scholarly journals Arima forecasting of the prevalence of anemia in children in Sierra Leone

2020 ◽  
Vol 4 ◽  
pp. 67-70
Author(s):  
Smartson. P. NYONI ◽  
Thabani NYONI
Keyword(s):  
Sierra Leone ◽  
Diagnostic Tests ◽  
Time Series Data ◽  
Series Data ◽  
Optimal Model ◽  
Out Of Sample ◽  
Annual Time Series ◽  
Annual Time ◽  
Prevalence Of Anemia ◽  
Children Under 5

Using annual time series data on the prevalence of anemia in children under 5 years of age in Sierra Leone from 1990 – 2016, the study makes predictions for the period 2017 – 2025. The study applies the Box-Jenkins ARIMA methodology. The diagnostic ADF tests show that the AS series under consideration is an I (0) variable. Based on the AIC, the study presents the AR (4) model, also known as the ARIMA (4, 0, 0) model as the optimal model. The diagnostic tests further show us that the presented model is stable and its residuals are not serially correlated. The results of the study indicate that the prevalence of anemia in children in Sierra Leone will rise over the out-of-sample period. By 2025, the country will be having a prevalence of anemia in children of approximately 78.6%.

scholarly journals Arima Forecasting of ohe prevalence of Anemia in children in Myanmar

2020 ◽  
Vol 4 ◽  
pp. 62-66
Author(s):  
Smartson. P. NYONI ◽  
Thabani NYONI
Keyword(s):  
Diagnostic Tests ◽  
Public Health Policy ◽  
Time Series Data ◽  
Series Data ◽  
Policy Makers ◽  
Annual Time Series ◽  
Parsimonious Model ◽  
Annual Time ◽  
Prevalence Of Anemia ◽  
Children Under 5

Using annual time series data on the prevalence of anemia in children under 5 years of age in Myanmar from 1990 – 2016, the study makes predictions for the period 2017 – 2025. The study applies the Box-Jenkins ARIMA methodology. The diagnostic ADF tests show that, AM, the series under consideration is an I (0) variable. Based on the AIC, the study presents an AR (4) model, which is also called the ARIMA (4, 0, 0) model. This has been found to be the parsimonious model. The diagnostic tests further reveal that the presented model is quite stable and its residuals are not serially correlated. The results of the research indicate that the prevalence of anemia in children in Myanmar will rise from approximately 54.5% in 2017 to almost 64.8% by 2025. This means that anemia is not yet under control in the country. This is a wake up call to both public health policy makers and nutrition specialists in the country. 

scholarly journals Arima forecasting of the prevalence of anemia in children in Myanmar

2020 ◽  
Vol 4 ◽  
pp. 57-61
Author(s):  
Smartson. P. NYONI ◽  
Thabani NYONI
Keyword(s):  
Diagnostic Tests ◽  
Public Health Policy ◽  
Time Series Data ◽  
Series Data ◽  
Policy Makers ◽  
Annual Time Series ◽  
Parsimonious Model ◽  
Annual Time ◽  
Prevalence Of Anemia ◽  
Children Under 5

Using annual time series data on the prevalence of anemia in children under 5 years of age in Myanmar from 1990 – 2016, the study makes predictions for the period 2017 – 2025. The study applies the Box-Jenkins ARIMA methodology. The diagnostic ADF tests show that, AM, the series under consideration is an I (0) variable. Based on the AIC, the study presents an AR (4) model, which is also called the ARIMA (4, 0, 0) model. This has been found to be the parsimonious model. The diagnostic tests further reveal that the presented model is quite stable and its residuals are not serially correlated. The results of the research indicate that the prevalence of anemia in children in Myanmar will rise from approximately 54.5% in 2017 to almost 64.8% by 2025. This means that anemia is not yet under control in the country. This is a wake up call to both public health policy makers and nutrition specialists in the country. 

scholarly journals Arima forecasting of the prevalence of anemia in children in Myanmar

2020 ◽  
Vol 5 ◽  
pp. 51-55
Author(s):  
Smartson. P. NYONI
Keyword(s):  
Time Series ◽  
Diagnostic Tests ◽  
Time Series Data ◽  
Series Data ◽  
Policy Makers ◽  
Annual Time Series ◽  
Parsimonious Model ◽  
Annual Time ◽  
Prevalence Of Anemia ◽  
Children Under 5

