Political Sciences and International Security

The course mainly consists of three parts: an introduction to the problem of causality in the economic and social sciences; a study of some statistical and econometric ttools for the study of evaluation methods; the presentation of the main statistical methodologies for policy evaluation. This is accompanied by a laboratory for the presentation of the main statistical programs for policy evaluation (Stata, R).It is a course with an empirical rather than a theoretical approach. Detailed program: 1. The problem of causality in policy evaluation. Causality and counterfactual. Lexicon 2. The cycle of evaluation. Evaluation through indicators 3. Statistical models: review of probability, statistics and basic models of econometrics 4. The evaluation of economic policies: the potential output approach, the SUTVA hypothesis 5. Statistical methods of experimental and non-experimental evaluation. Randomized experiments and their problems 6. Impact estimation: evaluation of the average effect of policies on the population and on treaties 7. The main statistical methods of evaluation (DID, IV, Matching, RDD, SC) 8. Case study. Application of the models presented to some instruments of European regional policies The program is identical for attending and non-attending students

No prerequisites.The main statistical and econometric tools will be presented in the course.

1. Instructor's Notes (slides presented in class) that will be made available during the course. 2. For the section on statistical models: J. Stock and M. Watson, Introduction to Econometrics, 4th ed., especially chapters 4, 6.3, 7, 9, and 10. 3. For the section on evaluation methods (basic): A. Martini and M. Sisti (2009), Evaluating the Success of Public Policies, il Mulino. An outdated version of this work is in Formez (2006), Evaluating the Effects of Public Policies. Methods and Applications to the Italian Case, Ufficio Stampa ed Editoria, Rome (electronic copy available). Or, for more in-depth study: J. Angrist and J.S. Pischke (2015), Mastering 'Metrics': The Path from Cause to Effect, Princeton University Press

In-person

Both a written and an oral exam are planned. The written exam consists of exercises and open-ended questions (e.g., theoretical questions) that account for half of the total score. The written exam lasts two hours. At the end of the course, an exemption (esonero) is made for this part. The oral exam accounts for half of the total score and involves the presentation of an academic article that uses one of the methods for evaluating public policies. The exam include the possibility of an essay that uses the R software on a specific dataset to be agreed with the teacher. Students can view the over 100 datasets in the MASS and AER libraries (both presented in class) and propose a topic to the teacher. Preferably students should work in groups of 2 or, alternatively, alone. The essay is worth up to a maximum of 3 additional points that are added to the exam grade

The program mainly consists of lectures, which are accompanied by classes and laboratories to develop the ability to use the appropriate statistical programs. In the lectures the main basic level tools used for policy evaluation will be presented and the critical interpretation of the results obtained will be stimulated. In the classes some exercises will be presented and discussed in preparation for the exam.

The course mainly consists of three parts: an introduction to the problem of causality in the economic and social sciences; a study of some statistical and econometric ttools for the study of evaluation methods; the presentation of the main statistical methodologies for policy evaluation. This is accompanied by a laboratory for the presentation of the main statistical programs for policy evaluation (Stata, R).It is a course with an empirical rather than a theoretical approach. Detailed program: 1. The problem of causality in policy evaluation. Causality and counterfactual. Lexicon 2. The cycle of evaluation. Evaluation through indicators 3. Statistical models: review of probability, statistics and basic models of econometrics 4. The evaluation of economic policies: the potential output approach, the SUTVA hypothesis 5. Statistical methods of experimental and non-experimental evaluation. Randomized experiments and their problems 6. Impact estimation: evaluation of the average effect of policies on the population and on treaties 7. The main statistical methods of evaluation (DID, IV, Matching, RDD, SC) 8. Case study. Application of the models presented to some instruments of European regional policies The program is identical for attending and non-attending students

No prerequisites.The main statistical and econometric tools will be presented in the course.

1. Note del Docente (slides presentate a lezione) che verranno rese disponibili durante il corso 2. Per la parte relativa ai modelli statistici: J. Stock e M. Watson, Introduzione all’econometria, 4a ed., in particolare i capp. 4, 6.3, 7, 9, 10. 3. Per la parte relativa ai metodi di valutazione (elementare): A. Martini e M. Sisti (2009), Valutare il successo delle politiche pubbliche, il Mulino. Una versione non aggiornata di questo lavoro è in Formez (2006), Valutare gli effetti delle politiche pubbliche. Metodi e applicazioni al caso italiano, Ufficio Stampa ed Editoria, Roma (copia elettronica disponibile) oppure, a livello più approfondito: J. Angrist e J.S. Pischke (2015), Mastering 'Metrics': The Path from Cause to Effect, Princeton University Press

In-person

Both a written and an oral exam are planned. The written exam consists of exercises and open-ended questions (e.g., theoretical questions) that account for half of the total score. The written exam lasts two hours. At the end of the course, an exemption (esonero) is made for this part. The oral exam accounts for half of the total score and involves the presentation of an academic article that uses one of the methods for evaluating public policies. The exam include the possibility of an essay that uses the R software on a specific dataset to be agreed with the teacher. Students can view the over 100 datasets in the MASS and AER libraries (both presented in class) and propose a topic to the teacher. Preferably students should work in groups of 2 or, alternatively, alone. The essay is worth up to a maximum of 3 additional points that are added to the exam grade

The program mainly consists of lectures, which are accompanied by classes and laboratories to develop the ability to use the appropriate statistical programs. In the lectures the main basic level tools used for policy evaluation will be presented and the critical interpretation of the results obtained will be stimulated. In the classes some exercises will be presented and discussed in preparation for the exam.