Univariate and Vector Autocorrelation Time Series Models for  Some Sectors in Nigeria

Univariate and Vector Autocorrelation Time Series Models for Some Sectors in Nigeria

Amadi, Godpower Dike

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Amadi

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Biu

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Arimie

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Christopher Onyema

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Univariate and Vector Autocorrelation Time Series Models for Some Sectors in Nigeria

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Abstract

This work on univariate and Vector Autocorrelation (VAR) time series model for the sectors in Nigeria, aims at providing an in-depth quantitative analysis of the variables (Agriculture, Industry, Building & Construction, Wholesale & Retail trade and Services). The study made use of secondary data, of all the variables investigated in the model, collected from the National Bureau of Statistics ‘ Statistical Bulletin (2018). The sample covers quarterly data from 1981 to 2018. Univariate and Multivariate time series estimation techniques -Autoregressive Integrated Moving Average (ARIMA) and Vector Autoregressive (VAR) were employed. Plots of the five sectors indicate that they all have Quadratic trend with appreciation and depreciation. Correlation analysis of the data set show that there exists a strong relationship among each variable. Each of the economic variables ARIMA model was built using Minitab 18 statistical software.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Amadi, Godpower Dike. 2020. \u201cUnivariate and Vector Autocorrelation Time Series Models for Some Sectors in Nigeria\u201d. Global Journal of Science Frontier Research - F: Mathematics & Decision GJSFR-F Volume 20 (GJSFR Volume 20 Issue F6).

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GJSFR Volume 20 Issue F6

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Journal Specifications

Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

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Classification

GJSFR-F Classification MSC 2010: 37M10

Submission ReceivedAugust 3, 2020
Peer Review Double Blind
Handling Editor
Accepted September 2, 2020
Published September 15, 2020

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v1.2

Issue date

September 30, 2020

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