Application of Vector Autoregressive (VAR) Model on the Interaction of Inflation Rates and Public Debt in Kenya from 2011 to 2021

John Maina; Robert Muriungi; Harun Gitonga

doi:doi:10.11648/j.ajtas.20241304.12

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Application of Vector Autoregressive (VAR) Model on the Interaction of Inflation Rates and Public Debt in Kenya from 2011 to 2021

John Maina

, Robert Muriungi

, Harun Gitonga^*

Published in American Journal of Theoretical and Applied Statistics (Volume 13, Issue 4)

Received: 30 July 2024 Accepted: 10 August 2024 Published: 22 August 2024

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Abstract

This study examines the relationship between public debt and inflation rates in Kenya from 2011 to 2021 using the Vector Autoregressive (VAR) model. Despite the models likeAutoregressive Integrated Moving Average (ARIMA), Seasonal Autoregressive Integrated Moving Average (SARIMA), and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) gaining popularity in time series analysis, the Vector Autoregressive model, being multivariate, is relevant in analyzing two or more time series variables simultaneously, benefiting from the bi-directional causality and providing a better outlook into the flow of the dynamic interaction between inflation and public debt. The main objectives are modelling the Vector Autoregressive model and forecasting future trends to provide insights for policymakers. Additionally, the methodological approach comprises descriptive statistics, stationarity tests, normality tests, and the Vector Autoregressive model. Descriptive statistics reveal significant variations, with public debt increasing from 1.35 trillion KES to a peak of 8.2 trillion KES, and inflation rates ranging from 3.2% to 19.72% for the period from 2011 to 2021. The Augmented Dickey-Fuller (ADF) test confirmed that both time series were stationary at their levels. The Vector Autoregressive model, chosen for its ability to analyze dynamic interactions, indicated a significant relationship between the variables, with inflation showing strong self-persistence (coefficient of 0.8731, p < 2 × 10⁻¹⁶), though public debt did not significantly impact inflation in the model (p = 0.5592). The models R-squared values, 95.82% for public debt and 84.74% for inflation, highlight its strong explanatory power. Moreover, findings indicate that while public debt does not directly affect inflation within the model lag structure, inflation exhibits a strong self-persistence. The model R-squared values are 95.82% for public debt and 84.74% for inflation, demonstrating high explanatory power. Recommendations include the implementation of a robust debt management strategy, emphasizing sustainable borrowing and enhancing revenue generation to mitigate inflationary pressures. Further research is recommended to explore the broader macroeconomic impacts of public debt on economic growth and employment in Kenya.

Published in	American Journal of Theoretical and Applied Statistics (Volume 13, Issue 4)
DOI	10.11648/j.ajtas.20241304.12
Page(s)	73-79
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

