Semiparametric single-index panel data models with cross-sectional dependence

Publisher:
Elsevier BV
Publication Type:
Journal Article
Citation:
Journal of Econometrics, 2015, 188 (1), pp. 301 - 312
Issue Date:
2015-09
Full metadata record
Files in This Item:
Filename Description Size
DGPshort (2).pdf391.55 kB
Adobe PDF
In this paper, we consider a semiparametric single-index panel data model with cross-sectional dependence and stationarity. Meanwhile, we allow fixed effects to be correlated with the regressors to capture unobservable heterogeneity. Under a general spatial error dependence structure, we then establish some consistent closed-form estimates for both the unknown parameters and the link function for the case where both cross-sectional dimension (N) and temporal dimension (T ) go to infinity. Rates of convergence and asymptotic normality are established for the proposed estimates. Our experience suggests that the proposed estimation method is simple and thus attractive for finite-sample studies and empirical implementations. Moreover, both the finite-sample performance and the empirical applications show that the proposed estimation method works well when the cross-sectional dependence exists in the data set.
Please use this identifier to cite or link to this item: