TrainingsMasterEconomicsCoursesEvaluation by econometric methods

Master EconomicsUE Evaluation by econometric methods


The objective of the course is to offer M1 students with an overview of the main empirical methods used for the evaluation of public policies. We will study key articles taken from various applied economics literature (health, education or activive labor policies). Practical case studies on STATA will be offered all along. We will point out advantages and limits of each method as well as guide in the selection of the appropriate method.

Course outline :


1. Why evaluate ? What do we evaluate ? What is the objective ?

2. Potential outcome framework

3. Treatment effects and counterfactuals

4. Selection bias

Chapter 1 : Randomized experiments

1. Random assignment

2. Underlying assumptions

3. Study of 2 empirical papers using the method

4. Randomized experiments in practice

Running example : exercise on National Supported Work (NSW) data

Chapter 2 : Natural experiment : Difference-in-difference method

1. Model and underlying assumptions

2. Study of 2 empirical papers using the method

3. Extensions

4. D-in-D in practice

Running example : exercise on National Supported Work (NSW) data

Professional skills

Through this course, students are expected to :

  • master basic technical tools used in the evaluation of public policies
  • design a final project in evaluation on STATA
  • use the skills in academic research and as professionals outside academia

Languages used

Main languages used by this course:

  • Français
  • Anglais


Textbooks :

• Angrist & Pischke (2009), ‘Mostly Harmless Econometrics : An Empiricist’s Companion’, Princeton University Press

• Wooldridge, ‘Introductory Econometrics : A Modern Approach’, 4th edition (2009), 5th edition (2013)

• Cameron and Trivedi (2010), ‘Microeconometrics using Stata’, Stata Press

• Angrist & Pischke (2015), ‘Mastering Metrics’, Princeton University Press

Reference articles :

• Angrist, J., Bettinger, E., Bloom E., King, E. and Kremer, M. “Vouchers for Private Schooling in Colombia : Evidence from a Randomized Natural Experiment”, The American Economic Review, vol. 95, no. 5, 2002, pp. 1535-1558.

• Ashenfelter, O., Ashmore, D. and Deschênes, O. “Do Unemployment Insurance Recipients Actively Seek Work ? Evidence from Randomized Trials in Four US States”. Journal of Econometrics, vol. 125, no. 1-2, 2005, pp. 53-75.

• Heckman J., Pinto R. and P. Savelyev. “Understanding the Mechanisms Through Which an Influence Early Childhood Program Boosted Adult Outcomes”. The American Economic Review, vol. 103, no. 6, 2013, pp. 2052-2086.

• Card, D., Mas, A., Moretti, E. and Saez, E. “Inequality at Work : The Effect of Peer Salaries on Job Satisfaction”, The American Economic Review, vol. 102, no. 6, 2012, pp. 2981-3003.

• Duflo, E., Dupas, P. and Kremer, M. “Peer Effects, Teacher Incentives, and the Impact of Tracking : Evidence from a Randomized Evaluation in Kenya”, vol. 101, no. 5, 2011, pp. 1739-74.

• Card, D., and Krueger, A.B. (1994). “Minimum Wages and Employment : A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania.” The American Economic Review, vol. 84, no. 4, 1994, pp. 772–793.

• Card, D. (1990) : “The Impact of the Mariel Boatlift on the Miami Labor Market,” Industrial and Labor Relations Review, vol. 43, no. 2, pp. 245–257.

• Qian, N. “Missing Women and The Price of Tea in China : The Effect of Sex-Specific Income on Sex Imbalance”, The Quarterly Journal of Economics, vol. 123, no. 3, 2008, pp. 12551-1285.

• Dumont E., Fortin, B., Jacquemet, N. and Shearer B. “Physicians’ Multitasking and Incentives : Empirical Evidence from a Natural Experiment”, Journal of Health Economics, vol. 27, no. 6, 2008, pp. 1436-1450.

• Blundell, R., Costa Dias, M., Meghir, C. and Van Reenen, J. “Evaluating the Employment Impact of a Mandatory Job Search Assistance Program”, Journal of European Economic Association, vol. 2, no. 4, 2010, pp. 569-606.

• Abadie, A., A. Diamond, et J. Hainmueller (2012) : “Synthetic Control Methods for Comparative Case Studies : Estimating the Effect of California’s Tobacco Control Program,” Journal of American Statistical Association, 105 (490).

• Duflo, E., R. Glennerster, et M. Kremer (2006) : “Using Randomization in Development Economics Research : A Toolkit,” NBER Working Paper, T0333.

• Heckman, James, Robert Lalonde and Jeffrey Smith. (1999). “The economics and econometrics of active labor market programs.” in Ashenfelter, O. and D. Card (eds), Handbook of Labor Economics. Vol. III. North Holland, Amsterdam.

• Bertrand, M., E. Duflo, et S. Mullainathan (2004) : “How much should we trust differences-in-differences estimates ?,” The Quarterly Journal of Economics, 119, 249–275.

• Athey, S., et G. W. Imbens (2006) : “Identification and Inference in Nonlinear Difference-in-differences Models,” Econometrica, 74, 431–497.

Fundamental prerequisites

Graduate econometrics (OLS, fundamentals of statistics) and basic knowledge of STATA (or some other software).

Structure and organisation

Two hours a week over 12 weeks (24 hours).

Mid-semester exam (week 6)

Final project in common with the course Logiciel for Economists II (Stata).

Volume of teachings

  • Lectures: 24 hours