Estimation and inference in special nonparametric models with applications to topics in development economics

Semiparametric additive regression models relax the common assumption of covariate effects to have a known functional form specified by some polynomial. These models only assume that relationships are smooth and are additively separable and thus are less restrictive than common parametric approaches. Estimation techniques for such models assuming all covariates to be exogenous, i.e. uncorrelated to the error term ruling out the presence of confounding omitted variables, for example, have become widely available. However, additive models with weaker assumptions on the error term and methods ...