Pub Date : 2024-05-07DOI: 10.9734/ajpas/2024/v26i4613
Abdul Basit Abdul Rahaman, J. Dioggban, A. Jackson
.
.
{"title":"An Improved Product Estimator for Finite Population Mean in the Presence of Nonignorable Nonresponse","authors":"Abdul Basit Abdul Rahaman, J. Dioggban, A. Jackson","doi":"10.9734/ajpas/2024/v26i4613","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i4613","url":null,"abstract":"<jats:p>.</jats:p>","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141002601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-02DOI: 10.9734/ajpas/2024/v26i4612
Termen Nanfwang Yunana, K. E. Lasisi, A. M. Kwami, Douglas Jah Pam, Sheyi Mafolasire, Chibuike John Echebiri, Friday Ezekiel Danung, S. Gambo
Diabetes Mellitus is a huge burden for human health, increasing number of patient is likely to result in rising demand for the medical emergencies. Due to limited number of hospitals with standard laboratory test kits to differentiate between type 1 and type 2 diabetes it is important to forecast the future incidences and prepare with proper resource planning. The monthly number of Diabetes patients obtained from Jos University Teaching Hospital is fitted by autoregressive integrated moving average (ARIMA) model. Dataset starting from January, 2010 to December,2020. Using ARIMA, several models were evaluated based on the Bayesian Information Criterion (BIC) and Ljung-Box Q statistics. ARIMA(3, 1, 1) is found to be better and used to describe and predict the future trends of Diabetes type 1 and ARIMA(1,1,1) is a better model to predict the future prevalence of diabetes type 2. Therefore, the proposed model will help in the appropriate planning and allocation of resources for emergencies.
{"title":"Arima Model to Predict the Prevalence of Diabetes Type 1 and Type 2 Patients: A Case Study of Jos University Teaching Hospital","authors":"Termen Nanfwang Yunana, K. E. Lasisi, A. M. Kwami, Douglas Jah Pam, Sheyi Mafolasire, Chibuike John Echebiri, Friday Ezekiel Danung, S. Gambo","doi":"10.9734/ajpas/2024/v26i4612","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i4612","url":null,"abstract":"Diabetes Mellitus is a huge burden for human health, increasing number of patient is likely to result in rising demand for the medical emergencies. Due to limited number of hospitals with standard laboratory test kits to differentiate between type 1 and type 2 diabetes it is important to forecast the future incidences and prepare with proper resource planning. The monthly number of Diabetes patients obtained from Jos University Teaching Hospital is fitted by autoregressive integrated moving average (ARIMA) model. Dataset starting from January, 2010 to December,2020. Using ARIMA, several models were evaluated based on the Bayesian Information Criterion (BIC) and Ljung-Box Q statistics. ARIMA(3, 1, 1) is found to be better and used to describe and predict the future trends of Diabetes type 1 and ARIMA(1,1,1) is a better model to predict the future prevalence of diabetes type 2. Therefore, the proposed model will help in the appropriate planning and allocation of resources for emergencies.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141017722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-16DOI: 10.9734/ajpas/2024/v26i3600
A. Langat, Michael Arthur Ofori, John Kamwele Mutinda, Mouhamadou Djima Baranon, A. Amegah, L. Kazembe
This study used spatial mapping techniques to examine the distribution of births and deaths in Kenya and their relationship with various factors related to child survival, such as maternal age, education, wealth, and access to health services. Data were obtained from the 2022 Kenya Demographic and Health Survey (KDHS). Spatial autocorrelation analyses were conducted to identify clusters of high or low child mortality rates. The results showed significant spatial autocorrelation in child mortality rates, indicating that neighboring areas had similar mortality rates. Factors such as maternal education, wealth, and access to health services were found to be significantly associated with child mortality rates. These findings can inform targeted interventions and policies to reduce child mortality rates in Kenya, particularly in areas with the highest risk of mortality.
