Economics 312, Spring 2022, Part B: Lecture Notes by Date

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2022 Lecture Notes

Lecture 1, Thursday, April 28, 2022

1. Goals of the Course, 2022
   • Link to private syllabus
2. Econometric Approach to Causality by Heckman and Pinto (2022)
3. What is a causal effect? How to express it? And why it matters.
4. Causal Frameworks for Complex Causal Models
5. Causality and Econometrics: Part I by Heckman and Pinto (2022)
6. Causality and Econometrics: Part II by Heckman and Pinto (2022)

Slide Supplement

• Causality and Econometrics by Heckman and Pinto (2022)
• Causality in Econometrics and Statistics: Structural Models are Causal Models Some Formal Statements Part III on Causality by Heckman and Pinto (2022)
• Econometric Causality by Heckman (2008)
  • Econometric Causality: Part I on Causality by Heckman (2008)
• Dialogue on Causality Between James Heckman and Ian Shrier by Heckman and Schrier (2022)

Lecture 2, Tuesday, May 3, 2022

1. Econometric Approach to Causality by Heckman and Pinto (2022)
2. Econometric Causality by Heckman (2008)
   • Econometric Causality: Part I on Causality by Heckman (2008)
3. Causality in Econometrics and Statistics: Structural Models are Causal Models (Do-Calculus Extract) by Pinto and Heckman (2022)
4. Hypothesis Testing: Part I

Supplemental Slides (from Lecture 1)

• What is a causal effect? How to express it? And why it matters.
• Causal Frameworks for Complex Causal Models
• Causality and Econometrics: Part I by Heckman and Pinto (2022)
• Causality and Econometrics: Part II by Heckman and Pinto (2022)

Lecture 3, Thursday, May 5, 2022

1. Econometric Causality: Part I on Causality by Heckman (2008)
2. Econometric Approach to Causality by Heckman and Pinto (2022)
3. Causality in Econometrics and Statistics: Structural Models are Causal Models (Do-Calculus Extract) by Pinto and Heckman (2022)

Supplemental Slides (from Lecture 2)

• Abducting Economics: How to Learn from Surprises,  Heckman and Singer (2016)
• Can an Attribution Assessment Be Made for Yellow Rain? by Katz and Singer (2007)
• The Causes and Consequences of Self-Employment Over the Life Cycle,  Humphries (2019).

Lecture 4, Tuesday, May 10, 2022

1. Hypothesis Testing: Part I
2. Classical Discrete Choice Theory
3. The Pre-Test Estimator by Heckman and Pinto
4. Extract: Notes on Roy Models and Generalized Roy
5. Roy Models of Policy Evaluation
6. The Normal Generalized Roy Model
7. Notes on Identification of the Roy Model and the Generalized Roy Model

Supplemental Slides (from Lecture 3)

• Econometric Causality: Part I on Causality by Heckman (2008)
• Econometric Approach to Causality by Heckman and Pinto (2022)
• Causality in Econometrics and Statistics: Structural Models are Causal Models (Do-Calculus Extract) by Pinto and Heckman (2022)

Lecture 5a, Thursday, May 12, 2022 and Lecture 5b, Friday, May 13, 2022

1. Classical Discrete Choice Theory
2. The Pre-Test Estimator by Heckman and Pinto
3. Extract: Notes on Roy Models and Generalized Roy
4. Roy Models of Policy Evaluation
5. The Normal Generalized Roy Model
6. Notes on Identification of the Roy Model and the Generalized Roy Model
7. Interpreting IV: What Economic Questions Can LATE Answer?
8. Interpreting IV: What Does IV Estimate?
9. What Does IV Estimate? “Estimating Marginal Returns to Education”
10. Comparing IV With Explicitly Formulated Economic Structural Models: What Simple IV Can and Cannot Identify
11. Revised Yitzhaki
12. Yitzhaki Weights Examples
13. Definition of Samples
14. How To Correct for Sampling Biases
15. Shadow Prices, Market Wages and Labor Supply
16. Randomized Evaluations from Econometric Evaluation of Social Programs, Part II
17. ITT: Randomize Eligibility
18. Some Problems with Experiments
19. The Principles Underlying Evaluation Estimators excerpted from Heckman, James J. (2008). “The Principles Underlying Evaluation Estimators with an Application to Matching.” Les Annales d’Economie et de Statistique, 91-92, pp. 9-74.

