Pub Date : 2024-01-03DOI: 10.9734/ajpas/2024/v26i1576
Ghareeb A. Marei, Hassan Ismail Faris Aly, Mohammed Ahmed Farouk
A time series is an ordered sequence of data points that are chronologically indexed. By evaluating the values in a time series both presently and retrospectively, it is possible to predict the future values of most time series with a reasonable degree of accuracy. In this paper modeling of Egyptian pound exchange rate per US dollar in the short term by using the ARIMA model and many probability distributions. The ARIMA is the best ARIMA that assumed in this study in modeling the data set of the exchange rate of the pound in Egypt per US dollar and the Burr probability distribution is the best probability distribution in modeling the same data set.
{"title":"Modeling and Predicting the Egyptian Pound's Exchange Rate Per the American Dollar on a Short-Term Scale by Using ARIMA – Probability Distributions","authors":"Ghareeb A. Marei, Hassan Ismail Faris Aly, Mohammed Ahmed Farouk","doi":"10.9734/ajpas/2024/v26i1576","DOIUrl":"https://doi.org/10.9734/ajpas/2024/v26i1576","url":null,"abstract":"A time series is an ordered sequence of data points that are chronologically indexed. By evaluating the values in a time series both presently and retrospectively, it is possible to predict the future values of most time series with a reasonable degree of accuracy. In this paper modeling of Egyptian pound exchange rate per US dollar in the short term by using the ARIMA model and many probability distributions. The ARIMA is the best ARIMA that assumed in this study in modeling the data set of the exchange rate of the pound in Egypt per US dollar and the Burr probability distribution is the best probability distribution in modeling the same data set.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139536526","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 : 2023-12-29DOI: 10.9734/ajpas/2023/v25i4574
S. N. Nwanneako, I. D. Essi, G. L. Tuaneh, Iyai Davies
Aims: The aim of this study is to apply Panel VAR (Vector Autoregressive) modeling and estimation to analyze the macroeconomic interaction and interdependence within the context of Nigeria, Ghana, and Cameroon. The study aims to understand the trends of key macroeconomic variables, namely gross domestic product (GDP), exchange rate, and foreign reserves. Methodology: The study adopted three macroeconomic variables—GDP, exchange rate, and foreign reserve—and utilized annual secondary data from the World Bank spanning from 1960 to 2022. Pretests, including unit root and cointegration tests, were conducted on the variables. The panel unit root tests (Levin, Lin, and Chu t, Augmented Dickey-Fuller Fisher Chi-Square, and Phillips-Perron Fisher Chi-Square) indicated that the series had unit roots at levels but were stationary at first difference, implying integration of order one. The absence of co-integration in the panel co-integration test established the necessary conditions for estimating a panel vector autoregressive model. Results: The trend analysis revealed that the variables were relatively low in the 1960s and 1970s but exhibited an increasing and fluctuating pattern afterward. Descriptive statistics showed variations among the countries, with Cameroon having higher GDP per capita and greater standard deviation, indicating more significant fluctuations. Ghana, in contrast, displayed lower per capita income with a lower standard deviation. The foreign exchange rate varied, with Cameroon having the highest and Ghana the lowest mean rates.Conclusion: The fixed effect model was estimated after the Hausman Test rejected the random effect model. The results indicated that foreign exchange rates had joint significance on GDP per capita, while foreign reserves did not. The study concludes that the economies of Nigeria, Ghana, and Cameroon are responsive to GDP per capita, foreign exchange rates, and foreign reserves. The policy implication is that economic practitioners in these countries should closely monitor these variables to anticipate changes in economic indicators. Therefore, the study recommends active monitoring of the economic variables used in this research to facilitate informed decision-making.