{"title":"Spatial Regression Modeling of Child Survival on the Distribution of Births and Deaths in Kenya Based on the Kenya Demographic and Health Survey (KDHS) 2022","authors":"A. Langat, Michael Arthur Ofori, John Kamwele Mutinda, Mouhamadou Djima Baranon, A. Amegah, L. Kazembe","doi":"10.9734/ajpas/2024/v26i3600","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i3600","url":null,"abstract":"This study used spatial mapping techniques to examine the distribution of births and deaths in Kenya and their relationship with various factors related to child survival, such as maternal age, education, wealth, and access to health services. Data were obtained from the 2022 Kenya Demographic and Health Survey (KDHS). Spatial autocorrelation analyses were conducted to identify clusters of high or low child mortality rates. The results showed significant spatial autocorrelation in child mortality rates, indicating that neighboring areas had similar mortality rates. Factors such as maternal education, wealth, and access to health services were found to be significantly associated with child mortality rates. These findings can inform targeted interventions and policies to reduce child mortality rates in Kenya, particularly in areas with the highest risk of mortality.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140237147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-15DOI: 10.9734/ajpas/2024/v26i3599
Ossaiugbo Ifeanyi Marcus, Okposo Newton Ighomaro, Apanapudor Joshua Sarduana
This paper aims to capture the dynamics of intra-communal violence in a deterministic model of ordinary differential equations, accordingly, the Authors found some interesting results. Lack of quality education, insecurity, bad roads, drugs and alcoholism, unequal representation in government and religious decay have been identified as key factors supporting intra-communal violence over the years. In this research work we built all these factors into a deterministic model describing intra-communal violence and performed some basic mathematical analysis such as positivity of solutions, existence of invariant region, violence-free equilibrium, violence-persistent equilibrium, basic reproduction number, sensitivity analysis, stability analysis and bifurcation analysis. It was revealed that the violence-free equilibrium is globally asymptotically stable. The model exhibits a forward bifurcation. The sensitivity analysis revealed that injustice and insecurity are highly sensitive parameters of the basic reproduction number. We also designed a questionnaire to ascertain the violence risk level of Obiaruku community in Delta State, Nigeria and the analysis revealed that the community is at the medium high risk level and thus violence may occur in most cases in the community. The results of the stability analysis and the sensitivity analysis showed that under certain conditions, a community can be brought to the maximum low risk level and the maximum high peace level.
{"title":"Mathematical Modeling of Intra-Communal Violence and Risk-Level Analysis. Case Study: Obiaruku Community in Delta State, Nigeria","authors":"Ossaiugbo Ifeanyi Marcus, Okposo Newton Ighomaro, Apanapudor Joshua Sarduana","doi":"10.9734/ajpas/2024/v26i3599","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i3599","url":null,"abstract":"This paper aims to capture the dynamics of intra-communal violence in a deterministic model of ordinary differential equations, accordingly, the Authors found some interesting results. Lack of quality education, insecurity, bad roads, drugs and alcoholism, unequal representation in government and religious decay have been identified as key factors supporting intra-communal violence over the years. In this research work we built all these factors into a deterministic model describing intra-communal violence and performed some basic mathematical analysis such as positivity of solutions, existence of invariant region, violence-free equilibrium, violence-persistent equilibrium, basic reproduction number, sensitivity analysis, stability analysis and bifurcation analysis. It was revealed that the violence-free equilibrium is globally asymptotically stable. The model exhibits a forward bifurcation. The sensitivity analysis revealed that injustice and insecurity are highly sensitive parameters of the basic reproduction number. We also designed a questionnaire to ascertain the violence risk level of Obiaruku community in Delta State, Nigeria and the analysis revealed that the community is at the medium high risk level and thus violence may occur in most cases in the community. The results of the stability analysis and the sensitivity analysis showed that under certain conditions, a community can be brought to the maximum low risk level and the maximum high peace level.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140240217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-12DOI: 10.9734/ajpas/2024/v26i2591
A. Danbaba, N. S. Dauran, A. Mustafa, M. Ibrahim
Robust parameter design is a principle in quality improvement methodologies that is directed towards reducing the effects of errors which are either poised by the noise factors or the control factors. Response surface methodology is an effective approach to robust parameter design. Previous studies discussed Robust parameter design based on the response surface model by considering measurement errors in control variables for a single response variable. However, in process design, determining optimal levels of control variables is an important issue in some problems with different outputs. This study therefore investigates the impacts of measurement errors in the levels of control variables on processes with multiple quality characteristics (responses). Different variances of error were tested on the levels of control variables and the analysis of response surface modeling and optimization was performed. The result showed that as measurement errors in the levels of control variables increase, the coefficient of determinations for the multi-response and the expected quality loss deviates from what is obtainable in the initial state. It can be concluded based on the result however, that measurement errors in the levels of control variables exert impacts on robust parameter design for multi-response.
