Time Series Analysis and Forecasting of Household Products’ Prices (A Case Study of Nyeri County)

Muriuki Brian Muriithi; Waiguru Samuel

doi:doi:10.11648/j.mma.20230801.11

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Time Series Analysis and Forecasting of Household Products’ Prices (A Case Study of Nyeri County)

Muriuki Brian Muriithi, Waiguru Samuel

Published in Mathematical Modelling and Applications (Volume 8, Issue 1)

Received: 17 March 2022 Accepted: 31 January 2023 Published: 22 May 2023

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Abstract

Inflation has a significant impact on both consumable and non-consumable products and plays a critical role in determining the cost of living. The study aimed to investigate the trend of household consumable and non-consumable prices over the past three years and identify the best ARIMA model for future price predictions. The results showed that consumable goods played a greater role in determining the national inflation compared to non-consumable goods. A relationship was found between the changes in local-level prices and national monthly inflation rates, with consumable goods being fitted to an ARIMA (1,2,2) model and national inflation rates to ARIMA (3,1,0). Non-consumable goods were found to be a white noise. The models were found to be adequate in forecasting changes in prices, with their validity confirmed by the Box-Ljung test and autocorrelation coefficients of model residuals. This study demonstrated the importance of analyzing changes in products’ prices at a local level and how it affects the national inflation rate. In future, similar studies can be carried out in different counties and with a more comprehensive model to investigate the impact of the COVID-19 pandemic on the prices of household consumable and non-consumable goods at the local level.

Published in	Mathematical Modelling and Applications (Volume 8, Issue 1)
DOI	10.11648/j.mma.20230801.11
Page(s)	1-12
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

ARIMA Model, Consumable Goods, Non-Consumable Goods, Inflation

References

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APA Style

Muriuki Brian Muriithi, Waiguru Samuel. (2023). Time Series Analysis and Forecasting of Household Products’ Prices (A Case Study of Nyeri County). Mathematical Modelling and Applications, 8(1), 1-12. https://doi.org/10.11648/j.mma.20230801.11

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ACS Style

Muriuki Brian Muriithi; Waiguru Samuel. Time Series Analysis and Forecasting of Household Products’ Prices (A Case Study of Nyeri County). Math. Model. Appl. 2023, 8(1), 1-12. doi: 10.11648/j.mma.20230801.11

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AMA Style

Muriuki Brian Muriithi, Waiguru Samuel. Time Series Analysis and Forecasting of Household Products’ Prices (A Case Study of Nyeri County). Math Model Appl. 2023;8(1):1-12. doi: 10.11648/j.mma.20230801.11

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@article{10.11648/j.mma.20230801.11,
  author = {Muriuki Brian Muriithi and Waiguru Samuel},
  title = {Time Series Analysis and Forecasting of Household Products’ Prices (A Case Study of Nyeri County)},
  journal = {Mathematical Modelling and Applications},
  volume = {8},
  number = {1},
  pages = {1-12},
  doi = {10.11648/j.mma.20230801.11},
  url = {https://doi.org/10.11648/j.mma.20230801.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.mma.20230801.11},
  abstract = {Inflation has a significant impact on both consumable and non-consumable products and plays a critical role in determining the cost of living. The study aimed to investigate the trend of household consumable and non-consumable prices over the past three years and identify the best ARIMA model for future price predictions. The results showed that consumable goods played a greater role in determining the national inflation compared to non-consumable goods. A relationship was found between the changes in local-level prices and national monthly inflation rates, with consumable goods being fitted to an ARIMA (1,2,2) model and national inflation rates to ARIMA (3,1,0). Non-consumable goods were found to be a white noise. The models were found to be adequate in forecasting changes in prices, with their validity confirmed by the Box-Ljung test and autocorrelation coefficients of model residuals. This study demonstrated the importance of analyzing changes in products’ prices at a local level and how it affects the national inflation rate. In future, similar studies can be carried out in different counties and with a more comprehensive model to investigate the impact of the COVID-19 pandemic on the prices of household consumable and non-consumable goods at the local level.},
 year = {2023}
}

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TY  - JOUR
T1  - Time Series Analysis and Forecasting of Household Products’ Prices (A Case Study of Nyeri County)
AU  - Muriuki Brian Muriithi
AU  - Waiguru Samuel
Y1  - 2023/05/22
PY  - 2023
N1  - https://doi.org/10.11648/j.mma.20230801.11
DO  - 10.11648/j.mma.20230801.11
T2  - Mathematical Modelling and Applications
JF  - Mathematical Modelling and Applications
JO  - Mathematical Modelling and Applications
SP  - 1
EP  - 12
PB  - Science Publishing Group
SN  - 2575-1794
UR  - https://doi.org/10.11648/j.mma.20230801.11
AB  - Inflation has a significant impact on both consumable and non-consumable products and plays a critical role in determining the cost of living. The study aimed to investigate the trend of household consumable and non-consumable prices over the past three years and identify the best ARIMA model for future price predictions. The results showed that consumable goods played a greater role in determining the national inflation compared to non-consumable goods. A relationship was found between the changes in local-level prices and national monthly inflation rates, with consumable goods being fitted to an ARIMA (1,2,2) model and national inflation rates to ARIMA (3,1,0). Non-consumable goods were found to be a white noise. The models were found to be adequate in forecasting changes in prices, with their validity confirmed by the Box-Ljung test and autocorrelation coefficients of model residuals. This study demonstrated the importance of analyzing changes in products’ prices at a local level and how it affects the national inflation rate. In future, similar studies can be carried out in different counties and with a more comprehensive model to investigate the impact of the COVID-19 pandemic on the prices of household consumable and non-consumable goods at the local level.
VL  - 8
IS  - 1
ER  -

