Ken_ Groove
University Of Benin,Benin City,Edo State Nigeria, Statistics, Graduate Student
This study uses time series regression with autoregressive integrated moving average (ARIMA) modeling to establish a model for forecasting inflation in Nigeria for the period 1981-2020. Akaike Information Criterion Corrected (AICC) and... more
This study uses time series regression with autoregressive integrated moving average (ARIMA) modeling to establish a model for forecasting inflation in Nigeria for the period 1981-2020. Akaike Information Criterion Corrected (AICC) and Bayesian Information Criterion (BIC) were used to select the best model among competing models. Through these methods, regression with ARIMA (0,0,1) error was selected as the most parsimonious model for inflation forecasting in Nigeria. The results of the out-sample-forecast show that a high inflation rate will be experienced by the end of 2023, and between 2024 and 2030, the inflation rate will be alternating but will maintain a lower rate than that of 2023.
Research Interests:
Commodity price forecasts play an important role in terms of guidance to economic agents and policymakers in developing countries. This paper focuses on the development of exponential smoothing state space (ETS) innovation models for... more
Commodity price forecasts play an important role in terms of guidance to economic agents and policymakers in developing countries. This paper focuses on the development of exponential smoothing state space (ETS) innovation models for forecasting monthly export price indexes of four different commodities in Nigeria for the period 2000-2021. The data are secondary and collected from the Central Bank of Nigeria (CBN) Statistical Bulletin. After examining the possible models using the computed information criteria, the results showed that the exponential smoothing state space model
Research Interests:
This paper examines the impact of fiscal policy on inflation in Nigeria for the period 1981-2021. The study adopts autoregressive distributed lag (ARDL) bounds testing approach. The unit root results revealed that other variables apart... more
This paper examines the impact of fiscal policy on inflation in Nigeria for the period 1981-2021. The study adopts autoregressive distributed lag (ARDL) bounds testing approach. The unit root results revealed that other variables apart from inflation were stationary after first difference. The bound test result shows that the variables cointegrate. The ARDL long-run result shows that oil revenue has a negative significant impact on inflation, while government recurrent expenditure and capital expenditure have positive impact on the inflation, with the impact of recurrent expenditure significant. The results further showed that the impacts of oil revenue, recurrent expenditure, and capital expenditure in long-run was also maintained in the short run. Lastly, exchange rate and total imports have negative impact on inflation, while foreign direct investment inflow has a positive impact on inflation in both long-and short-run. The government should review her fiscal policy to adjust recurrent and capital expenditure, and to reduce import by encouraging consumption of local products.
Research Interests:
This study uses time series regression with autoregressive integrated moving average (ARIMA) modeling to establish a model for forecasting inflation in Nigeria for the period 1981-2020. Akaike Information Criterion Corrected (AICC) and... more
This study uses time series regression with autoregressive integrated moving average (ARIMA) modeling to establish a model for forecasting inflation in Nigeria for the period 1981-2020. Akaike Information Criterion Corrected (AICC) and Bayesian Information Criterion (BIC) were used to select the best model among competing models. Through these methods, regression with ARIMA (0,0,1) error was selected as the most parsimonious model for inflation forecasting in Nigeria. The results of the out-sample-forecast show that a high inflation rate will be experienced by the end of 2023, and between 2024 and 2030, the inflation rate will be alternating but will maintain a lower rate than that of 2023.
Research Interests:
Hospital. A total of 5267 and 4371 patients' records in 2015 and 2022 respectively were included. Over weight and obesity (BMI) were considered the most prevalent CVD risk factor, followed by hypertension. Compared to females, males were... more
Hospital. A total of 5267 and 4371 patients' records in 2015 and 2022 respectively were included. Over weight and obesity (BMI) were considered the most prevalent CVD risk factor, followed by hypertension. Compared to females, males were 1.48 times more likely to have CVD in 2015 which increased in 2022. Compared to non-alcohol consumers, those that take alcohol every day were 0.74 times more likely in 2015 and 0.35 times more likely in 2017 to have CVD. Compared to non-smokers, every day smokers were 1.87 times more likely in 2015 and 3.08 times more likely in 2022 to have CVD. Persons with high cholesterol compared to low cholesterol were 2.45 times more likely in 2015 and 1.54 times more likely in 2022 to have CVD. Furthermore, persons with hypertension compared to nonhypertensive persons were 3.61 times more likely in 2015 and 5.17 times more likely in 2022 to have CVD, and those with diabetes status compared with non-diabetic persons were 2.95 times more likely in 2015 and 2.01 times more likely in 2022 to have CVD. Preventable cardiovascular risk factor should be prime target of both public health and healthcare providers across the state and the entire nation.
