scholarly journals The Determinants of Sukuk Issuance: Evidence from Top Sukuk Issuing Countries

2021 ◽  
Vol 16 (1) ◽  
pp. 21-34
Author(s):  
Mohamad Nizam Jaafar ◽  
◽  
Amirul Afif Muhamat ◽  
Norzita Abdul Karim ◽  
Mohd Faizal Basri ◽  
...  
Keyword(s):  
Panel Data ◽  
Random Effect Model ◽  
Political Stability ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Least Square ◽  
Macroeconomic Variables ◽  
Brunei Darussalam ◽  
Effect Model ◽  
Control Of Corruption

Macroeconomic variables may influence the issuance of Sukuk. The purpose of this study was to determine the relationship between macroeconomic variables namely Gross Domestic Product (GDP) per capita, inflation, rules of law, corruption of control and political stability. This study used a panel data study consisting of 11 countries that were mostly involved in the issuance of Sukuk. The countries are Bahrain, Brunei Darussalam, Indonesia, Kuwait, Malaysia, Pakistan, Qatar, Saudi Arabia, Singapore, Turkey and United Arab Emirates. The data was generated from 2006 until 2015 and collected from the authorized sources such as the Islamic Finance Information Services (IFIS), World Development Indicator and World Economic Outlook. This research employed several statistical methods like descriptive statistics, unit root test, and correlation analysis. In order to meet the objective of this research, an econometrics estimation of Pool Ordinary least square model, Fixed Effect Model and Random Effect Model were tested. The output from the Fixed Effect Model indicates that only GDP and control of corruption have a significant relationship to Sukuk issuance. It can be concluded that when the GDP increases, the number of Sukuk issued will increase accordingly. This is also applicable to corruption where better control of corruption will lead to an increase in Sukuk issuance. Therefore, good policies should in place to ensure a conducive economic environment that will encourage participation in the Sukuk market. Keywords: Sukuk, Islamic capital market, macroeconomic, panel data, least square model

Analysis of Board Size and Firm Performance: Evidence from NSE Companies Using Panel Data Approach

2016 ◽  
Vol 9 (2) ◽  
pp. 148-172 ◽  
Author(s):  
Anjala Kalsie ◽  
Shikha Mittal Shrivastav
Keyword(s):  
Firm Performance ◽  
Panel Data ◽  
Panel Data Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Least Square ◽  
Empirical Literature ◽  
Board Size ◽  
Effect Model

This article seeks to examine the relationship between the board size and firm performance. Existing literature on board size is based on different theories of corporate governance. While agency theory and resource dependency theory suggest that the board size positively affects performance, stewardship theory favours smaller board size and argues that larger board size negatively impacts the firm performance. The present article adds to the empirical literature by employing panel data analysis of 145 non-financial companies listed in the NSE CNX 200 Index of India corresponding to 16 industries. The study is carried out for a period of five years from 2008 to 2012. The firm performance has been measured using Tobin’s Q and the market-to-book value ratio (MBVR) as market-based measures and return on assets (ROA) and return on capital employed (ROCE) as accounting-based measures. The fixed effect model, random effect model and feasible generalised least square (FGLS) regression models are applied to achieve the above-mentioned objectives. The results conclude that the board size has a positive and significant impact on the firm performance.

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.

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>

Pengaruh Variabel Ekonomi Makro terhadap Yield Spread Negara-negara di Asia Timur, Amerika Latin, dan Karibian

2018 ◽  
Vol 3 (1) ◽  
pp. 61-67
Author(s):  
Irwan Diko Purba
Keyword(s):  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Least Square ◽  
Real Effective Exchange Rate ◽  
Yield Spread ◽  
Macroeconomic Variables ◽  
Effect Model ◽  
Effective Exchange ◽  
Effective Exchange Rate

