PART 1 Overview and Review

01 Economics Problems and Data
02 Review of Probability
03 Statistics Review

PART 2: Basics of Regression Analysis

04 Linear regression using a single explanatory variable
05 Regression Analysis with a Single Explanatory Variable: Hypothesis Testing and Confidence Intervals
06 Linear regression using multiple explanatory variables
07 Hypothesis Testing and Confidence Intervals in Multiple Regression
08 Nonlinear regression function
09 Research Evaluation Based on Multiple Regression Analysis

PART 3 APPLICATIONS OF REGRESSION ANALYSIS

10 Regression analysis using panel data
11 Regression analysis using binary dependent variables
12 Instrumental Variable Regression
13 Experiments and Quasi-Experiments
14 Prediction using multiple explanatory variables and big data

PART 4 ​​Economic Time Series Data and Regression Analysis

15 Time Series Regression Analysis and Forecasting
16 Estimation of dynamic causal effects
17 Additional Topics in Time Series Regression

PART 5 Econometric Theory of Regression Analysis

18 Theory of Simple Linear Regression Models
19 Multiple Regression Theory

What's New in the 4th Edition

*Big data and machine learning related content
*Time series data forecasting using large-scale data sets
*Dynamic factor model
*A parallel approach to prediction and causal inference using regression analysis
*Realized volatility and autoregressive conditional heteroskedasticity
*Updated information on tool variables