scholarly journals Peran Pertumbuhan Ekonomi Dalam Menurunkan Kemiskinan di Tingkat Provinsi di Indonesia Tahun 2004-2012

MODUS ◽  
2016 ◽  
Vol 28 (1) ◽  
pp. 91
Author(s):  
Denni Setiawan Jayadi ◽  
Aloysius Gunadi Brata
Keyword(s):  
Economic Growth ◽  
Poverty Reduction ◽  
Secondary Data ◽  
Data Bank ◽  
Fixed Effect Model ◽  
Negative Influence ◽  
Fixed Effect ◽  
Mining Sector ◽  
Effect Model ◽  
Panel Data Regression

Abstrak            Penelitian ini bertujuan untuk mengetahui dan menganalisis peran pertumbuhan ekonomi terhadap penurunan kemiskinan dilihat dari sektoral tahun 2004–2012. Variabel yang digunakan adalah jumlah penduduk miskin sebagai variabel dependen dan Produk Domestik Regional Bruto (PRDB) di sembilan sektor sebagai variabel independen. Data yang digunakan dalam penelitian ini merupakan data sekunder yang diperoleh dari terbitan world data bank. Metode analisis yang digunakan adalah regresi data panel dengan pendekatan model fixed effect. Dalam mengolah data, penulis menggunakan bantuan software Eviews 8.1.            Berdasarkan hasil estimasi di peroleh bahwa secara keseluruhan pertumbuhan ekonomi berpengaruh negatif dan signifikan terhadap kemiskinan di tingkat Provinsi di Indonesia. Selanjutnya dilihat dari segi sektoral ditemukan bahwa variabel sektor per-tambangan memiliki pengaruh yang negatif dan signifikan terhadap penurunan kemiskinan. Hal itu disebabkan adanya commodities boom terhadap komoditi hasil tambang. Sehingga sektor pertambangan bukanlah sektor yang menjadi kunci dalam penurunan kemiskinan namun terjadinya commodities boom memiliki pengaruh terhadap penurunan kemiskinan di Provinsi di Indonesia. Kata Kunci :  Fixed Effect, Kemiskinan, PDRB sektoral, pertumbuhan ekonomi, commodities boom. AbstractThis study aims to identify and analyze the role of economic growth on poverty reduction seen from sectors in 2004-2012. The variables used were the number of poverty as the dependent variable and the Gross Regional Domestic Product (GRDP) in nine sectors as independent variables. The data used in this research is secondary data obtained from the data published by the World Bank. The analytical method used is the panel data regression with fixed effect model approach. In processing the data, the authors using statistical software Eviews 8.1.Based on estimates obtained that overall economic growth is negative and have significant effect on poverty at the provincial level in Indonesia. Furthermore, in terms of sectoral found that variable per-mining sector has a negative influence and significant impact on poverty reduction. It was caused by the commodities boom of the commodity mined. So that the mining sector is not a sector that is key in reducing poverty, but the commodities boom have an impact on poverty reduction in the province in Indonesia. Keywords: Fixed Effect, poverty, the GDP sectoral, economic growth, commodities boom.

scholarly journals PERTUMBUHAN EKONOMI, DISPARITAS PENDAPATAN DAN KESEJAHTERAAN KABUPATEN/KOTA DI PROVINSI NUSA TENGGARA BARAT

GANEC SWARA ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 59
Author(s):  
BAIQ HIPZIWATY ◽  
PUTU KARISMAWAN ◽  
BAIQ ISMIWATY
Keyword(s):  
Economic Growth ◽  
Regression Analysis ◽  
Panel Data ◽  
Secondary Data ◽  
Fixed Effect Model ◽  
Income Disparity ◽  
The People ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

This study aims to analyze economic growth, income disparity and community welfare in the West Nusa Tenggara Province.     This research is a descriptive study using secondary data obtained from relevant agencies in the form of GRDP data, population, economic growth, HDI and per capita income between regencies / cities in NTB Province and data collection using the case method. With analytical procedures using Williamson index and panel data regression analysis.     The results showed that during the period of 2010-2016 the average economic growth of West Nusa Tenggara Province was 6.0%. The income disparity seen from the Williamson index in the 2010-2016 period is classified as a medium inequality criterion. The estimation results of the relationship between the variables of economic growth, income disparity and the welfare of the people of West Nusa Tenggara Province measured using HDI in 2010-2016 using panel data regression analysis with the Fixed Effect model (FEM), found that economic growth variables were positively related, but not significant to welfare society. The variable income disparity is significantly related to the welfare of the people of NTB Province.

