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INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 4e illustrates how empirical researchers think about and apply econometric methods in real-world practice. The text's unique approach reflects the fact that undergraduate econometrics has moved beyond just a set of abstract tools to being genuinely useful for answering questions in business, policy evaluation, and forecasting environments. The systematic approach, which reduces clutter by introducing assumptions only as they are needed, makes absorbing the material easier and leads to better econometric practices. Its unique organization separates topics by the kinds of data being analyzed , leading to an appreciation for the important issues that arise in drawing conclusions from the different kinds of data economists use. Packed with relevant applications, INTRODUCTORY ECONOMETRICS offers a wealth of interesting data sets that can be used to reproduce the examples in the text or as the starting point for original research projects. Key Features 1.Up to Date: The new edition covers the latest developments from the field and includes updated examples throughout, illustrating how chapter concepts apply to real-world practice. 2.Expanded Coverage: The text's comprehensive coverage includes expanded discussions on both the basics and advanced applications of dummy variables, new material on prediction after retransformation, expanded discussions of influential observations, weighted least squares, and least absolute deviations, and new coverage of weak instruments. 3.New Data Sets: New sets include productivity and salary statistics for economics professors in the Big Ten, a large data set on women's labor supply and fertility decisions, a current data set on elementary school teacher salaries and benefits (along with student-teacher ratios and spending), and time series data sets on economic activity, the Federal Funds rate, and minimum wages. 4.Practical Application: INTRODUCTORY ECONOMETRICS applies econometrics to real-world problems by motivating each method by a particular issue facing researchers analyzing nonexperimental data. 5.Unique Organization: Wooldridge's text pioneered the approach of explicitly covering cross-sectional applications first, followed by time series applications and ultimately panel data applications in the advanced chapters. 6.Expansive Data Sets: The text's large and varied data sets give students practical experience working with an interesting assortment of topics. 7.Variables: Explanatory variables -- along with the dependent variable -- are treated as outcomes of random variables. Table of Contents PART 1: REGRESSION ANALYSIS WITH CROSS-SECTIONAL DATA. 1.The Nature of Econometrics and Economic Data. 2.The Simple Regression Model. 3. Multiple Regression Analysis: Estimation. 4. Multiple Regression Analysis: Inference. 5. Multiple Regression Analysis: OLS Asymptotics. 6. Multiple Regression Analysis: Further Issues. 7. Multiple Regression Analysis with Qualitative Information: Binary (or Dummy) Variables. 8. Heteroskedasticity. 9. More on Specification and Data Problems. PART 2: REGRESSION ANALYSIS WITH TIME SERIES DATA. 10. Basic Regression Analysis with Time Series Data. 11. Further Issues in Using OLS with Time Series Data. 12. Serial Correlation and Heteroskedasticity in Time Series Regressions. PART 3: ADVANCED TOPICS. 13. Pooling Cross Sections across Time: Simple Panel Data Methods. 14. Advanced Panel Data Methods. 15. Instrumental Variables Estimation and Two Stage Least Squares. 16. Simultaneous Equations Models. 17. Limited Dependent Variable Models and Sample Selection Corrections. 18. Advanced Time Series Topics. 19. 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 Chapter Questions. Appendix G: Statistical Tables. References. Glossary. Index.