{"title":"Panel Vector Autoregressive Modeling of Macroeconomic Interaction in Nigeria, Ghana and Cameroon","authors":"S. N. Nwanneako, I. D. Essi, G. L. Tuaneh, Iyai Davies","doi":"10.9734/ajpas/2023/v25i4574","DOIUrl":"https://doi.org/10.9734/ajpas/2023/v25i4574","url":null,"abstract":"Aims: The aim of this study is to apply Panel VAR (Vector Autoregressive) modeling and estimation to analyze the macroeconomic interaction and interdependence within the context of Nigeria, Ghana, and Cameroon. The study aims to understand the trends of key macroeconomic variables, namely gross domestic product (GDP), exchange rate, and foreign reserves. Methodology: The study adopted three macroeconomic variables—GDP, exchange rate, and foreign reserve—and utilized annual secondary data from the World Bank spanning from 1960 to 2022. Pretests, including unit root and cointegration tests, were conducted on the variables. The panel unit root tests (Levin, Lin, and Chu t, Augmented Dickey-Fuller Fisher Chi-Square, and Phillips-Perron Fisher Chi-Square) indicated that the series had unit roots at levels but were stationary at first difference, implying integration of order one. The absence of co-integration in the panel co-integration test established the necessary conditions for estimating a panel vector autoregressive model. Results: The trend analysis revealed that the variables were relatively low in the 1960s and 1970s but exhibited an increasing and fluctuating pattern afterward. Descriptive statistics showed variations among the countries, with Cameroon having higher GDP per capita and greater standard deviation, indicating more significant fluctuations. Ghana, in contrast, displayed lower per capita income with a lower standard deviation. The foreign exchange rate varied, with Cameroon having the highest and Ghana the lowest mean rates.Conclusion: The fixed effect model was estimated after the Hausman Test rejected the random effect model. The results indicated that foreign exchange rates had joint significance on GDP per capita, while foreign reserves did not. The study concludes that the economies of Nigeria, Ghana, and Cameroon are responsive to GDP per capita, foreign exchange rates, and foreign reserves. The policy implication is that economic practitioners in these countries should closely monitor these variables to anticipate changes in economic indicators. Therefore, the study recommends active monitoring of the economic variables used in this research to facilitate informed decision-making.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139142157","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}
The reason for this research is to enable us know the use BFTSC (break for time series components) in identification of the structural change and the time series components existing in Australia GDP. The data (Australia GDP) statistics spanned for period of fifty five years. The GDP of Australia is a higher information gotten from the StreamData of Universiti Utara Malaysia Library. The precincts of BFAST in terms of structural change was advanced to become BFTSC. BFTSC was created from basic research conducted on BFAST, results shows an innovative technique that captures the recurring (cyclicals) and non-recurring cyclical (irregular) components that was not included in the original BFAST technique and it was included in the methodology of this study. BFTSC was created to give a mutual image of all the required time series components. The subsequently forecasting technique was determined and forecast is made.
{"title":"Forecasting Australia Gross Domestic Product (GDP) under Structural Change (SC) Using Break for Time Series Components (BFTSC)","authors":"Ajare Emmanuel Oloruntoba, Adefabi Adekunle, Adeyemo Abiodun","doi":"10.9734/ajpas/2023/v25i4573","DOIUrl":"https://doi.org/10.9734/ajpas/2023/v25i4573","url":null,"abstract":"The reason for this research is to enable us know the use BFTSC (break for time series components) in identification of the structural change and the time series components existing in Australia GDP. The data (Australia GDP) statistics spanned for period of fifty five years. The GDP of Australia is a higher information gotten from the StreamData of Universiti Utara Malaysia Library. The precincts of BFAST in terms of structural change was advanced to become BFTSC. BFTSC was created from basic research conducted on BFAST, results shows an innovative technique that captures the recurring (cyclicals) and non-recurring cyclical (irregular) components that was not included in the original BFAST technique and it was included in the methodology of this study. BFTSC was created to give a mutual image of all the required time series components. The subsequently forecasting technique was determined and forecast is made.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139150750","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 : 2023-12-18DOI: 10.9734/ajpas/2023/v25i4570
K. Dozie, C. C. Ibebuogu
This study examines the comparison of trend cycle and seasonal components in the presence and absence of missing observations. The method adopted in this study is based on the row, column and overall means of the time series arranged in a Buys-Ballot table with m rows and s columns. The method assumes that (1) Only one data is missing at a time in the Buys-Ballot table (2) the trending curve is exponential (3) the modal structure is additive. The study indicates that, the estimation of the missing observations as they occur consecutively with the errors being normally distributed. Results indicate that, the differences in the trend parameters for both situations are insignificant because they are approximately the same. In the case of corresponding seasonal effects, significant differences existed on the points in which there are missing values in the column of the Buys-Ballot table.
