Description
PEARSON INDIA Introduction To Econometrics 3Rd Edition by H STOCK JAMES and W WATSON MARK
Introduction to Econometrics is designed for a first course in undergraduate econometrics. It differs from other textbooks in three main ways. First, it integrates real-world questions and data into the development of the theory. Second, choice of topics reflects modern theory and practice. Third, theory and assumptions that are provided match the applications. Aim of this text is to teach students to become sophisticated consumers of econometrics and to do so at a level of mathematics appropriate for an introductory course.
The Third Edition Update maintains a focus on currency, while building on the philosophy that applications should drive the theory, not the other way around.
Table of Content
Part I. Introduction and Review
1. Economic Questions and Data
2. Review of Probability
3. Review of Statistics
Part II. Fundamentals of Regression Analysis
4. Linear Regression with One Regressor
5. Regression with a Single Regressor: Hypothesis Tests and Confidence Intervals
6. Linear Regression with Multiple Regressors
7. Hypothesis Tests and Confidence Intervals in Multiple Regression
8. Nonlinear Regression Functions
9. Assessing Studies Based on Multiple Regression
Part III. Further Topics in Regression Analysis
10. Regression with Panel Data
11. Regression with a Binary Dependent Variable
12. Instrumental Variables Regression
13. Experiments and Quasi-Experiments
Part IV. Regression Analysis of Economic Time Series Data
14. Introduction to Time Series Regression and Forecasting
15. Estimation of Dynamic Causal Effects
16. Additional Topics in Time Series Regression
Part V. The Econometric Theory of Regression Analysis
17. The Theory of Linear Regression with One Regressor
18. The Theory of Multiple Regression
Salient Features
• Updated treatment of standard errors for panel data regression
• Discussion of when and why missing data can present a problem for regression analysis
• The use of regression discontinuity design as a method for analyzing quasiexperiments
• Updated discussion of weak instruments
• Discussion of the use and interpretation of control variables integrated into the core development of regression analysis
• Introduction of the "potential outcomes" framework for experimental data
• Additional general interest boxes
• Additional exercises, both pencil-and-paper and empirical