Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper studies the analytic gradient of the local-constant estimator for the semiparametric smooth coefficient (SPSC) model. This gradient estimator is shown to be consistent and asymptotically normal. A gradient-based cross-validation method for bandwidth selection is proposed for the SPSC model. Simulation suggests that the analytic gradient of the local-constant estimator outperforms the local-linear counterpart with a relatively large sample size. The gradient estimators are then applied to estimate the marginal effects of research and development on capital and labor productivity in China’s high-technology industry.