scholarly journals PENERAPAN REGRESI DATA PANEL PADA ANALISIS PENGARUH INFRASTRUKTUR TERHADAP PRODUKTIFITAS EKONOMI PROVINSI-PROVINSI DI LUAR PULAU JAWA TAHUN 2010-2014

2018 ◽  
Vol 11 (1) ◽  
pp. 1-15
Author(s):  
Yosephine Magdalena Sitorus ◽  
Lia Yuliana
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Seemingly Unrelated Regression ◽  
Total Output ◽  
Economic Productivity ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

There is inequality between the economic growth of provinces in Java and outside of Java. The total area of Java  is only 6,77% from total area of Indonesia but the Growth Domestic Product (GDP) based on constant price in 2014, Java contributed 57,8% of the GDP total Indonesia. One cause that made this disparity is the development of infrastructure in outside Java is still weak. The development of infrastructure is a basic element for increasing total output production that later will increase the economic growth. However, there are so many problems that occur in developing the infrastructure in outside of Java. This study aimed to analyze the condition of infrastructure provinces outside Java in 2010-2014. The data used is the secondary data for 27 provinces outside of Java 2010-2014 from BPS. The analytical method used is panel data regression with fixed effect model and Seemingly Unrelated Regression (SUR) Model. Based on the results, the infrastructure that affects economic productivity significantly and positively is road infrastructure, health, and budget. Infrastructure that affects economic productivity significantly and negatively is the educational infrastructure. Water and electricity infrastructure did not significantly affect economic productivity.Keywords: Infrastructure, Economic productivity, Panel Data Regression, Fixed Effect Model

scholarly journals The impact of corruption on the economic growth in Bangladesh, India and Pakistan: An ARDL approach

2021 ◽  
Vol 12 (8) ◽  
pp. 2079-2093
Author(s):  
Md. Mamun Miah ◽  
Tahmina Akter Ratna ◽  
Shapan Chandra Majumder
Keyword(s):  
Economic Growth ◽  
Correction Term ◽  
Negative Relationship ◽  
Secondary Data ◽  
Fixed Effect Model ◽  
Positive Influence ◽  
Fixed Effect ◽  
Ardl Model ◽  
Effect Model ◽  
The Impact

Purpose of the study: Main purpose of the paper is to find out the impact of corruption on the economic growth of Bangladesh, India, and Pakistan. At the same time, our other objectives are to find the long and short-run effects of corruption on growth in these countries. Methodology: For conducting the study, we have taken the data from Bangladesh, India, and Pakistan. For this study necessary secondary data have been collected from 1990 to 2016 based on countries like Bangladesh, India, and Pakistan. Data for economic growth (dependent) and trade (independent) are collected from World Development Bank and data for corruption are taken from International Country Risk published by the PRS Group. The study has used ECM ARDL Model and the Fixed Effect Model.  Findings: The result of the fixed effect model shows a 1percent increase in corruption decreases GDP by 0.07 units and shows a negative relationship with economic growth. Again if trade increases by 1 percent then growth will increase by 0.09 units on average and shows a positive relationship with economic growth. ECM ARDL Model shows the positive coefficient of corruption but not significant but trade has a long-run positive influence on economic growth. The error correction term indicating that the adjustment is corrected by 70% in these three countries. Contributions: This paper may be helpful for existing literature gap and also for further research. It will be helpful for policy makers to control corruption in three countries.

scholarly journals IMPACT OF INVESTMENT, LABOR, AND INFRASTRUCTURE ON JAVA ISLAND ECONOMIC GROWTH 2011-2017

2018 ◽  
Vol 1 (3) ◽  
pp. 230-241
Author(s):  
Maya Aprilia Sari
Keyword(s):  
Economic Growth ◽  
Local Governments ◽  
Secondary Data ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Least Square ◽  
Clean Water ◽  
Domestic Investment ◽  
Central Java ◽  
Effect Model