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This paper examines the application of ARIMA model on forecasting Infant Mortality Rate (IMR) in Nigeria. It undertakes a comparison of Male and Female. The data used were obtained from the website of the World Bank. The data consist of... more
This paper examines the application of ARIMA model on forecasting Infant Mortality Rate (IMR) in Nigeria. It undertakes a comparison of Male and Female. The data used were obtained from the website of the World Bank. The data consist of annual Infant Mortality Rate (per 1000 live births) on Male and Female from 1980 to 2019. Akaike’s Information Criterion (AIC) was used to select the best model and Time Series Plot, Residual Plot and the Histogram for Residuals were used to check the forecast adequacy of the selected models. The results of this study showed that the Infant Mortality Rate (IMR) on Male and Female attain stationarity after the second differencing. ARIMA (2,2,0) with AIC of -9.94 and ARIMA (1,2,0) with AIC of -13.10 were selected for forecasting Infant Mortality Rate for Male and Female respectively. The results further showed that the selected ARIMA models are adequate for forecasting male and female Infant Mortality Rate, and that by 2030, Male infant mortality rate ...
Research Interests:
In the study, some bivariate distributions were developed from mixture model offspring, using the Independent (Product) distribution approach. These developments are categorized under the IID and IInD: where the Bivariate Exponential... more
In the study, some bivariate distributions were developed from mixture model offspring, using the Independent (Product) distribution approach. These developments are categorized under the IID and IInD: where the Bivariate Exponential distribution, Bivariate Lindley distribution and Bivariate Juchez distribution are constructed as IIDs; and Bivariate Exponential-Lindley distribution, Bivariate Exponential-Juchez distribution and Bivariate Lindley-Juchez distribution as (IInDs). The properties of these distributions which involve: the shape of the bivariate PDFs, moments, moment generating function, mean, covariance and coefficient of correlation, maximum likelihood estimator, reliability analysis, renewal property and probability patterns; are studied across the distributions. Finally, under renewal properties, functions are derived which can model two-dimensional queuing and renewal processes, for events where the arrival and service times are dependent.
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Tuberculosis (TB) is one of the leading causes of mortality in developing countries in world. It is an airborne disease spread through inhaling. This study investigated the cases of tuberculosis at Nnamdi Azikiwe University Teaching... more
Tuberculosis (TB) is one of the leading causes of mortality in developing countries in world. It is an airborne disease spread through inhaling. This study investigated the cases of tuberculosis at Nnamdi Azikiwe University Teaching Hospital (NAUTH) Nigeria. The TB data used in this study are secondary data sourced from NAUTH tuberculosis register from January 2005 to December 2021. This study is a retrospective cohort and time series analysis of all the cases of tuberculosis diagnosed and confirmed. The forecast methods used in this study are that of Box-Jenkins approach and Holt-Winters. Out of 395070 presumptive cases, 52311 (11.7%) were diagnosed with tuberculosis, and male had the highest rate. The age group that was most affected was the group 35-44 (24.68%). 8.4% of the tuberculosis diagnosed tested positive. ARIMA (0,0,1) (2,0,1) [12] was selected as the best model, used in forecasting tuberculosis cases for the next four years. Tuberculosis cases predicted showed that for t...
