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Give students an understanding of how econometrics can answer questions in business, policy evaluation and forecasting. Students see the importance of what they're learning as this practical, yet professional, approach demonstrates how today's empirical researchers apply econometric methods to answer questions across a variety of disciplines. The author organizes information around the type of data being analyzed and uses a systematic approach that introduces assumptions only when needed to obtain a certain result, making it easier for students to follow. Updated applications and examples demonstrate impact on today's policy and support or disprove contemporary economic theories. More than 100 data sets are available in different formats.
作者簡介
Jeffrey M. Wooldridge
現職：Michigan State University
Ch 1 The Nature of Econometrics and Economic Data
PART I: REGRESSION ANALYSIS WITH CROSS-SECTIONAL DATA
Ch 2 The Simple Regression Model
Ch 3 Multiple Regression Analysis: Estimation
Ch 4 Multiple Regression Analysis: Inference
Ch 5 Multiple Regression Analysis: OLS Asymptotics
Ch 6 Multiple Regression Analysis: Further Issues
Ch 7 Multiple Regression Analysis with Qualitative Information
Ch 8 Heteroskedasticity
Ch 9 More on Specification and Data Problems
PART II: REGRESSION ANALYSIS WITH TIME SERIES DATA
Ch10 Basic Regression Analysis with Time Series Data
Ch11 Further Issues in Using OLS with Time Series Data
Ch12 Serial Correlation and Heteroskedasticity in Time Series Regressions
PART III: ADVANCED TOPICS.
Ch13 Pooling Cross Sections Across Time: Simple Panel Data Methods
Ch14 Advanced Panel Data Methods
Ch15 Instrumental Variables Estimation and Two Stage Least Squares
Ch16 Simultaneous Equations Models
Ch17 Limited Dependent Variable Models and Sample Selection Corrections
Ch18 Advanced Time Series Topics
Ch19 Carrying Out an Empirical Project
APPENDIX A: Basic Mathematical Tools
APPENDIX B: Fundamentals of Probability
APPENDIX C: Fundamentals of Mathematical Statistics.
APPENDIX D: Summary of Matrix Algebra
APPENDIX E: The Linear Regression Model in Matrix Form
Answers to Exploring Further Chapter Exercises
Statistical Tables
Glossary
