Short courses
AAU
Summer school
Seminar Series
Crash course
in economics

Short courses PhD

Econometric Evaluation of Treatment Effects
8 to 12 December
 
Workload: 2 ECTS
Faculty: Pr. Pierre Dubois, Toulouse School of Economics (GREMAQ, INRA, IDEI), France
Assessment:
The course consists of a series of lectures and self-study of the applied literature leading to a written assignment.


Content and objectives

Since the 1990s, the econometric evaluation of economic policies has been cast with great benefits into the vocabulary of the statistical literature concerning “treatment effects”. It addresses questions of causality that economic policies purposively have on the economic behaviour of various economic agents. It aims at distinguishing causal or treatment effects from sheer descriptive correlations in a framework that is borrowed from treatment set-ups in biological sciences. It allows for ex-post evaluation of the objectives of economic policies in terms of targeting some sub-populations or in terms of their impact and allows for comparisons with the intended targeting and impact when those policies were designed.

This course is meant to provide an introduction and an overview of the main issues, theories and practices regarding the design and the implementation of econometric evaluation of treatment effects. The course aims at giving basic knowledge on the treatment effect literature that allows for critical reading of reports of analyses where some econometric evaluation of economic policies is performed.

Literature

  • Basic econometrics as Hayashi, F., 2000, Econometrics, Princeton University

  •  Heckman, JJ, R. Lalonde and J. Smith (1999), “The economics and econometrics of active labor market programs” in Handbook of Labor Economics 3B eds Ashenfelter and Card, North Holland.

  • Heckman J. and Vytlacil E. (2005) “Structural Equations, Treatment Effects and Econometric Policy Evaluation,”, Econometrica, 2005, 73(3): 669-738

  • Lee, MJ, (2005), Microeconometrics for policy, program and&nbs treatment effects, Cambridge UP.

  • Manski C. (1995) Identification Problems in the Social Sciences, Harvard University Press

  • Meyer, B., (1995), “Natural and quasi-experiments in economics”, Journal of Business and Economic Statistics, 13:151-61

  • Wooldridge, J., (2002), Econometric Analysis of Cross-Section and Panel Data, MIT Press.




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