scholarly journals Effect of Special Allocation Funds (DAK), Capital Expenditures, and Investment on Economic Growth in the Sulawesi Region

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Fera Nur Ariyani Ibrahim ◽  
Irawati Abdul
Keyword(s):  
Economic Growth ◽  
Significant Influence ◽  
Capital Expenditure ◽  
Random Effect ◽  
Random Effect Model ◽  
Secondary Data ◽  
Capital Expenditures ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

This study aims to analyze the effect of Special Allocation Funds, Capital Expenditures and Investment on Economic growth in the Sulawesi region. The data used are secondary data obtained from Simreg Bappenas and the Central Statistics Agency during 2007-2016. The unit of analysis is 6 provinces in the Sulawesi region. This study uses a panel data regression model with the Random Effect Model (REM) method. The results of this study indicate that, (i) the Special Allocation Fund has a negative and significant effect on economic growth in the Sulawesi region. (ii) Capital expenditure shows a positive and significant influence on economic growth in the Sulawesi region. (iii) Investment shows a positive and significant influence on economic growth in the Sulawesi region.Keywords: Special Allocation Funds, Capital Expenditures, Investment, Economic Growth, Random Effect Model (REM).

scholarly journals Pengaruh Pendidikan, Pengangguran, dan Kemiskinan terhadap Ketimpangan Pendapatan di Indonesia

2019 ◽  
Vol 8 (3) ◽  
pp. 250
Author(s):  
Hindun Hindun ◽  
Ady Soejoto ◽  
Hariyati Hariyati
Keyword(s):  
Data Analysis ◽  
Income Inequality ◽  
Random Effect ◽  
Random Effect Model ◽  
Secondary Data ◽  
Ministry Of Education ◽  
Effect Model ◽  
Panel Data Regression ◽  
Analysis Technique ◽  
Data Regression

This research aims to analyze the effect of education, unemployment, and poverty on income inequality in Indonesia, both partially and simultaneously. This research uses secondary data with a quantitative approach. The type of research used is the type of associative research. The variables in this study are education, unemployment, poverty, and income inequality — data source from BPS and the Ministry of Education and Culture. The data analysis technique used is panel data regression analysis with cross-section 34 provinces and time series for 2015-2018. The results of the research obtained the random effect model, the best models. The results of data analysis show that education and poverty had a partial effect on income inequality in Indonesia, while unemployment had not to affect income inequality. Simultaneously, education, unemployment, and poverty affect income inequality in Indonesia. However, education, unemployment, and poverty can only explain 22.37% of the effect on income inequality in Indonesia. The rest is influenced by factors outside the model.

scholarly journals PENGARUH CURRENT RATIO, DEBT TO EQUITY RATIO, DAN EARNING PER-SHARE TERHADAP HARGA SAHAM

2017 ◽  
Vol 11 (1) ◽  
Author(s):  
Arry Widodo ◽  
Renda Puspita Dewi
Keyword(s):  
Stock Prices ◽  
Random Effect ◽  
Random Effect Model ◽  
Secondary Data ◽  
Share Price ◽  
Current Ratio ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
Equity Ratio

This study also aimed to determine the effect of Current Ratio (CR), Debt to Equity Ratio (DER), and Earning per Share (EPS) to the Price Stock either partially or simultaneously. Secondary data collected based on time series and cross section from the 2008-2012 from 26 companies Costumer Goods sector. By using panel data regression analysis techniques and the Chow test and Hausman test shows that the model used in the estimation of the data is the Random Effect Model. The results showed that the independent variables, EPS significant effect on stock prices. While CR and partially DER no significant effect on stock prices. Simultaneously, CR, DER, and EPS significant effect on stock prices. Keywords: Current Ratio, Debt to Equity Ratio, Earnings per Share, Price Stock

scholarly journals Pengaruh pad, dau, dak terhadap ipm dengan belanja modal sebagai variabel intervening (studi pada kabupaten/kota di provinsi papua tahun 2009 -2013)

2017 ◽  
Vol 22 (2) ◽  
Author(s):  
Ayu Aldi Raviyanti ◽  
Sri Rahayu ◽  
Dewa Putra Krishna Mahardika
Keyword(s):  
Human Development ◽  
Human Development Index ◽  
Capital Expenditure ◽  
Random Effect ◽  
Random Effect Model ◽  
Composite Index ◽  
Development Index ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

