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Training Calendar

Econometrics of program evaluation

  • Location: Cass Business School
  • Duration: 3 days
  • Software: Stata
  • Level: Intermediate
  • Delivered By: Dr. Giovanni Cerulli
  • Topic:
Econometrics of program evaluation

COURSE DATES: 5th - 7th March 2018

This course will provide participants with the essential tools, both theoretical and applied, for a proper use of modern micro-econometric methods for policy evaluation and causal counterfactual modelling under the assumption of “selection on observables”. The course will cover these approaches: Regression adjustment (parametric and nonparametric), Matching (on covariates and on propensity score), Reweighting and Double-robust methods, Selection models, Instrumental-variables approaches, Difference-in-differences, Regression discontinuity design.

DAY 1

Session 1: Introduction to the econometrics of program evaluation
  • Introduction to the econometrics of program evaluation
  • Some statistical background
  • Experimental and non-experimental design
  • The selection problem: observable an unobservable nature
  • Assumptions and notation
  • Regression Adjustment (parametric and nonparametric)
  • Control-Function regression
Session 2: Applications using Stata
  • Use of the Stata 14 treatment-effects estimation package teffects
  • Presentation of DO-files and ADO-files provided by the teacher
  • Application on real data of teffects subcommands
  • Extensions by Stata user-written commands: ivtreatreg, treatrew.

DAY 2

Session 1: Matching and Reweighting
  • Matching estimator: covariate and propensity score methods
  • Reweighting estimator
  • Double-robust estimator
  • Summary of methods
Session 2: Applications using Stata
  • Use of the Stata 14 treatment-effects estimation package teffects
  • Presentation of DO-files and ADO-files provided by the teacher
  • Application on real data of teffects subcommands
  • Extensions by Stata user-written commands: pscore, psmatch2, treatrew.

DAY 3

Session 1: Econometrics of program evaluation under “unobservable selection”
  • Summary of program evaluation under “observable selection”
  • Statistical background: the endogeneity problem
  • Assumptions and notation
  • Selection models (Heckit)
  • Instrumental variables approaches (IV)
Session 2: Applications using Stata
  • Use of the Stata 14 treatment-effects estimation package teffects
  • Presentation of DO-files and ADO-files provided by the teacher
  • Application on real data of teffects subcommands
  • Extensions by Stata user-written commands: ivtreatreg.

DAY 4

Session 1: Difference-in-differences (DID)
  • DID: statistical setting and conceptualization
  • DID with longitudinal data
  • DID with repeated cross-section
  • Description and use on real data of the Stata command: diff. DO-files and ADO files provided by the teacher
Session 2: Regression discontinuity design (RDD)
  • Local Average Treatment Effect (LATE)
  • RDD as a local approximation of a natural experiment
  • Sharp RDD: setting and estimation
  • Fuzzy RDD: setting and estimation
  • Application, description and use on simulated and real data of Stata command: rd. DO-files provided by the teacher
Learning Ratio 30% Theory, 30% Demonstration and 40% Practical

Principal texts for pre-course reading:
  • Wooldridge, J.M. (2010). Econometric Analysis of cross section and panel data. Chapter 21. Cambridge: MIT Press.
  • Cameron, A.C., & Trivedi P.K. (2005). Microeconometrics: Methods and Applications. Chapter 25. Cambridge: Cambridge University Press.
  • Cerulli, G. (2012), An Assessment of the Econometric Methods for Program Evaluation and a Proposal to Extend the Difference-In-Differences estimator to dynamic treatment, in: Econometrics: New Developments, Nova Publishers, New York.
Principal texts for post-course reading:
  • Cerulli, G. (2015), Econometric Evaluation of Socio-Economic Programs: Theory and Applications, Springer.

DAILY TIMETABLE (subject to minor changes)

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)

15:30-17:00 Session 2b

  • Knowledge of basic econometrics: notion of conditional expectation and related properties; point and interval estimation; regression model and related properties; probit and logit regression.
  • Basic knowledge of the Stata software
  •  CommercialAcademicStudent
    May (05/03/2018 - 07/03/2018)

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