Research Interests:
Tuberculosis (TB) is one of the leading causes of mortality in developing countries in world. It is an airborne disease spread through inhaling. This study investigated the cases of tuberculosis at
Research Interests:
In the study, some bivariate distributions were developed from mixture model offspring, using the Independent (Product) distribution approach. These developments are categorized under the IID and II n D: where the Bivariate Exponential... more
In the study, some bivariate distributions were developed from mixture model offspring, using the Independent (Product) distribution approach. These developments are categorized under the IID and II n D: where the Bivariate Exponential distribution, Bivariate Lindley distribution and Bivariate Juchez distribution are constructed as IIDs; and Bivariate Exponential-Lindley distribution, Bivariate Exponential-Juchez distribution and Bivariate Lindley-Juchez distribution as (II n Ds). The properties of these distributions which involve: the shape of the bivariate PDFs, moments, moment generating function, mean, covariance and coefficient of correlation, maximum likelihood estimator, reliability analysis, renewal property and
Research Interests:
Research Interests:
This paper examines the application of autoregressive integrated moving average (ARIMA) model and regression model with ARIMA errors for forecasting Nigeria's GDP. The data used in this study are collected from the official website of... more
This paper examines the application of autoregressive integrated moving average (ARIMA) model and regression model with ARIMA errors for forecasting Nigeria's GDP. The data used in this study are collected from the official website of World Bank for the period 1990-2019. A response variable (GDP) and four predictor variables are used for the study. The ARIMA model is fitted only to the response variable, while regression with ARIMA errors is fitted on the data as a whole. The Akaike Information Criterion Corrected (AICc) was used to select the best model among the selected ARIMA models, while the best model for forecasting GDP is selected using measures of forecast accuracy. The result showed that regression with ARIMA(2,0,1) errors is the best model for forecasting Nigeria's GDP.
Research Interests:
This paper examines the application of ARIMA model on forecasting Infant Mortality Rate (IMR) in Nigeria. It undertakes a comparison of Male and Female. The data used were obtained from the website of the World Bank. The data consist of... more
This paper examines the application of ARIMA model on forecasting Infant Mortality Rate (IMR) in Nigeria. It undertakes a comparison of Male and Female. The data used were obtained from the website of the World Bank. The data consist of annual Infant Mortality Rate (per 1000 live births) on Male and Female from 1980 to 2019. Akaike's Information Criterion (AIC) was used to select the best model and Time Series Plot, Residual Plot and the Histogram for Residuals were used to check the forecast adequacy of the selected models. The results of this study showed that the Infant Mortality Rate (IMR) on Male and Female attain stationarity after the second differencing. ARIMA (2,2,0) with AIC of-9.94 and ARIMA (1,2,0) with AIC of-13.10 were selected for forecasting Infant Mortality Rate for Male and Female respectively. The results further showed that the selected ARIMA models are adequate for forecasting male and female Infant Mortality Rate, and that by 2030, Male infant mortality rate will decline to 58.54 per 1000 live births while Female infant mortality rate will decline to 44.50 per 1000 live births.
Research Interests:
This paper examines the application of ARIMA model on forecasting Infant Mortality Rate (IMR) in Nigeria. It undertakes a comparison of Male and Female. The data used were obtained from the website of the World Bank. The data consist of... more
This paper examines the application of ARIMA model on forecasting Infant Mortality Rate (IMR) in Nigeria. It undertakes a comparison of Male and Female. The data used were obtained from the website of the World Bank. The data consist of annual Infant Mortality Rate (per 1000 live births) on Male and Female from 1980 to 2019. Akaike's Information Criterion (AIC) was used to select the best model and Time Series Plot, Residual Plot and the Histogram for Residuals were used to check the forecast adequacy of the selected models. The results of this study showed that the Infant Mortality Rate (IMR) on Male and Female attain stationarity after the second differencing. ARIMA (2,2,0) with AIC of-9.94 and ARIMA (1,2,0) with AIC of-13.10 were selected for forecasting Infant Mortality Rate for Male and Female respectively. The results further showed that the selected ARIMA models are adequate for forecasting male and female Infant Mortality Rate, and that by 2030, Male infant mortality rate will decline to 58.54 per 1000 live births while Female infant mortality rate will decline to 44.50 per 1000 live births.