**“What to read for the upcoming lecture?”** is a common question I get asked.

Below you will find a number of recommended readings per “topic” rather than per “lecture”. Usually, we will cover a particular topic over a number of lectures, so it best for students to __start __the readings__ before the first lecture on that topic,__ and__ finish__ them __before the last lecture on that topic.__ The three topics before the first midterm are the following:

### Foundations of Causal Inference

These should help you review and wake-up memories of what you learned in RMDA 1

Real Stats, Chapter 1 “The Quest for Causality” Part 1

Real Stats, Chapter 1 “The Quest for Causality” Part 2

Mastering Metrics Chapter 1 - up to page 17 is the main part. The rest is useful as review.

### Linear Regression

**Foundations**

Real Stats, Chapter 3 “Bivariate OLS: The Foundation of Econometric Analysis”

Real Stats, Chapter 5 “Multivariate OLS: Where the action is”

Master Metrics Chapter 2 “Regression”. ** If you plan to read this chapter, note that they cover “matching” here, which we will not cover this semester. That may be confusing. It is fine if you choose to skip this chapter.

Bad Covariates: Real Stats 2nd Edition Section 7.3

**Regression Mechanics**

Real Stats, Chapter 6 “Dummy Variables: Smarter than you think” section 6.1-6.3

Real Stats, Chapter 6 “Dummy Variables: Smarter than you think”, section 6.4

Real Stats 1st Edition Chapter 7 “Transforming Variables, Comparing Variables” (1st edition)

Quadratic in a regression: Real Stats 2nd Edition Specifiying models section 7.1

Logs in a regression: Real Stats 2nd Edition Specifiying models section 7.2

Dummy Variables as dependent variables: Real Stats 2nd Edition section 12.1

Dummy Variables as independent variables: Real Stats 2nd Edition section 6.1, 6.2

Categorical Variables as independent variables: Real Stats 2nd Edition Section 6.3

Interaction Variables: Real Stats 2nd Edition Section 6.4

### Instrumental Variables

Mastering Metrics, Chapter 3 “Instrumental Variables”

Real Stats, Chapter 10.2 and 10.3 “Experiments: Dealing with Real-World Challenges” (Review)

Real Stats Chapter 9.1 and 9.2 “Instrumental Variables: Using Exogenous Variation to Fight Endogeneity”

### Regression Discontinuity

- Real Stats. Chapter 11 (Regression Discontinuity) 11.1-11.2, binned graphs, 11.4
- Mastering Metrics Chapter 4 (Regression Discontinuity). Whole Chapter.

### Panel Data

Real Stats Chapter 8 (Panel Data). 8.1-8.4

### Differences-in-Differences

Real Stats Chapter 8 (Panel Data). 8.5

Mastering Metrics Chapter 5