Asignatura de segundo año del programa de Doctorado en Economía Cuantitativa.

• El alumno debe ser capaz de leer razonadamente y evaluar de forma crítica artículos de investigación en Economía del Desarrollo, captando cuáles son las contribuciones esenciales y las debilidades de cada uno de ellos. Además, el alumno debe ser capaz de entender cómo se han resuelto en cada caso los problemas técnicos con los que se han tenido que enfrentar los autores de estos artículos.
• El alumno debe aprender a realizar pruebas de proposiciones y teoremas.
• El alumno también debe ser capaz de comprender y replicar los análisis empíricos y los experimentos de simulación en que se basan las conclusiones presentadas en los artículos de investigación de otros autores.

This course will focus on the evaluation of social programs and will provide a thorough understanding of randomized evaluations. Through a combination of lectures and case studies from real randomized evaluations, the course will focus on the benefits and methods of randomization, choosing an appropriate sample size, and common threats and pitfalls to the validity of the experiment.

In addition to the lecture sequences, the course also includes various case studies. The case studies explore the concepts and issues discussed in the lecture sequences and involve some readings, followed by discussion topics. The discussion topics include multiple choice questions open response assessments. Students will also take multiple choice tests during the course that will be linked to the lectures’ contents and the compulsory readings for the case studies.

CONTENIDOS:
Summary

This course will focus on the evaluation of social programs and will provide a thorough understanding of randomized evaluations. Through a combination of lectures and case studies from real randomized evaluations, the course will focus on the benefits and methods of randomization, choosing an appropriate sample size, and common threats and pitfalls to the validity of the experiment.

In addition to the lecture sequences, the course also includes various case studies. The case studies explore the concepts and issues discussed in the lecture sequences and involve some readings, followed by discussion topics. The discussion topics include multiple choice questions open response assessments. Students will also take multiple choice tests during the course that will be linked to the lectures’ contents and the compulsory readings for the case studies.

Important note: this course relies, among others, on the materials used in J-PAL’s/MIT course “Evaluating Social Programs – JPAL101x”.

Program
1. What is evaluation?
2. Theory of change and measurement
3. Why randomize?
4. How to randomize
5. Sample size and power
6. Threats and analysis
7. RCT: start to finish
(8. Cost-effectiveness analysis and scaling up) – if time allows

References
Duflo, E. (2005). “Women as Policy Makers: Evidence from a Randomized Policy Experiment in India”, Econometrica, Vol. 72, No. 5. (UNIT 2)

Banerjee, A. V. et al. (2011). “Pitfalls of Participatory Programs: Evidence from a Randomized Evaluation in Education in India”, American Economic Journal: Economic Policy, 2-1, 1: 30. (UNIT 3)

Duflo, E. (2011). “Peer Effects, Teacher Incentives, and the Impact of Tracking: Evidence from a Randomized Evaluation in Kenya”, American Economic Review 101: 1779-1734. (UNIT 4)

Miguel, E. and E. Kremer (2004). “Worms: Identifying the Impact on Education and Health in the Presence of Treatment Externalities”, Econometrica, Vol. 72, No. 1. (UNIT 6)

Davey, C, Aiken, AM, Hayes, RJ and Hargreaves, JR. (2015). “Reanalysis of health and educational impacts of a school based deworming program in western Kenya: a statistical replication of a cluster quasi-randomized stepped wedged trial”, International Journal of Epidemiology, 1–12. Available at http://ije.oxfordjournals.org/content/early/2015/07/21/ije.dyv128.full.pdf. An earlier version available at http://www.3ieimpact.org/media/filer_public/2015/01/07/rps_3_part_2_top_copy_reduced_size_1_7_15-top.pdf. (UNIT 6)

Hicks, J. H., Kremer, M., and E. Miguel, (2014). “Estimating deworming school participation impacts in Kenya: A Comment on Aiken et al.(2014b)”, Document available at http://www.3ieimpact.org/media/filer_public/2015/01/07/rps3_worms-3ie-pure-response_2014-12-22-part_2.pdf (UNIT 6)

Hicks, J. H., Kremer, M., and E. Miguel, (2015). “Commentary: Deworming externalities and schooling impacts in Kenya: a comment on Aiken et. al. (2015) and Davey et. al. (2015)”, International Journal of Epidemiology, 1-4. Available at http://ije.oxfordjournals.org/content/early/2015/07/21/ije.dyv129.full.pdf (UNIT 6)
Duflo, E., Glennerster, R. and M. Kremer (2007). “Using Randomization in Development Economics Research: A Toolkit”, en T. Paul Schults y John Strauss (eds.), Handbook of Development Economics, Elsevier Science Ltd.: North Holland, Vol. 4, págs. 3895-62. (Also available as CEPR Discussion Paper No. 6059).

Gertler, P. J., Martínez, S., Premand, P., Rawlings, L. B. and C. M. J. Vermeesch (2011). Impact Evaluation in Practice, World Bank. Document available at http://www.worldbank.org/pdt

Teerenstra, S. et. al. (2012). “A simple simple size formula for analysis of covariance in cluster randomized trials”, Statistics in Medicine 31, 2169-2178.

Case studies –one presentation per student (see list of papers above and we’ll discuss details in class) and open response assessments during the course: 40%
Multiple choice tests during the course (no warning, they will be short and simple and happen along the way): 40%
Stata take home problem set on power calculations: 20%

The final grade in the second evaluation period is EXCLUSIVELY given by the grade obtained
in a retake exam (with theory and practice questions) about the whole content of the course.
Grades from continuous assessment, if any, will not be taken into account.

Additional resources and comments
All materials (slides, readings, Stata resources, take-home exercises, etc.) will be sent by email before each class.
Stata training modules: you do them at home if you need them. If your Stata skills are rusty do this before Unit 5 because this is not a Stata or a programming course.