本研究探讨了在存在和不存在缺失观测数据的情况下趋势周期和季节成分的比较。本研究采用的方法基于时间序列的行、列和总平均值，并将其排列在一个有 m 行和 s 列的买方投掷表中。 该方法假定：(1) 在买方博尔特表中每次只缺失一个数据；(2) 趋势曲线是指数型的；(3) 模态结构是加法型的。研究表明，对连续出现的缺失观测值进行估计，误差呈正态分布。结果表明，这两种情况下的趋势参数差异不大，因为它们大致相同。就相应的季节效应而言，在买入-卖出表列中存在缺失值的点上存在显著差异。
{"title":"Comparison of Trend Parameters and Seasonal Indices in the Presence and Absence of Missing Values of Exponential Trend-Cycle in Time Series Analysis","authors":"K. Dozie, C. C. Ibebuogu","doi":"10.9734/ajpas/2023/v25i4570","DOIUrl":"https://doi.org/10.9734/ajpas/2023/v25i4570","url":null,"abstract":"This study examines the comparison of trend cycle and seasonal components in the presence and absence of missing observations. The method adopted in this study is based on the row, column and overall means of the time series arranged in a Buys-Ballot table with m rows and s columns. The method assumes that (1) Only one data is missing at a time in the Buys-Ballot table (2) the trending curve is exponential (3) the modal structure is additive. The study indicates that, the estimation of the missing observations as they occur consecutively with the errors being normally distributed. Results indicate that, the differences in the trend parameters for both situations are insignificant because they are approximately the same. In the case of corresponding seasonal effects, significant differences existed on the points in which there are missing values in the column of the Buys-Ballot table.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139174644","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 : 2023-12-18DOI: 10.9734/ajpas/2023/v25i4571
A. Langat, John Kamwele Mutinda, S. Mwalili, L. Kazembe
The global onslaught of COVID-19 brought about unforeseen disruptions, significantly imprinting on sectors like essential goods, services, manufacturing, and education. African nations, characterized by theirdistinct socio-economic tapestries, stood at an intriguing juncture—facing both systemic vulnerabilities and demonstrating admirable adaptability. This research delves into the multifaceted impacts experienced by these nations during the global economic turmoil.Our exploration, bolstered by graphical analyses, examines shifts in demand dynamics, particularly contrasting essential and luxury goods. The pandemic inducedphenomena like panic buying, while simultaneously causing economic slowdowns, reshaping consumption patterns. The services sector’s narrative is bifurcated: while traditional services faced setbacks, digitalcounterparts witnessed exponential growth. In manufacturing, disrupted supply chains contrasted with surges in essential goods production. With global trade facing unprecedented challenges, a noticeable tilt towards local alternatives emerges in Least Developed Countries (LDCs). This trend signals both adaptability and a potential pivot towards self-reliance amidst escalating living costs. Moreover, the burgeoning influence oftechnology, particularly Artificial Intelligence (AI), proposes a transformative phase for African education, hinting at enhanced accessibility and quality. However, this optimism is tempered by challenges such as infrastructural gaps and the imperative for improved digital literacy.In Conclusion, this paper provides a concise yet encompassing perspective on the economic reverberations of the COVID-19 pandemic, centering on the unique experiences and lessons from the African landscape.
{"title":"COVID-19 Impact Analysis: Assessing African Sectors - Commodity, Service, Manufacturing, and Education using Mixed Model Approach","authors":"A. Langat, John Kamwele Mutinda, S. Mwalili, L. Kazembe","doi":"10.9734/ajpas/2023/v25i4571","DOIUrl":"https://doi.org/10.9734/ajpas/2023/v25i4571","url":null,"abstract":"The global onslaught of COVID-19 brought about unforeseen disruptions, significantly imprinting on sectors like essential goods, services, manufacturing, and education. African nations, characterized by theirdistinct socio-economic tapestries, stood at an intriguing juncture—facing both systemic vulnerabilities and demonstrating admirable adaptability. This research delves into the multifaceted impacts experienced by these nations during the global economic turmoil.Our exploration, bolstered by graphical analyses, examines shifts in demand dynamics, particularly contrasting essential and luxury goods. The pandemic inducedphenomena like panic buying, while simultaneously causing economic slowdowns, reshaping consumption patterns. The services sector’s narrative is bifurcated: while traditional services faced setbacks, digitalcounterparts witnessed exponential growth. In manufacturing, disrupted supply chains contrasted with surges in essential goods production. With global trade facing unprecedented challenges, a noticeable tilt towards local alternatives emerges in Least Developed Countries (LDCs). This trend signals both adaptability and a potential pivot towards self-reliance amidst escalating living costs. Moreover, the burgeoning influence oftechnology, particularly Artificial Intelligence (AI), proposes a transformative phase for African education, hinting at enhanced accessibility and quality. However, this optimism is tempered by challenges such as infrastructural gaps and the imperative for improved digital literacy.In Conclusion, this paper provides a concise yet encompassing perspective on the economic reverberations of the COVID-19 pandemic, centering on the unique experiences and lessons from the African landscape.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139172966","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 : 2023-12-15DOI: 10.9734/ajpas/2023/v25i4569
