An Observation on the Disaggregation of Annual Time Series Data

1975 ◽  
Vol 24 (3) ◽  
pp. 352
Author(s):  
D. W. Balmer
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Series Data ◽  
Annual Time Series ◽  
Annual Time

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.

Subsidies and Fiscal Deficit in Post Reforms India

2014 ◽  
Vol 1 (1) ◽  
Author(s):  
Jasoda Jena ◽  
Chittaranjan Nayak
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
National Policy ◽  
Petroleum Products ◽  
Series Data ◽  
Fiscal Deficit ◽  
Annual Time Series ◽  
The Government ◽  
Economic Goods ◽  
Annual Time

The Government of India has been subsidising various economic goods, mainly food, fertiliser and petroleum. It is argued that subsidies are responsible for persistent high fiscal deficit over the years. The present paper attempts to study the trend of major subsidies given by the Government of India, and then examines whether all the forms of subsidies are uniformly responsible for fiscal deficit or otherwise. Based on annual time series data from 1992-93 to 2012-13, the study observes that in the post-reforms period, food and fertiliser subsidies have grown at a sharper rate than petroleum subsidies. The regression results also confirm that food and fertiliser subsidies have a positive and significant impact on fiscal deficit. The analysis of petroleum subsidies is more complicated. If we see only the explicit subsidies for petroleum products, then their rise is not significant over the post-reforms period, except for 2008-12. However, when we include the under-recoveries of Oil Marketing Companies (OMCs), the story of petroleum subsidies becomes completely different. While the effectiveness of subsidies vis-à-vis their fiscal burden need a detailed scrutiny, the present paper argues for a National Policy on Subsidies.

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 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. 

The Influence of Unemployment on the Level and Rate of Company Formation in Scotland, 1950–1984

1986 ◽  
Vol 18 (10) ◽  
pp. 1401-1404 ◽  
Author(s):  
R T Hamilton
Keyword(s):  
Time Series ◽  
Unemployment Rate ◽  
Time Series Data ◽  
Series Data ◽  
Yearly Variation ◽  
Self Employment ◽  
Annual Time Series ◽  
The Relationship ◽  
Annual Time

In this paper annual time-series data are used to examine the relationship between unemployment and both the level and the rate of new company registrations in Scotland between 1950 and 1984. Lagged unemployment rate and changes in this rate (also lagged) are shown to explain in excess of 90% of the yearly variation in registration activity. The results indicate the importance of those factors, for example, unemployment or the threat thereof, which act to ‘push’ individuals into self-employment.

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 Impact of Fiscal Deficit on Inflation in Sri Lanka: An Econometric Time Series Analysis

2016 ◽  
Vol 70 ◽  
pp. 8-13
Author(s):  
A.L.M. Aslam ◽  
S.M. Ahamed Lebbe
Keyword(s):  
Time Series ◽  
Sri Lanka ◽  
Price Index ◽  
Time Series Data ◽  
Consumer Price Index ◽  
Series Data ◽  
Fiscal Deficit ◽  
Annual Time Series ◽  
The Impact ◽  
Annual Time

There is a relationship between the fiscal deficit and inflation, which was confirmed empirically in several studies conducted in many countries. Sri Lanka has been encountering the problem of inflation for the recent years. But in Sri Lanka, this proposition has not yet been studied scientifically. Therefore, this study was going to fill this gap. The objective of this study was to test the impact of fiscal deficit on inflation in Sri Lanka. For this study, the annual time series data were used during the period of 1959 to 2013. The fiscal deficit, exchange rate, government expenditures and import outflow were used as independent variables while the Colombo consumer price index was considered as dependent variable. In addition, the multiple regressions model was used to test the impact of fiscal deficit on inflation. Based on the regression results, the fiscal deficit preserved the positive relationship with inflation in Sri Lanka at one percent significant level. Therefore, this study confirmed that the fiscal deficit accelerates the inflation in Sri Lanka.

scholarly journals Estimating Consumer Preferences for Food, Using Time Series Data of Pakistan

1997 ◽  
Vol 36 (2) ◽  
pp. 131-153 ◽  
Author(s):  
Abid A. Burki
Keyword(s):  
Time Series ◽  
Structural Change ◽  
Time Series Data ◽  
Consumer Preferences ◽  
Series Data ◽  
Data Set ◽  
Aids Model ◽  
Price And Income Elasticities ◽  
Annual Time Series ◽  
Annual Time

Consumer preferences for food and non-food items in Pakistan are frequently estimated by using data from the household surveys. However, structural change in consumer preferences, caused by changes in tastes, can be studied by using the annual time series data, a time series of cross sections, or the panel data. This paper uses Pakistan’s annual time series disappearance data for eight food commodities from 1972 to 1991 to study consumer behaviour. The existence and the nature of structural change is tested by using both the generalised axiom of revealed preference (GARP) and the first-difference LA/AIDS model. It turns out that GARP tests are low-powered as tests of structural change on our data-set. However, the results from the LA/AIDS model show a shift in consumer demand from gram (split) to chicken after 1982. The data set satisfies symmetry and homogeneity. The estimates of price and income elasticities are also consistent with economic theory. The implications of these results for policy are also discussed.

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