One way to measure the success or performance of a country or region in the field of human development used the Human Development Index (HDI). Human Development Index (HDI) is a composite index to measure the achievement of human development based on a number of basic components of quality of life. The purpose of this study is to determine how much Local Genuine Revenue (PAD), General Allocation Fund (DAU), Special Allocation Fund (DAK), Human Index Development (HDI) and Capital Expenditure in the Regencies/Cities of Papua Provinci for years 2009-2013, as well as determine the influence of PAD, DAU and DAK to HDI with Capital Expenditure as an intervening variable either simultaneously or partially. The method that used in this research is panel data regression using Random Effect Model (REM) with research period of year 2009-2013 using software Eviews 8.0. Total population in this research were 29 regencies/cities. By using purposive sampling, obtained sample of 24 regencies/cities. The results of this study indicate that PAD, DAU, and DAK jointly is influenced on Human Development Index with Capital Expenditure as an intervening variable. Partially, PAD is influenced of positive on HDI through Capital Expenditure, DAU is influenced of positive on HDI through Capital Expenditure, while DAK is not influenced on HDI through Capital Expenditure.

scholarly journals Pemodelan Pertumbuhan Ekonomi Provinsi Sulawesi Selatan dengan Menggunakan Regresi Data Panel

2020 ◽  
Vol 2 (3) ◽  
pp. 158
Author(s):  
Misriani Suardin ◽  
Muhammad Nadjib Bustan ◽  
Ansari Saleh Ahmar
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Total Population ◽  
Random Effect ◽  
Random Effect Model ◽  
South Sulawesi ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
Human Capital Index

Abstract. Economic growth is a process for change the economic condition a country or regional by continuously for the better condition as long as definite period. Economic growth in South Sulawesi for 2013-2016 have up and down because many factors have influence it. Like jobless, human capital index, regional revenue, expenditure, and total population. This research was conducted to determine the factors that influence economic growth in South Sulawesi by using data panel regression methods. Panel data regression is a regression by using panel data. Panel data is a statistics analysis method that combines between time series data and cross section data. The result indicates that the result if the regression analysis on the =5% show that the best panel data regression model is random effect model and human capital index variable have significant effect on economic growth with probability value about 0,0227. Meanwhile, jobless, regional revenue, expenditure, and total population no significant.Keywords: Panel Data Regression, Economic Growth, Common Effect Model, Fixed Effcet Model, Random Effect Model

scholarly journals KETIMPANGAN PEMBANGUNAN EKONOMI REGIONAL KALIMANTAN

2020 ◽  
Vol 3 (1) ◽  
pp. 22-25
Author(s):  
Mutia Madina ◽  
Muzdalifah M
Keyword(s):  
Economic Development ◽  
Panel Data ◽  
Quantitative Research ◽  
Random Effect ◽  
Random Effect Model ◽  
Secondary Data ◽  
Research Approach ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

Abstrack- This research was conducted to (1) Know the economic development in  Kalimantan region from 2011 to 2018; (2) Analyze the effect of regional share, proportional shift, and competitive shift on inequality in economic development. The data analysis technique used are: the first, Klassen typology analysis as a descriptive approach, and the second, the panel data regression analysis with random effect model estimation as a quantitative research approach. This research uses secondary data. Klassen's typological analysis showed the results that not all the provinces have positive growth every year. The analysis of panel data regression showed the results that the regional share and the competitive shift do not affect the development disparities which occurred in Kalimantan. Meanwhile, the proportional shifts affect the imbalance of development which occurred in Kalimantan region. Keywords: Economic Development Inequality, Klassen Typology, Regional Share, Proportional Shift, Competitive Shift. Abstrak- Penelitian ini dilakukan untuk (1) Mengetahui perkembangan perekonomian region kalimantan mulai tahun 2011 sampai 2018; (2) Menganalisis pengaruh regional share, proportional shift, dan competitive shift terhadap ketimpangan pembangunan ekonomi.Teknik analisa data yang digunakan yaitu pertama analisis tipologi klassen sebagai pendekatan deskriptif dan yang kedua yaitu analisis regresi data panel dengan estimasi random effect model sebagai pendekatan penelitian kuantitatif. Penelitian ini menggunakan data sekunder.Analisis tipologi klassen menunjukkan hasil bahwa tidak semua provinsi memiliki pertumbuhan positif setiap tahunnya. Analisis regresi data panel menunjukkan hasil bahwa regional share dan competitive shift tidak mempengaruhi ketimpangan pembangunan yang terjadi di regional Kalimantan. Sedangkan proportional shift mempengaruhi ketimpangan pembangunan yang terjadi di regional Kalimantan. Kata kunci : Ketimpangan Pembangunan Ekonomi, Tipologi Klassen, Regional Share, Proportional Shift, Competitive Shift.