Vector Autoregressive (VAR) Model, Public Debt, Inflation Rates

References

[1]	Volz, Ulrich, Shamshad Akhtar, Kevin P. Gallagher, Stephany Griffith-Jones, Jörg Haas, and Moritz Kraemer. “Debt relief for a green and inclusive recovery: Securing private-sector participation and creating policy space for sustainable development.” (2021).
[2]	Kithinji, Dr. Angela Mucece. “THE INFLUENCE of PUBLICDEBTonECONOMICGROWTHinKENYAN GOVERNMENT.” International Journal of Business Management and Economic Review 03, no. 01 (2020): 120-25. https://doi.org/10.35409/ijbmer.2020.3144
[3]	Akoto, Dickson. “The Relationship between Interest Rates and Inflation in Ghana and Their Impact on Economic Growth for the Period 2006-2019.” Journal of Finance and Economics 9, no. 1 (2021): 34-41.
[4]	Bonizzi, Bruno, Christina Laskaridis, and Jesse Griffiths. “Private Lending and Debt Risks of Low-Income Developing Countries.” www.econstor.eu, 2020. https://www.econstor.eu/handle/10419/233928
[5]	Roza, Afnita, Evony Silvino Violita, and Sherly Aktivani. “Study of inflation using stationary test with augmented dickey fuller & phillips-peron unit root test (Case in bukittinggi city inflation for 2014-2019).” EKSAKTA: Berkala Ilmiah Bidang MIPA 23, no. 02 (2022): 106- 116.
[6]	Krukovi, Borivoje D. “Central Bank Intervention in the Inflation Targeting.” Journal of Central Banking Theory and Practice 11, no. 1 (January 1, 2022): 67?85. https://doi.org/10.2478/jcbtp-2022-0003
[7]	Tobal, Martin, and Lorenzo Menna. “Monetary Policy and Financial Stability in Emerging Market Economies.” Latin American Journal of Central Banking 1, no. 1-4 (2020): 100017. https://doi.org/10.1016/j.latcb.2020.100017
[8]	Tiony, Obed Kipkemboi. “The Effects of Fiscal Policy Shocks on Aggregate Demand and Economic Growth in Kenya: A VAR Analysis.” Modern Economy 14, no. 8 (August 8, 2023): 1074-1107. https://doi.org/10.4236/me.2023.148056
[9]	Maroa, Simon. “Does Government Borrowing Affect the Supply of Private-sector Credit? A Kenyan Experience.” PhD diss., University of Nairobi, 2022.
[10]	Schwan, Michael, Christine Trampusch, and Florian Fastenrath. “Financialization Of, Not by the State. Exploring Changes in the Management of Public Debt and Assets across Europe.” Review of International Political Economy, September 18, 2020, 1-23. https://doi.org/10.1080/09692290.2020.1823452
[11]	Olamide, Ebenezer, Andrew Maredza, and Kanayo Ogujiuba. “Monetary Policy, External Shocks and Economic Growth Dynamics in East Africa: An S-VAR Model.” Sustainability 14, no. 6 (March 16, 2022): 3490. https://doi.org/10.3390/su14063490
[12]	Li, Huajun, and Si Liu. “Higher Education, Technological Innovation, and Regional Sustainable Development: Insights from a VAR Model.” Discrete Dynamics in Nature and Society 2021 (September 20, 2021): 1-15. https://doi.org/10.1155/2021/8434528
[13]	Liu, Yong, Haixu Wu, Jianmin Wang, and Mingsheng Long. “Non-stationary transformers: Exploring the stationarity in time series forecasting.” Advances in Neural Information Processing Systems 35 (2022): 9881- 9893.
[14]	Ajewole, K. P., S. O. Adejuwon, and V. G. Jemilohun. “Test for stationarity on inflation rates in Nigeria using augmented dickey fuller test and Phillips-persons test.” J. Math 16, no. 2020 (2020): 11-14.
[15]	Joshua Wafula and Dr. Chesoli. “IMPACT of PUBLIC DEBT on ECONOMIC GROWTH in the PUBLIC SECTOR in KENYA: A CRITICAL REVIEW of LITERATURE.” EPH - International Journal of Business & Management Science 6, no. 4 (December 27, 2020): 8-21. https://doi.org/10.53555/eijbms.v6i4.108
[16]	Mawejje, Joseph, and Nicholas M. Odhiambo. “The Dynamics of Fiscal Deficits in Kenya: A Review of Reforms, Trends, and Determinants.” African Journal of Business and Economic Research 15, no. 2 (June 10, 2020): 27-44. https://doi.org/10.31920/1750- 4562/2020/v15n2a2
[17]	Njoroge, Liston. “Impact of Kenya’s public debt on economic stability.” PhD diss., Walden University, 2020.
[18]	Koech, Lily. “RELATIONSHIP between BUDGET FINANCING and ECONOMIC GROWTH in KENYA”, 2023. https://repository.kcau.ac.ke/bitstream/handle/123456789/1481/Koech%2CRelationship%20Between%20Budget%20Financing%20And%20Economic%20Growth%20in%20Kenya.pdf?sequence=1&isAllowed=y

