TY  - BOOK
AU  - Robinson,Peter
TI  - Inference on nonparametrically trending time series with fractional errors
AV  - HB139.T52 ECO 
PY  - 2009///
CY  - Cambridge
PB  - Cambridge University Press
KW  - Time series analysis
KW  - Estimation theory
N2  - The central limit theorem for nonparametric kernel estimates of a smooth trend, with linearly-generated errors, indicates asymptotic independence and homoscedasticity across fixed points, irrespective of whether disturbances have short memory, long memory, or anti persistence. However, the asymptotic variance depends on the kernel function in a way that varies across these three circumstances, and in the latter two involves a double integral that cannot necessarily be evaluated in closed form. For a particular class of kernels, we obtain analytic formulae. We discuss extensions to more general settings, including ones involving possible cross-sectional or spatial dependence
UR  - https://doi.org/10.1017/S0266466609990302
ER  -