scholarly journals ANALISIS PENGARUH JUMLAH PENDUDUK, PENDIDIKAN, UPAH MINIMUM DAN PRODUK DOMESTIK REGIONAL BRUTO (PDRB) TERHADAP JUMLAH PENGANGGURAN DI KABUPATEN DAN KOTAPROVINSI JAWA TIMUR TAHUN 2010-2014

2017 ◽  
Vol 2 (1) ◽  
Author(s):  
Trianggono Budi Hartanto
Keyword(s):  
Panel Data ◽  
Gross Domestic Product ◽  
Minimum Wage ◽  
Random Effect ◽  
Random Effect Model ◽  
Domestic Product ◽  
Population Education ◽  
Panel Data Regression ◽  
Data Regression ◽  
The Impact

AbstractThis research aims to analyze the impact of variable population, education (Means Years School), minimum wage and gross domestic regional product on unemployment in district and cities East Java from 2010 to 2014. The analytical method used panel data regression (pooled data) with the Random Effect Model approach. Results of panel data regression analysis in this research showed population, education (means years school), minimum wage and regional gross domestic product is simultaneously significant positive effect on unemployment in distric and cities East Java. Partially, population, education (means year school) and regional gross domestic product is significant and positive impact on unemployment, while minimum wage has no significant impact on unemployment in distric and cities East Java. Keywords : Unemployment,  Population,  Education,  Minimum  Wage,  Gross Domestic Regional Bruto (GDRP) Research Area: District and City East Java

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 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 Migration und Geld: Können Remittances den Wohlstand eines Landes fördern?

2018 ◽  
Vol 87 (3) ◽  
pp. 165-179
Author(s):  
Marcus Deetz ◽  
Anna Ammon ◽  
Neele Döpkens
Keyword(s):  
Foreign Direct Investment ◽  
Panel Data ◽  
Gross Domestic Product ◽  
Direct Investment ◽  
Home Country ◽  
Positive Influence ◽  
Domestic Product ◽  
Control Variables ◽  
Panel Data Regression ◽  
Data Regression

Zusammenfassung: Haben Remittances, also der Geldtransfer von Migrantinnen und Migranten zur Unterstützung der Familien im Heimatland, einen positiven Einfluss auf den Wohlstand eines Landes? Hierzu können die empirischen Befunde wie folgt zusammengefasst werden: Bei den durchgeführten Paneldatenregressionen von Remittances pro Person auf das Bruttoinlandsprodukt pro Einwohner, wobei die Kontrollvariablen Arbeitslosigkeit, Export, ausländische Direktinvestitionen, Bruttoinvestitionen sowie der Einfluss der Finanzkrise 2008–2009 berücksichtigt wurden, ist der Koeffizient der Variablen Remittances pro Person mit einer Höhe von 0,026 statistisch hochsignifikant. Remittances haben demnach einen positiven Einfluss auf den Wohlstand eines Landes, wenn dieser in Bruttoinlandsprodukt pro Einwohner gemessen wird. Auch die Ergebnisse der Robustheitsanalysen haben den positiven Zusammenhang bestätigt, der auch bei Veränderung von Kontrollvariablen statistisch signifikant bleibt. Summary: Do remittances, that is, the transfer of money from migrants to support families in their home country, have a positive influence on the prosperity of a country? The empirical findings can be summarized as follows: In the panel data regression of remittances per person to the gross domestic product per inhabitant, whereby the control variables unemployment, export, foreign direct investment, gross investment and the influence of the financial crisis 2008–2009 were taken into account, the coefficient of the variable remittances per person is statistically highly significant at 0.026. Thus, remittances have a positive influence on a country’s prosperity when measured in gross domestic product per inhabitant. The results of the robustness analyses also confirmed the positive correlation, which remains statistically significant even if control variables are changed.

scholarly journals THE EFFECT OF SPIN-OFF POLICY AND MACROECONOMIC FUNDAMENTAL FACTORS ON THIRD PARTY FUNDS AT SHARIA GENERAL BANKS

