Includes bibliographical references and index.

Machine generated contents note: Chapter 1 An Introduction to Econometrics. -- A Probability Primer. -- Chapter 2 The Simple Linear Regression Model. -- Chapter 3 Interval Estimation and Hypothesis Testing. -- Chapter 4 Prediction, Goodness-of-Fit and Modeling Issues. -- Chapter 5 The Multiple Regression Model. -- Chapter 6 Further Inference in the Multiple Regression Model. -- Chapter 7 Using Indicator Variables. -- Chapter 8 Heteroskedasticity. -- Chapter 9 Regression with Time Series Data: Stationary Variables. -- Chapter 10 Random Regressors and Moment Based Estimation. -- Chapter 11 Simultaneous Equations Models. -- Chapter 12 Regression with Time Series Data: Nonstationary Variables. -- Chapter 13 Vector Error Correction and Vector Autoregressive Models. -- Chapter 14 Time-Varying Volatility and ARCH Models. -- Chapter 15 Panel Data Models. -- Chapter 16 Qualitative and Limited Dependent Variable Models. -- Appendix A Mathematical Tools. -- Appendix B Probability Concepts. -- Appendix C Review of Statistical Inference.

"Designed to arm finance professionals with an understanding of why econometrics is necessary, this book also provides them with a working knowledge of basic econometric tools. The fourth edition has been thoroughly updated to reflect the current state of economic and financial markets. New discussions are presented on Kennel Density Fitting and the analysis of treatment effects. A new summary of probability and statistics has been added. In addition, numerous new end-of-chapter questions and problems have been integrated throughout the chapters. This will help finance professionals apply basic econometric tools to modeling, estimation, inference, and forecasting through real world problems."--