S. Nagesh, Laxmi. B. Dharmannavar
In recent years, due to climate change, catastrophic events are increased largely in India. Hence researchers are forced to consider non-stationary flood frequency analysis as an improved method. In this paper, non-stationarity of annual daily maximum flood heights were studied at 12 sites of Mahanadi River Basin (MRB) by analyzing the flood frequency of a stationary model and 4 non-stationary models using time dependent q-GEV model by considering trend as a linear function of its location and scale parameters. The q-GEV distribution is utilized in this study because of its flexibility and accuracy than GEV distribution in modeling extreme flood heights. The results found that there is strong evidence of a linear trend existence for both the location and scale parameters at the Kesinga site; for the location parameter at Pathardi and Simga sites; for the scale parameter at Dharmajagarh, Kotni and Seorinarayan, and no linear trend exists for both location and scale parameters at Alipingal, Bomnidhi, Manendragarh, Mohana, Rajim and Sundargarh, there may be exists other form of trend at these sites. The findings also indicate that nonstationarity is present in the MRB due to climate change, which help to water practitioner for taking precautions against adverse effect of extreme floods.
{"title":"Non-Stationary Modeling of Annual Flood Peak Heights of Mahanadi River Basin with the q-Generalized Extreme Value Distribution","authors":"S. Nagesh, Laxmi. B. Dharmannavar","doi":"10.9734/ajpas/2023/v25i4569","DOIUrl":"https://doi.org/10.9734/ajpas/2023/v25i4569","url":null,"abstract":"In recent years, due to climate change, catastrophic events are increased largely in India. Hence researchers are forced to consider non-stationary flood frequency analysis as an improved method. In this paper, non-stationarity of annual daily maximum flood heights were studied at 12 sites of Mahanadi River Basin (MRB) by analyzing the flood frequency of a stationary model and 4 non-stationary models using time dependent q-GEV model by considering trend as a linear function of its location and scale parameters. The q-GEV distribution is utilized in this study because of its flexibility and accuracy than GEV distribution in modeling extreme flood heights. The results found that there is strong evidence of a linear trend existence for both the location and scale parameters at the Kesinga site; for the location parameter at Pathardi and Simga sites; for the scale parameter at Dharmajagarh, Kotni and Seorinarayan, and no linear trend exists for both location and scale parameters at Alipingal, Bomnidhi, Manendragarh, Mohana, Rajim and Sundargarh, there may be exists other form of trend at these sites. The findings also indicate that nonstationarity is present in the MRB due to climate change, which help to water practitioner for taking precautions against adverse effect of extreme floods.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138998595","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 : 2023-12-14DOI: 10.9734/ajpas/2023/v25i4568
W. M. S. Bandara, W. A. R. D. Mel
Aims/ objectives: This study develops and evaluates a novel hybrid model (HB) for forecasting monthly inflation rates in Sri Lanka, a country with a unique economic context, from 1988 to 2021. By integrating the Autoregressive Integrated Moving Average (ARIMA) and Artificial Neural Networks (ANNs), the study aims to overcome the limitations of traditional linear models in capturing the nonlinear patterns often observed in Sri Lankan economic data. Objectives: The study aims to assess the predictive accuracy of the HB model against established models, emphasizing its adaptability and robustness over a historically significant period. Methodology: Utilizing historical data, the study compares the HB model's forecasting performance with other established models, focusing on the Mean Absolute Percentage Error (MAPE) as a key metric of predictive accuracy. Results: The HB model demonstrates superior forecasting accuracy, with a notable reduction in MAPE to 7.10%, indicating its effectiveness in capturing the complexities of the Sri Lankan inflation trend. Conclusion: This study contributes to the field of economic forecasting by presenting a model that not only provides more accurate predictions but also adapts to the specific economic conditions of Sri Lanka. The findings have significant implications for economic planning and policy-making, highlighting the utility of hybrid forecasting models in developing economies.
