Social policies are of the utmost importance in contemporaneous societies. They consist of legislation and activities concerning governmental responses to specific human and social needs in many areas of intervention, such as health care, human services, criminal justice, inequality, education, migration and labour.
However, only in recent years the evaluation of social policies’ effects on targeted individuals, and on larger sets of a given population has become central in the policymakers’ agenda. Indeed, an unprecedented availability of new information collected by specialized surveys and administrative registries at individual, regional, and national level, has expanded the opportunity for researchers and policymakers to investigate social-related phenomena and policies in an increasingly finer detail. Moreover, today information technology based on larger computing power and storage, big data management, along with recent developments in causal modelling, make the analysis and evaluation of social policies (at any level) easier to carry out than it has been previously.
Social policy evaluation can have either an ex-ante or an ex-post nature, and can be either qualitative, or quantitative. This course focuses on the ex-post and quantitative side of the coin. Indeed, by making use of the most recent counterfactual statistical and econometric techniques, participants will become knowledgeable of the essential tools, both theoretical and applied, for a proper application of modern micro-econometric methods for social policy evaluation using counterfactual modelling in Stata.
The course will cover various counterfactual methods, such as, Regression adjustment (parametric and nonparametric), Matching (on covariates and on propensity score), Selection models, and Difference-in-differences. Moreover, it will provide the participant with Stata solutions to estimate social policy in the presence of indirect effects, and more specifically, neighbourhood effects.
In line with the general philosophy of our training courses, the lessons will be very interactive and will have mostly applied content. They will include numerous empirical applications on real social policy datasets. Participants will be able to experiment with the techniques learned through exercises performed by their own calculation stations under the guidance of the instructor.
After attending the course, the participant will be able to set up and manage a correct social policy evaluation design under observable and unobservable selection on their own, thus mastering the identification of the policy framework, the collection and management of suitable datasets, the use of the appropriate econometric methods, and the interpretation of results. Finally, the instructor will assist participants in setting-up their own personal policy evaluation case study.
Session 1: Introduction to social policy evaluation
Session 2: Counterfactual social policy evaluation
Session 1: Social policy evaluation under unobservable selection
Session 2: Estimating social policy “neighbourhood” effects
This course has a learning ratio of approximately 30% Theory, 30% Demonstration and 40% Practical
Principal texts for pre-course reading:
Principal texts for post-course reading:
(subject to minor changes)
|Time||Session / Description|
|09:00 - 09:20||Registration|
|09:30 - 11:00||Session 1a|
|11:00 - 11:15||Tea/coffee break|
|11:15 - 12:45||Session 1b|
|12:45 - 14:00||Lunch|
|14:00 - 15:15||Session 2a|
|15:15 - 15:30||Tea/coffee break (Feedback Session)|
The number of delegates is restricted. Please register early to guarantee your place.