Modelling and Forecasting Somalia's Consumer Price Index Using the ARIMA Model

Abdirashid Mohamed Hussein; Ahmed Hassan Abdillahi

doi:doi:10.11648/j.ajtas.20251402.14

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Modelling and Forecasting Somalia's Consumer Price Index Using the ARIMA Model

Abdirashid Mohamed Hussein^*

, Ahmed Hassan Abdillahi

Published in American Journal of Theoretical and Applied Statistics (Volume 14, Issue 2)

Received: 25 March 2025 Accepted: 2 April 2025 Published: 29 April 2025

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Abstract

This study examines the modeling and forecasting of Somalia’s Consumer Price Index (CPI) using the ARIMA model, with data from November 2022 to November 2024. Descriptive analysis reveals a mean CPI of 144.26, moderate variability, and a slight negative skew. The CPI series is unstable in its original form but achieves stability after first differencing. The ARIMA (1,1,0) model is selected as the best fit, based on its low AIC and BIC values, with diagnostic checks confirming its effectiveness in capturing the data patterns. Forecasts suggest a stable CPI of approximately 152.95 from December 2024 to November 2026, though prediction intervals widen over time, reflecting increased uncertainty. The model performs well, with a Mean Absolute Percentage Error (MAPE) of 6.18%, though slight underestimation bias is noted. These findings demonstrate that ARIMA forecasts can aid policymakers in designing effective inflation control measures in volatile economies. These insights can help the Central Bank and policymakers implement timely interventions to stabilize prices and manage inflation expectations. Future research should incorporate external economic factors for more robust long-term predictions.

Published in	American Journal of Theoretical and Applied Statistics (Volume 14, Issue 2)
DOI	10.11648/j.ajtas.20251402.14
Page(s)	89-98
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), 2025. Published by Science Publishing Group

Keywords

Somalia's Consumer Price Index (CPI), ARIMA Model, Time Series Forecasting, CPI Trend Analysis, Inflation Forecasting in Somalia

References

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APA Style

Hussein, A. M., Abdillahi, A. H. (2025). Modelling and Forecasting Somalia's Consumer Price Index Using the ARIMA Model. American Journal of Theoretical and Applied Statistics, 14(2), 89-98. https://doi.org/10.11648/j.ajtas.20251402.14

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ACS Style

Hussein, A. M.; Abdillahi, A. H. Modelling and Forecasting Somalia's Consumer Price Index Using the ARIMA Model. Am. J. Theor. Appl. Stat. 2025, 14(2), 89-98. doi: 10.11648/j.ajtas.20251402.14

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AMA Style

Hussein AM, Abdillahi AH. Modelling and Forecasting Somalia's Consumer Price Index Using the ARIMA Model. Am J Theor Appl Stat. 2025;14(2):89-98. doi: 10.11648/j.ajtas.20251402.14

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@article{10.11648/j.ajtas.20251402.14,
  author = {Abdirashid Mohamed Hussein and Ahmed Hassan Abdillahi},
  title = {Modelling and Forecasting Somalia's Consumer Price Index Using the ARIMA Model
},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {14},
  number = {2},
  pages = {89-98},
  doi = {10.11648/j.ajtas.20251402.14},
  url = {https://doi.org/10.11648/j.ajtas.20251402.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20251402.14},
  abstract = {This study examines the modeling and forecasting of Somalia’s Consumer Price Index (CPI) using the ARIMA model, with data from November 2022 to November 2024. Descriptive analysis reveals a mean CPI of 144.26, moderate variability, and a slight negative skew. The CPI series is unstable in its original form but achieves stability after first differencing. The ARIMA (1,1,0) model is selected as the best fit, based on its low AIC and BIC values, with diagnostic checks confirming its effectiveness in capturing the data patterns. Forecasts suggest a stable CPI of approximately 152.95 from December 2024 to November 2026, though prediction intervals widen over time, reflecting increased uncertainty. The model performs well, with a Mean Absolute Percentage Error (MAPE) of 6.18%, though slight underestimation bias is noted. These findings demonstrate that ARIMA forecasts can aid policymakers in designing effective inflation control measures in volatile economies. These insights can help the Central Bank and policymakers implement timely interventions to stabilize prices and manage inflation expectations. Future research should incorporate external economic factors for more robust long-term predictions.
},
 year = {2025}
}

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TY  - JOUR
T1  - Modelling and Forecasting Somalia's Consumer Price Index Using the ARIMA Model

AU  - Abdirashid Mohamed Hussein
AU  - Ahmed Hassan Abdillahi
Y1  - 2025/04/29
PY  - 2025
N1  - https://doi.org/10.11648/j.ajtas.20251402.14
DO  - 10.11648/j.ajtas.20251402.14
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 89
EP  - 98
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20251402.14
AB  - This study examines the modeling and forecasting of Somalia’s Consumer Price Index (CPI) using the ARIMA model, with data from November 2022 to November 2024. Descriptive analysis reveals a mean CPI of 144.26, moderate variability, and a slight negative skew. The CPI series is unstable in its original form but achieves stability after first differencing. The ARIMA (1,1,0) model is selected as the best fit, based on its low AIC and BIC values, with diagnostic checks confirming its effectiveness in capturing the data patterns. Forecasts suggest a stable CPI of approximately 152.95 from December 2024 to November 2026, though prediction intervals widen over time, reflecting increased uncertainty. The model performs well, with a Mean Absolute Percentage Error (MAPE) of 6.18%, though slight underestimation bias is noted. These findings demonstrate that ARIMA forecasts can aid policymakers in designing effective inflation control measures in volatile economies. These insights can help the Central Bank and policymakers implement timely interventions to stabilize prices and manage inflation expectations. Future research should incorporate external economic factors for more robust long-term predictions.

