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Published in:
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2014 | OriginalPaper | Chapter

1. Introduction

Author : Marco Percoco

Published in: Regional Perspectives on Policy Evaluation

Publisher: Springer International Publishing

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Abstract

This chapter discusses the fundamentals of counterfactual policy evaluation. It presents the notions of “counterfactual”, confounding factors and causal inference through examples and provides a discussion of multivariate regression as the baseline policy evaluation model. Average Treatment Effect and Average Treatment on the Treated parameters are also presented, along with the identification of heterogeneous impact.

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next chapter Regression Discontinuity Design: When Series Interrupt
Footnotes
1
I would like to thank a referee for raising the issue concerning the definition of a suitable control group within a spatial context.
 
Literature
Angrist JD, Pischke JS (2009) Mostly harmless econometrics: an empiricist’s companion. Princeton University Press, Princeton
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Gibbons S, Machin S (2005) Valuing rail access using transport innovations. J Urban Econ 57(1):148–169CrossRef
Gibbons S, Overman HG (2010) Mostly pointless spatial econometrics? LSE SERC discussion paper n.61
Heckman JJ, Ichimura H, Todd PE (1997) Matching as an econometric evaluation estimator: evidence from evaluating a job training programme. Rev Econ Stud 64:605–654CrossRef
Imbens G, Angrist JD (1994) Identification and estimation of local average treatment effects. Econometrics 62:467–475CrossRef
McMillen DP, McDonald J (2004) Reaction of house prices to a new rapid transit line: Chicago’s midway line, 1983–1999. Real Estate Econ 32(3):463–486CrossRef
Metadata
Title
Introduction
Author
Marco Percoco
Copyright Year
2014
Book
Regional Perspectives on Policy Evaluation

Print ISBN: 978-3-319-09518-9

Electronic ISBN: 978-3-319-09519-6

Copyright Year: 2014

DOI
https://doi.org/10.1007/978-3-319-09519-6_1