How to analyse time series data using cointegration techniques / Nik Muhd Naziman Ab Rahman

This paper examines the methods and procedures that are employed in order to analyse time series data. Unit root tests (Augmented Dickey-Fuller and Phillips-Perron) are performed to investigate the order of integration of each variable that enters the model. Models containing non-stationary variabl...

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Main Author: Ab Rahman, Nik Muhd Naziman
Format: Article
Language:English
Published: Universiti Teknologi MARA Kedah, Sungai Petani 2002
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/11846/
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author Ab Rahman, Nik Muhd Naziman
author_facet Ab Rahman, Nik Muhd Naziman
author_sort Ab Rahman, Nik Muhd Naziman
building UiTM Institutional Repository
collection Online Access
description This paper examines the methods and procedures that are employed in order to analyse time series data. Unit root tests (Augmented Dickey-Fuller and Phillips-Perron) are performed to investigate the order of integration of each variable that enters the model. Models containing non-stationary variables normally lead to problems of spurious regression whereby the obtained statistical results indicate significant relationships between the variables in the equation when in actual fact they are only evidence of contemporaneous correlations instead of true causal relations. Analysis of cointegration enables researchers to deal with models involving non-stationary variables.
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spelling uitm-118462017-11-13T05:57:21Z https://ir.uitm.edu.my/id/eprint/11846/ How to analyse time series data using cointegration techniques / Nik Muhd Naziman Ab Rahman Ab Rahman, Nik Muhd Naziman Mathematical economics. Quantitative methods This paper examines the methods and procedures that are employed in order to analyse time series data. Unit root tests (Augmented Dickey-Fuller and Phillips-Perron) are performed to investigate the order of integration of each variable that enters the model. Models containing non-stationary variables normally lead to problems of spurious regression whereby the obtained statistical results indicate significant relationships between the variables in the equation when in actual fact they are only evidence of contemporaneous correlations instead of true causal relations. Analysis of cointegration enables researchers to deal with models involving non-stationary variables. Universiti Teknologi MARA Kedah, Sungai Petani 2002 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/11846/1/AJ_NIK%20MUHD%20NAZIMAN%20AB%20RAHMAN%20WA%2002.pdf Ab Rahman, Nik Muhd Naziman (2002) How to analyse time series data using cointegration techniques / Nik Muhd Naziman Ab Rahman. (2002) Wahana Akademik <https://ir.uitm.edu.my/view/publication/Wahana_Akademik.html>, 1 (1). pp. 30-37. ISSN 1675-2414
spellingShingle Mathematical economics. Quantitative methods
Ab Rahman, Nik Muhd Naziman
How to analyse time series data using cointegration techniques / Nik Muhd Naziman Ab Rahman
title How to analyse time series data using cointegration techniques / Nik Muhd Naziman Ab Rahman
title_full How to analyse time series data using cointegration techniques / Nik Muhd Naziman Ab Rahman
title_fullStr How to analyse time series data using cointegration techniques / Nik Muhd Naziman Ab Rahman
title_full_unstemmed How to analyse time series data using cointegration techniques / Nik Muhd Naziman Ab Rahman
title_short How to analyse time series data using cointegration techniques / Nik Muhd Naziman Ab Rahman
title_sort how to analyse time series data using cointegration techniques / nik muhd naziman ab rahman
topic Mathematical economics. Quantitative methods
url https://ir.uitm.edu.my/id/eprint/11846/