Using annual time series data on the prevalence of anemia in children under 5 years of age in Myanmar from 1990 – 2016, the study makes predictions for the period 2017 – 2025. The study applies the Box-Jenkins ARIMA methodology. The diagnostic ADF tests show that, AM, the series under consideration is an I (0) variable. Based on the AIC, the study presents an AR (4) model, which is also called the ARIMA (4, 0, 0) model. This has been found to be the parsimonious model. The diagnostic tests further reveal that the presented model is quite stable and its residuals are not serially correlated. The results of the research indicate that the prevalence of anemia in children in Myanmar will rise from approximately 54.5% in 2017 to almost 64.8% by 2025. This means that anemia is not yet under control in the country. This is a wake up call to both public health policy makers and nutrition specialists in the country. Using annual time series data on the prevalence of anemia in children under 5 years of age in Myanmar from 1990 – 2016, the study makes predictions for the period 2017 – 2025. The study applies the Box-Jenkins ARIMA methodology. The diagnostic ADF tests show that, AM, the series under consideration is an I (0) variable. Based on the AIC, the study presents an AR (4) model, which is also called the ARIMA (4, 0, 0) model. 

scholarly journals Total new HIV infections in Togo: a box-jenkins arima approach

2020 ◽  
Vol 5 ◽  
pp. 16-21
Author(s):  
Smartson. P. NYONI ◽  
Thabani NYONI
Keyword(s):  
Time Series ◽  
Diagnostic Tests ◽  
Time Series Data ◽  
Hiv Infections ◽  
Series Data ◽  
Optimal Model ◽  
Annual Time Series ◽  
Annual Time ◽  
Normally Distributed

Using annual time series data on the total number of new HIV infections in Togo from 1990 – 2018, the study makes predictions for the period 2019 – 2030. The research applies the Box-Jenkins ARIMA methodology. The diagnostic ADF tests show that, J, the series under consideration is an I (2) variable. Based on the AIC, the study presents the ARIMA (0, 2, 2) model as the optimal model. The diagnostic tests further indicate that the presented model is indeed stable and its residuals are not serially correlated and are also normally distributed. The results of the study indicate that the total number of new HIV infections in Togo is projected to decline sharply by 53.5% from the estimated 4791 new infections in 2019 to approximately 2229 new infections by 2030.

scholarly journals Total New Hiv Infections In Gabon: A Box-Jenkins Arima Approach

2020 ◽  
Vol 3 (10) ◽  
pp. 1-5
Author(s):  
Smartson. P. NYONI ◽  
Thabani NYONI
Keyword(s):  
Time Series ◽  
Diagnostic Tests ◽  
Time Series Data ◽  
Hiv Infections ◽  
Series Data ◽  
Sample Period ◽  
Out Of Sample ◽  
Annual Time Series ◽  
Parsimonious Model ◽  
Annual Time

Using annual time series data on the total number of new HIV infections in Gabon from 1990 – 2018, the study makes predictions for the period 2019 – 2030. The paper employs the Box-Jenkins ARIMA methodology. The diagnostic ADF tests show that, H, the series under consideration is an I (1) variable. Based on the AIC, the study presents the ARIMA (1, 1, 0) model as the parsimonious model. The diagnostic tests further reveal that the presented model is very stable and its residuals are not serially correlated. The results of the study indicate that the total number of new HIV infections in Gabon is likely to continue declining over the out-of-sample period.

scholarly journals Analyzing neonatal deaths in Zimbabwe using box-jenkins arima models

2020 ◽  
Vol 3 (7) ◽  
pp. 39-50
Author(s):  
Dr. Smartson. P. Nyoni ◽  
Mr. Thabani NyonI
Keyword(s):  
Time Series ◽  
Diagnostic Tests ◽  
Time Series Data ◽  
Series Data ◽  
Arima Models ◽  
Optimal Model ◽  
Neonatal Deaths ◽  
Annual Time Series ◽  
Annual Time ◽  
Policy Prescription

Using annual time series data on neonatal deaths in Zimbabwe from 1966 to 2018, we model and forecast number of neonatal deaths over the next 25 years using the Box – Jenkins ARIMA technique. Diagnostic tests such as the ADF tests show that Neonatal Deaths (ND) series is I (2). Based on the AIC, the study presents the ARIMA (8, 2, 0) model as the optimal model. The diagnostic tests further indicate that the presented model is stable and its residuals are stationary in levels. The results of the study reveal that the numbers of neonatal deaths per year are expected to decline sharply in the next 25 years. In order to keep on reducing neonatal deaths in Zimbabwe, the study offered a four-fold policy prescription.

scholarly journals Adults newly infected with hiv in burundi: a box-jenkins arima approach