Tingkat Kemiskinan di Sumatra Selatan dan Analisisnya

2020 ◽  
Vol 8 (2) ◽  
pp. 127-133
Author(s):  
Doni Putra ◽  
Rifki Khoirudin
Keyword(s):  
Research Method ◽  
Random Effect ◽  
Random Effect Model ◽  
Poverty Rate ◽  
Variable Number ◽  
Regression Method ◽  
Poverty Level ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

This study aims to determine the factors that affect the poverty rate of regencies / cities in South Sumatra Province in 2011 to 2017. In this study the factors that affect poverty rates are related to unemployment, HDI, MSE, and population. The research method used is the panel data regression method using the help of Eviews software. The final thanks is the Random Effect Model. The results of this study are the variable Number of Population has a significant effect on the level of poverty in the District / City in South Sumatra Province. However, the Unemployment Rate Variable, HDI, and UMK were not significant to the poverty level in the regencies / cities in South Sumatra Province.

scholarly journals Analysis Of Effect Of ZIS (Zakat, Infaq, And Shadaqah), Regional Domestic Products Of Bruto, Regional Minimum Wage And Inflation On Levels Poverty In Indonesia 2012 – 2016

2019 ◽  
Vol 2 (2) ◽  
pp. 193-211
Author(s):  
Fiky Nila Mustika ◽  
Eni Setyowati ◽  
Azhar Alam
Keyword(s):  
Panel Data ◽  
Random Effect ◽  
Random Effect Model ◽  
Secondary Data ◽  
Minimum Wages ◽  
Effect Model ◽  
Panel Data Regression ◽  
The Impact ◽  
Poverty Levels ◽  
Domestic Products

This study investigated the impact of ZIS (Zakat, Infaq, and Sadaqah) Gross Regional Domestic Products, Regional Minimum Wages, and Inflation on Poverty Levels in Indonesia during the 2012-2016 period. .This paper used secondary data in the panel data form. This research conducted a quantitative approach using panel data regression. Based on the results of the panel data testing, the best model chosen is the Random Effect Model (REM). Variables of gross regional domestic products and regional minimum wages have a significant effect on poverty levels in Indonesia while the variables of zakat, infaq, and shadaqah (ZIS) and inflation do not influence the level of poverty in Indonesia.

scholarly journals DIVERSIFIKASI EKSPOR NON MIGAS INDONESIA KE PASAR NON TRADISIONAL

2020 ◽  
Vol 14 (2) ◽  
pp. 215-238
Author(s):  
Hotsawadi Harahap ◽  
Widyastutik
Keyword(s):  
United Arab Emirates ◽  
Oil And Gas ◽  
Random Effect ◽  
Random Effect Model ◽  
Structural Match ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
Oil Exports

Abstrak Penelitian ini bertujuan untuk menganalisis diversifikasi ekspor non migas Indonesia ke pasar non tradisional. Metode penelitian yang digunakan adalah analisis statistik deskriptif dengan pendekatan pengelompokan (clustering), Structural Match Index dan Demand Index, serta regresi data panel. Hasil penelitian menunjukkan bahwa negara yang diidentifikasikan sebagai negara non tradisional potensial adalah Brazil, Pantai Gading, Mesir, Georgia, Jamaica, Kazakhstan, Kuwait, Myanmar, Nigeria, Norway, Oman, Pakistan, Russian Federation, Trinidad and Tobago, Turkey, United Arab Emirates, dan Uruguay. Hasil regresi data panel menunjukkan bahwa Random Effect Model merupakan model yang terbaik untuk menjelaskan faktor-faktor yang memengaruhi ekspor non migas Indonesia ke negara non tradisional. Hasil regresi menunjukkan bahwa GDP riil negara tujuan, populasi negara tujuan, nilai tukar riil, FDI dan kualitas pelabuhan Indonesia berpengaruh signifikan secara statistik terhadap ekspor non migas Indonesia ke negara non tradisional potensial tersebut. Beberapa rekomendasi kebijakan yang perlu dilakukan untuk meningkatkan ekspor non migas ke negara tujuan non tradisional diantaranya perlu dilakukan intelejen pasar mengenai kebutuhan dan selera dari masing-masing negara non tradisional atas produk Indonesia, peningkatan kualitas pelabuhan Indonesia dan kebijakan tambahan yang memberikan insentif untuk menarik Foreign Direct Investment ke Indonesia. Kata Kunci: Diversifikasi Ekspor, Demand Index, Non traditional, Random Effect Model, Structural Match Index   Abstract This study aims to analyze the diversification of Indonesia's non-oil and gas exports to non-traditional markets. The research method used is descriptive statistical analysis with a clustering approach, Structural Match Index and demand index, and panel data regression. The results showed that countries identified as potential non-traditional countries were Brazil, Ivory Coast, Egypt, Georgia, Jamaica, Kazakhstan, Kuwait, Myanmar, Nigeria, Norway, Oman, Pakistan, Russian Federation, Trinidad and Tobago, Turkey, United Arab Emirates, and Uruguay. The panel data regression results show that the random effect model is the best model to explain the factors that influence Indonesia's non-oil exports to non-traditional countries. The results show that the real GDP of the destination country, the population of the destination country, the real exchange rate, FDI and the quality of Indonesia's ports have a statistically significant effect on Indonesia's non-oil exports to these potential non-traditional countries. Then, in this study there are several policy recommendations that need to be done to increase non-oil and gas exports to non-traditional destination countries including market intelligence regarding the needs and tastes of each non-traditional country for Indonesian products, improving the quality of Indonesian ports and additional policies that provide incentives to attract Foreign Direct Investment to Indonesia. Keywords:  Export Diversification, Demand Index, Non-traditional, Random Effect Model, Structural Match Index JEL Classifications: F13, F15, F18