2021 ◽  
Vol 5 (1) ◽  
pp. 08-22
Author(s):  
Fatima Tuzzahara Alkaf ◽  
Nana Nawasiah
Keyword(s):  
Panel Data ◽  
Random Effect ◽  
Random Effect Model ◽  
Third Party ◽  
Financial Report ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
Report Data ◽  
The Government

In enhancing the development of Islamic banking, the government issued Law No. 21 of 2008 concerning spin-off. With this policy, it is expected that Islamic Commercial Banks will develop. This study aims to implement panel data regression to examine in depth the influence of spin-off policy and macroeconomic fundamental factors on third party funds of Sharia General Banks. Sampling by purposive sampling, six (6) Sharia General Banks that have conducted spin-offs and financial report data from 2014-2018. The Chow Test and the Hausman Test show that the panel data regression model that matches the variable data used in 2014-2018 is the Random Effect Model (REM). Empirical results show that during the 2014-2018 period, the spin-off policy and macroeconomic fundamental factors had a significant effect on the bank's third-party funds simultaneously. Partially, only the spin-off policy has a significant effect on third party funds.

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 Faktor–faktor yang mempengaruhi inflasi Provinsi-Provinsi di Sumatera

2019 ◽  
Vol 8 (1) ◽  
pp. 1-14
Author(s):  
Lailan Syafrina Hasibuan ◽  
Rahma Nurjanah ◽  
Etik Umiyati
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Minimum Wage ◽  
Government Spending ◽  
Quantitative Methods ◽  
Descriptive Analysis ◽  
Random Effect ◽  
Road Infrastructure ◽  
Panel Data Regression ◽  
Data Regression

This study aims to: 1) analyze inflationary developments, road infrastructure, government spending, provincial minimum wage, and economic growth provincial in Sumatra; 2) analyze the influence of road infrastructure, government spending, provincial minimum wage, and economic growth provincial in Sumatra. This research uses a descriptive analysis method to determine the development of each research variable and quantitative methods using panel data regression approach random effect. Based on the descriptive analysis of inflationary development, road infrastructure stagnated, government spending, provincial minimum wage, and economic growth was increased every year. The regression of panel data with random effect approach variable of the provincial minimum wage has a positive and significant influence on the inflation of provincial in Sumatra. While road infrastructure, government spending, economic growth have no significant effect on provincial inflation in Sumatra. Keywords: Inflation, Government spending, Economic growth.

scholarly journals THE IMPACT OF MACROECONOMIC DETERMINANTS ON COMMERCIAL BANK PROFITABILITY IN CENTRAL AND SOUTHEASTERN EUROPEAN COUNTRIES

TEME ◽  
2021 ◽  
pp. 1391
Author(s):  
Branimir M. Kalaš ◽  
Vera Mirović ◽  
Nada Milenković ◽  
Jelena Andrašić
Keyword(s):  
Interest Rate ◽  
Gross Domestic Product ◽  
Real Interest Rate ◽  
Panel Study ◽  
Random Effect ◽  
Random Effect Model ◽  
European Countries ◽  
Domestic Product ◽  
Bank Profitability ◽  
The Impact

The purpose of this paper is to investigate the impact of macroeconomic variables on bank profitability indicators in Central and Southeastern European countries (CESE). The research sample includes 13 countries of CESE countries: Albania, Bosnia and Herzegovina, Bulgaria, Croatia, the Czech Republic, Hungary, Macedonia, Montenegro, Poland, Romania, Serbia, Slovakia and Slovenia, for the period 2008-2015. The core idea is to empirically evaluate the impact of the main macro indicators, such as gross domestic product, inflation and the real interest rate on bank profitability and their potential relationship. The subject of this paper applies a two-step model: model 1 includes return on asset (ROA), while model 2 includes return on equity (ROE) as the dependent variable. On the other hand, independent variables are gross domestic product (GDP), inflation (INF) and real interest rate (RIR). The results of the panel study indicate that there is a significant effect of GDP and INF on bank profitability indicators in selected countries. Namely, the 1% increase in GDP and INF rise ROA for 0.47% and 0.48%, where inflation has a greater influence on ROA and ROE compared to GDP. The results of the random effect model show that the 1% increase in GDP and INF raise ROE for 0.49% and 0.42%. Likewise, real interest rate has no significant effect on ROA and ROE in selected countries. Based on empirical findings, policymakers should focus on rapid economic growth with controlled inflation that will enhance bank profitability in Central and Southeastern European countries.

