Locally optimal tests against periodic linear regression in short panels

This paper aims to detect the periodic coefficients of a Linear Regression model with Panel Data. Nonparametric locally and asymptotically optimal tests are proposed for testing the null hypothesis of a traditional linear regression model, against an alternative of a Periodic Coefficient Regression...

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Bibliographic Details
Published inCommunications in statistics. Simulation and computation Vol. 54; no. 6; pp. 2221 - 2235
Main Authors Regui, Slimane, Akharif, Abdelhadi, Mellouk, Amal
Format Journal Article
LanguageEnglish
Published Taylor & Francis 03.06.2025
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Summary:This paper aims to detect the periodic coefficients of a Linear Regression model with Panel Data. Nonparametric locally and asymptotically optimal tests are proposed for testing the null hypothesis of a traditional linear regression model, against an alternative of a Periodic Coefficient Regression model. The Uniform Local Asymptotic Normality (ULAN) property is established for Periodic Linear Regression (PLR) model, to construct Locally asymptotically optimal tests. The rank-based version of the optimal parametric test is provided in particular cases. The performance of the proposed tests is valid with numerical simulations using the Monte Carlo study. Real data was studied for applying the periodic linear regression model which compared to both traditional regression and random coefficient regression models.
ISSN:0361-0918
1532-4141
DOI:10.1080/03610918.2024.2314662