scholarly journals Analisis Faktor-Faktor yang Mempengaruhi Jumlah Penduduk di Kota Semarang Menggunakan Metode Regresi Data Panel

2019 ◽  
Vol 12 (2) ◽  
pp. 36-41
Author(s):  
Prizka rismawati Arum
Keyword(s):  
Panel Data ◽  
Random Effect ◽  
Geographical Area ◽  
Random Effect Model ◽  
Factors Affecting ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
The Relationship ◽  
Number Of Births

Residents are all people who live in the geographical area of Indonesia for six months or more and or those who have been domiciled for less than six months but aim to settle. Population growth is caused by two components, namely: fertility and mortality. To find out how big the relationship between the  population and the number of births and deaths in each sub-district of Semarang, must observed in several specific time periods and places at once. So in this study, the panel data regression method was used. In panel data regression testing, the results show that the panel data regression model formed to determine the factors that influence the level of population is the random effect model. In this model all assumptions are fulfilled. Significant factors affecting population are number of births. Births and deaths affect the population of 99.95% and the remaining 0.05% is influenced by other factors not examined Penduduk adalah semua orang yang berdomisili di wilayah geografis Indonesia selama enam bulan atau lebih dan atau mereka yang berdomisili kurang dari enam bulan tetapi bertujuan menetap. Pertumbuhan penduduk diakibatkan oleh dua komponen yaitu: fertilitas dan mortalitas. Untuk mengetahui seberapa besar keterkaitan antara jumlah penduduk dengan jumlah kelahiran dan kematian di setiap kecamataan Kota Semarang, harus diamati dalam beberapa periode waktu tertentu dan beberapa tempat secara bersamaan. Sehingga dalam penelitian ini digunakan metode regresi data panel. Dalam pengujian regresi data panel, didapatkan hasil bahwa Model regresi data panel yang terbentuk untuk mengetahui faktor-faktor yang mempengaruhi tingkat jumlah penduduk adalah model random Effect. Pada model tersebut semua asumsi terpenuhi. Faktor yang signifikan mempengaruhi jumlah penduduk adalah jumlah kelahiran. Kelahiran dan kematian mempengaruhi jumlah penduduk sebesar 99.95% dan sisanya sebesar 0.05% dipengaruhi oleh faktor- faktor lain yang tidak di teliti.    

scholarly journals ANALISIS FAKTOR YANG MEMPENGARUHI PRODUKSI TEBU PADA SUB SEKTOR PERKEBUNAN DI PROVINSI JAWA TIMUR TAHUN 2011-2015

2017 ◽  
Vol 15 (2) ◽  
pp. 193
Author(s):  
Moch. Arif Dausin Nazula Achadin
Keyword(s):  
Random Effect ◽  
Random Effect Model ◽  
Coefficient Of Determination ◽  
Analysis Tool ◽  
Land Area ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
Production Value ◽  
Plantation Labor

The goal of this research is to know the influence of the land area and the amount of sugar cane plantation labor in the plantation in East Java province year 2011-2015 and analysis whether there is a difference between production of Kabupaten/Kota cane producer on a plantation in East Java province year 2011-2015. Analysis tool used is a panel data regression then do hypothesis testing with F-test, t-test, and the coefficient of Determination () on error rate α = 5%.The results of the regression analysis of the data panel with the selected model is a Random Effect Model showed that the land area of influential labor and significantly to the amount of production value of each 0.97 to land area and 0.04 for amount of labor. While the value of the coefficient of determination () is 0.99 or 99%, this indicates that the ability of the variable land area and the amount of labor in explaining the amount of production of 99%.

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