{"title":"A Study of the Impacts of Measurement errors on Robust Parameter Design for Multi-response","authors":"A. Danbaba, N. S. Dauran, A. Mustafa, M. Ibrahim","doi":"10.9734/ajpas/2024/v26i2591","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i2591","url":null,"abstract":"Robust parameter design is a principle in quality improvement methodologies that is directed towards reducing the effects of errors which are either poised by the noise factors or the control factors. Response surface methodology is an effective approach to robust parameter design. Previous studies discussed Robust parameter design based on the response surface model by considering measurement errors in control variables for a single response variable. However, in process design, determining optimal levels of control variables is an important issue in some problems with different outputs. This study therefore investigates the impacts of measurement errors in the levels of control variables on processes with multiple quality characteristics (responses). Different variances of error were tested on the levels of control variables and the analysis of response surface modeling and optimization was performed. The result showed that as measurement errors in the levels of control variables increase, the coefficient of determinations for the multi-response and the expected quality loss deviates from what is obtainable in the initial state. It can be concluded based on the result however, that measurement errors in the levels of control variables exert impacts on robust parameter design for multi-response.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139844179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-12DOI: 10.9734/ajpas/2024/v26i2590
Ariayefa Francis Eniekezimene, Ebimowei Wodu, Joseph Peres Anda-Owei
This study examined the impact of foreign direct investment (FDI) on economic growth in Nigeria from 1981 to 2022. Real gross domestic product growth rate (RGDPGR) was the proxy for economic growth while foreign direct investment (FDI), gross fixed capital formation (GFCF), per capita income (PCI) and exchange rate (EXR) were the explanatory variables. The study employed the autoregressive distributed lag (ARDL) technique to estimate the model, while the eclectic paradigm and endogenous growth theory served as the theoretical framework for the study. The results revealed that in the long run, foreign direct investment, per capita income and exchange rate were positive but statistically insignificant to economic growth in Nigeria, while gross fixed capital formation was insignificant. However, in the short, GFCF had significant negative impact on economic growth in the second lagged year showing that a unit increase in GFCF decreased RGDPGR by approximately 10.21% while per capita income impacted positively on the growth of the Nigerian economy. Consequently, the study recommended that as a signal of market size for the inflow of FDI and particularly as a signal of human capital development, the government should increase her investment in human capital development focusing on technical skills relevant in manufacturing and service sectors to engender growth in per capita income to attract FDI and economic growth in Nigeria.
{"title":"Foreign Direct Investment and Economic Growth in Nigeria: A Revisit","authors":"Ariayefa Francis Eniekezimene, Ebimowei Wodu, Joseph Peres Anda-Owei","doi":"10.9734/ajpas/2024/v26i2590","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i2590","url":null,"abstract":"This study examined the impact of foreign direct investment (FDI) on economic growth in Nigeria from 1981 to 2022. Real gross domestic product growth rate (RGDPGR) was the proxy for economic growth while foreign direct investment (FDI), gross fixed capital formation (GFCF), per capita income (PCI) and exchange rate (EXR) were the explanatory variables. The study employed the autoregressive distributed lag (ARDL) technique to estimate the model, while the eclectic paradigm and endogenous growth theory served as the theoretical framework for the study. The results revealed that in the long run, foreign direct investment, per capita income and exchange rate were positive but statistically insignificant to economic growth in Nigeria, while gross fixed capital formation was insignificant. However, in the short, GFCF had significant negative impact on economic growth in the second lagged year showing that a unit increase in GFCF decreased RGDPGR by approximately 10.21% while per capita income impacted positively on the growth of the Nigerian economy. Consequently, the study recommended that as a signal of market size for the inflow of FDI and particularly as a signal of human capital development, the government should increase her investment in human capital development focusing on technical skills relevant in manufacturing and service sectors to engender growth in per capita income to attract FDI and economic growth in Nigeria.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139784344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-12DOI: 10.9734/ajpas/2024/v26i2591
A. Danbaba, N. S. Dauran, A. Mustafa, M. Ibrahim
Robust parameter design is a principle in quality improvement methodologies that is directed towards reducing the effects of errors which are either poised by the noise factors or the control factors. Response surface methodology is an effective approach to robust parameter design. Previous studies discussed Robust parameter design based on the response surface model by considering measurement errors in control variables for a single response variable. However, in process design, determining optimal levels of control variables is an important issue in some problems with different outputs. This study therefore investigates the impacts of measurement errors in the levels of control variables on processes with multiple quality characteristics (responses). Different variances of error were tested on the levels of control variables and the analysis of response surface modeling and optimization was performed. The result showed that as measurement errors in the levels of control variables increase, the coefficient of determinations for the multi-response and the expected quality loss deviates from what is obtainable in the initial state. It can be concluded based on the result however, that measurement errors in the levels of control variables exert impacts on robust parameter design for multi-response.
