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Inference on a semiparametric model with global power law and local nonparametric trends

journal contribution
posted on 2020-04-01, 00:00 authored by Jiti Gao, Oliver Linton, Bin Peng
We consider a model with both a parametric global trend and a nonparametric local trend. This model may be of interest in a number of applications in economics, finance, ecology, and geology. We first propose two hypothesis tests to detect whether two nested special cases are appropriate. For the case where both null hypotheses are rejected, we propose an estimation method to capture certain aspects of the time trend. We establish consistency and some distribution theory in the presence of a large sample. Moreover, we examine the proposed hypothesis tests and estimation methods through both simulated and real data examples. Finally, we discuss some potential extensions and issues when modelling time effects.

History

Journal

Econometric theory

Volume

36

Pagination

223-249

Location

Cambridge, Eng.

ISSN

0266-4666

eISSN

1469-4360

Language

eng

Publication classification

C1.1 Refereed article in a scholarly journal, C Journal article

Copyright notice

2019, Cambridge University Press

Issue

2

Publisher

Cambridge University Press