scholarly journals Time Series Analysis of Global Energy Indices: Logarithmic and Normalized Techniques for Developmental Studies

2022 ◽  
Vol 9 (1) ◽  
pp. 1-19
Author(s):  
S N Nnamchi ◽  
Z O Jagun ◽  
M A Ijomah ◽  
O A Nnamchi ◽  
J D Busingye
Keyword(s):  
Carbon Dioxide ◽  
Energy Consumption ◽  
Gross Domestic Product ◽  
Human Development ◽  
Human Development Index ◽  
Carbon Dioxide Emission ◽  
Oil Price ◽  
Domestic Product ◽  
Development Index ◽  
Energy Indices

Diverse opinions exist in the time series analysis of energy and related indices, difference in methodology, sample size, and time variation. This paper will make a conscious effort to converge the divergent outlooks. To accomplish this essential task, five energy indices consisting of energy consumption (EC), gross domestic product (GDP), carbon dioxide emission (CDE), the human development index (HDI), and oil price (OP) were selected. Two analytical methods were adopted, namely logarithmic and normalized techniques, which are designed to complement each other in drawing unfalsified statistical inference concerning the causality between the energy indices. The methods were subjected to four statistical tests and analyses: the augmented Dickey-Fuller, cointegration, pairwise Granger causality, and vector error correction model (VECM). Irrespective of prevailing challenges, both logarithmic and normalized techniques unanimously filtered out causalities. This consisted of neural flow between oil price and energy consumption, gross domestic product and carbon dioxide emission, and energy consumption and the human development index, unidirectional flow between energy consumption and the human development index, oil price and energy consumption, gross domestic product and carbon dioxide emission, and the human development index and oil price, whereas a normalized technique established bidirectional flow between gross domestic product and the human development index, and the human development index and oil price. Pertinently, the research suggests appropriate policies that will generate sustainable development in all the causal directions. Assiduously, the overwhelming agreement between both techniques at the 0.05 level is recommended for further validation with more modern econometric tests.

scholarly journals PENGARUH PRODUK DOMESTIK BRUTO (PDB) DAN INDEKS PEMBANGUNAN MANUSIA (IPM) TERHADAP ANGKA KEMISKINAN DI INDONESIA

2010 ◽  
Vol 8 (2) ◽  
pp. 357
Author(s):  
Muhammad Sri Wahyudi Suliswanto
Keyword(s):  
Gross Domestic Product ◽  
Human Development ◽  
Human Development Index ◽  
Random Effect ◽  
Random Effect Model ◽  
Negative Influence ◽  
Domestic Product ◽  
Development Index ◽  
Effect Model ◽  
Independent Variable

Poverty is classic issue faced by most developing countries and is one of economic indicators to view public welfare level in any region. The research aimed to analyze effect of Gross Domestic Product (GDP), and human development index on poverty in Indonesia. Analysis used quantitative with Random Effect Model (REM) method in Panel Data with time series year 2006 to 2008. Anaysis result concluded that all independent variable simultaneously had significant effect on poverty variable in Indonesia and partially Gross Domestic Product (GDP) variable had significant negative influence on poverty with α 20%, and Human Development Index (HDI) variable had significant negative influence on poverty with α 5%.

scholarly journals Macroeconomic, demographic and human developmental correlates of physical activity and sitting time among South American adults

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
André O. Werneck ◽  
◽  
Kabir P. Sadarangani ◽  
Robinson Ramírez-Vélez ◽  
Se-Sergio Baldew ◽  
...  
Keyword(s):  
Physical Activity ◽  
Population Density ◽  
Gross Domestic Product ◽  
Human Development ◽  
Human Development Index ◽  
Total Population ◽  
Sitting Time ◽  
Domestic Product ◽  
South American ◽  
Development Index

Abstract Background Our aim was to investigate the association of macroeconomic, human development, and demographic factors with different domains of physical activity and sitting time among South American adults. Methods We used data from nationally representative samples in Argentina (n = 26,932), Brazil (n = 52,490), Chile (n = 3866), Colombia (n = 14,208), Ecuador (n = 19,883), Peru (n = 8820), and Uruguay (n = 2403). Our outcomes included leisure time (≥150 min/week), transport (≥10 min/week), occupational (≥10 min/week), and total (≥150 min/week) physical activity, as well as sitting time (≥4 h/day), which were collected through self-reported questionnaires. As exposures, gross domestic product, total population, population density, and human development index indicators from the most updated national census of each country were used. Age and education were used as covariates. Multilevel logistic regressions with harmonized random effect meta-analyses were conducted, comparing highest vs. lowest (reference) tertiles. Results Higher odds for transport physical activity were observed among the highest tertiles of total population (ORmen: 1.41; 95% CI: 1.23–1.62), ORwomen: 1.51; 95% CI:1.32–1.73), population density (ORmen: 1.36; 95% CI: 1.18–1.57, ORwomen: 1.49; 95% CI: 1.30–1.70), and gross domestic product (ORmen: 1.16; 95% CI: 1.00–1.35, ORwomen: 1.39; 95% CI: 1.20–1.61). For leisure physical activity, women living in departments with higher human development index presented 18% higher odds for being active, and for total physical activity a similar estimate in both sexes was observed among those who live in more populated areas. No consistent associations were found for occupational physical activity and sitting time. Conclusion Macroeconomic, demographic and human development indicators are associated with different domains of physical activity in the South American context, which can in turn guide policies to promote physical activity in the region.

