Economic Freedom and Human Development Index. A Panel Data Analysis (2000- 2012).

2015 ◽  
Author(s):  
Miltiades N. Georgiou
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Human Development ◽  
Human Development Index ◽  
Economic Freedom ◽  
Panel Data Analysis ◽  
Development Index

scholarly journals Effect Of Human Development Index Fund on Economic Growth Through A Special Autonomy

2017 ◽  
Vol 18 (1) ◽  
pp. 50
Author(s):  
Irham Iskandar
Keyword(s):  
Economic Growth ◽  
Data Analysis ◽  
Panel Data ◽  
Human Development ◽  
Human Development Index ◽  
Panel Data Analysis ◽  
Research Development ◽  
Development Index ◽  
Is Research ◽  
Negative Effect

This study aims to determine the human development index on economic growth through the provision of special autonomy. The method used is research development with panel data analysis in 23 districts / cities. The results showed that the moderation between the human development index through special autonomy fund a significant negative effect on economic growth. It indicates the use of special autonomy funds for the human development index is still up, so the future is expected to need to be allocated according to the needs in the region, so that the special autonomy funds can effectively and efficiently.

scholarly journals Modeling Human Development Index of Bali with Spatial Panel Data Regression

2019 ◽  
Vol 4 (5) ◽  
pp. 132-137
Author(s):  
Mita Lasdiyanti ◽  
Eka N. Kencana ◽  
Putu Suciptawati
Keyword(s):  
Panel Data ◽  
Human Development ◽  
Human Development Index ◽  
Panel Data Analysis ◽  
Spatial Error ◽  
Development Index ◽  
Spatial Panel ◽  
Panel Data Regression ◽  
Data Regression ◽  
Spatial Panel Data

Human development index (HDI) is an index that represents the successfulness of human development in a region. For Bali, one of 34 provinces in Indonesia, the progress of HDI in the period 2010–2017 showed an increasing trend. In the year 2010, the Bali’s HDI is accounted for 70.10, gradually increase to 74.30 in the year 2017. However, in 2017 there are some regions with their HDIs are below of Bali’s HDI, namely Jembrana, Buleleng, Klungkung, Bangli, and Karangasem. The aim of this work is to model the HDI of 9 regencies of Bali so that the main determinant to increase the HDIs especially for the regencies with lower HDIs could be determined. The model consists of one dependent variable (HDI) with three indicators as the independent ones, there are (a) life expectancy, (b) education, and (b) standard of living. By applying spatial panel data analysis, five models were built i.e. CEM, FEM (individual), FEM (time), REM, and spatial error FEM to determine the effect of each indicator. The result shows the best model is spatial error FEM in which education has the biggest influence compare than the others.

scholarly journals Government Expenditure and Human Development in Indonesia

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Johan Beni Maharda ◽  
Bunga Zharfa Aulia
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Human Development ◽  
Human Development Index ◽  
Panel Data Analysis ◽  
Government Expenditure ◽  
Fixed Effect Model ◽  
Effect Model ◽  
Per Capita

This study aims to estimate the association between government expenditure and human development index (HDI) in Indonesia. Due to inequal HDI attainment, this study focuses on 12 provinces which categorized as provinces with low level of HDI in Indonesia. This study employs fixed effect model (FEM) panel data analysis on provincial level datasets from 2010 to 2018. This study found that the increase of government expenditure on education significantly increases HDI, while government expenditure on health has no significant association with HDI. Major finding of the study highlights the role of gross regional domestic product (GRDP) per capita in increasing HDI on 12 provinces in Indonesia. Keywords: Government expenditure on education, government expenditure on health, HDI, FEM.

scholarly journals Examining the Relationship Between Human Development Index and Socio-Economic Variables: A Panel Data Analysis

2018 ◽  
Vol 3 (2) ◽  
pp. 37
Author(s):  
Siti Ayu Jalil ◽  
Mohamad Nadzrul Kamaruddin
Keyword(s):  
Data Analysis ◽  
Life Expectancy ◽  
Human Development ◽  
Human Development Index ◽  
Health Expenditure ◽  
Fixed Effects ◽  
Panel Data Analysis ◽  
Development Index ◽  
Socio Economic Variables ◽  
Years Of Schooling

Human Development Index (HDI) measures the average achievements from three basic dimensions of human development: a long and healthy life, access to knowledge and a decent standard of living. This study is to investigate the impact of socio-economic variables represented by the three dimensions i.e. mean years of schooling, expected years of schooling, gross domestic product, life expectancy and health expenditure on HDI in fifteen selected developing countries within a 5-year period (2010-2014). The panel data analysis tested the pooled regression model, fixed effects and random effects models. The findings indicated that the Panel Fixed Effects Model (FEM) has proven to be the best model to describe the study. From the FEM model, four predictors have shown significant positive effect on human development index which are, the mean years of schooling, expected years of schooling, life expectancy and GDP per capita whereas, health expenditure is the only variable that shows insignificant relationship. Hence, it can be stated that in these fifteen selected nations despite education and higher GDP are essential to achieve a higher level of HDI, life expectancy is also perceived as a vital indicator to imply a better level of HDI.

scholarly journals PENGARUH DANA OTONOMI KHUSUS TERHADAP INDEKS PEMBANGUNAN MANUSIA KABUPATEN/KOTA DI PROVINSI ACEH

2020 ◽  
Vol 3 (4) ◽  
Author(s):  
Muhammad Hijrah Saputra
Keyword(s):  
Time Series ◽  
Panel Data ◽  
Human Development ◽  
Human Development Index ◽  
Panel Data Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Secondary Data ◽  
Development Index ◽  
Effect Model