{"title":"Evaluating the Predictive Performance of Monthly Inflation Rates in Sri Lanka using the Hybrid Model (HB)","authors":"W. M. S. Bandara, W. A. R. D. Mel","doi":"10.9734/ajpas/2023/v25i4568","DOIUrl":"https://doi.org/10.9734/ajpas/2023/v25i4568","url":null,"abstract":"Aims/ objectives: This study develops and evaluates a novel hybrid model (HB) for forecasting monthly inflation rates in Sri Lanka, a country with a unique economic context, from 1988 to 2021. By integrating the Autoregressive Integrated Moving Average (ARIMA) and Artificial Neural Networks (ANNs), the study aims to overcome the limitations of traditional linear models in capturing the nonlinear patterns often observed in Sri Lankan economic data.\u0000Objectives: The study aims to assess the predictive accuracy of the HB model against established models, emphasizing its adaptability and robustness over a historically significant period.\u0000Methodology: Utilizing historical data, the study compares the HB model's forecasting performance with other established models, focusing on the Mean Absolute Percentage Error (MAPE) as a key metric of predictive accuracy.\u0000Results: The HB model demonstrates superior forecasting accuracy, with a notable reduction in MAPE to 7.10%, indicating its effectiveness in capturing the complexities of the Sri Lankan inflation trend. \u0000Conclusion: This study contributes to the field of economic forecasting by presenting a model that not only provides more accurate predictions but also adapts to the specific economic conditions of Sri Lanka. The findings have significant implications for economic planning and policy-making, highlighting the utility of hybrid forecasting models in developing economies.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139002075","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 : 2023-12-11DOI: 10.9734/ajpas/2023/v25i3567
Timothy Olaniyi Morounfolu Israel, Nwuju, Kingdom, Da-wariboko Asikiye Yvonne, Wegbom Anthony Ike
Aims: The aim of this study is to model the relationship between Nigerian quasi money and money supply using the Bayesian Vector Autoregressive (BVAR) model. Study design: The study collected and analyzed monthly data from the Central Bank of Nigeria (CBN) money and credit statistics over an 8-year period (November 2015 to December 2022). The analysis utilized both Vector Autoregressive (VAR) Model and BVAR model to examine the dynamics between these variables and their implications for monetary policy. Methodology: The study employed the Bayesian Vector Autoregressive (BVAR) model to analyze the relationship between Nigerian quasi money and money supply. Monthly data from the Central Bank of Nigeria (CBN) over an 8-year period was collected and subjected to both Vector Autoregressive (VAR) Model and BVAR model for analysis. Results: The findings indicated that there is no long-run relationship between Nigerian narrow money and quasi money, but quasi money does granger cause changes in narrow money, and vice versa. This suggests a multi-directional effect between the two variables. The BVAR model consistently outperformed the VAR model in terms of higher Adjusted-R² values, indicating its stronger ability to explain the variance in the data. The BVAR model provided a more robust and accurate representation of the relationship between these variables. The model exhibited stability and the absence of heteroscedasticity in the residuals, indicating a stable relationship between the variables. The impulse response function showed an immediate impact of changes in narrow money on the overall money supply in Nigeria. Conclusion: This study contributes to existing knowledge by empirically examining the relationship between Nigerian narrow money and quasi money and also concluded that there existed no co-integrating relationship between narrow money and quasi money, which has important implications for effective monetary policy strategies, particularly in Nigeria.
