To understand the impact of policies or programs implemented, policymakers regularly need to do the quantitative analysis themselves or they need to interpret the results presented to them. In order to do this at least a certain level of statistical knowledge is necessary. This 1-day class aims to provide policymakers with a basic set of statistical tools and quantitative analysis methods showing the logic behind these methods and interpretation of their results. Topics covered in the training include simple regression model, deriving ordinary least squares estimates, expected value, and variance of the OLS estimators, multiple regression analysis, t-tests, hypothesis testing, multiple regression analysis with binary variables, etc.  
The training is composed of a theoretical part for three-quarters of the day and for the rest of the day, the applications will be shown with a hands-on training using STATA (STATA is an interactive data management and statistical analysis software, which is popular among researchers and policy-makers in most social science disciplines).

Participants: The module targets policymakers, researchers, local government or development agency staff, monitoring and evaluation staff who are looking to gain knowledge and expertise in basic statistical tools and quantitative analysis methods as well as to learn about this commonly used statistical package.  (10-20 people)
Prerequisites:  Participants are expected to have a basic knowledge of statistics/econometrics.
Duration: 1 day

​Development programs and policies are typically designed to change outcomes. Whether or not these changes are actually achieved is a crucial public policy question but that is not often examined. More commonly, program managers and policymakers focus on controlling and measuring the inputs and immediate outputs of a program—how much money is spent, how many textbooks are distributed, rather than assessing whether programs have achieved their intended goals of improving well-being.  Impact evaluations are part of a broader agenda of evidence-based policymaking. 

This two-day technical course is designed to introduce concepts and methodologies in quantitative impact evaluation. The course uses country and program case studies to illustrate methodologies and introduces the following methodologies: (i) Randomized evaluations (ii) Matching methods, specifically propensity score matching (PSM), (iii) Double-difference (DD) methods, (iv) Instrumental variable (IV) methods (v) Regression discontinuity (RD) design. The course also includes a module on operationalizing and managing an impact evaluation.

​

Participants: The course targets policymakers, researchers and development specialists working for government ministries, municipalities and local development agencies, statistical agencies, and NGOs, looking to gain knowledge of impact evaluation methods. (10-20 people)
Prerequisites:  The course will require basic knowledge of statistics.
Duration: 3 days

Data collected from qualitative research methods serve two key functions for the successful design and execution of social policy interventions. Firstly, qualitative research methods provide project and policy designers and evaluators with a nuanced and thorough understanding of the needs of individuals, households, and communities as well as social relations and state-citizen relations.  Qualitative research methods are particularly useful in capturing target communities’ reactions to social policy programs and interventions. Secondly, data collected using qualitative research methods for monitoring and evaluation purposes help identify both the successful and problematic features of a policy or project.This seminar is intended to familiarize researchers with the more commonly used qualitative research methods. It will help them to utilize these methods in their own research, or evaluate the qualitative work that others have done.  Semi-structured interviews, in-depth interviews,  focus groups, participant observation, ethnographic work, qualitative data collection such as the use of images, personal experiences, biographical and historical methods are such methods that are used widely in social research, and which will be covered in this training at an introductory level.

This beginner-level course will also include a general introduction to data analysis software packages in particular NVIVO for qualitative researchers. NVivo is a qualitative data analysis software package, which is used widely among social scientists. It provides tools for qualitative analysis of large bodies of textual, graphical, audio and video data.  The section of the course is designed as a hands-on workshop where participants will get to explore the basic functions of NVIVO for qualitative data coding and analysis. Participants will also be introduced to useful online manuals, which they can use to self-teach advanced functions of the software packages.

Participants: The course targets anyone involved in conducting a needs assessment for policy and project design purposes, and those who are involved in policy or project monitoring and evaluation activities. (10-20 people)
Prerequisites:  No requirements
Duration: 1 day