Training Calendar

Advances in Causal Inference using Stata

Dublin, Ireland 2 days (14th September 2020 - 15th September 2020) Stata Advanced, Intermediate
Casual Analysis, Econometrics


Econometric modelling for causal inference and program evaluation has received tremendous development in the last decade, with new approaches and methods addressing an expanding set of challenging problems, both in medical and the social sciences. This course covers some recent developments in causal inference and program evaluation using Stata.

It will provide participants with the essential tools, both theoretical and applied, for a proper use of recent micro-econometric methods for policy evaluation and causal modelling in situations where the standard “binary” treatment setting poses limitations.

More specifically, the course will focus on these approaches:

  • Difference-in-differences (DID) with time-varying binary treatment
  • The Synthetic Control Method (SCM) for program evaluation, suitable when datasets on many times and locations are available
  • Models for multivalued and quantile treatment effect estimation
  • Causal inference with continuous treatment (namely, dose-response models)

After attending the course, the participants will be comfortable with setting up and and managing correct evaluation design using Stata, by identifying the policy framework, the appropriate econometric method to use interpreting correctly the results. The course will provide various practical examples using real datasets.

Course Agenda

Day 1

Session 1: Econometrics of program evaluation: an overview

  • Causal inference and program evaluation
  • Observable vs. unobservable selection
  • Statistical background for the binary treatment setting
  • Assumptions and notation: Conditional independence and endogeneity
  • Review of the econometric methods for binary treatment
  • Limits of the binary treatment setting and new developments

Session 2: Difference-in-differences (DID) with time-varying binary treatment

  • Standard DID: statistical setting and conceptualization
  • DID with panel data and repeated cross-section
  • DDID: Difference-in-differences with time-varying binary treatment
  • DDID application on real data using the Stata command ddid

Session 3: DID with many times and locations: the Synthetic-Control Method (SCM)

  • SCM: statistical setting and conceptualization
  • Parametric SCM and Stata implementation using synth
  • Nonparametric SCM and Stata implementation via npsynth

Day 2

Session 1: Multivalued and quantile treatment effect estimation

  • Causal inference with multivalued treatment
  • Statistical setting and estimation under conditional independence
  • Application using the Stata command poparms
  • Estimation of quantile treatment effect under conditional independence

Session 2: Causal inference with continuous treatment: dose-response models

  • The logic of dose-response models
  • The Generalized Propensity Score (GPS) approach
  • Application of the GPS via the Stata commands gpscore and doseresponseM
  • Regression-Adjustment based dose-response models (RADR)
  • Application of the RADR via the Stata command ctreatreg

Principal texts for pre- and post-course reading

  • Cerulli, G. (2015), Econometric Evaluation of Socio-Economic Programs: Theory and Applications, Springer.
  • Wooldridge, J.M. (2010). Econometric Analysis of cross section and panel data. Chapter 21. Cambridge: MIT Press.Differences estimator to dynamic treatment, Econometrics: New Developments, Nova Publishers, New York.
  • Abadie, A., Diamond, A., and Hainmueller, J. (2010), Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program, Journal of the American Statistical Association, Vol. 105, No. 490, 493-505.
  • Bia, M. and Mattei, A. (2008), A Stata package for the estimation of the dose–response function through adjustment for the generalized propensity score, Stata Journal, Volume 8, Number 3.
  • Cattaneo, M., Drukker, D., and Holland, A. (2013), Estimation of multivalued treatment effects under conditional independence, Stata Journal, Volume 13, Number 3.
  • Cerulli, G. (2015), ctreatreg: Command for fitting dose-response models under exogenous and endogenous treatment, Stata Journal, Volume 15, Number 4.

Daily Timetable (subject to minor changes)

TimeSession / Description
08:30-09:00 Arrival and Registration
09:00-10:45 Session 1
10:45-11:00 Break
11:00-12:30 Session 2
12:30-13:30 Lunch
13:30-15:15 Session 3
15:15-15:30 Break
15:30-17:15 Session 4


  • Basic knowledge of Stata
  • Some knowledge of the basics of counterfactual modelling is preferable

Terms & Conditions

  • Student registrations: Attendees must provide proof of full time student status at the time of booking to qualify for student registration rate (valid student ID card or authorised letter of enrolment).
  • Additional discounts are available for multiple registrations.
  • Cost includes course materials, lunch and refreshments.
  • Delegates are provided with temporary licences for the software(s) used in the course and will be instructed to download and install the software prior to the start of the course. (Alternatively, laptops can be hired for a fee of £10.00 (ex. VAT) per day).
  • If you need assistance in locating hotel accommodation in the region, please notify us at the time of booking.
  • Payment of course fees required prior to the course start date.
  • Registration closes 5-calendar days prior to the start of the course.
    • 100% fee returned for cancellations made over 28-calendar days prior to start of the course.
    • 50% fee returned for cancellations made 14-calendar days prior to the start of the course.
    • No fee returned for cancellations made less than 14-calendar days prior to the start of the course.

The number of delegates is restricted. Please register early to guarantee your place.

  •  CommercialAcademicStudent
    2-Day Course (14/09/2020 - 15/09/2020)

All prices exclude VAT or local taxes where applicable.

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Cass Business School is located approximately five to ten minutes walk from the nearest underground and railway stations (Moorgate, Old Street, Barbican and Liverpool Street).

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