Publications

19 Jul 11

Nonparametric Estimators of Dose-Response Functions.

Authors: BIA Michela, FLORES Carlos A., MATTEI Alessandra.

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.

Reference: BIA Michela, FLORES Carlos A., MATTEI Alessandra. Nonparametric Estimators of Dose-Response Functions. CEPS/INSTEAD, 2011, Working Papers n°2011-40, 24 p.

Keywords:
Continuous treatment,
Dose-response function,
Generalized Propensity Score,
Non-parametric methods,
R&D investment

JEL: C13, J31, J70.

Linked publications
BIA Michela, MATTEI Alessandra
Statistical Methods & Applications, 2012 (Online first 1 may 2012).
PASQUARIELLO Massimo, BIA Michela, CASSONE Alberto
Rivista di Economia e Statistica del Territorio, 2011, n°1, pp. 43-81.