Nonparametric Estimators of Dose-Response Functions

Michela Bia (), FLORES Carlos A. and Alessandra Mattei

No 2011-40, LISER Working Paper Series from Luxembourg Institute of Socio-Economic Research (LISER)

Abstract: We propose two semiparametric estimators of the dose-response function based on spline techniques. Under uncounfoundedness, the generalized propensity score can be used to estimate dose-response functions (DRF) and marginal treatment effect functions. In many observational studies treatment may not be binary or categorical. In such cases, one may be interested in estimating the dose-response function in a setting with a continuous treatment. We evaluate the performance of the proposed estimators using Monte Carlo simulation methods. The simulation results suggested that the estimated DRF is robust to the specific semiparametric estimator used, while the parametric estimates of the DRF were sensitive to model mis-specification. We apply our approach to the problem of evaluating the effect on innovation sales of Research and Development (R&D) financial aids received by Luxembourgish firms in 2004 and 2005.

Keywords: Continuous treatment; Dose-response function; Generalized Propensity Score; Non-parametric methods; R&D investment (search for similar items in EconPapers)
JEL-codes: C13 J31 J70 (search for similar items in EconPapers)
Pages: 24 pages
Date: 2011-07
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (8)

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