Lecture 6, Tuesday, May 17, 2022

1. Classical Discrete Choice Theory
2. The Pre-Test Estimator by Heckman and Pinto
3. Extract: Notes on Roy Models and Generalized Roy
4. Roy Models of Policy Evaluation
5. The Normal Generalized Roy Model
6. Notes on Identification of the Roy Model and the Generalized Roy Model
7. Interpreting IV: LATE
8. Interpreting IV: More On Roy Model
9. Interpreting IV: What Economic Questions Can LATE Answer?
10. Interpreting IV: What Does IV Estimate?
11. What Does IV Estimate? “Estimating Marginal Returns to Education”
12. Comparing IV With Explicitly Formulated Economic Structural Models: What Simple IV Can and Cannot Identify
13. Revised Yitzhaki
14. Yitzhaki Weights Examples
15. Definition of Samples
16. How To Correct for Sampling Biases
17. Shadow Prices, Market Wages and Labor Supply
18. Randomized Evaluations from Econometric Evaluation of Social Programs, Part II
19. ITT: Randomize Eligibility
20. Some Problems with Experiments
21. The Principles Underlying Evaluation Estimators excerpted from Heckman, James J. (2008). “The Principles Underlying Evaluation Estimators with an Application to Matching.” Les Annales d’Economie et de Statistique, 91-92, pp. 9-74.
22. RDD

Lecture 7, Thursday, May 19, 2022

1. What Does IV Estimate? “Estimating Marginal Returns to Education”
2. MTE as Generator of All Treatment Eects: IV and Policy Weights: EXTRACT
3. Yitzhaki Derived the Weights Used by the Proponents of LATE but Without Citation; The Weights Have a Lot of Intuition
4. Revised Yitzhaki
5. RDD
6. Comparing IV With Explicitly Formulated Economic Structural Models: What Simple IV Can and Cannot Identify
7. ITT: Randomize Eligibility
8. The Principles Underlying Evaluation Estimators excerpted from Heckman, James J. (2008). “The Principles Underlying Evaluation Estimators with an Application to Matching.” Les Annales d’Economie et de Statistique, 91-92, pp. 9-74.

Supplemental Slides

• Classical Discrete Choice Theory
• The Pre-Test Estimator by Heckman and Pinto
• Extract: Notes on Roy Models and Generalized Roy
• Roy Models of Policy Evaluation
• The Normal Generalized Roy Model
• Notes on Identification of the Roy Model and the Generalized Roy Model
• Interpreting IV: LATE
• Interpreting IV: More On Roy Model
• Interpreting IV: What Economic Questions Can LATE Answer?
• Interpreting IV: What Does IV Estimate?
• Yitzhaki Weights Examples
• Definition of Samples
• How To Correct for Sampling Biases
• Shadow Prices, Market Wages and Labor Supply
• Randomized Evaluations from Econometric Evaluation of Social Programs, Part II
• Some Problems with Experiments
• Cost Benefit Analysis Using the MTE, Heckman and Vytlacil (2004)

Lecture 8, Tuesday, May 24, 2022

• Guest Lecturer, Thomas Coleman
  • Methodology of Economics: Importance of Good Data Analysis, Methodology, and Theory

Lecture 9, Thursday, May 26, 2022

1. Modeling the Income Process
2. Factor Models: A Review
3. Factor Models

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2021 Lecture Notes

Lecture 1, Thursday, April 29, 2021

1. Goals of the Course
2. Syllabus for Part B
3. Learning from Data
4. The Causes and Consequences of Self-Employment over the Life Cycle, Humphries (2019)
5. Abducting Economics: How to Learn from Surprises, Heckman and Singer (2016)
6. Abduction, Singer (2008)
7. Continuous Versus Episodic Change…, Donohue and Heckman (1991)
8. The Causes and Consequences of Self-Employment over the Life Cycle, Humphries (2019).
9. Friedman’s Approach to Empirical Economics
10. Hypothesis Testing, Part 1