ARDL as an Elixir Approach to Cure for Spurious Regression in Nonstationary Time Series

In conventional Econometrics, the unit root and cointegration analysis are the only ways to circumvent the spurious regression which may arise from missing variable (lag values) rather than the nonstationarity process in time series data. We propose the Ghouse equation solution of autoregressive dis...

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Autores principales:	Ghulam Ghouse, Saud Ahmad Khan, Atiq Ur Rehman, Muhammad Ishaq Bhatti
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	spurious regression missing lag value unit root cointegration ARDL Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/5291aa7420cf4fbda33481249b149442
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spelling	oai:doaj.org-article:5291aa7420cf4fbda33481249b1494422021-11-25T18:16:26ZARDL as an Elixir Approach to Cure for Spurious Regression in Nonstationary Time Series10.3390/math92228392227-7390https://doaj.org/article/5291aa7420cf4fbda33481249b1494422021-11-01T00:00:00Zhttps://www.mdpi.com/2227-7390/9/22/2839https://doaj.org/toc/2227-7390In conventional Econometrics, the unit root and cointegration analysis are the only ways to circumvent the spurious regression which may arise from missing variable (lag values) rather than the nonstationarity process in time series data. We propose the Ghouse equation solution of autoregressive distributed lag mechanism which does not require additional work in unit root testing and bound testing. This advantage makes the proposed methodology more efficient compared to the existing cointegration procedures. The earlier tests weaken their position in comparison to it, as they had numerous linked testing procedures which further increase the size of the test and/or reduce the test power. The simplification of the Ghouse equation does not attain any such type of error, which makes it a more powerful test as compared to widely cited exiting testing methods in econometrics and statistics literature.Ghulam GhouseSaud Ahmad KhanAtiq Ur RehmanMuhammad Ishaq BhattiMDPI AGarticlespurious regressionmissing lag valueunit rootcointegrationARDLMathematicsQA1-939ENMathematics, Vol 9, Iss 2839, p 2839 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	spurious regression missing lag value unit root cointegration ARDL Mathematics QA1-939
spellingShingle	spurious regression missing lag value unit root cointegration ARDL Mathematics QA1-939 Ghulam Ghouse Saud Ahmad Khan Atiq Ur Rehman Muhammad Ishaq Bhatti ARDL as an Elixir Approach to Cure for Spurious Regression in Nonstationary Time Series
description	In conventional Econometrics, the unit root and cointegration analysis are the only ways to circumvent the spurious regression which may arise from missing variable (lag values) rather than the nonstationarity process in time series data. We propose the Ghouse equation solution of autoregressive distributed lag mechanism which does not require additional work in unit root testing and bound testing. This advantage makes the proposed methodology more efficient compared to the existing cointegration procedures. The earlier tests weaken their position in comparison to it, as they had numerous linked testing procedures which further increase the size of the test and/or reduce the test power. The simplification of the Ghouse equation does not attain any such type of error, which makes it a more powerful test as compared to widely cited exiting testing methods in econometrics and statistics literature.
format	article
author	Ghulam Ghouse Saud Ahmad Khan Atiq Ur Rehman Muhammad Ishaq Bhatti
author_facet	Ghulam Ghouse Saud Ahmad Khan Atiq Ur Rehman Muhammad Ishaq Bhatti
author_sort	Ghulam Ghouse
title	ARDL as an Elixir Approach to Cure for Spurious Regression in Nonstationary Time Series
title_short	ARDL as an Elixir Approach to Cure for Spurious Regression in Nonstationary Time Series
title_full	ARDL as an Elixir Approach to Cure for Spurious Regression in Nonstationary Time Series
title_fullStr	ARDL as an Elixir Approach to Cure for Spurious Regression in Nonstationary Time Series
title_full_unstemmed	ARDL as an Elixir Approach to Cure for Spurious Regression in Nonstationary Time Series
title_sort	ardl as an elixir approach to cure for spurious regression in nonstationary time series
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/5291aa7420cf4fbda33481249b149442
work_keys_str_mv	AT ghulamghouse ardlasanelixirapproachtocureforspuriousregressioninnonstationarytimeseries AT saudahmadkhan ardlasanelixirapproachtocureforspuriousregressioninnonstationarytimeseries AT atiqurrehman ardlasanelixirapproachtocureforspuriousregressioninnonstationarytimeseries AT muhammadishaqbhatti ardlasanelixirapproachtocureforspuriousregressioninnonstationarytimeseries
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ARDL as an Elixir Approach to Cure for Spurious Regression in Nonstationary Time Series

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