{"title":"A Study of the Impacts of Measurement errors on Robust Parameter Design for Multi-response","authors":"A. Danbaba, N. S. Dauran, A. Mustafa, M. Ibrahim","doi":"10.9734/ajpas/2024/v26i2591","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i2591","url":null,"abstract":"Robust parameter design is a principle in quality improvement methodologies that is directed towards reducing the effects of errors which are either poised by the noise factors or the control factors. Response surface methodology is an effective approach to robust parameter design. Previous studies discussed Robust parameter design based on the response surface model by considering measurement errors in control variables for a single response variable. However, in process design, determining optimal levels of control variables is an important issue in some problems with different outputs. This study therefore investigates the impacts of measurement errors in the levels of control variables on processes with multiple quality characteristics (responses). Different variances of error were tested on the levels of control variables and the analysis of response surface modeling and optimization was performed. The result showed that as measurement errors in the levels of control variables increase, the coefficient of determinations for the multi-response and the expected quality loss deviates from what is obtainable in the initial state. It can be concluded based on the result however, that measurement errors in the levels of control variables exert impacts on robust parameter design for multi-response.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139784483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-12DOI: 10.9734/ajpas/2024/v26i2590
Ariayefa Francis Eniekezimene, Ebimowei Wodu, Joseph Peres Anda-Owei
This study examined the impact of foreign direct investment (FDI) on economic growth in Nigeria from 1981 to 2022. Real gross domestic product growth rate (RGDPGR) was the proxy for economic growth while foreign direct investment (FDI), gross fixed capital formation (GFCF), per capita income (PCI) and exchange rate (EXR) were the explanatory variables. The study employed the autoregressive distributed lag (ARDL) technique to estimate the model, while the eclectic paradigm and endogenous growth theory served as the theoretical framework for the study. The results revealed that in the long run, foreign direct investment, per capita income and exchange rate were positive but statistically insignificant to economic growth in Nigeria, while gross fixed capital formation was insignificant. However, in the short, GFCF had significant negative impact on economic growth in the second lagged year showing that a unit increase in GFCF decreased RGDPGR by approximately 10.21% while per capita income impacted positively on the growth of the Nigerian economy. Consequently, the study recommended that as a signal of market size for the inflow of FDI and particularly as a signal of human capital development, the government should increase her investment in human capital development focusing on technical skills relevant in manufacturing and service sectors to engender growth in per capita income to attract FDI and economic growth in Nigeria.
{"title":"Foreign Direct Investment and Economic Growth in Nigeria: A Revisit","authors":"Ariayefa Francis Eniekezimene, Ebimowei Wodu, Joseph Peres Anda-Owei","doi":"10.9734/ajpas/2024/v26i2590","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i2590","url":null,"abstract":"This study examined the impact of foreign direct investment (FDI) on economic growth in Nigeria from 1981 to 2022. Real gross domestic product growth rate (RGDPGR) was the proxy for economic growth while foreign direct investment (FDI), gross fixed capital formation (GFCF), per capita income (PCI) and exchange rate (EXR) were the explanatory variables. The study employed the autoregressive distributed lag (ARDL) technique to estimate the model, while the eclectic paradigm and endogenous growth theory served as the theoretical framework for the study. The results revealed that in the long run, foreign direct investment, per capita income and exchange rate were positive but statistically insignificant to economic growth in Nigeria, while gross fixed capital formation was insignificant. However, in the short, GFCF had significant negative impact on economic growth in the second lagged year showing that a unit increase in GFCF decreased RGDPGR by approximately 10.21% while per capita income impacted positively on the growth of the Nigerian economy. Consequently, the study recommended that as a signal of market size for the inflow of FDI and particularly as a signal of human capital development, the government should increase her investment in human capital development focusing on technical skills relevant in manufacturing and service sectors to engender growth in per capita income to attract FDI and economic growth in Nigeria.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139844039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-10DOI: 10.9734/ajpas/2024/v26i2589
E. U. Ohaegbulem, Victor Chijindu Iheaka
This study majorly considered establishing the relationship that existed among the Nigerian-Naira (NGN) Exchange Rate and External Reserve, Inflation Rate, GDP Growth, Public Debt, Unemployment Rate and Exports for the period, (1981-2021). Also, the macroeconomic variables that influenced the NGN exchange rate fluctuations were determined. Multiple linear regression and correlation analyses were employed in this study. Results showed that the significant variables that influenced the NGN exchange rate fluctuations were External Reserve, Public Debt and Unemployment Rate; and each of them had very strong significant positive relationships with NGN exchange rate fluctuations. It was equally revealed that about 97% of the total variations in the NGN exchange rate fluctuations, from 1981 to 2021, were accounted for by variations in External Reserve, Public Debt and Unemployment Rate; while about 3% of the total variations in the NGN exchange rate could be attributed to other macroeconomic factors outside the ones used in this study. It was concluded that External Reserve, Public Debt and Unemployment Rate were the most macroeconomic factors that influenced the Nigerian-Naira exchange rate fluctuations from 1981 to 2021.