A country’s credit worthiness decided by macroeconomic factors. This research aims to examine the impact of macroeconomic and external factor on yield spread of East Asia, Latin America, and Caribbean countries. Macroeconomic variables used in this research are classified as macroeconomic variables that influence liquidity and solvency, and macroeconomic variables that influence macroeconomic fundamental. This research is conducted by using quarterly yield spread data of 11 countries from 2000Q1 to 2015Q4 and analyzed panel data regression using Pooled Least Square (PLS), Fixed Effect Model (FEM) and Random Effect Model (REM). Study results show that macroeconomic variables that have impact on yield spread are external debt to GDP ratio, fiscal balance to GDP ratio, amortization to international reserve ratio, current account to GDP ratio, real effective exchange rate, and GDP per capita growth. External factors that have impact on yield spread are US Treasury Bond 10 year yield and Volatility Index. Abstrak Kelayakan utang (credit worthiness) sebuah negara ditentukan dari kondisi ekonomi makro negara tersebut dan faktor eksternal. Penelitian ini bertujuan untuk menguji pengaruh faktor ekonomi makro serta faktor eksternal terhadap yield spread negara-negara di Asia Timur, Amerika Latin dan Karibian.  Variabel ekonomi makro yang digunakan dalam penelitian ini digolongkan dalam dua kelompok yakni yang memengaruhi likuiditas dan solvensi serta yang memengaruhi fundamental ekonomi makro. Penelitian dilakukan dengan menggunakan yield spread triwulanan dari 11 negara untuk periode 2000Q1:2015Q4 dan analisis regresi data panel menggunakan Pooled Least Square (PLS), Fixed Effect Model (FEM) dan Random Effect Model (REM). Hasil penelitian menunjukkan bahwa variabel ekonomi makro yang memengaruhi yield spread adalah rasio utang luar negeri terhadap PDB,  rasio keseimbangan anggaran fiskal terhadap PDB, rasio amortisasi terhadap cadangan devisa, rasio transaksi berjalan terhadap PDB, nilai tukar riil (real effective exchange rate) dan  pertumbuhan PDB per kapita. Faktor eksternal yang memengaruhi yield spread adalah yield US Treasury 10 tahun dan Volatility Index (VIX).

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 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 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 ANALISIS REGRESI UNTUK DATA PANEL PADA PEMODELAN TINGKAT KEMATIAN IBU DI PROVINSI SULAWESI SELATAN

2020 ◽  
Vol 2 (1) ◽  
pp. 20
Author(s):  
Muhammad Imran Rahman ◽  
Muhammad Nusrang ◽  
S. Sudarmin
Keyword(s):  
Parameter Estimation ◽  
Panel Data ◽  
Regression Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Least Square ◽  
South Sulawesi ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

Abstrak. Penelitian ini membahas mengenai estimasi parameter model regresi data panel pada pemodelan tingkat kematian ibu di Provinsi Sulawesi Selatan dari tahun 2014 sampai dengan 2016. Data yang digunakan adalah data sekunder dari Dinas Kesehatan Provinsi Sulawesi Selatan yang berupa jumlah kematian ibu, perdarahan, hipertensi dalam kehamilan, infeksi dan gangguan sistem peredaran darah di seluruh Kabupaten/Kota di Provinsi Sulawesi Selatan tahun 2014-2016. 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 dengan nilai 𝑅2 = 90%. Adapun peubahpeubah yang berpengaruh signifikan terhadap kematian ibu adalah perdarahan, hipertensi dalam kehamilan dan infeksi. Dari hasil analisis diperoleh juga daerah yang memiliki jumlah kematian ibu terbesar di Provinsi Sulawesi Selatan tahun 2014-2016 adalah Bone dan Jeneponto.Kata Kunci: Regresi data Panel, Angka Kematian Ibu, Fixed Effect Model, Least Square Dummy Variable.Abstract. This research discusses about parameter estimation of panel data regression model of mother mortality level modelling in South Sulawesi from 2014 to 2016. The data used were secondary data from Dinas Kesehatan Provinsi Sulawesi Selatan in the form of number of mother mortality, bleeding, infection, circulatory system disorders and metabolic disorders in the whole district/town in South Sulawesi year 2014-2016. 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 with value of 𝑅2 = 90%. The variables that significantly influence maternal mortality are bleeding, hypertension in pregnancy and infection. From the results of the analysis, it was also found that the regions that had the largest number of maternal deaths in South Sulawesi Province in 2014-2016 were Bone and Jeneponto.Keywords: Panel Data Regression, Mother Mortality Rate, Fixed Effect Model, Least Square Dummy Variable.

