Time Series Analysis of Monthly Internally Generated Revenue in Hulbarag Woreda, Silte Zone, Central Ethiopia

Shambel Selman Abdo

doi:doi:10.11648/j.scif.20250101.12

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Time Series Analysis of Monthly Internally Generated Revenue in Hulbarag Woreda, Silte Zone, Central Ethiopia

Shambel Selman Abdo^*

Published in Science Futures (Volume 1, Issue 1)

Received: 29 September 2025 Accepted: 13 October 2025 Published: 8 December 2025

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Abstract

The effective mobilization of internal revenue is crucial for sustaining local government operations and supporting development initiatives. This study aimed to analyze the dynamics of monthly internally generated revenue (MIGR) in Hulbarag Woreda, Silte Zone, over the period 2008-2023, with a focus on trend, volatility, seasonality, and forecasting. The study utilized secondary data obtained from Hulbarag Woreda Finance and Economic Development Office, encompassing monthly revenue collections across direct taxes, indirect taxes, non-tax revenue, and municipality fees. Data preparation included log transformation and differencing to address non-stationarity, confirmed through Augmented Dickey-Fuller (ADF) and KPSS tests. Time series modeling was performed using ARIMA for mean dynamics and GARCH (1, 1) for conditional variance, allowing the identification of volatility clustering and predictive forecasting. The results indicate a consistent upward trend in revenue, with June recording the highest collections and August the lowest. Direct taxes contributed the largest share (52.66%), followed by non-tax revenue (17.37%), indirect taxes (16.25%), and municipality revenue (13.71%). The GARCH (1, 1) model demonstrated strong volatility persistence (α + β = 0.91) and effectively forecasted a total revenue of 164,902,287 ETB for 2023/2024, exceeding planned projections by 47,737,198 ETB. These findings highlight the potential of advanced time series models in guiding fiscal planning, resource allocation, and budget optimization. The study is limited by its reliance on secondary administrative data and its focus on a single woreda, which may affect generalizability. Future research could incorporate socio-economic and macroeconomic factors and extend the analysis to multiple woredas to enhance predictive accuracy and policy relevance.

Published in	Science Futures (Volume 1, Issue 1)
DOI	10.11648/j.scif.20250101.12
Page(s)	9-20
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

Internally Generated Revenue, Time Series Analysis, ARIMA-GARCH Modeling, Revenue Volatility and Fiscal Forecasting

References

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[7]	Engle, R. F. (2001). GARCH 101: The use of ARCH/GARCH models in applied econometrics. Journal of Economic Perspectives, 15(4), 157-168.
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[10]	Hansen, P. R., & Lunde, A. (2021). Forecasting volatility in financial markets. Annual Review of Financial Economics, 13, 213-236.
[11]	Hyndman, R. J., & Athanasopoulos, G. (2021). Forecasting: Principles and practice (3rd ed.). OTexts. https://otexts.com/fpp3/
[12]	IMF. (2023). Revenue administration: Performance and measurement. International Monetary Fund.
[13]	Jarque, C. M., & Bera, A. K. (1980). Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economics Letters, 6(3), 255-259.
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[18]	Wang, Y., Chen, H., & Zhao, Y. (2023). Advances in volatility modeling: A review of GARCH-type models. Economic Modelling, 123, 106-120.
[19]	World Bank. (2019). Municipal finance in Ethiopia: Strengthening revenue mobilization and local service delivery. Washington, DC: World Bank.
[20]	HWARDO. (2013). Hulbarag Woreda Administration and Rural Development Office.

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Abdo, S. S. (2025). Time Series Analysis of Monthly Internally Generated Revenue in Hulbarag Woreda, Silte Zone, Central Ethiopia. Science Futures, 1(1), 9-20. https://doi.org/10.11648/j.scif.20250101.12

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ACS Style

Abdo, S. S. Time Series Analysis of Monthly Internally Generated Revenue in Hulbarag Woreda, Silte Zone, Central Ethiopia. Sci. Futures 2025, 1(1), 9-20. doi: 10.11648/j.scif.20250101.12

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AMA Style

Abdo SS. Time Series Analysis of Monthly Internally Generated Revenue in Hulbarag Woreda, Silte Zone, Central Ethiopia. Sci Futures. 2025;1(1):9-20. doi: 10.11648/j.scif.20250101.12

