Modelling the Relationship Between Merchandise Trade Flows and Some Macroeconomic Variables in Ghana

Azebre Abu Ibrahim; Anuwoje Ida Logubayom Abonongo

doi:doi:10.11648/j.ajtas.20241305.15

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Modelling the Relationship Between Merchandise Trade Flows and Some Macroeconomic Variables in Ghana

Azebre Abu Ibrahim^*

, Anuwoje Ida Logubayom Abonongo

Published in American Journal of Theoretical and Applied Statistics (Volume 13, Issue 5)

Received: 2 September 2024 Accepted: 25 September 2024 Published: 29 October 2024

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Abstract

Macroeconomic variables serve as economic indicators that offer valuable insights into the overall health and stability of an economy. Changes in these variables can have significant impacts on a country's trade balance and overall economic performance. This study employed multivariate time series analysis to study the relationship between Merchandise Trade Flows (MTF), Monetary Policy Rate (MPR), Commercial Lending Rate (CLR), Nominal Growth Rate (NGR) and Consumer Price Index (CPI) with Money Supply (MoS) as exogenous variable. The nature of trend in each series was investigated. The results revealed that quadratic trend model best models MTF, MPR, CLR and NGR whiles an exponential trend best models CPI. Johansen’s co-integration test with unrestricted trend performed revealed the existence of long-run equilibrium relationships between the variables and three (3) co-integrating equations described this long-run relationship. In terms of short-run relationships, the VEC (2) model revealed that, CLR, NGR, MoS have positive and significant impact on MTF. CLR, NGR and MoS have positive and significant impact on MPR, NGR have positive and significant impact on CLR, CPI and MoS have significant impact on NGR whiles NGR and MoS have significant impact on CPI. Model diagnostics performed on the VEC (2) model showed that, all the model parameters are structurally stable over time and the residuals of the individual models are free from serial correlation and conditional heteroscedasticity. Forecast error variance decomposition (FEVD) analysis showed that each variable primarily explained its own variance and the influence of other variables increase over time. Hence, adopting a broad perspective on macroeconomic variables can help policymakers anticipate and mitigate ripple effects across various economic sectors.

Published in	American Journal of Theoretical and Applied Statistics (Volume 13, Issue 5)
DOI	10.11648/j.ajtas.20241305.15
Page(s)	157-174
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

Macroeconomic Variables, Merchandise Trade Flows, Co-Integration

References

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APA Style

Ibrahim, A. A., Abonongo, A. I. L. (2024). Modelling the Relationship Between Merchandise Trade Flows and Some Macroeconomic Variables in Ghana. American Journal of Theoretical and Applied Statistics, 13(5), 157-174. https://doi.org/10.11648/j.ajtas.20241305.15

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ACS Style

Ibrahim, A. A.; Abonongo, A. I. L. Modelling the Relationship Between Merchandise Trade Flows and Some Macroeconomic Variables in Ghana. Am. J. Theor. Appl. Stat. 2024, 13(5), 157-174. doi: 10.11648/j.ajtas.20241305.15

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AMA Style

Ibrahim AA, Abonongo AIL. Modelling the Relationship Between Merchandise Trade Flows and Some Macroeconomic Variables in Ghana. Am J Theor Appl Stat. 2024;13(5):157-174. doi: 10.11648/j.ajtas.20241305.15

