APPLICATION OF TIME SERIES MODEL ON CONSUMER PRICE INDEX (CPI)

Authors

  • Aliyu Baba Masaya Department of Computer Science, Yobe State University, Yobe, Nigeria
  • Ibrahim Usman Bura Department of Environmental Science, School of Basic Science and Research, Sharda University, India

Keywords:

Seasonal Auto-Regressive Integrated Moving Average (SARIMA)., Consumer Price Index, Auto-correlation Function (ACF), Partial auto-correlation Function (PACF), Auto-Regressive Integrated Moving Average (ARIMA)

Abstract

This work examines time series analysis on consumer price index (CPI) in Nigeria for the period 2003 to 2016 on yearly basis. The main objective of the study was to determine the pattern, the adequacy and also to develop a model for forecasting the consumer price index (CPI). A secondary data was collected from the Central Bank of Nigeria website. The statistical software used to analyze the data was the MINITAB version 17.0. It was found that as the year increases the CPI also increases. The analysis also reveals that the fitted values were highly reliable. The SARIMA (1,1,1) (1,0,1)12 model fitted well into our data and could be used to  forecast the consumer price index (CPI) for the future.

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Published

2024-07-25

How to Cite

Aliyu Baba Masaya, & Ibrahim Usman Bura. (2024). APPLICATION OF TIME SERIES MODEL ON CONSUMER PRICE INDEX (CPI) . BW Academic Journal, 1(3), 1–13. Retrieved from https://mail.bwjournal.org/index.php/bsjournal/article/view/2139

Issue

Vol. 1 No. 3 (2024): Bushwealth Academic Journals

Section

Articles