scholarly journals Pengaruh Migrasi Masuk, Pendidikan dan Upah Minimum terhadap Pengangguran Terbuka di Kabupaten dan Kota Provinsi Jawa Timur

2020 ◽  
Vol 4 (1) ◽  
pp. 83
Author(s):  
Candra Gunawan Wibisono
Keyword(s):  
Panel Data ◽  
Minimum Wage ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Level Of Education ◽  
Effect Model

This research aims to analyze the influence of variable on migration, education and the minimum wage of open unemployment in regency/cities East Java province in 2009-2012 either simultaneously or partial. This research uses panel data (2009-2012) expectedly for migration, education, minimum wage and open unemployment variable. The sample ranges round 38 regency/cities in East Java. The model is choice use approach to analyze this problem is Fixed Effect Model (FEM). From the results of estimation is obtain that the migration variable entry and minimum wage significantly affect open unemployment. While the level of education variables have no effect on the open unemployment.

scholarly journals PENGARUH UPAH MINIMUM PROVINSI, PENDIDIKAN DAN KESEHATAN TERHADAP KEMISKINAN DI INDONESIA

2019 ◽  
Vol 1 (3) ◽  
pp. 939
Author(s):  
Nadia Islami ◽  
Ali Anis
Keyword(s):  
Panel Data ◽  
Minimum Wage ◽  
Research Method ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Least Square ◽  
Ordinary Least Square ◽  
Education And Health ◽  
Effect Model ◽  
Library Studies

This research aims to examined the impactt of provincial minimum wage, education and health on poverty in Indonesia with the selected model is the Fixed Effect Model (FEM). The data used is panel data during the period 2012-2017, with the technique of collecting documentation data and library studies obtained from relevant institutions and agencies.The variables use are poverty, provincial minimum wage, education and health. The research method used is Ordinary Least Square (OLS). The estimation results show that, provincial minimum wage have a positive and significant effect on poverty in Indonesia. Education have a negative and significant effect on poverty in Indonesia. Health have a negative and its not significant effect on poverty in Indoneisa. Meanwhile simultaneously province minimum wage, education and health affect the poverty in Indonesia.

scholarly journals PENGARUH TINGKAT PENDIDIKAN, PENGANGGURAN , DAN KEMISKIAN TERHADAP KRIMINALITAS DI INDONESIA

2019 ◽  
Vol 1 (1) ◽  
pp. 21
Author(s):  
Suci Rahmalia ◽  
Ariusni Ariusni ◽  
Mike Triani
Keyword(s):  
Panel Data ◽  
Significant Influence ◽  
Secondary Data ◽  
Fixed Effect Model ◽  
Equation Model ◽  
Fixed Effect ◽  
Regression Equation ◽  
Panel Regression ◽  
Level Of Education ◽  
Effect Model

This study aims to determine and analyze the influence of (1) Level of Education, (2) Unemployment, and (3) Poverty against crime in Indonesia by using the panel regression equation model and using the Fixed Effect Model (FEM) approach. The estimation results show that (1) the level of education has a negative and not significant effect on criminality in Indonesia, (2) unemployment has a negative and significant effect on crime in Indonesia, (3) poverty has a positive and significant influence on crime in Indonesia.This type of research is descriptive and associative. Data type is secondary data. This study uses panel data, which uses 31 provinces in Indonesia using the Fixed Effect Model (FEM) approach.The results of this study indicate that: (1) The level of education has a negative and insignificant influence on crime in Indonesia, (2) Unemployment has a negative and significant effect on crime in Indonesia, (3) Poverty has a positive and significant influence on crime in Indonesia.

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 Determinants of Financial Performance of Nepalese Commercial Banks: Evidence from Panel Data Approach

2020 ◽  
Vol 32 (2) ◽  
pp. 45-59
Author(s):  
Purna Man Shrestha
Keyword(s):  
Panel Data ◽  
Financial Performance ◽  
Commercial Banks ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Lagrangian Multiplier ◽  
Effect Model ◽  
Specific Factors ◽  
The Impact ◽  
Bank Specific Factors

The impact of bank specific factors on the financial performance of Nepalese commercial banks is analyzed in this paper. The financial performance is measured by using return on assets (ROA). Similarly, managerial efficiency (ME), liquidity (LIQ), credit risk (CR), assets quality (AQ) and operational efficiency (OE) is used as proxy of bank specific factors. This study used panel data of 17 commercial banks for the period of 2010/11 to 2017/18. Breusch and Pagan Lagrangian multiplier test showed that Pooled Regression model is not appropriate and Hausman test concluded that Fixed Effect model is appropriate rather than Random Effect model. Using the Fixed Effect model; this study concludes that bank specific factors have significant impact on financial performance of Nepalese commercial banks. Finally, this study reveals that ME, AQ and OE have significant positive impact, and CR has negative impact on the financial performance of Nepalese commercial banks.  