VL  - 14
IS  - 2
ER  -

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Author Information

Abdirashid Mohamed Hussein

Department of Mathematics and Statistics, Kampala International University, Kansanga, Kampala, Uganda

Contact Email

http://orcid.org/0009-0003-3177-7891
Ahmed Hassan Abdillahi

Department of Mathematics and Statistics, Kampala International University, Kansanga, Kampala, Uganda

Contact Email

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Plain Text BibTeX RIS

APA Style

Hussein, A. M., Abdillahi, A. H. (2025). Modelling and Forecasting Somalia's Consumer Price Index Using the ARIMA Model. American Journal of Theoretical and Applied Statistics, 14(2), 89-98. https://doi.org/10.11648/j.ajtas.20251402.14

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ACS Style

Hussein, A. M.; Abdillahi, A. H. Modelling and Forecasting Somalia's Consumer Price Index Using the ARIMA Model. Am. J. Theor. Appl. Stat. 2025, 14(2), 89-98. doi: 10.11648/j.ajtas.20251402.14

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AMA Style

Hussein AM, Abdillahi AH. Modelling and Forecasting Somalia's Consumer Price Index Using the ARIMA Model. Am J Theor Appl Stat. 2025;14(2):89-98. doi: 10.11648/j.ajtas.20251402.14

Copy | Download

@article{10.11648/j.ajtas.20251402.14,
  author = {Abdirashid Mohamed Hussein and Ahmed Hassan Abdillahi},
  title = {Modelling and Forecasting Somalia's Consumer Price Index Using the ARIMA Model
},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {14},
  number = {2},
  pages = {89-98},
  doi = {10.11648/j.ajtas.20251402.14},
  url = {https://doi.org/10.11648/j.ajtas.20251402.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20251402.14},
  abstract = {This study examines the modeling and forecasting of Somalia’s Consumer Price Index (CPI) using the ARIMA model, with data from November 2022 to November 2024. Descriptive analysis reveals a mean CPI of 144.26, moderate variability, and a slight negative skew. The CPI series is unstable in its original form but achieves stability after first differencing. The ARIMA (1,1,0) model is selected as the best fit, based on its low AIC and BIC values, with diagnostic checks confirming its effectiveness in capturing the data patterns. Forecasts suggest a stable CPI of approximately 152.95 from December 2024 to November 2026, though prediction intervals widen over time, reflecting increased uncertainty. The model performs well, with a Mean Absolute Percentage Error (MAPE) of 6.18%, though slight underestimation bias is noted. These findings demonstrate that ARIMA forecasts can aid policymakers in designing effective inflation control measures in volatile economies. These insights can help the Central Bank and policymakers implement timely interventions to stabilize prices and manage inflation expectations. Future research should incorporate external economic factors for more robust long-term predictions.
},
 year = {2025}
}

Copy | Download

TY  - JOUR
T1  - Modelling and Forecasting Somalia's Consumer Price Index Using the ARIMA Model

AU  - Abdirashid Mohamed Hussein
AU  - Ahmed Hassan Abdillahi
Y1  - 2025/04/29
PY  - 2025
N1  - https://doi.org/10.11648/j.ajtas.20251402.14
DO  - 10.11648/j.ajtas.20251402.14
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 89
EP  - 98
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20251402.14
AB  - This study examines the modeling and forecasting of Somalia’s Consumer Price Index (CPI) using the ARIMA model, with data from November 2022 to November 2024. Descriptive analysis reveals a mean CPI of 144.26, moderate variability, and a slight negative skew. The CPI series is unstable in its original form but achieves stability after first differencing. The ARIMA (1,1,0) model is selected as the best fit, based on its low AIC and BIC values, with diagnostic checks confirming its effectiveness in capturing the data patterns. Forecasts suggest a stable CPI of approximately 152.95 from December 2024 to November 2026, though prediction intervals widen over time, reflecting increased uncertainty. The model performs well, with a Mean Absolute Percentage Error (MAPE) of 6.18%, though slight underestimation bias is noted. These findings demonstrate that ARIMA forecasts can aid policymakers in designing effective inflation control measures in volatile economies. These insights can help the Central Bank and policymakers implement timely interventions to stabilize prices and manage inflation expectations. Future research should incorporate external economic factors for more robust long-term predictions.

VL  - 14
IS  - 2
ER  -

Copy | Download