The study aims to determine and analyze the effect of investment, labor, and infrastructure on economic growth in Java in 2011-2017. This research is a quantitative study using secondary data from six provinces in Java (DKI Jakarta, West Java, Central Java, Special Region of Yogyakarta, East Java and Banten) obtained from the Central Statistics Agency. Analysis of the data used in this study is panel regression of fixed effect model data using the General Least Square (GLS) method. The results showed that individually the domestic investment variable, labor, clean water infrastructure had a significant influence on economic growth while foreign investment had no significant effect on economic growth. Suggestions: 1) local governments are expected to increase the potential of each region to attract investors; 2) local governments are expected to create a conducive investment climate and facilitate investment licensing; 3) local governments are expected to increase the allocation of education funds and provide training in foreign languages ​​and skills to the workforce; 4) local governments should make better plans for the distribution of clean water and improve the efficiency of the use of clean water.© 2019, Universitas Negeri Semarang Penelitian bertujuan untuk mengetahui dan menganalisis pengaruh investasi,tenaga kerja, dan infrastruktur terhadap pertumbuhan ekonomi di Pulau Jawa tahun 2011-2017. Penelitian ini merupakan penelitian kuantitatif menggunakan data sekunder enam provinsi di Pulau Jawa (DKI Jakarta, Jawa Barat, Jawa Tengah, Daerah Istimewa Yogyakarta, Jawa Timur, dan Banten) yang diperoleh dari Badan Pusat Statistik.Analisis data yang digunakan pada penelitian ini adalah regresi data panel model fixed effect menggunakan metode General Least Square (GLS). Hasil penelitian menunjukkan bahwa secara individu variabel penanaman modal dalam negeri, tenaga kerja, infrastruktur air bersih memiliki pengaruh signifikanterhadap pertumbuhan ekonomi sedangkanpenanaman modal luar negeri tidak berpengaruh signifikan terhadap pertumbuhan ekonomi. Saran: 1) pemerintah daerah diharapkan meningkatkan potensi setiap daerah agar menarik para investor; 2) pemerintah daerah diharapkan menciptakan iklim investasi yang kondusif dan mempermudah perizinan investasi; 3) pemerintah daerah diharapkan meningkatkan alokasi dana pendidikan dan memberikan pelatihan bahasa asing dan ketrampilan kepada tenaga kerja; 4) pemerintah daerah hendaknya membuat perencanaan distribusi air bersih yang lebih baik lagi dan meningkatkan efisiensi penggunaan air bersih.

scholarly journals ANALYSIS OF INFRASTRUCTURE EFFECT ON INDONESIA'S ECONOMIC GROWTH YEAR 2007 - 2014

2019 ◽  
Vol 4 (02) ◽  
pp. 121
Author(s):  
Rismanto Irawan ◽  
Deden Dinar Iskandar
Keyword(s):  
Economic Growth ◽  
Positive Impact ◽  
Capital Expenditure ◽  
Secondary Data ◽  
Fixed Effect Model ◽  
Social Infrastructure ◽  
Institutional Infrastructure ◽  
Effect Model ◽  
Panel Data Regression ◽  
Increase Productivity

<p><em>A production process requires inputs to be used to produce output. The input according to Solow is the capital and labor described in the Cobb – Douglas function. Infrastructure can be said as capital in an effort to increase productivity, since labor requires supporting facilities that can increase their productivity. Therefore infrastructure is seen as having an important role in driving economic growth, so that adequate infrastructure is expected to have a positive impact on economic growth. This study aims to analyze the influence of the availability of infrastructure that is divided into economic infrastructure, social infrastructure and institutional infrastructure, on the economy in Indonesia which is described by the GDP. This study uses secondary data in 33 provinces in Indonesia in 2007-2014. This study uses panel data regression using the fixed effect model and correction of Heteroscedasticity and Autocorrelation Consistent (HAC). </em><em>Based on the results of econometric regression, it is known that the variables of road, electricity, education, health and capital expenditure have a positive and significant effect. While the employee expenditure variable has a positive but not significant relationship. In addition, it is known that telephone variables have a negative and insignificant relationship. The results of this study also show that electricity infrastructure has the biggest influence on economic growth..</em></p>

scholarly journals Analisis Regresi Panel pada Pemodelan Tingkat Kematian Bayi di Provinsi Sulawesi Selatan

