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 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.

ANALISIS PENGARUH INDEKS PEMBANGUNAN MANUSIA DAN TINGKAT PENGANGGURAN TERBUKA TERHADAP KEMISKINAN DI INDONESIA

2019 ◽  
Vol 2 (2) ◽  
pp. 77-89
Author(s):  
Saparuddin Mukhtar ◽  
Ari Saptono ◽  
As’ad Samsul Arifin
Keyword(s):  
Regression Analysis ◽  
Data Analysis ◽  
Human Development ◽  
Unemployment Rate ◽  
Human Development Index ◽  
Secondary Data ◽  
Lagrange Multiplier Test ◽  
Development Index ◽  
Analysis Techniques ◽  
Negative Effect

Abstract - This study aims to determine the effect of Human Development Index and Open Unemployment to poverty in Indonesia. The data in this study are secondary data about the human development index, the opened unemployment rate, and the percentage of poverty. The data is obtained from panel data of 33 provinces in Indonesia for 4 years from 2011 to 2014. The data analysis techniques uses regression analysis by using Random Effects based on the results of the Lagrange Multiplier test. The results showes that the Human Development Index hasa significant negative effect to poverty. Meanwhile, the level of opened unemployment has no significant effect to poverty in Indonesia. Keywords: Human Development Index, Opened Unemployment Rate, Poverty

scholarly journals Faktor-Faktor yang Mempengaruhi Tingkat Pengangguran di Kabupaten Jember

2017 ◽  
Vol 4 (1) ◽  
pp. 117
Author(s):  
Riza Firdhania ◽  
Fivien Muslihatinningsih
Keyword(s):  
Economic Growth ◽  
Data Analysis ◽  
Human Development ◽  
Minimum Wage ◽  
Unemployment Rate ◽  
Human Development Index ◽  
Descriptive Analysis ◽  
Linear Regression Analysis ◽  
Secondary Data ◽  
Development Index

This research describes the relation between variables of population, inflation, minimum wage, economic growth, and humandevelopment index toward the unemployment rate in Jember. The type of data used in this research was secondary data in theform of ‘time series’ obtained from Jember Department of Labor and Central Bureau of Statistics in the year of 2002-2013.The research method was a kind of statistical descriptive analysis and multiple linear regression analysis. Moreover, theresearcher used partial test (T-test), simultaneous test (F-test), and coefficients determination test (R2) for the hypothesis.Whereas the assumption test was conducted in the use of normality, multicollinearity, heteroscedasticity, and autocorrelationtest. From the result of the data analysis, it confirmed that the population positively and significantly affected theunemployment rate in Jember. The variables of inflation, minimum wage, and human development index negatively andsignificantly affected the unemployment rate in Jember. Whereas the variables of economic growth positively and significantlyaffected unemployment rate in Jember. Finally, the result of the data analysis highlighted the variables of population,inflation, minimum wage,economic growth, and human development index that simultaneously and significantly affectedunemployment rate in Jember.

scholarly journals DETERMINASI PERTUMBUHAN EKONOMI DI TUJUH NEGARA ASEAN PERIODE TAHUN 1996-2013

Media Ekonomi ◽  
2015 ◽  
Vol 23 (2) ◽  
pp. 107
Author(s):  
Desyana Eka Pramasty ◽  
Lydia Rosintan
Keyword(s):  
Economic Growth ◽  
Foreign Direct Investment ◽  
Data Analysis ◽  
Panel Data ◽  
Direct Investment ◽  
Panel Data Analysis ◽  
Foreign Debt ◽  
National Income ◽  
Negative Effect ◽  
Asean Countries

<p><em>Economic growth is also one of the most important indicators</em><em> </em><em>in determining the standard of living of people in a country, because of an increase in the production capacity of an economy that is manifested in the form of national income. Economic growth is an indication of the success of economic development, measured by comparing, for example, for domestic size, Gross Domestic Product (GDP) in the current year with the previous year. This study aimed to analyze the factors that affect economic growth in seven ASEAN countries period from 1996-2013. This study use panel data analysis. The factors that affect economic growth in seven ASEAN countries, namely foreign debt, foreign direct investment, and the rate of inflation. Based on panel data analysis of the results showed that the foreign debt has negative effect and significant on economic growth, foreign direct investment has positive effect and significant on economic growth and inflation rate has negative effect and significant on economic growth in seven ASEAN countries period from 1996-2013.</em></p>

scholarly journals Analisis Situasi Pembangunan Manusia di Jawa Tengah

2020 ◽  
Vol 3 (1) ◽  
pp. 12
Author(s):  
Laeli Sugiyono
Keyword(s):  
Economic Growth ◽  
Data Analysis ◽  
Human Development ◽  
Human Development Index ◽  
Secondary Data ◽  
Cross Sectional ◽  
Development Index ◽  
Central Java ◽  
Cartesian Diagram

