TY - JOUR

T1 - On robust testing for trend

AU - Скроботов, Антон Андреевич

N1 - Publisher Copyright: © 2022 Elsevier B.V.

PY - 2022/3

Y1 - 2022/3

N2 - 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 utilizes t-statistic approach of Ibragimov and Müller (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

AB - 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 utilizes t-statistic approach of Ibragimov and Müller (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

KW - Asymptotic normality

KW - Heterogeneous errors

KW - Linear trend

KW - Nonstationarity

KW - Robust inference

UR - http://www.scopus.com/inward/record.url?scp=85123756858&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/cadca67b-37ba-37fc-a88e-c37f4c089fb7/

U2 - 10.1016/j.econlet.2022.110276

DO - 10.1016/j.econlet.2022.110276

M3 - Article

VL - 212

JO - Economics Letters

JF - Economics Letters

SN - 0165-1765

M1 - 110276

ER -