scholarly journals Analisis Regresi Balanced Panel dengan Komponen Galat Dua Arah pada Kasus Melek Huruf Masyarakat di Provinsi NTB

2021 ◽  
Vol 3 (1) ◽  
pp. 10
Author(s):  
Muhammad Irwansyah ◽  
R. Ruliana ◽  
Muhammad Kasim Aidid
Keyword(s):  
Time Series ◽  
Panel Data ◽  
Cross Section ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Common Effect ◽  
Effect Model

Abstract. Analsis regresi adalah suatu metode untuk melihat pengaruh antara satu atau lebih peubah bebas terhadap peubah terikat. Data yang digunakan untuk analisis regresi ada yang berupa penggabungan antara data cross section dengan data time series yang dikenal dengan nama data panel. Data panel yang memiliki jumlah pengamatan waktu yang sama di setiap objek pada tabulasi silang merupakan data panel lengkap (Balanced panel). Penelitian ini mencari nilai dugaan terhadap model regresi data panel dengan komponen galat dua arah yaitu galat pada waktu dan galat pada individu. Analisis regresi data panel dapat menggunakan tiga pendekatan yaitu common effect model, fixed effect model, dan random effect model. Pemilihan model terbaik dari ketiga pendekatan regresi data panel menggunakan uji hausman, uji chow, dan uji lagrange multipler. Dalam penelitian ini didapatkan model terbaik yaitu model random effect dimana peubah yang memiliki pengaruh signifikan terhadap melek huruf di Provinsi NTB yaitu rasio murid guru tingkat SMP rasio murid guru tingkat SMA, dan persentase penduduk miskin. Model regresi data panel yang terbentuk yaitu: Y = 117,5728 - 0,1967X5 - 0,3091X6 - 0,3297X7 + eKeywords: regresi data panel, common effect model, fixed effect model, random effect model, melek huruf.

scholarly journals PENGARUH PROFITABILITAS TERHADAP KEBIJAKAN DIVIDEN DENGAN ANALISA DATA PANEL PADA MULTI-BISNIS DI BURSA EFEK INDONESIA PERIODE 2007-2017

2020 ◽  
Vol 8 (1) ◽  
pp. 15-27
Author(s):  
Jan Horas Veryady Purba
Keyword(s):  
Panel Data ◽  
Dividend Policy ◽  
Stock Exchange ◽  
Panel Data Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Dividend Payout ◽  
Effect Model

The issue of dividends is very important to show the prospects for the company's growth in the future, and also important in the company's capital structure. Dividend policy can be influenced by profitability and other variables. In this study, profitability is chosen due to its role as main indicator that shows the company's capacity to pay dividends.  This study aims to analyze the effect of profitability on dividend policy. The study population is a company listed on the Indonesia Stock Exchange. Purposively selected eight companies that have a good liquidity category. Data for each company is taken from 2007 to 2017. With this data structure, the analysis used is panel data regression analysis. Panel data analysis models include the Common Effect Model (CEM) Fixed Effect Model (FEM) and Random Effect Model (REM). The best model was tested with the Chow test and Hausman Test and obtained The Fixed Effect Model. Dividend policy is measured by the variable dividend payout ratio. The findings in this study conclude that the dividend policy (Dividend Payout Ratio) is influenced by ROE, EPS and NPM, where these independent variables have a positive and significant influence on DPR.

Sign in / Sign up

Export Citation Format

Share Document