Time indicator of the Human Development Index

2017 ◽  
Vol 28 (1) ◽  
pp. 273-296
Author(s):  
R Ibar-Alonso ◽  
C Cosculluela-Martínez ◽  
GJD Hewings
Keyword(s):  
Life Expectancy ◽  
Gross Domestic Product ◽  
United Nations ◽  
Human Development ◽  
Human Development Index ◽  
Domestic Product ◽  
Discriminant Functions ◽  
Development Index ◽  
Fisher Discriminant ◽  
The United Nations

The Human Development Index, computed by the United Nations, has been challenged since it does not measure the real development of a country. It needs to be combined with other indexes and ratios (poverty, Gini index). Using the same data as the United Nations, an additional dimension (time) is added to create a Time Human Development Index (THDI) where the weights differ for each cluster of countries. Fisher discriminant functions classify countries in each period of time, allowing different weights of the variables for the same country each year. Results suggest that when the Literacy and gross enrolment rates decrease in the four countries occupying the lower positions in the THDI, the THDI falls. In those countries where the THDI increases, gross domestic product and life expectancy rates do not seem to be positively correlated to the THDI, while the gross enrolment rate also increases. Thus, gross enrolment and literacy rates are variables related to the evolution of THDI; while, surprisingly, gross domestic product and life expectancy has few influence in its evolution.

scholarly journals Government Spending, Gross Domestic Product, Human Development Index (Evidence from East Java Province)

2020 ◽  
Author(s):  
Farida Rahmawati ◽  
Meirna Nur Intan
Keyword(s):  
Local Government ◽  
Gross Domestic Product ◽  
Human Development ◽  
Government Spending ◽  
Human Development Index ◽  
Capita Income ◽  
Gdp Per Capita ◽  
Domestic Product ◽  
Development Index ◽  
Per Capita

Government spending is expected to improve the Human Development Index (HDI) in order to increase public welfare. Theoretically, if the number of government expenditure is increasing then the Human Development Index (HDI) will be higher as well. Based on earlier research, it was found few differences about the result of influence Government spending to Human Index. The purpose of the study was to analyze the influence of government spending and Gross Domestic Product to the Human Development Index of East Java Province (during 2014-2017). The research method using descriptive quantitative approach. Local government expenditures were analyzed by direct local government spending by looking at three aspects namely employees expenditure, spending on goods and services, and capital expenditures. Whereas, for the GDP per capita income is analyzed based on three aspects: production, income, and expenditure. Then the human development index to see the effects of these two variables based on three dimensions that exist in the human development index healthiness dimensions, dimensions of knowledge, and economic dimensions. The results showed that the local government spending income and the GDP per capita income has a significant effect on the human development index. Government spending has a significant influence on the educational dimension, while GDP per capita has a significant effect on the purchasing power of people thus affecting the economic dimension. Keywords: Government spending, Gross Domestic Product, Human Development Index

scholarly journals The relationship between macro-socioeconomics determinants and COVID-19 vaccine distribution

2021 ◽  
Vol 8 (4) ◽  
pp. 655-664
Author(s):  
Ali Roghani ◽  
Keyword(s):  
Gross Domestic Product ◽  
Human Development ◽  
Human Development Index ◽  
Ordinary Least Squares ◽  
Domestic Product ◽  
Development Index ◽  
Successful Vaccine ◽  
Vaccine Distribution ◽  
The Relationship ◽  
Over Time

<abstract> <p>Since coronavirus disease 2019 (COVID-19) has continued to spread globally, many countries have started vaccinations at the end of December 2020. This research examines the relationship between COVID-19 vaccine distribution and two macro-socioeconomics measures, including human development index and gross domestic product, among 25 countries for two points in time, including February and August 2021. The COVID-19 dataset is a collection of the COVID-19 data maintained by Our World in Data. It is a daily updated dataset and includes confirmed cases, vaccinations, deaths, and testing data. Ordinary Least Squares was applied to examine how macro-socioeconomic measures predict the distribution of the COVID-19 vaccine over time.</p> <sec> <title>Results</title> <p>The results indicate that a higher gross domestic product per capita is positively associated with higher COVID-19 vaccine distribution, and this relationship becomes more robust over time. However, some countries may have more successful vaccine distribution results regardless of their gross domestic product. In addition, the result shows human development index does not have a significant relationship with vaccine distribution.</p> </sec><sec> <title>Conclusion</title> <p>Economic measures may be counted as a more vital indicator for vaccine distribution as they have a more direct relationship distribution with health infrastructure than social measures such as human development index.</p> </sec></abstract>

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