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@article{10.11648/j.ajtas.20241305.15,
  author = {Azebre Abu Ibrahim and Anuwoje Ida Logubayom Abonongo},
  title = {Modelling the Relationship Between Merchandise Trade Flows and Some Macroeconomic Variables in Ghana
},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {13},
  number = {5},
  pages = {157-174},
  doi = {10.11648/j.ajtas.20241305.15},
  url = {https://doi.org/10.11648/j.ajtas.20241305.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20241305.15},
  abstract = {Macroeconomic variables serve as economic indicators that offer valuable insights into the overall health and stability of an economy. Changes in these variables can have significant impacts on a country's trade balance and overall economic performance. This study employed multivariate time series analysis to study the relationship between Merchandise Trade Flows (MTF), Monetary Policy Rate (MPR), Commercial Lending Rate (CLR), Nominal Growth Rate (NGR) and Consumer Price Index (CPI) with Money Supply (MoS) as exogenous variable. The nature of trend in each series was investigated. The results revealed that quadratic trend model best models MTF, MPR, CLR and NGR whiles an exponential trend best models CPI. Johansen’s co-integration test with unrestricted trend performed revealed the existence of long-run equilibrium relationships between the variables and three (3) co-integrating equations described this long-run relationship. In terms of short-run relationships, the VEC (2) model revealed that, CLR, NGR, MoS have positive and significant impact on MTF. CLR, NGR and MoS have positive and significant impact on MPR, NGR have positive and significant impact on CLR, CPI and MoS have significant impact on NGR whiles NGR and MoS have significant impact on CPI. Model diagnostics performed on the VEC (2) model showed that, all the model parameters are structurally stable over time and the residuals of the individual models are free from serial correlation and conditional heteroscedasticity. Forecast error variance decomposition (FEVD) analysis showed that each variable primarily explained its own variance and the influence of other variables increase over time. Hence, adopting a broad perspective on macroeconomic variables can help policymakers anticipate and mitigate ripple effects across various economic sectors.
},
 year = {2024}
}

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TY  - JOUR
T1  - Modelling the Relationship Between Merchandise Trade Flows and Some Macroeconomic Variables in Ghana

AU  - Azebre Abu Ibrahim
AU  - Anuwoje Ida Logubayom Abonongo
Y1  - 2024/10/29
PY  - 2024
N1  - https://doi.org/10.11648/j.ajtas.20241305.15
DO  - 10.11648/j.ajtas.20241305.15
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  - 157
EP  - 174
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20241305.15
AB  - Macroeconomic variables serve as economic indicators that offer valuable insights into the overall health and stability of an economy. Changes in these variables can have significant impacts on a country's trade balance and overall economic performance. This study employed multivariate time series analysis to study the relationship between Merchandise Trade Flows (MTF), Monetary Policy Rate (MPR), Commercial Lending Rate (CLR), Nominal Growth Rate (NGR) and Consumer Price Index (CPI) with Money Supply (MoS) as exogenous variable. The nature of trend in each series was investigated. The results revealed that quadratic trend model best models MTF, MPR, CLR and NGR whiles an exponential trend best models CPI. Johansen’s co-integration test with unrestricted trend performed revealed the existence of long-run equilibrium relationships between the variables and three (3) co-integrating equations described this long-run relationship. In terms of short-run relationships, the VEC (2) model revealed that, CLR, NGR, MoS have positive and significant impact on MTF. CLR, NGR and MoS have positive and significant impact on MPR, NGR have positive and significant impact on CLR, CPI and MoS have significant impact on NGR whiles NGR and MoS have significant impact on CPI. Model diagnostics performed on the VEC (2) model showed that, all the model parameters are structurally stable over time and the residuals of the individual models are free from serial correlation and conditional heteroscedasticity. Forecast error variance decomposition (FEVD) analysis showed that each variable primarily explained its own variance and the influence of other variables increase over time. Hence, adopting a broad perspective on macroeconomic variables can help policymakers anticipate and mitigate ripple effects across various economic sectors.

VL  - 13
IS  - 5
ER  -

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Author Information

Azebre Abu Ibrahim

Department of Statistics and Actuarial Science, School of Mathematical Sciences, C. K. Tedam University of Technology and Applied Sciences, Navrongo, Ghana

Contact Email

http://orcid.org/0009-0001-8225-0630
Anuwoje Ida Logubayom Abonongo

Department of Statistics and Actuarial Science, School of Mathematical Sciences, C. K. Tedam University of Technology and Applied Sciences, Navrongo, Ghana

http://orcid.org/0009-0001-6783-8073

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APA Style

Ibrahim, A. A., Abonongo, A. I. L. (2024). Modelling the Relationship Between Merchandise Trade Flows and Some Macroeconomic Variables in Ghana. American Journal of Theoretical and Applied Statistics, 13(5), 157-174. https://doi.org/10.11648/j.ajtas.20241305.15

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ACS Style

Ibrahim, A. A.; Abonongo, A. I. L. Modelling the Relationship Between Merchandise Trade Flows and Some Macroeconomic Variables in Ghana. Am. J. Theor. Appl. Stat. 2024, 13(5), 157-174. doi: 10.11648/j.ajtas.20241305.15

