Public Policy Analysis
Netherlands, Maastricht
| Study location | Netherlands, Maastricht |
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| Type | Summer Courses, Full-time |
| Nominal duration | 1 week (2 ECTS) |
| Study language | English |
| Tuition fee | €299 one-time |
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| Entry qualification | Enrolled as an Undergraduate student or Undergraduate diploma Taking the public policy processes course before this class is recommended: The entry qualification documents are accepted in the following languages: English. Often you can get a suitable transcript from your school. If this is not the case, you will need official translations along with verified copies of the original. |
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| Language requirements | English The language of the course is English, so we expect a fluent level and the ability to follow and participate in class. |
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| More information |
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Overview
Course Description
There is growing recognition that relevant, evidence-based policymaking is key to achieving significant and sustainable change and fulfilment of the Sustainable Development Goals. In this course, you will be introduced to the fundamentals of public policy analysis tools used commonly throughout the world. Monitoring and evaluation of policies and projects are often required by international organizations, NGOs, and national governments to produce meaningful, rigorous, evidence-based recommendations based on the outcomes of existing programmes, as well as an essential part of accountability to donors and affected populations. It is therefore imperative for anyone interested in the realm of public policy to have a grasp of what it means to conduct rigorous evaluations.
The course is divided over five days, with an introduction meeting, four content units with assessments and a closing oral exam. The first unit is an introduction to public policy analysis. In the second unit, students are introduced in greater detail to the monitoring process and relevant tools. Units three and four are dedicated to the description of impact evaluation methods and their practical application in real-world settings.
Goals
• Understand the basis of public policy analysis and evidence-based public policy.
• Understand the distinction between monitoring and evaluation.
• Understand the different types of data used in policy evaluation and their sources.
• Understand the different types of monitoring and its evolution through time.
• Be able to critically assess when monitoring is preferable to impact evaluation.
• Understand the different analytical methods used to perform impact evaluation.
• Grasp the statistics behind experimental and quasi-experimental techniques.
• Overall, the student should be able to critically reflect on the literature provided and be able to distil this knowledge into their own country’s context.
Recommended Literature
Mark Bovens, Paul ‘t Hart, Sanneke Kuipers, The Politics of Policy Evaluation, 2009.
Mariana Wongtschowski, Lisanne Oonk and Remco Mur, Monitoring and evaluation for accountability and learning, KIT Working Paper Series (2016-3)
Gertler et al., Impact Evaluation in Practice, World Bank Group (2016)
WFP Food Assistance to Refugees. Standard Project Report 2016.
Prennushi, G., Rubio, G., & Subbarao, K. (2002). Monitoring and evaluation. A sourcebook for poverty reduction strategies, 107-30. Chapter 3.
Alkire, S., & Samman, E. (2014). Mobilising the household data required to progress toward the SDGs
Tomlinson, M., Solomon, W., Singh, Y., Doherty, T., Chopra, M., Ijumba, P., … & Jackson, D. (2009). The use of mobile phones as a data collection tool: a report from a household survey in South Africa. BMC medical informatics and decision making, 9(1), 51.
Swiss Agency for Development and Cooperation & ETHZ, NADEL Centre. What are impact evaluations?
Daniel F. Chambliss, Russell K. Schutt, Causation and Experimental Design, in Daniel F. Chambliss, Russell K. Schutt, Making Sense of the Social World: 6th edition, SAGE publishing (2018), Chapter 5, pp. 106-113.
Abhijit Banerjee, Sharon Barnhardt, Esther Duflo, Can Iron-Fortified Salt Control Anemia? Evidence from Two Experiments in Rural Bihar, Journal of Development Economics, December 18, 2017
Rubin, 1974. Estimating causal effects of treatments in randomised and non-randomised studies
Angrist, 1990. Lifetime earnings and the Vietnam era draft lottery: evidence from social security administrative records
King, G., Nielsen, R., Coberley, C., Pope, J. E., & Wells, A. (2011). Comparative effectiveness of matching methods for causal inference. Unpublished manuscript, 15, 41
WFP, Malawi, School Meals Programme (2016-2018): an evaluation, (2018).
Teaching Methods
Assignments, Lectures, PBL
Assessment Methods
Assignment, Attendance, Oral exam, Participation
Course Coordinator
via UNU-MERIT