scholarly journals Pengaruh Perkembangan Usaha Mikro, Kecil, dan Menengah Terhadap Pendapatan Nasional Pada Sektor UMKM di Indonesia

2019 ◽  
Vol 8 (2) ◽  
pp. 127-135
Author(s):  
Lies Maria Hamza ◽  
Devi Agustien
Keyword(s):  
Panel Data ◽  
Small And Medium Enterprises ◽  
National Income ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Effect Model ◽  
Medium Enterprises

This study aims to analyze the influence of the development of Micro, Small, and Medium Enterprises on the national income of the UMKM sector in Indonesia. This research used a panel data method with Fixed Effect Model. The data used are secondary in the value of GDP of UMKM, Labours of UMKM, investment of UMKM, and the number of units of UMKM from the 2000-2013 period. The results showed that labors of UMKM and placement of UMKM have a positive and significant effect on the national income of the UMKM sector in Indonesia. While for the number of units of UMKM not affect the national income of the UMKM sector in Indonesia.

Estimasi Fixed Effect Model dari Likuiditas Aset, Financial Leverage dan Likuiditas Saham di Indonesia

2019 ◽  
Vol 4 (3) ◽  
pp. 412
Author(s):  
Irdha Yusra ◽  
Awidi Mulfita
Keyword(s):  
Panel Data ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Financial Leverage ◽  
Stock Liquidity ◽  
Common Effect ◽  
Effect Model ◽  
Asset Liquidity

<p><em>In investing, investors don’t assess the expected return, but also liquidity in shares. Because the aspect of liquidity is very important for investors to decide which stocks are attractive investments. This study aims to examine the effect of asset liquidity and financial leverage on stock liquidity. The population is all companies which are listed in Indonesia Stock Exchange in 2013-2017 periods. The sampling technique uses a purposive sampling method with predetermined criteria and obtained a sample of 58 companies with 290 observations. The data of the financial statement of the companies has been obtained from the official website of IDX. The analytical method used is regression analysis of panel data with the help of application E-Views 8. Panel data regression can be estimated using three models, namely Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM). From the results of the estimation model, it is found that FEM is the best model in this study. Furthermore, the results of the study show that asset liquidity has a positive and not significant effect on stock liquidity, while financial leverage has a negative and significant effect on stock liquidity.</em></p><p>Dalam berinvestasi, investor tidak hanya menilai dari return yang diharapkan, namun juga likuiditas pada saham. Karena aspek likuiditas sangat penting bagi investor untuk memutuskan mana saham yang menarik investasi. Penelitian ini bertujuan untuk menguji pengaruh likuiditas aset dan financial leverage terhadap likuiditas saham. Populasi dalam penelitian ini adalah perusahaan yang terdaftar di Bursa Efek Indonesia (BEI) periode 2013-2017. Teknik pengambilan sampel menggunakan metode purposive sampling dengan kriteria yang telah ditentukan dan diperoleh sampel sebanyak 58 perusahaan. Data laporan keuangan diperoleh dari website resmi BEI. Metode analisis yang dipakai adalah analisis regresi data panel dengan bantuan aplikasi E-Views 8. Regresi data panel dapat diestimasi menggunakan tiga model, yaitu Common Effect Model (CEM), Fixed Effect Model (FEM), dan Random Effect Model (REM). Untuk mendapatkan model terbaik digunakan uji lanjut, yaitu Uji Chow dan Uji Hausman. Dari hasil estimasi model diperoleh bahwa FEM sebagai model terbaik dalam penelitian ini. Lebih lanjut, hasil penelitian menemukan bahwa likuiditas aset berpengaruh positif dan tidak signifikan terhadap likuiditas saham, sedangkan financial leverage berpengaruh negatif dan signifikan terhadap likuiditas saham.</p>

scholarly journals MODEL REGRESI DATA PANEL UNTUK MENGETAHUI FAKTOR YANG MEMPENGARUHI TINGKAT KEMISKINAN DI PULAU MADURA

2020 ◽  
Vol 9 (3) ◽  
pp. 355-363
Author(s):  
Artanti Indrasetianingsih ◽  
Tutik Khalimatul Wasik
Keyword(s):  
Panel Data ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Series Data ◽  
Poverty Level ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