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AMA Style

Ibrahim AA, Abonongo AIL. Modelling the Relationship Between Merchandise Trade Flows and Some Macroeconomic Variables in Ghana. Am J Theor Appl Stat. 2024;13(5):157-174. doi: 10.11648/j.ajtas.20241305.15

Copy | Download

@article{10.11648/j.ajtas.20241305.15,
  author = {Azebre Abu Ibrahim and Anuwoje Ida Logubayom Abonongo},
  title = {Modelling the Relationship Between Merchandise Trade Flows and Some Macroeconomic Variables in Ghana
},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {13},
  number = {5},
  pages = {157-174},
  doi = {10.11648/j.ajtas.20241305.15},
  url = {https://doi.org/10.11648/j.ajtas.20241305.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20241305.15},
  abstract = {Macroeconomic variables serve as economic indicators that offer valuable insights into the overall health and stability of an economy. Changes in these variables can have significant impacts on a country's trade balance and overall economic performance. This study employed multivariate time series analysis to study the relationship between Merchandise Trade Flows (MTF), Monetary Policy Rate (MPR), Commercial Lending Rate (CLR), Nominal Growth Rate (NGR) and Consumer Price Index (CPI) with Money Supply (MoS) as exogenous variable. The nature of trend in each series was investigated. The results revealed that quadratic trend model best models MTF, MPR, CLR and NGR whiles an exponential trend best models CPI. Johansen’s co-integration test with unrestricted trend performed revealed the existence of long-run equilibrium relationships between the variables and three (3) co-integrating equations described this long-run relationship. In terms of short-run relationships, the VEC (2) model revealed that, CLR, NGR, MoS have positive and significant impact on MTF. CLR, NGR and MoS have positive and significant impact on MPR, NGR have positive and significant impact on CLR, CPI and MoS have significant impact on NGR whiles NGR and MoS have significant impact on CPI. Model diagnostics performed on the VEC (2) model showed that, all the model parameters are structurally stable over time and the residuals of the individual models are free from serial correlation and conditional heteroscedasticity. Forecast error variance decomposition (FEVD) analysis showed that each variable primarily explained its own variance and the influence of other variables increase over time. Hence, adopting a broad perspective on macroeconomic variables can help policymakers anticipate and mitigate ripple effects across various economic sectors.
},
 year = {2024}
}

Copy | Download

TY  - JOUR
T1  - Modelling the Relationship Between Merchandise Trade Flows and Some Macroeconomic Variables in Ghana

AU  - Azebre Abu Ibrahim
AU  - Anuwoje Ida Logubayom Abonongo
Y1  - 2024/10/29
PY  - 2024
N1  - https://doi.org/10.11648/j.ajtas.20241305.15
DO  - 10.11648/j.ajtas.20241305.15
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  - 157
EP  - 174
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20241305.15
AB  - Macroeconomic variables serve as economic indicators that offer valuable insights into the overall health and stability of an economy. Changes in these variables can have significant impacts on a country's trade balance and overall economic performance. This study employed multivariate time series analysis to study the relationship between Merchandise Trade Flows (MTF), Monetary Policy Rate (MPR), Commercial Lending Rate (CLR), Nominal Growth Rate (NGR) and Consumer Price Index (CPI) with Money Supply (MoS) as exogenous variable. The nature of trend in each series was investigated. The results revealed that quadratic trend model best models MTF, MPR, CLR and NGR whiles an exponential trend best models CPI. Johansen’s co-integration test with unrestricted trend performed revealed the existence of long-run equilibrium relationships between the variables and three (3) co-integrating equations described this long-run relationship. In terms of short-run relationships, the VEC (2) model revealed that, CLR, NGR, MoS have positive and significant impact on MTF. CLR, NGR and MoS have positive and significant impact on MPR, NGR have positive and significant impact on CLR, CPI and MoS have significant impact on NGR whiles NGR and MoS have significant impact on CPI. Model diagnostics performed on the VEC (2) model showed that, all the model parameters are structurally stable over time and the residuals of the individual models are free from serial correlation and conditional heteroscedasticity. Forecast error variance decomposition (FEVD) analysis showed that each variable primarily explained its own variance and the influence of other variables increase over time. Hence, adopting a broad perspective on macroeconomic variables can help policymakers anticipate and mitigate ripple effects across various economic sectors.

VL  - 13
IS  - 5
ER  -

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