A New Semiparametric Quantile Panel Data Model: Theory and Applications

In this paper, to estimate the impact of FDI on economic growth in host countries, we propose a new semiparametric quantile panel data model with correlated random effects, in which some of the coefficients are allowed to depend on some smooth economic variables while other coefficients remain constant. A three-stage estimation procedure based on quasi-maximum (local) likelihood estimation (QMLE) is proposed to estimate both constant and functional coefficients and their asymptotic properties are investigated. We show that the estimator of constant coefficients is √ N consistent and the estimator of varying coefficients converges in a nonparametric rate. A Monte Carlo simulation is conducted to examine the finite sample performance of the proposed estimators. Finally, using the cross-country data from 1970 to 1999, we find a strong empirical evidence of the existence of the absorptive capacity hypothesis. Moreover, another new finding is that FDI has a much stronger growth effects for countries with fast economic growth than for those with slow economic growth.