Introduction to Econometrics
by James H. Stock, Mark W. Watson
4th Edition
Publisher: Pearson
Book Details
| Print ISBN | 9780134461991 |
| eText ISBN | 9780134448046 |
| Publisher | Pearson |
| Publishing Year | 2019 |
| Edition | 4th Edition |
| Language | English |
| Pages | 800 |
Introduction to Econometrics, 4th Edition, connects economic theory and empirical practice by letting real-world questions guide theoretical development. Published by Pearson in 2019, the textbook pairs substantive economic problems and data with analytical tools designed for practical research.
Coverage begins with foundational reviews of probability and statistics before examining single and multiple linear regression models, confidence intervals, and hypothesis testing. Readers also explore regression analysis of economic time series data, forecasting techniques, and dynamic causal effects.
Written by James H. Stock and Mark W. Watson, this edition added a dedicated chapter on Big Data and prediction with many regressors. The overall pedagogical framework aims to help students become sophisticated consumers of econometrics.
Table of Contents
PART I: INTRODUCTION AND REVIEW
Chapter 1: Economic Questions and Data
Chapter 2: Review of Probability
Chapter 3: Review of Statistics
PART II: FUNDAMENTALS OF REGRESSION ANALYSIS
Chapter 4: Linear Regression with One Regressor
Chapter 5: Regression with a Single Regressor: Hypothesis Tests and Confidence Intervals
Chapter 6: Linear Regression with Multiple Regressors
Chapter 7: Hypothesis Tests and Confidence Intervals in Multiple Regression
Chapter 8: Nonlinear Regression Functions
Chapter 9: Assessing Studies Based on Multiple Regression
PART III: FURTHER TOPICS IN REGRESSION ANALYSIS
Chapter 10: Regression with Panel Data
Chapter 11: Regression with a Binary Dependent Variable
Chapter 12: Instrumental Variables Regression
Chapter 13: Experiments and Quasi-Experiments
Chapter 14: Prediction with Many Regressors and Big Data
PART IV: REGRESSION ANALYSIS OF ECONOMIC TIME SERIES DATA
Chapter 15: Introduction to Time Series Regression and Forecasting
Chapter 16: Estimation of Dynamic Causal Effects
Chapter 17: Additional Topics in Time Series Regression
PART V: THE ECONOMIC THEORY OF REGRESSION ANALYSIS
Chapter 18: The Theory of Linear Regression with One Regressor
Chapter 19: The Theory of Multiple Regression
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