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@article{10.11648/j.scif.20250101.12,
  author = {Shambel Selman Abdo},
  title = {Time Series Analysis of Monthly Internally Generated Revenue in Hulbarag Woreda, Silte Zone, Central Ethiopia},
  journal = {Science Futures},
  volume = {1},
  number = {1},
  pages = {9-20},
  doi = {10.11648/j.scif.20250101.12},
  url = {https://doi.org/10.11648/j.scif.20250101.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.scif.20250101.12},
  abstract = {The effective mobilization of internal revenue is crucial for sustaining local government operations and supporting development initiatives. This study aimed to analyze the dynamics of monthly internally generated revenue (MIGR) in Hulbarag Woreda, Silte Zone, over the period 2008-2023, with a focus on trend, volatility, seasonality, and forecasting. The study utilized secondary data obtained from Hulbarag Woreda Finance and Economic Development Office, encompassing monthly revenue collections across direct taxes, indirect taxes, non-tax revenue, and municipality fees. Data preparation included log transformation and differencing to address non-stationarity, confirmed through Augmented Dickey-Fuller (ADF) and KPSS tests. Time series modeling was performed using ARIMA for mean dynamics and GARCH (1, 1) for conditional variance, allowing the identification of volatility clustering and predictive forecasting. The results indicate a consistent upward trend in revenue, with June recording the highest collections and August the lowest. Direct taxes contributed the largest share (52.66%), followed by non-tax revenue (17.37%), indirect taxes (16.25%), and municipality revenue (13.71%). The GARCH (1, 1) model demonstrated strong volatility persistence (α + β = 0.91) and effectively forecasted a total revenue of 164,902,287 ETB for 2023/2024, exceeding planned projections by 47,737,198 ETB. These findings highlight the potential of advanced time series models in guiding fiscal planning, resource allocation, and budget optimization. The study is limited by its reliance on secondary administrative data and its focus on a single woreda, which may affect generalizability. Future research could incorporate socio-economic and macroeconomic factors and extend the analysis to multiple woredas to enhance predictive accuracy and policy relevance.},
 year = {2025}
}

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TY  - JOUR
T1  - Time Series Analysis of Monthly Internally Generated Revenue in Hulbarag Woreda, Silte Zone, Central Ethiopia
AU  - Shambel Selman Abdo
Y1  - 2025/12/08
PY  - 2025
N1  - https://doi.org/10.11648/j.scif.20250101.12
DO  - 10.11648/j.scif.20250101.12
T2  - Science Futures
JF  - Science Futures
JO  - Science Futures
SP  - 9
EP  - 20
PB  - Science Publishing Group
UR  - https://doi.org/10.11648/j.scif.20250101.12
AB  - The effective mobilization of internal revenue is crucial for sustaining local government operations and supporting development initiatives. This study aimed to analyze the dynamics of monthly internally generated revenue (MIGR) in Hulbarag Woreda, Silte Zone, over the period 2008-2023, with a focus on trend, volatility, seasonality, and forecasting. The study utilized secondary data obtained from Hulbarag Woreda Finance and Economic Development Office, encompassing monthly revenue collections across direct taxes, indirect taxes, non-tax revenue, and municipality fees. Data preparation included log transformation and differencing to address non-stationarity, confirmed through Augmented Dickey-Fuller (ADF) and KPSS tests. Time series modeling was performed using ARIMA for mean dynamics and GARCH (1, 1) for conditional variance, allowing the identification of volatility clustering and predictive forecasting. The results indicate a consistent upward trend in revenue, with June recording the highest collections and August the lowest. Direct taxes contributed the largest share (52.66%), followed by non-tax revenue (17.37%), indirect taxes (16.25%), and municipality revenue (13.71%). The GARCH (1, 1) model demonstrated strong volatility persistence (α + β = 0.91) and effectively forecasted a total revenue of 164,902,287 ETB for 2023/2024, exceeding planned projections by 47,737,198 ETB. These findings highlight the potential of advanced time series models in guiding fiscal planning, resource allocation, and budget optimization. The study is limited by its reliance on secondary administrative data and its focus on a single woreda, which may affect generalizability. Future research could incorporate socio-economic and macroeconomic factors and extend the analysis to multiple woredas to enhance predictive accuracy and policy relevance.
VL  - 1
IS  - 1
ER  -

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Author Information

Shambel Selman Abdo

Department of Statistics, Wachemo University, Hossana, Ethiopia

Contact Email

http://orcid.org/0009-0007-8128-6811

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APA Style

Abdo, S. S. (2025). Time Series Analysis of Monthly Internally Generated Revenue in Hulbarag Woreda, Silte Zone, Central Ethiopia. Science Futures, 1(1), 9-20. https://doi.org/10.11648/j.scif.20250101.12

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ACS Style

Abdo, S. S. Time Series Analysis of Monthly Internally Generated Revenue in Hulbarag Woreda, Silte Zone, Central Ethiopia. Sci. Futures 2025, 1(1), 9-20. doi: 10.11648/j.scif.20250101.12