This study aimed to determine the effect of the Special Autonomy Fund AgainstHuman Development Index in Aceh, to achieve these objectives, this study uses the Human Development Index (HDI) as the dependent variable and the SpecialAutonomy Fund (Autonomy) as independent variables. The data analyzed in thisstudy are secondary data from the reports on the realization of the Government's budget 23 districts / municipalities in the province of Aceh which was obtained through a survey BAPPEDA Aceh and the Central Statistics Agency (BPS) of Aceh. The data used are panel data which is a combination of Time Series and Cross Section. Data time series used is the 23 districts / cities in the period 2009 - 2012. The method used in this study is one of three in a panel data analysis techniques that pool (common) effect model, fixed effect model and random effect model. Based on data processing studies concluded that the SAF has a positive and significant effect on the Human Development Index, which the SAF increase in tandem with the increase in the Human Development Index. So it can be concluded that the increase in SAF positive effect on the Human Development Index in 23 districts / municipalities in the Aceh Province.

scholarly journals Determinan Ketimpangan Indeks Pembangunan Manusia di Provinsi Jambi

2020 ◽  
Vol 5 (2) ◽  
pp. 227
Author(s):  
Arniwita Arniwita ◽  
Deka Veronica ◽  
Ahmad Soleh
Keyword(s):  
Data Analysis ◽  
Human Development ◽  
Human Development Index ◽  
Hypothesis Test ◽  
Well Being ◽  
Poor People ◽  
Analysis Tool ◽  
Economic Variables ◽  
Development Index ◽  
Dependent Variables

The Human Development Index (HDI) is an index to measure human achievement and is one of the indicators used in looking at people's well-being in a region. The higher the HDI value in a region, the better the level of welfare in the region. So often HDI is considered to have been able to represent the welfare level of the population, because in the HDI includes elements that include economic and noneconomic variables. Non-economic variables are measured from the level of public education and the degree of public health. While economic variables are measured from income levels indicating people's purchasing power, the three are related to each other. However, if you look at the conditions in Jambi Province, there is an interesting phenomenon where the development of the government does not or lack a real impact on the improvement of the Human Development Index (HDI), so it is necessary to do this research. The purpose of this study is to analyze the inequality, influence and relationship of the variables of the human development index which includes Gross Regional Domestic Product (GRDP) per capita, the number of medical personnel, the number of basic health facilities, the number of poor people as well as the number of teachers in public elementary schools as dependent variables with the human development index (HDI) as dependent variables. The data analysis method used in this study is a qualitative and qualitative descriptive method of explanatory properties, using sekuder data in the period 2008-2017. The data analysis tool used in this study uses the usual Weighted Coefficient of Variation (CVw) method for the first problem, the subsequent regression of the data panel for the second problem and the person correlation for the third problem. The hypothesis test in this study shows that there is inequality in IPM-forming variables in Jambi Province, further influence and significant relationship between ipm-forming variable inequality and HDI in Jambi Province.

scholarly journals ANALISIS PENGARUH BELANJA PENDIDIKAN, BELANJA KESEHATAN, TINGKAT KEMISKINAN DAN PDRB TERHADAP IPM DI PROVINSI ACEH

2017 ◽  
Vol 3 (1) ◽  
pp. 51-69
Author(s):  
Muliza Muliza ◽  
Teuku Zulham ◽  
Chenny Seftarita
Keyword(s):  
Panel Data ◽  
Human Development ◽  
Government Spending ◽  
Human Development Index ◽  
Random Effect ◽  
Random Effect Model ◽  
Health Sector ◽  
City Governments ◽  
Development Index ◽  
Negative Effect

This study aims to look at the influence of the variables government spending on health and education, poverty and Gross Domestic Product (GDP) of the Human Development Index (HDI) in the province of Aceh. The analytical method used in this research is the analysis of the panel data regression model parameter estimation using a random effects model (REM). The data used is the panel data during the period 2010-2014. The results showed that the variables government spending on education and health sector no significant effect on the human development index, this happens because the district/city governments allocate their spending still more dominant that the type of expenditure that are not directly impact the IPM. While poverty variables significant negative effect on the human development index, then with reduced levels of poverty can enhance human development index. GRDP positive and significant effect on the human development index, which means that the GDP increases, IPM will also increase.Penelitian ini bertujuan untuk melihat pengaruh dari variabel-variabel belanja pemerintah pada sektor kesehatan dan pendidikan, tingkat kemiskinan serta Produk Domestik Regional Bruto (PDRB) terhadap Indeks Pembangunan Manusia (IPM) di Provinsi Aceh. Metode analisis yang digunakan dalam penelitian ini adalah analisis regresi data panel dengan estimasi parameter model menggunakan random effect model (REM). Data yang digunakan adalah data panel selama periode 2010-2014. Hasil penelitian menunjukan bahwa variabel pengeluaran pemerintah di sektor pendidikan dan kesehatan tidak berpengaruh signifikan terhadap indeks pembangunan manusia, hal ini terjadi karena pemerintah kabupaten/kota masih lebih dominan mengalokasikan belanjanya yang pada jenis belanja yang secara tidak lansung memberikan pengaruh terhadap IPM. Sedangkan variabel kemiskinan berpengaruh negatif dan signifikan terhadap indeks pembangunan manusia, maka dengan menurunnya tingkat kemiskinan dapat meningkatkan indeks pembangunan manusia. PDRB berpengaruh positif dan signifikan terhadap indeks pembangunan manusia, yang berarti PDRB meningkat maka IPM juga akan meningkat.

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