<p>This study aims to analyze the disclosure distribution of the position regency/city in Central Java based on the linkage of Economic Growth (EG) and Human Development Index (HDI). The study uses secondary data in the form of cross-sectional regional regency/city based on EG and HDI components. Data analysis uses regency/city distribution plot diagram based on EG and HDI components in the Cartesian diagram which divides the space into 4 Quadrants, namely: Quadrant I of the regency/city distribution plots with high EG and HDI, Quadrant II of the regency/city distribution plots with low EG and high HDI, Quadrant III of the regency/city distribution plots with high EG and low HDI, and Quadrant IV of the regency/city distribution plots with low EG and HDI. This study concludes that the position of cities in Central Java in general is in line with the Quadrant I group, the HDI of regency/city in the area of the ex-Semarang and ex-Surakarta residency is in Quadrant I. Other regencies/cities are spread in Quadrant II, III, and IV.</p><p><strong>Keywords</strong><strong> : </strong>human development index, economic growth, Central Java, distribution plot</p><p> </p>

scholarly journals MEMODELKAN KEMISKINAN PENDUDUK PROVINSI BALI DENGAN REGRESI DATA PANEL

2018 ◽  
Vol 7 (3) ◽  
pp. 219
Author(s):  
KADEK BUDINIRMALA ◽  
NI LUH PUTU SUCIPTAWATI ◽  
KETUT JAYANEGARA ◽  
I PUTU EKA NILA KENCANA
Keyword(s):  
Economic Growth ◽  
Human Development ◽  
Human Development Index ◽  
Total Population ◽  
Panel Data Analysis ◽  
Fixed Effect Model ◽  
Poor People ◽  
Development Programs ◽  
Development Index ◽  
The Poor

One indicator of the success of development programs undertaken is the declining percentage of the poor, defined as the ratio of the number of people classified as poor to the total population. For Bali province, despite its economic growth is higher than national rate; 6.03 percent and 6.24 percent compared to 4.88 percent and 5.02 percent in 2015 and 2016, respectively; the poor are still observed in this province by 4.15 percent of its 4.2 million population in September 2016. In order to make development programs in Bali more effective to decrease the number of poor people, significant determinants of poor have to be recognised. The purpose of this work is to model and to determine the significant factor(s) that affect the percentage of poor in Bali province by applying panel data analysis. Percentage of poor for period 2007 to 2015 is positioned as the dependent variable while economic growth, unemployment rate, labor force participation rates, total population, and human development index as the independent ones. We found the best model to describe the causal relationship among variables is fixed effect model and two predictors, the economic growth rate and human development index, were significant in affecting the number of poor in Bali province.

scholarly journals Foreign Aid, Corruption, Economic Growth Rate and Development Index in Nigeria: The ARDL Approach

2020 ◽  
Vol 11 (5) ◽  
pp. 348
Author(s):  
Amenawo Ikpa Offiong ◽  
Glory Sunday Etim ◽  
Rebecca Oliver Enuoh ◽  
Stephen Ekpo Nkamare ◽  
Godwin Bassey James
Keyword(s):  
Economic Growth ◽  
Growth Rate ◽  
Foreign Aid ◽  
Human Development ◽  
Human Development Index ◽  
Positive Impact ◽  
Economic Growth Rate ◽  
Development Index ◽  
Ex Post ◽  
Negative Effect

Foreign aid when properly utilized is expected to grow the economy of the receiving nation. Over the years Nigeria has benefitted from foreign aid inflows in a bid to stabilize its economy and build its infrastructure. This study desires to look into how the various foreign aid components (humanitarian aids, project aids and programme aids) have impacted the Nigerian economic growth rate and human development index giving the prevailing corruption index in the country as a moderating variable. Ex-post facto research design was adopted and data obtained from the Central Bank of Nigeria (CBN) Statistical Bulletin from 1990 to 2019. The study adopted autoregressive distributive lag (ARDL) techniques. It was revealed that as a result of the corruption perception index, there was a significant negative effect of foreign aid on the growth rate of Nigeria economy in the long run, while having a significant positive impact on human development index as well. In short run, foreign aids had a significant positive effect on the growth rate of the Nigerian economy, but an insignificant negative effect on human development index. However, government is encouraged to ensure that foreign aid is effectively channeled into agriculture, health, education and other productive areas.

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.

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