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: Binary (or Dummy) Variables
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 ime: 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
APPENDICES
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
Appendix F: Answers to Exploring Further Chapter Exercises
Appendix G: Statistical Tables