Introductory Econometrics: A Modern Approach (6 Ed.) | 誠品線上

Introductory Econometrics: A Modern Approach (6 Ed.)

內容簡介

內容簡介 Demonstrate how empirical researchers apply econometric methods to answer questions across a variety of disciplines. The practical, professional approach in Wooldridge's INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 6E is organized around the type of data being analyzed, using a systematic approach that introduces assumptions only when needed to obtain a certain result. This approach is easier for students to comprehend. Timely applications and examples demonstrate impact on policy and support or disprove economic theories. More than 100 data sets are available in six formats for your flexibility. New and revised author-written resources include an Instructor's Manual with Solutions, teaching tips, suggestions for using data files, updated PowerPoint® and Scientific Word® slides, and a current Data Set Handbook with the latest developments. Give students a full understanding of how econometrics answers questions in business, policy evaluation, and forecasting with INTRODUCTORY ECONOMETRICS: A MODERN APPROACH 6E.

作者介紹

作者介紹 ■作者簡介Jeffrey M. Wooldridge現職：Michigan State University

產品目錄

產品目錄 Ch 1 The Nature of Econometrics and Economic DataPART I: REGRESSION ANALYSIS WITH CROSS-SECTIONAL DATACh 2 The Simple Regression ModelCh 3 Multiple Regression Analysis: EstimationCh 4 Multiple Regression Analysis: InferenceCh 5 Multiple Regression Analysis: OLS AsymptoticsCh 6 Multiple Regression Analysis: Further IssuesCh 7 Multiple Regression Analysis with Qualitative Information: Binary (or Dummy) VariablesCh 8 HeteroskedasticityCh 9 More on Specification and Data ProblemsPART II: REGRESSION ANALYSIS WITH TIME SERIES DATACh10 Basic Regression Analysis with Time Series DataCh11 Further Issues in Using OLS with Time Series DataCh12 Serial Correlation and Heteroskedasticity in Time Series RegressionsPART III: ADVANCED TOPICSCh13 Pooling Cross Sections Across ime: Simple Panel Data MethodsCh14 Advanced Panel Data Methods.Ch15 Instrumental Variables Estimation and Two Stage Least SquaresCh16 Simultaneous Equations Models.Ch17 Limited Dependent Variable Models and Sample Selection CorrectionsCh18 Advanced Time Series TopicsCh19 Carrying Out an Empirical ProjectAPPENDICESAppendix A: Basic Mathematical ToolsAppendix B: Fundamentals of ProbabilityAppendix C: Fundamentals of Mathematical Statistics.Appendix D: Summary of Matrix AlgebraAppendix E: The Linear Regression Model in Matrix FormAppendix F: Answers to Exploring Further Chapter ExercisesAppendix G: Statistical Tables

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