Poverty arises when a person or group of people is unable to meet the level of economic prosperity which is considered a minimum requirement of a certain standard of living or poverty is understood as a state of lack of money and goods to ensure survival. Panel data regression is the development of regression analysis which is a combination of time series data and cross section data. Panel data regression is usually used to make observations of data that is examined continuously for several periods. The purpose of this study is to determine the factors that influence the level of poverty in Madura Island in the period 2008 - 2017. In this study the variables used in this study are life expectancy (X1), average length of school (X2), level open unemployment (X3), and labor force participation (X4) with the Comman Effect Model (CEM) approach, Fixed Effect Model and Random Effect Model (REM). To choose the best model from the three is the chow test, the hausman test and the breusch-pagan test. In this study, the best model chosen was the Fixed Effect Model. Keywords: CEM, Fixed Effect Model, Data Panel Regression, REM, Poverty level.

scholarly journals PENGARUH PROFITABILITAS, LEVERAGE, DAN LIKUIDITAS TERHADAP KEBIJAKAN DIVIDEN PADA PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BURSA EFEK INDONESIA

JURNAL PUNDI ◽  
2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Kasnita Bawamenewi ◽  
Afriyeni Afriyeni
Keyword(s):  
Panel Data ◽  
Stock Exchange ◽  
Manufacturing Sector ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Current Ratio ◽  
Dividend Payout ◽  
Return On Equity ◽  
Effect Model ◽  
Equity Ratio

The purpose of this research is to test the influence of Profitability variable by using Return On Equity (ROE), Leverage by using Debt to Equity Ratio (DER), and Liquidity variabel by using Current Ratio (CR), to the Dividend Payout Ratio (DPR) on manufacturing sector company are listed in Indonesian Stock Exchange in 2013-2017 periods. In this research the data used was obtained from the official IDX website. This research was included in the explanatory research using quantitative approach. Data analysis method used is regression analysis in panel data with the help of application E-Views8. Panel data regression estimatedr using Fixed Effect Model (FEM).The result showed that the profitability has a negative and significant effect on Dividend Payout Ratio, Leverage has a negative and hasn’t significant effect on Dividend Payout Ratio, while Liquidity has a positive and hasn’t significant effect on Dividend Payout Ratio.Keywords: Dividend Payout Ratio,Profitability, Leverage, LiquidityTujuan dari penelitian ini adalah untuk menguji pengaruh variabel Profitabilitas dengan menggunakan Return On Equity (ROE), Leverage dengan menggunakan Debt to Equity Ratio (DER), dan variabel likuiditas dengan menggunakan Current Ratio (CR), terhadap Kebijakan Deviden ( DPR) pada perusahaan sektor manufaktur yang terdaftar di Bursa Efek Indonesia pada periode 2013-2017. Dalam penelitian ini data yang digunakan diperoleh dari situs web resmi BEI. Penelitian ini termasuk dalam penelitian penjelasan dengan menggunakan pendekatan kuantitatif. Metode analisis data yang digunakan adalah analisis regresi data panel dengan bantuan aplikasi E-Views . Data panel regresi menggunakan Fixed Effect Model (FEM). Hasil penelitian menunjukkan bahwa profitabilitas berpengaruh negatif dan signifikan terhadap Kebijakan Deviden, leverage berpengaruh negatif dan tidak signifikan terhadap Kebijakan Deviden, sedangkan likuiditas berpengaruh positif dan tidak signifikan terhadap Kebijakan Deviden.Kata Kunci : Kebijakan Dividen, Profitabilitas, Leverage, Likuiditas 

scholarly journals APLIKASI REGRESI DATA PANEL DENGAN PENDEKATAN FIXED EFFECT MODEL (STUDI KASUS: PT PLN GIANYAR)

2014 ◽  
Vol 3 (1) ◽  
pp. 1 ◽  
Author(s):  
NI PUTU ANIK MAS RATNASARI ◽  
I PUTU EKA NILA KENCANA ◽  
G.K. GANDHIADI
Keyword(s):  
Panel Data ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Least Square ◽  
Dummy Variable ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

Panel data regression has three approaches. One of these approaches is Fixed Effect Model (FEM). FEM is common estimated using Least Square Dummy Variable. The use of dummy variable in FEM is based on assumption that slope coefficients are constant but intercept varies over individuals. One of application of FEM is to find out motivation of employees at PT PLN Gianyar for non-outsourcing and outsourcing employees based on existence, relatedness, and growth. This research yields the following two models:with 67% motivation non-outsourcing employees represented by existenceand73% motivation non-outsourcing employees represented by existence and growth.

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

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