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 Pengaruh inflasi dan laju pertumbuhan penduduk terhadap kemiskinan di Sumatera Bagian Selatan tahun 2011-2018

SOROT ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. 33
Author(s):  
Kevin Kevin ◽  
Aning Kesuma Putri ◽  
Aja Nasrun
Keyword(s):  
Growth Rate ◽  
Panel Data ◽  
Population Growth ◽  
Population Growth Rate ◽  
Random Effect ◽  
Random Effect Model ◽  
Effect Model ◽  
Panel Data Regression ◽  
Analysis Technique ◽  
Data Regression

Penelitian ini bertujuan untuk mengetahui pengaruh inflasi dan laju pertumbuhan penduduk terhadap kemiskinan di Sumatera bagian Selatan (Sumbagsel) tahun 2011-2018. Penelitian ini menggunakan pendekatan kuantitatif. Data yang digunakan adalah data panel ibu kota provinsi di Sumbagsel yang terdiri dari Palembang, Pangkalpinang, Bandar Lampung, Bengkulu, dan Jambi tahun 2011-2018. Teknik analisis data dalam penelitian ini menggunakan analisis regresi data panel dengan model Random Effect. Hasil penelitian menunjukkan bahwa secara simultan variabel inflasi dan laju pertumbuhan penduduk berpengaruh signifikan terhadap kemiskinan. Secara parsial variabel inflasi tidak berpengaruh signifikan terhadap kemiskinan sedangkan variabel laju pertumbuhan penduduk berpengaruh signifikan terhadap kemiskinan.This research aimed to find out the effect of inflation and population growth rate on the poverty in Southern Sumatera in 2011-2018. This research used the quantitative approach. The data used is panel data of the capital of province in Southern Sumatera which consists of Palembang, Pangkalpinang, Bandar Lampung, Bengkulu, dan Jambi in 2011-2018. The data analysis technique was the panel data regression analysis using random effect model. The result of the research showed that simultaneously the variable of inflation and population growth rate have a significant effect on the poverty. Partially the variable of inflation have no significant effect on the poverty while the variable of population growth rate has a significant effect on the poverty.

scholarly journals Regresi Data Panel dengan Pendekatan Common Effect Model (CEM), Fixed Effect model (FEM) dan Random Effect Model (REM) (Studi Kasus: Persentase Penduduk Miskin Menurut Kabupaten/Kota di Kalimantan Timur Tahun 2015-2018)

2020 ◽  
Vol 1 (2) ◽  
pp. 106
Author(s):  
Eka Nur Amaliah ◽  
Darnah Darnah ◽  
Sifriyani Sifriyani
Keyword(s):  
Panel Data ◽  
Random Effect ◽  
Random Effect Model ◽  
Series Data ◽  
Poor People ◽  
Fem Model ◽  
East Kalimantan ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

Panel data regression is a regression that combines cross section data and time series data. Panel data regression estimation can be done through 3 estimates namely CEM, FEM and REM. This research will make a modeling of the percentage of poor people according to regencies / cities in East Kalimantan using panel data regression analysis. Poverty occurs due to lack of income and assets to meet basic needs. For this reason, variables that are assumed to affect the percentage of the poor are used, including the Population Growth Rate (LPP), Human Development Index (HDI), and Adjustable Per capita Expenditure (PPD). By using 3 CEM, FEM and REM approaches based on testing, the best FEM model is obtained. Based on the FEM model the factors that significantly influence are the HDI and PPD. A value of 0.7755 means that the HDI and PPD can explain the percentage of poor people according to the Regency / City in East Kalimantan of 77.55% while the remaining 22.45% is influenced by other variables not yet included in the model.

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