2020 ◽  
Vol 2 (2) ◽  
pp. 115
Author(s):  
Syafruddin Side ◽  
S. Sukarna ◽  
Raihana Nurfitrah
Keyword(s):  
Panel Data ◽  
Infant Mortality ◽  
Regression Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Least Square ◽  
Dummy Variable ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

Penelitian ini membahas mengenai estimasi parameter model regresi data panel pada pemodelan tingkat kematian bayi di Provinsi Sulawesi Selatan dari tahun 2014 sampai dengan 2015. Data yang digunakan adalah data sekunder dari Dinas Kesehatan Provinsi Sulawesi Selatan yang berupa jumlah kematian bayi, berat bayi lahir rendah, persalinan yang ditolong oleh tenaga kesehatan, penduduk miskin, bayi yang diberi ASI ekslusif dan rumah tangga berperilaku bersih sehat di seluruh Kabupaten/Kota di Provinsi Sulawesi Selatan tahun 2014-2016. Analisis data dilakukan dengan menggunakan penghitungan manual dan dengan menggunakan software EViews 9. Pembahasan dimulai dari melakukan estimasi parameter model regresi data panel, menentukan model regresi data panel terbaik, , menguji asumsi model regresi data panel, pengujian signifikansi parameter dan interpretasi model regresi. Dalam penelitian ini diperoleh kesimpulan yaitu estimasi model regresi data panel terbaik dengan pendekatan fixed effect model.Kata kunci:Regresi Data Panel, Kematian Bayi, Fixed Effect Model, Least Square Dummy Variable. This research discusses about parameter estimation of panel data regression model of infant mortality level modelling in South Sulawesi from 2014 to 2015. The data used were secondary data from Dinas Kesehatan Provinsi Sulawesi Selatan in the form of number of infant mortality, low weight of infant, childbirth rescued by health workers, poor population, infants who were given exclusive breast milk and household that behaves well in the whole district/town in South Sulawesi year 2014-2016. Data analysis was performed using the calculation manually and by using EViews 9 software. The discussion started from doing parameter estimation of panel data regression model, determining the best panel data regression model, testing the assumption of panel data regression model, testing the signification of parameter and interpretation of regression model. Conclusion of this research are the estimation of regression model is the best panel data regression model with fixed effects model approach.Keywords:Panel Data Regression, Infant Mortality, Fixed Effect Model, Least Square Dummy Variable.

scholarly journals Pengaruh ketimpangan pendapatan dan kemiskinan terhadap pertumbuhan ekonomi antar pulau di Indonesia

2019 ◽  
Vol 14 (2) ◽  
pp. 55-66
Author(s):  
Selamet Rahmadi ◽  
Parmadi Parmadi
Keyword(s):  
Economic Growth ◽  
Fixed Effect Model ◽  
Model Estimation ◽  
Estimation Model ◽  
Hausman Test ◽  
Pooled Data ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
Estimation Models

This study aims to find out and analyze the effect of income inequality and poverty on economic growth on each island in Indonesia. To answer these objectives, panel data regression (pooled data) is used. The results of the study show: (1). the best regressions on estimation models are based on the Chow and the Hausman test using the Fixed Effect Model estimation model for each island in Indonesia. (2). Income and poverty inequality negatively affected economic growth in all islands in Indonesia during the 2015-2018.

scholarly journals Inequality and Economic Growth: An Analysis of 8-Panels

2017 ◽  
Vol 3 (2) ◽  
pp. 173
Author(s):  
Khadijah A. Idowu ◽  
Yusuf Bababtunde Adeneye
Keyword(s):  
Economic Growth ◽  
Panel Data Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Specific Effect ◽  
Developed Countries ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Effect Model ◽  
The World

