time series regression when Y and X have unit roots but are NOTcointegrated 227\u003c\/p\u003e \u003cp\u003e7.5 Granger causality 227\u003c\/p\u003e \u003cp\u003e7.6 Vector autoregressions 233\u003c\/p\u003e \u003cp\u003e7.7 Chapter summary 247\u003c\/p\u003e \u003cp\u003eExercises 248\u003c\/p\u003e \u003cp\u003eAppendix: The theory of forecasting 251\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8 Models for Panel Data 255\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 255\u003c\/p\u003e \u003cp\u003e8.2 The pooled model 256\u003c\/p\u003e \u003cp\u003e8.3 Individual effects models 256\u003c\/p\u003e \u003cp\u003e8.4 Chapter summary 271\u003c\/p\u003e \u003cp\u003eExercises 272\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9 Qualitative Choice and Limited Dependent Variable Models 277\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 277\u003c\/p\u003e \u003cp\u003e9.2 Qualitative choice models 278\u003c\/p\u003e \u003cp\u003e9.3 Limited dependent variable models 296\u003c\/p\u003e \u003cp\u003e9.4 Chapter summary 304\u003c\/p\u003e \u003cp\u003eExercises 306\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10 Bayesian Econometrics 309\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 An overview of Bayesian econometrics 309\u003c\/p\u003e \u003cp\u003e10.2 The normal linear regression model with natural conjugate prior and a single explanatory variable 315\u003c\/p\u003e \u003cp\u003e10.3 Chapter summary 326\u003c\/p\u003e \u003cp\u003eExercises 326\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix: Bayesian analysis of the simple regression model with unknown variance 328\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAppendix A: Mathematical Basics 333\u003c\/p\u003e \u003cp\u003eAppendix B: Probability Basics 338\u003c\/p\u003e \u003cp\u003eAppendix C: Basic Concepts in Asymptotic Theory 348\u003c\/p\u003e \u003cp\u003eAppendix D: Writing an Empirical Project 353\u003c\/p\u003e \u003cp\u003e\u003cb\u003eTables 359\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eTable 1. Area under the standard normal distribution Pr(0 ≤ \u003ci\u003eZ\u003c\/i\u003e ≤ \u003ci\u003ez\u003c\/i\u003e) 359\u003c\/p\u003e \u003cp\u003eTable 2. Area under the Student \u003ci\u003et\u003c\/i\u003e distribution for different degrees of freedom (DF), Pr(\u003ci\u003eZ\u003c\/i\u003e ≥ \u003ci\u003ez\u003c\/i\u003e) = \u003ci\u003eα\u003c\/i\u003e 360\u003c\/p\u003e \u003cp\u003eTable 3. Percentiles of the chi-square distribution 361\u003c\/p\u003e \u003cp\u003eTable 4a. Area under the \u003ci\u003eF\u003c\/i\u003e-distribution for different degrees of freedom, \u003ci\u003eν\u003c\/i\u003e1 and \u003ci\u003eν\u003c\/i\u003e2, Pr(\u003ci\u003eZ\u003c\/i\u003e ≥ \u003ci\u003ez\u003c\/i\u003e) = 0.05 362\u003c\/p\u003e \u003cp\u003eTable 4b. Area under the \u003ci\u003eF\u003c\/i\u003e-distribution for different degrees of freedom, \u003ci\u003eν\u003c\/i\u003e1 and \u003ci\u003eν\u003c\/i\u003e2, Pr(\u003ci\u003eZ\u003c\/i\u003e ≥ \u003ci\u003ez\u003c\/i\u003e) = 0.01 363\u003c\/p\u003e \u003cp\u003eBibliography 364\u003c\/p\u003e \u003cp\u003eIndex 365\u003c\/p\u003e “An introductory text offering econometric methodology for quantifying and managing this variety of risk, illustrated by empirical examples.” (\u003ci\u003eTimes Higher Education Supplement\u003c\/i\u003e, Thursday 28th February) \u003cb\u003eGary Koop\u003c\/b\u003e is Professor of Economics at the University of Strathclyde. Gary has published numerous articles econometrics in journals such as the \u003ci\u003eJournal of Econometrics\u003c\/i\u003e and \u003ci\u003eJournal of Applied Econometrics\u003c\/i\u003e. Gary has taught econometrics for many years and is the author of following textbooks, all published by John Wiley \u0026amp; Sons Ltd: \u003ci\u003eAnalysis of Economic Data 2ed, Analysis of Financial Data\u003c\/i\u003e and \u003ci\u003eBayesian Econometrics\u003c\/i\u003e  \u003ci\u003eIntroduction to Econometrics\u003c\/i\u003e has been written as a core textbook for a first course in econometrics taken by undergraduate or graduate students. It is intended for students taking a single course in econometrics with a view towards doing practical data work.  It will also be highly useful for students interested in understanding the basics of econometric theory with a view towards future study of advanced econometrics. To achieve this end, it has a practical emphasis, showing how a wide variety of models can be used with the types of data sets commonly used by economists. However, it also has enough discussion of the underlying econometric theory to give the student a knowledge of the statistical tools used in advanced econometrics courses.  \u003cp\u003e\u003cb\u003eKey Features:\u003c\/b\u003e\u003c\/p\u003e \u003cul type=\"disc\"\u003e \u003cli\u003eA non-technical summary of the basic tools of econometrics is given in chapters 1 and 2, which allows the reader to quickly start empirical work.\u003c\/li\u003e \u003cli\u003eThe foundation offered in the first two chapters makes the theoretical econometric material, which begins in chapter 3, more accessible.\u003c\/li\u003e \u003cli\u003eProvides a good balance between econometric theory and empirical applications.\u003c\/li\u003e \u003cli\u003eDiscusses a wide range of models used by applied economists including many variants of the regression model (with extensions for panel data), time series models (including a discussion of unit roots and cointegration) and qualitative choice models (probit and logit).\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eAn extensive collection of web-based supplementary materials is provided for this title, including: data sets, problem sheets with worked through answers, empirical projects, sample exercises with answers, and slides for lecturers.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eURL: www.wileyeurope.com\/college\/koop\u003c\/b\u003e\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989458764005,"sku":"NP9780470032701","price":61.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780470032701.jpg?v=1761784182","url":"https:\/\/k12savings.com\/products\/introduction-to-econometrics-isbn-9780470032701","provider":"K12savings","version":"1.0","type":"link"}