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APA Style

Maina, J., Muriungi, R., Gitonga, H. (2024). Application of Vector Autoregressive (VAR) Model on the Interaction of Inflation Rates and Public Debt in Kenya from 2011 to 2021. American Journal of Theoretical and Applied Statistics, 13(4), 73-79. https://doi.org/10.11648/j.ajtas.20241304.12

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ACS Style

Maina, J.; Muriungi, R.; Gitonga, H. Application of Vector Autoregressive (VAR) Model on the Interaction of Inflation Rates and Public Debt in Kenya from 2011 to 2021. Am. J. Theor. Appl. Stat. 2024, 13(4), 73-79. doi: 10.11648/j.ajtas.20241304.12

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AMA Style

Maina J, Muriungi R, Gitonga H. Application of Vector Autoregressive (VAR) Model on the Interaction of Inflation Rates and Public Debt in Kenya from 2011 to 2021. Am J Theor Appl Stat. 2024;13(4):73-79. doi: 10.11648/j.ajtas.20241304.12

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@article{10.11648/j.ajtas.20241304.12,
  author = {John Maina and Robert Muriungi and Harun Gitonga},
  title = {Application of Vector Autoregressive (VAR) Model on the Interaction of Inflation Rates and Public Debt in Kenya from 2011 to 2021},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {13},
  number = {4},
  pages = {73-79},
  doi = {10.11648/j.ajtas.20241304.12},
  url = {https://doi.org/10.11648/j.ajtas.20241304.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20241304.12},
  abstract = {This study examines the relationship between public debt and inflation rates in Kenya from 2011 to 2021 using the Vector Autoregressive (VAR) model. Despite the models likeAutoregressive Integrated Moving Average (ARIMA), Seasonal Autoregressive Integrated Moving Average (SARIMA), and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) gaining popularity in time series analysis, the Vector Autoregressive model, being multivariate, is relevant in analyzing two or more time series variables simultaneously, benefiting from the bi-directional causality and providing a better outlook into the flow of the dynamic interaction between inflation and public debt. The main objectives are modelling the Vector Autoregressive model and forecasting future trends to provide insights for policymakers. Additionally, the methodological approach comprises descriptive statistics, stationarity tests, normality tests, and the Vector Autoregressive model. Descriptive statistics reveal significant variations, with public debt increasing from 1.35 trillion KES to a peak of 8.2 trillion KES, and inflation rates ranging from 3.2% to 19.72% for the period from 2011 to 2021. The Augmented Dickey-Fuller (ADF) test confirmed that both time series were stationary at their levels. The Vector Autoregressive model, chosen for its ability to analyze dynamic interactions, indicated a significant relationship between the variables, with inflation showing strong self-persistence (coefficient of 0.8731, p −16), though public debt did not significantly impact inflation in the model (p = 0.5592). The models R-squared values, 95.82% for public debt and 84.74% for inflation, highlight its strong explanatory power. Moreover, findings indicate that while public debt does not directly affect inflation within the model lag structure, inflation exhibits a strong self-persistence. The model R-squared values are 95.82% for public debt and 84.74% for inflation, demonstrating high explanatory power. Recommendations include the implementation of a robust debt management strategy, emphasizing sustainable borrowing and enhancing revenue generation to mitigate inflationary pressures. Further research is recommended to explore the broader macroeconomic impacts of public debt on economic growth and employment in Kenya.},
 year = {2024}
}

