Nonparametric Estimators of Dose-Response Functions
AbstractWe 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.
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Bibliographic InfoPaper provided by CEPS/INSTEAD in its series CEPS/INSTEAD Working Paper Series with number 2011-40.
Length: 24 pages
Date of creation: Jul 2011
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Continuous treatment; Dose-response function; Generalized Propensity Score; Non-parametric methods; R&D investment;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
- J70 - Labor and Demographic Economics - - Labor Discrimination - - - General
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