Wooldridge Jeffrey M. Introductory Econometrics: A Modern Approach

6th edition. — South-Western; Cengage Learning, 2016. — 878 p. — ISBN10: 130527010X; ISBN13: 9781305270107.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.The Nature of Econometrics and Economic Data.
Regression Analysis with Cross-Sectional Data.
The Simple Regression Model.
Multiple Regression Analysis: Estimation.
Multiple Regression Analysis: Inference.
Multiple Regression Analysis: OLS asymptotics.
Multiple Regression Analysis: Further Issues.
Multiple Regression Analysis with Qualitative Information: Binary (or Dummy) Variables.
Heteroskedasticity.
More on Specification and Data Problems.
Regression Analysis with Time Series Data.
Basic Regression Analysis with Time Series Data.
Further Issues in Using Ols with Time Series Data.
Serial Correlation and Heteroskedasticity in Time Series Regressions.
Advanced Topics.
Pooling Cross Sections Across Time: Simple Panel Data Methods.
Advanced Panel Data Methods.
Instrumental Variables Estimation and Two Stage Least Squares.
Simultaneous Equations Models.
Limited Dependent Variable Models and Sample Selection Corrections.
Advanced Time Series Topics.
Carrying Out an Empirical Project.
Appendices.
Basic Mathematical Tools.
Fundamentals of Probability.
Fundamentals of Mathematical Statistics.
Summary of Matrix Algebra.
The Linear Regression Model in Matrix Form.
Answers to Exploring Further Chapter Exercises.
Statistical Tables.