Course description
This course is oriented to students with previous basic to intermediate knowledge in statistics (inferential and descriptive). This introductory course aims to give students the basic tools to interpret results from impact evaluation studies. It is not oriented to teach students how to carry on impact evaluations, but mostly to provide them with the tools to identify the key elements of a high quality evaluation when reading a research paper, properly interpret the main findings, as well as to identify the possible caveats in the analysis presented.
This course will cover the main areas of social policy, including education, health, earnings, productivity, agriculture, gender empowerment, among other relevant topics in the development sector.
Course learning objectives
- Understand the difference between the levels of development interventions: policy, programs and projects and their scope in terms of results.
- Introduce students to the basic concepts of impact evaluation in the development field.
- Provide students with the tools to analyze and understand the results from impact evaluation articles.
Course design
The course is divided in 13 sessions. The first section of the course is dedicated to provide students with the basic knowledge about the different levels of development interventions, followed up by the most common impact evaluation designs used in the field. From here, each session we will analyze one or two evaluation articles in one specific development field (e.g. education, jobs, health, infrastructure) to identify their main elements, methodology, interpretation of results, and limitations.
Grading
Essay 1 35%
Essay 2 35%
Final Exam 30%
Class calendar
|
Date |
Topic |
Readings |
|
Class 1 Mo. Apr 4th |
Introduction to the course Introduction to social policy and programs I |
Dean, H. (2006). Social policy. Polity. P. 1-12. Spiker, P. Social Policy, Theory and Practice. P. 1-19 |
|
Class 2 Mo. Apr 11th |
Introduction to social policy and programs II |
Dean, H. (2006). Social policy. Polity. P. 43-60 Spiker, P. Social Policy, Theory and Practice. P. 145-157. Rodrik D, Stantcheva S. A Policy Matrix for Inclusive Prosperity. Economics for Inclusive Prosperity. 2021;Policy Brief No. 30. |
|
Class 3 Mo. Apr 25th |
Introduction to social policy and programs III |
Spiker, P. Social Policy, Theory and Practice. P.409-427 Capano, G., Howlett, M., Ramesh, M., & Virani, A. (2019). Making Policies Work. Edward Elgar Publishing. https://doi.org/10.4337/9781788118194. P 59-72 Howlett, M., & Mukherjee, I. (Eds.). (2018). Routledge handbook of policy design. Routledge, Taylor and Francis Group. P 3-7 |
|
Class 4 Mo. May 2 |
Introduction to impact evaluation methods I |
Gertler, P. J., Martinez, S., Premand, P., Rawlings, L. B., & Vermeersch, C. M. J. (2016). Impact Evaluation in Practice, Second Edition. Washington, DC: Inter-American Development Bank and World Bank. https://doi.org/10.1596/978-1-4648-0779-4., P. 3-11, 21-28 Wooldridge, J. M. (2013). Introductory econometrics: A modern approach (5th ed). South-Western Cengage Learning. P1-17. Khandker, S., B. Koolwal, G., & Samad, H. (2009). Handbook on Impact Evaluation: Quantitative Methods and Practices. The World Bank. https://doi.org/10.1596/978-0-8213-8028-4. P 18-25. |
|
Class 5 Mo. May 9 |
Introduction to impact evaluation methods II |
|
|
Class 6
Mo. May 16 |
Impact evaluation in education |
Gottfredson, D. C., Cross, A., Wilson, D., Rorie, M., & Connell, N. (2010). An Experimental Evaluation of the All Stars Prevention Curriculum in a Community After School Setting. Prevention Science, 11(2), 142–154. https://doi.org/10.1007/s11121-009-0156-7 |
|
Class 7 Mo. May 23 |
Impact evaluation in health |
Ehlert, A. (2021). The socio-economic determinants of COVID-19: A spatial analysis of German county level data. Socio-Economic Planning Sciences, 101083. https://doi.org/10.1016/j.seps.2021.101083 Kurdi, S. (2021). The nutritional benefits of cash transfers in humanitarian crises: Evidence from Yemen. World Development, 148, 105664. https://doi.org/10.1016/j.worlddev.2021.105664 |
|
Class 8 Mo. May 30 |
Impact evaluation in gender projects |
Quisumbing, A., Ahmed, A., Hoddinott, J., Pereira, A., & Roy, S. (2021). Designing for empowerment impact in agricultural development projects: Experimental evidence from the Agriculture, Nutrition, and Gender Linkages (ANGeL) project in Bangladesh. World Development, 146, 105622. https://doi.org/10.1016/j.worlddev.2021.105622 |
|
Class 9 Mo Jun. 13 |
Impact evaluation in agriculture |
Slade, Roger; Renkow, Mitch; Place, Frank; and Hazell, Peter B. R. 2018. Evaluating the impact of policy research: Lessons from the evaluation of rural policy research in developing countries. IFPRI Discussion Paper 1779. Washington, DC: International Food Policy Research Institute (IFPRI). http://ebrary.ifpri.org/cdm/singleitem/collection/p15738coll2/id/133023 |
|
Class 10 Mo. Jun. 20 |
Impact evaluation in employability |
Kluve, J. (2010). The effectiveness of European active labor market programs. Labour Economics, 17(6), 904–918. https://doi.org/10.1016/j.labeco.2010.02.004 |
|
Class 11 Mo. Jun. 27 |
Impact evaluation in microfinances |
Mallick, R. (2002). Implementing and evaluating microcredit in Bangladesh. Development in Practice, 12(2), 153–163. https://doi.org/10.1080/09614520220127676 Islam, A. (2011). Medium‐ and Long‐Term Participation in Microcredit: An Evaluation Using a New Panel Dataset from Bangladesh. American Journal of Agricultural Economics, 93(3), 847–866. https://doi.org/10.1093/ajae/aar012 |
|
Class 12 Mo. Jul. 4 |
Impact evaluation in social policies |
Parker, S. W., & Teruel, G. M. (2005). Randomization and Social Program Evaluation: The Case of Progresa. The ANNALS of the American Academy of Political and Social Science, 599(1), 199–219. https://doi.org/10.1177/0002716205274515 |
|
Class 13 Mo Jul. 11. |
Impact evaluation in conservation projects |
Jayachandran, S., de Laat, J., Lambin, E. F., Stanton, C. Y., Audy, R., & Thomas, N. E. (2017). Cash for carbon: A randomized trial of payments for ecosystem services to reduce deforestation. Science, 357(6348), 267–273. https://doi.org/10.1126/science.aan0568 |
- Lehrende/r: Karla Vanessa Rubio Jovel