<p><em>Purpose: This paper investigates the effects of inequality on economic growth in the world using continental approach.</em><em></em></p><p><em>Design/methodology:<strong> </strong>Gini Coefficient and Gross Domestic Products (GDP) per capita were used to measure inequality and economic growth respectively. The study conducted a panel data analysis of the relationship between inequality and economic growth. The data span from 1991-2015. Five countries were selected each from seven continents and were also pooled together to constitute a single panel for 35 countries, thus establishing 8 panels. The Hausman test was conducted to determine whether a random or fixed effect model best fit pooled countries analysis or not.</em><em></em></p><p><em>Findings: Findings revealed that for the developing countries, high income inequality retards economic growth while for the developed countries such as Europe countries; the situation seems to be different. European countries as revealed in the findings showed that developed countries have benefited from inequality which has significantly and positively affected their economic growth. The results for Panel II (Asia countries) and Panel III (Europe countries) are in line with the study of Forbes (2000) and Li and Zou (1998) that documented that inequality boosts economic growth. Importantly, we found that inequality positively affects economic growth for Panels/Continents with fixed effect model while inequality negatively affects economic growth for Panels/Continents with random effect model.</em></p><p><em>Research Limitation: The study did not control for each continent differences. For African countries, weak institutional settings and environment is a key factor contributing to high inequality.</em><em></em></p><p><em>Originality: The paper was able to know the specific effect of inequality on economic growth in each continent in the World. This documents continents that have benefited from inequality and those that inequality has greatly affected their economies negatively.</em><em></em></p>

Dana pihak ketiga, Inflasi dan Pembiayaan Mudharabah terhadap Non Performing Financing pada Bank Islam di Indonesia dan Malaysia

2019 ◽  
Vol 16 (2) ◽  
pp. 74-80
Author(s):  
Afrillia Tiara Putri ◽  
Saadah Yuliana ◽  
Anna Yulianita
Keyword(s):  
Panel Data ◽  
Secondary Data ◽  
Fixed Effect Model ◽  
Third Party ◽  
Coefficient Of Determination ◽  
Islamic Banks ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
Negative Effect

This study aimed to analyze the influence of third party funds, inflation, and mudharabah against non performing financing on Islamic Banks in Indonesia and Malaysia. Data used is secondary data. The method used in this analysis is the panel data regression. The results showed that in partial third party fund and mudharabah significant negative effect on the Non Performing Financing, while inflation is positive and not significant to the Non Performing Financing. Variable Third Party Funds, Inflation and mudharabah jointly significant effect on Non Performing Financing. Based on the regression equation fixed effect model results show the results of the coefficient of determination (R2) is 0.369198, or 36.91 per cent means that the variation of the variable third party funds, inflation and mudharabah have an influence on the non performing financing for the coefficient of determination, while the rest 63.09 percent influenced by variables outside the model

ANALISIS:PENGARUH;DEMOKRASI TERHADAP;PERTUMBUHAN;EKONOMI INDONESIA;BAGIAN TIMUR

2019 ◽  
Vol 1 (3) ◽  
pp. 877
Author(s):  
Vina Indriani ◽  
Melti Roza Adry
Keyword(s):  
Economic Growth ◽  
Significant Influence ◽  
Fixed Effect Model ◽  
Free Variable ◽  
Fixed Effect ◽  
Analysis Tool ◽  
Control Variables ◽  
Eastern Indonesia ◽  
Effect Model ◽  
Educational Variables

The;purpose of;this research is;to;know:and;analyze:>(1);The;influence of;democracy;on;the economic;growth;of;eastern;Indonesia. (2) Investment influence on the economic growth of eastern Indonesia. (3) The influence of education on economic growth in eastern Indonesia. (4) The influence of democracy, investment, and education jointly towards the;economic;growth;of;eastern;Indonesia.The variables used;in;this study were economic growth as a bound variable and democracy as a free variable, as well as investment and educational variables as control variables. The research used the 17 provincial data panel in eastern Indonesia in 2009-2017. Data is obtained from the Central Statistics agency.The analysis tool used in this study is a regression panel with the model chosen is the Fixed Effect Model. The results showed that: (1) democracy is positive and significant to the economic growth of Eastern Indonesia, (2) investments have positive and significant impact on the economic growth of Eastern Indonesia, (3) education Positive and significant influence on the economic growth of Eastern Indonesia, (4) Democracy, investment, and education jointly significantly]influence{the}economic?growth/of/eastern Indonesia.

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