2020 ◽  
Vol 4 ◽  
pp. 48-56
Author(s):  
Smartson P. NYONI ◽  
Thabani NYONI
Keyword(s):  
Time Series Data ◽  
Hiv Infections ◽  
Series Data ◽  
Annual Number ◽  
Optimal Model ◽  
Applied Model ◽  
Annual Time Series ◽  
And Control ◽  
Blue Print ◽  
Annual Time

Using annual time series data on the number of adults (ages 15 and above) newly infected with HIV in Burundi from 1990 – 2018, the study predicts the annual number of adults who will be newly infected with HIV over the period 2019 – 2025. The study applied the Box-Jenkins ARIMA methodology. The diagnostic ADF tests as well as correlogram analysis show that the G series under consideration is an I (2) variable. Based on the AIC, the study presents the ARIMA (0, 2, 1) model as the optimal model. The residual correlogram and the inverse roots of the applied model further reveal that the presented model is stable and suitable for forecasting new HIV infections in adults in Burundi. The results of the study indicate that the number of new HIV infections in adults in Burundi will most likely decline, over the period 2019 – 2023, from approximately 698 to almost 90 new HIV infections. By 2025, Burundi could experience her first zero new HIV infections in adults! This implies that, despite the fact that Vision Burundi 2025 is a highly ambitious blue-print; Vision Burundi 2025 will largely be achieved as far as HIV/AIDS prevention and control is concerned.

scholarly journals Open defecation in Kenya: A Box-Jenkins Arima Approach

2020 ◽  
Vol 5 ◽  
Author(s):  
Smartson. P. NYONI ◽  
Thabani NYONI
Keyword(s):  
Total Population ◽  
Time Series Data ◽  
Series Data ◽  
Annual Number ◽  
Policy Recommendation ◽  
Optimal Model ◽  
Open Defecation ◽  
Annual Time Series ◽  
The Government ◽  
Annual Time

Using annual time series data on the number of people who practice open defecation in Kenya from 2000 – 2017, the study predicts the annual number of people who will still be practicing open defecation over the period 2018 – 2021. The authors apply the Box-Jenkins ARIMA methodology. The diagnostic ADF tests show that the ODK series under consideration is an I (1) variable. Based on the AIC, the study presents the ARIMA (0, 1, 2) model as the optimal model. The diagnostic tests further indicate that the presented model is quite stable and its residuals are stationary in levels. The results of the study indicate that the number of people practicing open defecation in Kenya is likely to decline, although slightly, over the period 2018 – 2022, from approximately 9.9% to almost 8.2% of the total population. Hence, it is possible for Kenya to completely eliminate the practice of open defecation by 2030. The study basically suggested a 3-fold policy recommendation to be put into consideration, especially by the government of Kenya.

Income and Price Elasticities in India's Trade

1994 ◽  
Vol 19 (2) ◽  
pp. 13-20
Author(s):  
G S Gupta ◽  
H Keshava
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Series Data ◽  
Individual Country ◽  
Price Elasticities ◽  
The World ◽  
Annual Time Series ◽  
Income And Price Elasticities ◽  
Annual Time

This article by G S Gupta and H Keshava estimates the export and import functions for India both at the aggregate (rest of the world) as well as the important individual country levels using annual time series data for the period 1960-61 through 1990-91.

Government Partisanship, Labor Organization, and Macroeconomic Performance

1991 ◽  
Vol 85 (2) ◽  
pp. 539-556 ◽  
Author(s):  
R. Michael Alvarez ◽  
Geoffrey Garrett ◽  
Peter Lange
Keyword(s):  
Time Series Data ◽  
Organized Labor ◽  
Series Data ◽  
Labor Movements ◽  
Economic Policies ◽  
Macroeconomic Performance ◽  
Industrial Democracies ◽  
Annual Time Series ◽  
Left And Right ◽  
Annual Time

Governments of the Left and Right have distinct partisan economic policies and objectives that they would prefer to pursue. Their propensity to do so, however, is constrained by their desire for reelection. We argue that the ability of governments to further their partisan interests and preside over reelectable macroeconomic outcomes simultaneously is dependent on the organization of the domestic economy, particularly the labor movement. We hypothesize that there are two different paths to desirable macroeconomic performance. In countries with densely and centrally organized labor movements, leftist governments can promote economic growth and reduce inflation and unemployment. Conversely, in countries with weak labor movements, rightist governments can pursue their partisan-preferred macroeconomic strategies and achieve similarly beneficial macroeconomic outcomes. Performance will be poorer in other cases. These hypotheses are supported by analysis of pooled annual time series data for 16 advanced industrial democracies between 1967 and 1984.

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