{"title":"Application of Bayesian Vector Autoregressive Models in the Analysis of Quasi Money and Money Supply: A Case Study of Nigeria","authors":"Timothy Olaniyi Morounfolu Israel, Nwuju, Kingdom, Da-wariboko Asikiye Yvonne, Wegbom Anthony Ike","doi":"10.9734/ajpas/2023/v25i3567","DOIUrl":"https://doi.org/10.9734/ajpas/2023/v25i3567","url":null,"abstract":"Aims: The aim of this study is to model the relationship between Nigerian quasi money and money supply using the Bayesian Vector Autoregressive (BVAR) model. \u0000Study design: The study collected and analyzed monthly data from the Central Bank of Nigeria (CBN) money and credit statistics over an 8-year period (November 2015 to December 2022). The analysis utilized both Vector Autoregressive (VAR) Model and BVAR model to examine the dynamics between these variables and their implications for monetary policy. \u0000Methodology: The study employed the Bayesian Vector Autoregressive (BVAR) model to analyze the relationship between Nigerian quasi money and money supply. Monthly data from the Central Bank of Nigeria (CBN) over an 8-year period was collected and subjected to both Vector Autoregressive (VAR) Model and BVAR model for analysis. \u0000Results: The findings indicated that there is no long-run relationship between Nigerian narrow money and quasi money, but quasi money does granger cause changes in narrow money, and vice versa. This suggests a multi-directional effect between the two variables. The BVAR model consistently outperformed the VAR model in terms of higher Adjusted-R² values, indicating its stronger ability to explain the variance in the data. The BVAR model provided a more robust and accurate representation of the relationship between these variables. The model exhibited stability and the absence of heteroscedasticity in the residuals, indicating a stable relationship between the variables. The impulse response function showed an immediate impact of changes in narrow money on the overall money supply in Nigeria. \u0000Conclusion: This study contributes to existing knowledge by empirically examining the relationship between Nigerian narrow money and quasi money and also concluded that there existed no co-integrating relationship between narrow money and quasi money, which has important implications for effective monetary policy strategies, particularly in Nigeria.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138981441","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 : 2023-12-07DOI: 10.9734/ajpas/2023/v25i3566
Shamsuddeen Suleiman, Muhammad Sani, Aliyu Usman Goga
The use of virtual meeting technologies is becoming widespread in the educational field especially due to the outbreak of the Coronavirus Disease (COVID-19) that suddenly traumatized educational institutions activities in many countries across the world. However, despite the numerous advantages of virtual meeting technology, many higher institutions in Nigeria have not embraced the technology even during COVID-19 pandemic due to poor internet connectivity, poor facilities, negative attitudes (non-acceptance) of both teachers and students etc. In this study, partial least squares structural equation modelling (PLS-SEM) based on Davis technology acceptance model (TAM) was used to test the proposed model. The reliability and validity tests of the data collection instrument re-established the suitability of the TAM model in measuring the students’ acceptance of virtual meeting technologies. The research indicated that perceived usefulness as established by TAM was also found to have a significant impact on students’ attitude and behavioral intention to use virtual meeting technology. Similarly, the result has shown that perceived ease of use (PEOU) had a strong effect on perceived usefulness (PU).
{"title":"Application of Technology Acceptance Model in Examining Students’ Behavioural Intention to Use Virtual Meeting Technology: A Partial Least Squares Structural Equation Modeling Approach","authors":"Shamsuddeen Suleiman, Muhammad Sani, Aliyu Usman Goga","doi":"10.9734/ajpas/2023/v25i3566","DOIUrl":"https://doi.org/10.9734/ajpas/2023/v25i3566","url":null,"abstract":"The use of virtual meeting technologies is becoming widespread in the educational field especially due to the outbreak of the Coronavirus Disease (COVID-19) that suddenly traumatized educational institutions activities in many countries across the world. However, despite the numerous advantages of virtual meeting technology, many higher institutions in Nigeria have not embraced the technology even during COVID-19 pandemic due to poor internet connectivity, poor facilities, negative attitudes (non-acceptance) of both teachers and students etc. In this study, partial least squares structural equation modelling (PLS-SEM) based on Davis technology acceptance model (TAM) was used to test the proposed model. The reliability and validity tests of the data collection instrument re-established the suitability of the TAM model in measuring the students’ acceptance of virtual meeting technologies. The research indicated that perceived usefulness as established by TAM was also found to have a significant impact on students’ attitude and behavioral intention to use virtual meeting technology. Similarly, the result has shown that perceived ease of use (PEOU) had a strong effect on perceived usefulness (PU).","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138590732","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 : 2023-11-29DOI: 10.9734/ajpas/2023/v25i3565
V. S. Mukha
In the article, the theory of the Fourier series on the orthogonal multidimensional-matrix polynomials is developed. The known results from the theory of the orthogonal polynomials of the vector variable and the Fourier series are given and the new results are presented. In particular, the known results of the Fourier series are extended to the case of the multidimensional-matrix functions, what allows us to solve more general approximation problems. The general case of the approximation of the multidimensional-matrix function of the vector argument by the Fourier series on the orthogonal multidimensional-matrix polynomials is realized programmatically as the program function and its efficiency is confirmed. The analytical expressions for the coefficients of the second degree orthogonal polynomials and Fourier series for the potential studies are obtained.
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