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Author Information

Muriuki Brian Muriithi

Department of Pure and Applied Sciences, Kirinyaga University, Kerugoya, Kenya
Waiguru Samuel

Department of Mathematics and Statistics, Jomo Kenyatta University of Agriculture and Technology, Juja, Kenya

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APA Style

Muriuki Brian Muriithi, Waiguru Samuel. (2023). Time Series Analysis and Forecasting of Household Products’ Prices (A Case Study of Nyeri County). Mathematical Modelling and Applications, 8(1), 1-12. https://doi.org/10.11648/j.mma.20230801.11

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ACS Style

Muriuki Brian Muriithi; Waiguru Samuel. Time Series Analysis and Forecasting of Household Products’ Prices (A Case Study of Nyeri County). Math. Model. Appl. 2023, 8(1), 1-12. doi: 10.11648/j.mma.20230801.11

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AMA Style

Muriuki Brian Muriithi, Waiguru Samuel. Time Series Analysis and Forecasting of Household Products’ Prices (A Case Study of Nyeri County). Math Model Appl. 2023;8(1):1-12. doi: 10.11648/j.mma.20230801.11

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@article{10.11648/j.mma.20230801.11,
  author = {Muriuki Brian Muriithi and Waiguru Samuel},
  title = {Time Series Analysis and Forecasting of Household Products’ Prices (A Case Study of Nyeri County)},
  journal = {Mathematical Modelling and Applications},
  volume = {8},
  number = {1},
  pages = {1-12},
  doi = {10.11648/j.mma.20230801.11},
  url = {https://doi.org/10.11648/j.mma.20230801.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.mma.20230801.11},
  abstract = {Inflation has a significant impact on both consumable and non-consumable products and plays a critical role in determining the cost of living. The study aimed to investigate the trend of household consumable and non-consumable prices over the past three years and identify the best ARIMA model for future price predictions. The results showed that consumable goods played a greater role in determining the national inflation compared to non-consumable goods. A relationship was found between the changes in local-level prices and national monthly inflation rates, with consumable goods being fitted to an ARIMA (1,2,2) model and national inflation rates to ARIMA (3,1,0). Non-consumable goods were found to be a white noise. The models were found to be adequate in forecasting changes in prices, with their validity confirmed by the Box-Ljung test and autocorrelation coefficients of model residuals. This study demonstrated the importance of analyzing changes in products’ prices at a local level and how it affects the national inflation rate. In future, similar studies can be carried out in different counties and with a more comprehensive model to investigate the impact of the COVID-19 pandemic on the prices of household consumable and non-consumable goods at the local level.},
 year = {2023}
}

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TY  - JOUR
T1  - Time Series Analysis and Forecasting of Household Products’ Prices (A Case Study of Nyeri County)
AU  - Muriuki Brian Muriithi
AU  - Waiguru Samuel
Y1  - 2023/05/22
PY  - 2023
N1  - https://doi.org/10.11648/j.mma.20230801.11
DO  - 10.11648/j.mma.20230801.11
T2  - Mathematical Modelling and Applications
JF  - Mathematical Modelling and Applications
JO  - Mathematical Modelling and Applications
SP  - 1
EP  - 12
PB  - Science Publishing Group
SN  - 2575-1794
UR  - https://doi.org/10.11648/j.mma.20230801.11
AB  - Inflation has a significant impact on both consumable and non-consumable products and plays a critical role in determining the cost of living. The study aimed to investigate the trend of household consumable and non-consumable prices over the past three years and identify the best ARIMA model for future price predictions. The results showed that consumable goods played a greater role in determining the national inflation compared to non-consumable goods. A relationship was found between the changes in local-level prices and national monthly inflation rates, with consumable goods being fitted to an ARIMA (1,2,2) model and national inflation rates to ARIMA (3,1,0). Non-consumable goods were found to be a white noise. The models were found to be adequate in forecasting changes in prices, with their validity confirmed by the Box-Ljung test and autocorrelation coefficients of model residuals. This study demonstrated the importance of analyzing changes in products’ prices at a local level and how it affects the national inflation rate. In future, similar studies can be carried out in different counties and with a more comprehensive model to investigate the impact of the COVID-19 pandemic on the prices of household consumable and non-consumable goods at the local level.
VL  - 8
IS  - 1
ER  -

Copy | Download