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Module · Elective/Applied Econometrics

Econometrics of Program Evaluation

This course will provide participants with the essential tools, both theoretical and applied, for proper use of modern microeconometric methods for policy evaluation and causal counterfactual modelling. The course will cover various approaches, namely: 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, and Regression Discontinuity Design. Each student should be able to read and understand applications from different policy sub-fields, such as finance and banking, the labour market, the investment activities of enterprises, education policy and regional cooperation, incentives for business research and development, etc. This module can be taken as part of a PG Certificate, PG Diploma or Full Masters Program.

Prerequisites

Please note to take this course you must first have completed Microeconometrics and Panel Data Econometrics.

Delivery

This module consists of 2-hour lectures per day for 5 days, plus a 1-hour tutorial per day. There will be optional clinics on the last day of the course.

Study Hours

Approximately 100 hours of study, of which 15 are contact hours and 85 are private study.

Software Used

Stata

Credits

10 CATS credits

Module Lead
Prof. Mathieu Lefebvre

Prof. Mathieu Lefebvre

Programme Faculty

Key Outcomes

  • —Set up and manage a correct evaluation design, either under observable or unobservable selection
  • —Identify, collect, and organize datasets for a correct ex-post program evaluation
  • —Understand the theoretical underpinnings of the most widely studied econometric models for program evaluation, using mainly intuitive examples and graphical approaches
  • —Select the appropriate methods to use and interpret results accordingly
  • —Read and understand applications from different policy sub-fields, such as: finance and banking, the labour market, the investment activities of enterprises, education policy and regional cooperation, incentives for business research and development, etc.

Desired Skills

  • —Engage in abstract thinking by extracting the essential features of complex systems to facilitate problem solving and decision-making
  • —Communicate and present complex arguments in oral and written form with clarity and succinctness
  • —Present, interpret and analyse information in numerical form
  • —Utilise effectively statistical and other packages
  • —Apply basic statistical techniques to analyse economic and financial datasets
  • —Work effectively both individually and within a team environment

Lecture Programme

  1. WK 01

    Lecture 1: Introduction to the Econometrics of Program Evaluation I

    • ·Econometrics of program evaluation: statistical background
    • ·Experimental and non-experimental design
    • ·The selection problem: observable and unobservable selection
    • ·Assumptions and notation
  2. WK 02

    Lecture 2: Introduction to the Econometrics of Program Evaluation II

    • ·Regression Adjustment (parametric and nonparametric)
    • ·Control-function regression
  3. WK 03

    Lecture 3: Applications using Stata I

    • ·Use of the Stata treatment-effects estimation package teffects
    • ·Presentation of DO-files and ADO-files provided by the lecturer
  4. WK 04

    Lecture 4: Applications using Stata II

    • ·Application on real data of teffects subcommands
    • ·Extensions by Stata user-written commands: ivtreatreg, treatrew
  5. WK 05

    Lecture 5: Matching Estimator

    • ·Matching estimator: covariate and propensity score methods
  6. WK 06

    Lecture 6: Reweighting and Double-Robust Estimator

    • ·Reweighting estimator
    • ·Double-robust estimator
    • ·Summary of methods
  7. WK 07

    Lecture 7: Applications using Stata I

    • ·Use of the Stata treatment-effects estimation package teffects
    • ·Presentation of DO-files and ADO-files provided by the lecturer
  8. WK 08

    Lecture 8: Applications using Stata II

    • ·Application on real data of teffects subcommands
    • ·Extensions by Stata user-written commands: pscore, psmatch2, treatrew
  9. WK 09

    Lecture 9: Econometrics of Program Evaluation under "Selection on Unobservables" I

    • ·Summary of program evaluation under "observable selection"
    • ·Statistical background: the endogeneity problem
    • ·Assumptions and notation
    • ·Selection models (Heckit)
  10. WK 10

    Lecture 10: Econometrics of Program Evaluation under "Selection on Unobservables" II

    • ·Instrumental variables approaches (IV) and LATE
    • ·Difference-in-differences (DID)
    • ·A primer into the Regression discontinuity design (RD)
  11. WK 11

    Lecture 11: Applications using Stata I

    • ·Use of the Stata treatment-effects estimation package teffects
    • ·Presentation of DO-files and ADO-files provided by the lecturer
  12. WK 12

    Lecture 12: Applications using Stata II

    • ·Application on real data of teffects subcommands

Assessment

Online coursework submission with the support of your module lecturer and tutor. All sessions are conducted live online at a scheduled time and recorded for review.

Build your qualification

Take Econometrics of Program Evaluation as a standalone module, or as part of a buildable MSc.

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