On Robust Testing for Trend

23 Pages Posted: 28 Jul 2021 Last revised: 6 Jan 2022

See all articles by Anton Skrobotov

Anton Skrobotov

Russian Academy of National Economy and Public Administration under the President of the Russian Federation (RANEPA) - Department of Economics

Date Written: November 17, 2021

Abstract

This paper provides a simple approach for robust testing for the trend function in the time series under uncertainty over the order of integration of the error term. The proposed approach relies on the asymptotic normality of the trend coefficient estimator and utilises t-statistic approach of Ibragimov and Muler (2010) based on splitting the sample. The Monte-Carlo results demonstrate that the approach has the correct finite sample size and favorable finite sample power properties for all data generating processes considered. The proposed approach is robust to very general assumptions on the error term including various forms of non-stationary volatility and heavy tails.

Keywords: robust inference, linear trend, asymptotic normality, heterogeneous errors, nonstationarity

JEL Classification: C12, C22

Suggested Citation

Skrobotov, Anton, On Robust Testing for Trend (November 17, 2021). Available at SSRN: https://ssrn.com/abstract=3893116 or http://dx.doi.org/10.2139/ssrn.3893116

Anton Skrobotov (Contact Author)

Russian Academy of National Economy and Public Administration under the President of the Russian Federation (RANEPA) - Department of Economics ( email )

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