Structural quantitative work in international economics typically models trade costs as a log-linear function of exogenous trade-policy variables. We propose a structural approach that allows for a nonparametric relationship and for treating tariff and nontariff trade-policy variables as...

We explore inference on regression coefficients in semiparametric multinomial response models. We consider cross-sectional, and both static and dynamic panel settings where we focus throughout on inference under sufficient conditions for point identification. The approach to identification uses...

This paper analyzes the process of real economic convergence in the New Member States (NMS) being formerly centrally planned economies, using nonparametric methods instead of conventional parametric measurement tools like beta and sigma models. This methodological framework allows the examining...

This article uses a nonparametric varying coefficient panel data model to study the convergence of real GDP per capita among 120 world economies for the sample period of 1980-2010. The estimates show that the indirect contribution of initial income via the control variables is important. The...

We investigate the relationship between remittances inflow and economic growth in a sample of 65 emerging countries over the period 1988-2018 using the semi-parametric panel data model with fixed effects as proposed by Baltagi and Li (2002). Our empirical results show that the effect of...

This paper examines the effect of immigration on the U.S. trade flows. The model hypothesizes that immigration facilitates international trade with home countries by lowering transaction costs. Immigrants also demand products from their country of origin and thus stimulate trade. Using a panel...

Accurate credit-granting decisions are crucial to the efficiency of the decentralized capital allocation mechanisms in modern market economies. Credit bureaus and many financial institutions have developed and used credit-scoring models to standardize and automate, to the extent possible, credit...

This paper studies nonparametric estimation of conditional moment models in which the residual functions could be nonsmooth with respect to the unknown functions of endogenous variables. It is a problem of nonparametric nonlinear instrumental variables (IV) estimation, and a difficult nonlinear...

This note argues that nonparametric regression not only relaxes functional form assumptions vis-a-vis parametric regression, but that it also permits endogenous control variables. To control for selection bias or to make an exclusion restriction in instrumental variables regression valid,...

In semiparametric models it is a common approach to under-smooth the nonparametric functions in order that estimators of the finite dimensional parameters can achieve root-n consistency. The requirement of under-smoothing may result as we show from inefficient estimation methods or technical...