Document Type
Discussion Paper
Publication Date
12-1-2019
CFDP Number
2211
CFDP Pages
42
Journal of Economic Literature (JEL) Code(s)
C13, C22
Abstract
This paper develops an asymptotic theory for nonlinear cointegrating power function regression. The framework extends earlier work on the deterministic trend case and allows for both endogeneity and heteroskedasticity, which makes the models and inferential methods relevant to many empirical economic and financial applications, including predictive regression. Accompanying the asymptotic theory of nonlinear regression, the paper establishes some new results on weak convergence to stochastic integrals that go beyond the usual semi-martingale structure and considerably extend existing limit theory, complementing other recent findings on stochastic integral asymptotics. The paper also provides a general framework for extremum estimation limit theory that encompasses stochastically nonstationary time series and should be of wide applicability.
Recommended Citation
Hu, Zhishui; Phillips, Peter C.B.; and Wang, Qiying, "Nonlinear Cointegrating Power Function Regression with Endogeneity" (2019). Cowles Foundation Discussion Papers. 37.
https://elischolar.library.yale.edu/cowles-discussion-paper-series/37