Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/124346 
Erscheinungsjahr: 
2014
Schriftenreihe/Nr.: 
54th Congress of the European Regional Science Association: "Regional development & globalisation: Best practices", 26-29 August 2014, St. Petersburg, Russia
Verlag: 
European Regional Science Association (ERSA), Louvain-la-Neuve
Zusammenfassung: 
This paper presents an original econometric model for estimating a dose-response function through a regression approach when: (i) treatment is continuous, (ii) individuals may react heterogeneously to observable confounders, and (iii) selection-into-treatment may be potentially endogenous. After describing the model, two estimation procedures are suggested: one based on OLS under Conditional Mean Independence (or CMI), and one based on Instrumental-Variables (IV) under selection endogeneity. The paper goes on by presenting ctreatreg, a user-written Stata routine for an easy implementation of such a model, thereby performing a Monte Carlo experiment to test the reliability of the model and of its software implementation. Finally, an application to real data for assessing the effect of public R&D support on companies' R&D expenditure is presented and results briefly commented. The usefulness of such a model for program evaluation is clearly stressed.
Schlagwörter: 
treatment effects
dose-response function
continuous treatment
Monte Carlo
R&D support
JEL: 
C21
C87
D04
Dokumentart: 
Conference Paper

Datei(en):
Datei
Größe





Publikationen in EconStor sind urheberrechtlich geschützt.