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We consider a semiparametric generalized linear model and study estimation ofboth marginal and quantile effects in this model. We propose an approximatemaximum likelihood estimator, and rigorously establish the consistency, theasymptotic normality, and the semiparametric efficiency of our method in boththe marginal effect and the quantile effect estimation. Simulation studies areconducted to illustrate the finite sample performance, and we apply the newtool to analyze a Swiss non-labor income data and discover a new interestingpredictor.

Semiparametric Approach to Estimation of Marginal and Quantile Effects