{"title":"The Impact of Macroeconomic Factors on Nigerian-Naira Exchange Rate Fluctuations (1981-2021)","authors":"E. U. Ohaegbulem, Victor Chijindu Iheaka","doi":"10.9734/ajpas/2024/v26i2589","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i2589","url":null,"abstract":"This study majorly considered establishing the relationship that existed among the Nigerian-Naira (NGN) Exchange Rate and External Reserve, Inflation Rate, GDP Growth, Public Debt, Unemployment Rate and Exports for the period, (1981-2021). Also, the macroeconomic variables that influenced the NGN exchange rate fluctuations were determined. Multiple linear regression and correlation analyses were employed in this study. Results showed that the significant variables that influenced the NGN exchange rate fluctuations were External Reserve, Public Debt and Unemployment Rate; and each of them had very strong significant positive relationships with NGN exchange rate fluctuations. It was equally revealed that about 97% of the total variations in the NGN exchange rate fluctuations, from 1981 to 2021, were accounted for by variations in External Reserve, Public Debt and Unemployment Rate; while about 3% of the total variations in the NGN exchange rate could be attributed to other macroeconomic factors outside the ones used in this study. It was concluded that External Reserve, Public Debt and Unemployment Rate were the most macroeconomic factors that influenced the Nigerian-Naira exchange rate fluctuations from 1981 to 2021.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139846004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-10DOI: 10.9734/ajpas/2024/v26i2589
E. U. Ohaegbulem, Victor Chijindu Iheaka
This study majorly considered establishing the relationship that existed among the Nigerian-Naira (NGN) Exchange Rate and External Reserve, Inflation Rate, GDP Growth, Public Debt, Unemployment Rate and Exports for the period, (1981-2021). Also, the macroeconomic variables that influenced the NGN exchange rate fluctuations were determined. Multiple linear regression and correlation analyses were employed in this study. Results showed that the significant variables that influenced the NGN exchange rate fluctuations were External Reserve, Public Debt and Unemployment Rate; and each of them had very strong significant positive relationships with NGN exchange rate fluctuations. It was equally revealed that about 97% of the total variations in the NGN exchange rate fluctuations, from 1981 to 2021, were accounted for by variations in External Reserve, Public Debt and Unemployment Rate; while about 3% of the total variations in the NGN exchange rate could be attributed to other macroeconomic factors outside the ones used in this study. It was concluded that External Reserve, Public Debt and Unemployment Rate were the most macroeconomic factors that influenced the Nigerian-Naira exchange rate fluctuations from 1981 to 2021.
{"title":"The Impact of Macroeconomic Factors on Nigerian-Naira Exchange Rate Fluctuations (1981-2021)","authors":"E. U. Ohaegbulem, Victor Chijindu Iheaka","doi":"10.9734/ajpas/2024/v26i2589","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i2589","url":null,"abstract":"This study majorly considered establishing the relationship that existed among the Nigerian-Naira (NGN) Exchange Rate and External Reserve, Inflation Rate, GDP Growth, Public Debt, Unemployment Rate and Exports for the period, (1981-2021). Also, the macroeconomic variables that influenced the NGN exchange rate fluctuations were determined. Multiple linear regression and correlation analyses were employed in this study. Results showed that the significant variables that influenced the NGN exchange rate fluctuations were External Reserve, Public Debt and Unemployment Rate; and each of them had very strong significant positive relationships with NGN exchange rate fluctuations. It was equally revealed that about 97% of the total variations in the NGN exchange rate fluctuations, from 1981 to 2021, were accounted for by variations in External Reserve, Public Debt and Unemployment Rate; while about 3% of the total variations in the NGN exchange rate could be attributed to other macroeconomic factors outside the ones used in this study. It was concluded that External Reserve, Public Debt and Unemployment Rate were the most macroeconomic factors that influenced the Nigerian-Naira exchange rate fluctuations from 1981 to 2021.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139786121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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