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TY  - JOUR
T1  - Application of Vector Autoregressive (VAR) Model on the Interaction of Inflation Rates and Public Debt in Kenya from 2011 to 2021
AU  - John Maina
AU  - Robert Muriungi
AU  - Harun Gitonga
Y1  - 2024/08/22
PY  - 2024
N1  - https://doi.org/10.11648/j.ajtas.20241304.12
DO  - 10.11648/j.ajtas.20241304.12
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  - 73
EP  - 79
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20241304.12
AB  - This study examines the relationship between public debt and inflation rates in Kenya from 2011 to 2021 using the Vector Autoregressive (VAR) model. Despite the models likeAutoregressive Integrated Moving Average (ARIMA), Seasonal Autoregressive Integrated Moving Average (SARIMA), and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) gaining popularity in time series analysis, the Vector Autoregressive model, being multivariate, is relevant in analyzing two or more time series variables simultaneously, benefiting from the bi-directional causality and providing a better outlook into the flow of the dynamic interaction between inflation and public debt. The main objectives are modelling the Vector Autoregressive model and forecasting future trends to provide insights for policymakers. Additionally, the methodological approach comprises descriptive statistics, stationarity tests, normality tests, and the Vector Autoregressive model. Descriptive statistics reveal significant variations, with public debt increasing from 1.35 trillion KES to a peak of 8.2 trillion KES, and inflation rates ranging from 3.2% to 19.72% for the period from 2011 to 2021. The Augmented Dickey-Fuller (ADF) test confirmed that both time series were stationary at their levels. The Vector Autoregressive model, chosen for its ability to analyze dynamic interactions, indicated a significant relationship between the variables, with inflation showing strong self-persistence (coefficient of 0.8731, p −16), though public debt did not significantly impact inflation in the model (p = 0.5592). The models R-squared values, 95.82% for public debt and 84.74% for inflation, highlight its strong explanatory power. Moreover, findings indicate that while public debt does not directly affect inflation within the model lag structure, inflation exhibits a strong self-persistence. The model R-squared values are 95.82% for public debt and 84.74% for inflation, demonstrating high explanatory power. Recommendations include the implementation of a robust debt management strategy, emphasizing sustainable borrowing and enhancing revenue generation to mitigate inflationary pressures. Further research is recommended to explore the broader macroeconomic impacts of public debt on economic growth and employment in Kenya.
VL  - 13
IS  - 4
ER  -

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Author Information

John Maina

Department of Pure and Applied Sciences, Kirinyaga University, Nairobi, Kenya

Contact Email

http://orcid.org/0009-0008-2109-2916
Robert Muriungi

Department of Pure Mathematics, Meru University of Science and Technology, Nairobi, Kenya

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http://orcid.org/0009-0007-0972-5971
Harun Gitonga

Department of Pure Mathematics, Meru University of Science and Technology, Nairobi, Kenya

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http://orcid.org/0000-0003-3572-719X

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APA Style

Maina, J., Muriungi, R., Gitonga, H. (2024). Application of Vector Autoregressive (VAR) Model on the Interaction of Inflation Rates and Public Debt in Kenya from 2011 to 2021. American Journal of Theoretical and Applied Statistics, 13(4), 73-79. https://doi.org/10.11648/j.ajtas.20241304.12

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ACS Style

Maina, J.; Muriungi, R.; Gitonga, H. Application of Vector Autoregressive (VAR) Model on the Interaction of Inflation Rates and Public Debt in Kenya from 2011 to 2021. Am. J. Theor. Appl. Stat. 2024, 13(4), 73-79. doi: 10.11648/j.ajtas.20241304.12

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AMA Style

Maina J, Muriungi R, Gitonga H. Application of Vector Autoregressive (VAR) Model on the Interaction of Inflation Rates and Public Debt in Kenya from 2011 to 2021. Am J Theor Appl Stat. 2024;13(4):73-79. doi: 10.11648/j.ajtas.20241304.12