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AMA Style

Abdo SS. Time Series Analysis of Monthly Internally Generated Revenue in Hulbarag Woreda, Silte Zone, Central Ethiopia. Sci Futures. 2025;1(1):9-20. doi: 10.11648/j.scif.20250101.12

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@article{10.11648/j.scif.20250101.12,
  author = {Shambel Selman Abdo},
  title = {Time Series Analysis of Monthly Internally Generated Revenue in Hulbarag Woreda, Silte Zone, Central Ethiopia},
  journal = {Science Futures},
  volume = {1},
  number = {1},
  pages = {9-20},
  doi = {10.11648/j.scif.20250101.12},
  url = {https://doi.org/10.11648/j.scif.20250101.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.scif.20250101.12},
  abstract = {The effective mobilization of internal revenue is crucial for sustaining local government operations and supporting development initiatives. This study aimed to analyze the dynamics of monthly internally generated revenue (MIGR) in Hulbarag Woreda, Silte Zone, over the period 2008-2023, with a focus on trend, volatility, seasonality, and forecasting. The study utilized secondary data obtained from Hulbarag Woreda Finance and Economic Development Office, encompassing monthly revenue collections across direct taxes, indirect taxes, non-tax revenue, and municipality fees. Data preparation included log transformation and differencing to address non-stationarity, confirmed through Augmented Dickey-Fuller (ADF) and KPSS tests. Time series modeling was performed using ARIMA for mean dynamics and GARCH (1, 1) for conditional variance, allowing the identification of volatility clustering and predictive forecasting. The results indicate a consistent upward trend in revenue, with June recording the highest collections and August the lowest. Direct taxes contributed the largest share (52.66%), followed by non-tax revenue (17.37%), indirect taxes (16.25%), and municipality revenue (13.71%). The GARCH (1, 1) model demonstrated strong volatility persistence (α + β = 0.91) and effectively forecasted a total revenue of 164,902,287 ETB for 2023/2024, exceeding planned projections by 47,737,198 ETB. These findings highlight the potential of advanced time series models in guiding fiscal planning, resource allocation, and budget optimization. The study is limited by its reliance on secondary administrative data and its focus on a single woreda, which may affect generalizability. Future research could incorporate socio-economic and macroeconomic factors and extend the analysis to multiple woredas to enhance predictive accuracy and policy relevance.},
 year = {2025}
}

Copy | Download

TY  - JOUR
T1  - Time Series Analysis of Monthly Internally Generated Revenue in Hulbarag Woreda, Silte Zone, Central Ethiopia
AU  - Shambel Selman Abdo
Y1  - 2025/12/08
PY  - 2025
N1  - https://doi.org/10.11648/j.scif.20250101.12
DO  - 10.11648/j.scif.20250101.12
T2  - Science Futures
JF  - Science Futures
JO  - Science Futures
SP  - 9
EP  - 20
PB  - Science Publishing Group
UR  - https://doi.org/10.11648/j.scif.20250101.12
AB  - The effective mobilization of internal revenue is crucial for sustaining local government operations and supporting development initiatives. This study aimed to analyze the dynamics of monthly internally generated revenue (MIGR) in Hulbarag Woreda, Silte Zone, over the period 2008-2023, with a focus on trend, volatility, seasonality, and forecasting. The study utilized secondary data obtained from Hulbarag Woreda Finance and Economic Development Office, encompassing monthly revenue collections across direct taxes, indirect taxes, non-tax revenue, and municipality fees. Data preparation included log transformation and differencing to address non-stationarity, confirmed through Augmented Dickey-Fuller (ADF) and KPSS tests. Time series modeling was performed using ARIMA for mean dynamics and GARCH (1, 1) for conditional variance, allowing the identification of volatility clustering and predictive forecasting. The results indicate a consistent upward trend in revenue, with June recording the highest collections and August the lowest. Direct taxes contributed the largest share (52.66%), followed by non-tax revenue (17.37%), indirect taxes (16.25%), and municipality revenue (13.71%). The GARCH (1, 1) model demonstrated strong volatility persistence (α + β = 0.91) and effectively forecasted a total revenue of 164,902,287 ETB for 2023/2024, exceeding planned projections by 47,737,198 ETB. These findings highlight the potential of advanced time series models in guiding fiscal planning, resource allocation, and budget optimization. The study is limited by its reliance on secondary administrative data and its focus on a single woreda, which may affect generalizability. Future research could incorporate socio-economic and macroeconomic factors and extend the analysis to multiple woredas to enhance predictive accuracy and policy relevance.
VL  - 1
IS  - 1
ER  -

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