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@article{10.11648/j.ajtas.20241304.12,
  author = {John Maina and Robert Muriungi and Harun Gitonga},
  title = {Application of Vector Autoregressive (VAR) Model on the Interaction of Inflation Rates and Public Debt in Kenya from 2011 to 2021},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {13},
  number = {4},
  pages = {73-79},
  doi = {10.11648/j.ajtas.20241304.12},
  url = {https://doi.org/10.11648/j.ajtas.20241304.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20241304.12},
  abstract = {This study examines the relationship between public debt and inflation rates in Kenya from 2011 to 2021 using the Vector Autoregressive (VAR) model. Despite the models likeAutoregressive Integrated Moving Average (ARIMA), Seasonal Autoregressive Integrated Moving Average (SARIMA), and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) gaining popularity in time series analysis, the Vector Autoregressive model, being multivariate, is relevant in analyzing two or more time series variables simultaneously, benefiting from the bi-directional causality and providing a better outlook into the flow of the dynamic interaction between inflation and public debt. The main objectives are modelling the Vector Autoregressive model and forecasting future trends to provide insights for policymakers. Additionally, the methodological approach comprises descriptive statistics, stationarity tests, normality tests, and the Vector Autoregressive model. Descriptive statistics reveal significant variations, with public debt increasing from 1.35 trillion KES to a peak of 8.2 trillion KES, and inflation rates ranging from 3.2% to 19.72% for the period from 2011 to 2021. The Augmented Dickey-Fuller (ADF) test confirmed that both time series were stationary at their levels. The Vector Autoregressive model, chosen for its ability to analyze dynamic interactions, indicated a significant relationship between the variables, with inflation showing strong self-persistence (coefficient of 0.8731, p −16), though public debt did not significantly impact inflation in the model (p = 0.5592). The models R-squared values, 95.82% for public debt and 84.74% for inflation, highlight its strong explanatory power. Moreover, findings indicate that while public debt does not directly affect inflation within the model lag structure, inflation exhibits a strong self-persistence. The model R-squared values are 95.82% for public debt and 84.74% for inflation, demonstrating high explanatory power. Recommendations include the implementation of a robust debt management strategy, emphasizing sustainable borrowing and enhancing revenue generation to mitigate inflationary pressures. Further research is recommended to explore the broader macroeconomic impacts of public debt on economic growth and employment in Kenya.},
 year = {2024}
}

Copy | Download

TY  - JOUR
T1  - Application of Vector Autoregressive (VAR) Model on the Interaction of Inflation Rates and Public Debt in Kenya from 2011 to 2021
AU  - John Maina
AU  - Robert Muriungi
AU  - Harun Gitonga
Y1  - 2024/08/22
PY  - 2024
N1  - https://doi.org/10.11648/j.ajtas.20241304.12
DO  - 10.11648/j.ajtas.20241304.12
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  - 73
EP  - 79
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20241304.12
AB  - This study examines the relationship between public debt and inflation rates in Kenya from 2011 to 2021 using the Vector Autoregressive (VAR) model. Despite the models likeAutoregressive Integrated Moving Average (ARIMA), Seasonal Autoregressive Integrated Moving Average (SARIMA), and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) gaining popularity in time series analysis, the Vector Autoregressive model, being multivariate, is relevant in analyzing two or more time series variables simultaneously, benefiting from the bi-directional causality and providing a better outlook into the flow of the dynamic interaction between inflation and public debt. The main objectives are modelling the Vector Autoregressive model and forecasting future trends to provide insights for policymakers. Additionally, the methodological approach comprises descriptive statistics, stationarity tests, normality tests, and the Vector Autoregressive model. Descriptive statistics reveal significant variations, with public debt increasing from 1.35 trillion KES to a peak of 8.2 trillion KES, and inflation rates ranging from 3.2% to 19.72% for the period from 2011 to 2021. The Augmented Dickey-Fuller (ADF) test confirmed that both time series were stationary at their levels. The Vector Autoregressive model, chosen for its ability to analyze dynamic interactions, indicated a significant relationship between the variables, with inflation showing strong self-persistence (coefficient of 0.8731, p −16), though public debt did not significantly impact inflation in the model (p = 0.5592). The models R-squared values, 95.82% for public debt and 84.74% for inflation, highlight its strong explanatory power. Moreover, findings indicate that while public debt does not directly affect inflation within the model lag structure, inflation exhibits a strong self-persistence. The model R-squared values are 95.82% for public debt and 84.74% for inflation, demonstrating high explanatory power. Recommendations include the implementation of a robust debt management strategy, emphasizing sustainable borrowing and enhancing revenue generation to mitigate inflationary pressures. Further research is recommended to explore the broader macroeconomic impacts of public debt on economic growth and employment in Kenya.
VL  - 13
IS  - 4
ER  -

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