A Panel Data Analysis of Globalization, Peace and Stability: Implications for Governance and the Global Knowledge Economy

This study attempts to explore the relationship between globalization and the knowledge economy via governance. It intends to explain the channel of their relationship through peace and stability. Knowledge economy pillars (Education and Information and communication technology) are used as the dependent variable and globalization is used as an independent variable. To obtain the objectives of the study, the panel data set of 198 countries is used for the period of 1996-2016. The study has employed econometric techniques of panel data set such as the Fixed Effect Model (FEM), Random Effect Model (REM), and Hausman test. The results reveal that globalization has a significant and positive impact on the knowledge economy. Hence the study recommends that the country should execute such reforms that help enhance the globalization and increase the development of the knowledge economy.

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

Indian Journal of Corporate Governance ◽

10.1177/0974686216666456 ◽

2016 ◽

Vol 9 (2) ◽

pp. 148-172 ◽

Cited By ~ 9

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.

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

Jurnal Apresiasi Ekonomi ◽

10.31846/jae.v8i1.261 ◽

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.

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ANALISIS PENGARUH UPAH MINIMUM TERHADAP KESEMPATAN KERJA SEKTOR INDUSTRI DENGAN PANEL DATA ANALYSIS

IQTISHODUNA ◽

10.18860/iq.v0i0.314 ◽

2011 ◽

Author(s):

Luthfiya Fathi Pusposari

Keyword(s):

Data Analysis ◽

Panel Data ◽

Panel Data Analysis ◽

Random Effect ◽

Random Effect Model ◽

Control Variable ◽

Industrial Sector ◽

Fixed Effect ◽

Minimum Wages ◽

Effect Model

This study aims to determine the effect of minimum wages and employment of industrial sector in East Java. Researchers include two control variables are GDP as control variable of demand labor and work force as control variable of supply labor by using panel data from all districts and cities in East Java (29 districts and nine cities). Analysis of this study used panel data analysis which consisting of the Common Effect model, Fixed Effect model and Random Effect model, then chosed the most appropriate model. The result of this study show after testing the models, the appropriate model is fixed effect where minimum wages have negative effect of employment in industrial sector in east java.

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Inequality and Economic Growth: An Analysis of 8-Panels

Journal of Economics and Public Finance ◽

10.22158/jepf.v3n2p173 ◽

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

Purpose: This paper investigates the effects of inequality on economic growth in the world using continental approach.Design/methodology: 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.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.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.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.

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PENGARUH BELANJA PEMERINTAH PUSAT TERHADAP PENERIMAAN NEGARA BUKAN PAJAK PADA KEMENTERIAN NEGARA/LEMBAGA PERIODE 2012-2017

Indonesian Treasury Review Jurnal Perbendaharaan Keuangan Negara dan Kebijakan Publik ◽

10.33105/itrev.v6i3.343 ◽

2021 ◽

Vol 6 (3) ◽

pp. 227-245

Author(s):

Puji Wibowo ◽

Yoopi Abimanyu ◽

Heri Syafardi ◽

Muhadi Prabowo ◽

Iin Indrawati

Keyword(s):

Panel Data ◽

Central Government ◽

Panel Data Analysis ◽

Random Effect ◽

Random Effect Model ◽

Tax Revenue ◽

Purposive Sampling ◽

Goods And Services ◽

Effect Model ◽

The Impact

Various studies evaluate the impact of budget on government revenue at sub national levels. There are few empirical findings that show how central government budget may influence federal revenue collected by ministries. This study aims to investigate the budget impact of non tax revenue across Indonesian line ministries/agencies in the 2012-2017 period prior to the implementation of Act 9 Year 2018 concerning Non Tax Revenue. By using purposive sampling method, we found there were 24 government institutions observed in this study. We conducted granger causality and panel data analysis by adopting random effect model to examine the effect of goods and services expenditure, capital expenditure, and employee expenditure on non-tax revenue. It is concluded that only government spending on goods and services significantly affects on non-tax revenue performance, while the two other variables have no impacts. Abstrak Sejumlah riset telah dilakukan untuk menguji pengaruh anggaran belanja terhadap pendapatan pemerintah pada level pemerintahan daerah. Sampai saat masih sedikit bukti yang mengungkapkan adanya pengaruh alokasi anggaran belanja pemerintah pusat terhadap pendapatan yang diperoleh Kementerian Negara/Lembaga (K/L). Riset ini bertujuan untuk mengungkapkan pengaruh alokasi anggaran terhadap realisasi Penerimaan Negara Bukan Pajak (PNBP) pada K/L selama periode 2012-2017, sebelum pemberlakuan UU Nomor 9 Tahun 2018 tentang Penerimaan Negara Bukan Pajak. Metode pengambilan sampel yang digunakan adalah purposive sampling, diperoleh 24 instansi pemerintah sebagai objek penelitian. Dengan menggunakan analisis granger dan panel data dengan pendekatan random effect model, penelitian ini menguji pengaruh belanja barang, belanja modal, dan belanja pegawai terhadap kinerja PNBP. Hasil studi ini menyimpulkan bahwa belanja barang berpengaruh signifikan terhadap capaian realisasi PNBP pada K/L, sementara kedua variabel belanja yang lain tidak berdampak signifikan

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

Jurnal Benefita ◽

10.22216/jbe.v4i3.3932 ◽

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

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.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.

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

Jurnal Gaussian ◽

10.14710/j.gauss.v9i3.28925 ◽

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.

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Explaining Recent Romanian Migration: A Modified Gravity Model with Panel Data

Journal of Social and Economic Statistics ◽

10.2478/jses-2020-0006 ◽

2020 ◽

Vol 9 (1) ◽

pp. 46-64

Author(s):

Mihaela Iordache ◽

Mihaela Matei

Keyword(s):

Panel Data ◽

Gravity Model ◽

Random Effect ◽

Random Effect Model ◽

Fixed Effect Model ◽

Demographic Variables ◽

The European Union ◽

Temporal Perspective ◽

Demographic Situation ◽

Effect Model

AbstractThe present paper contributes to studies on Romanian emigration from a demographic, spatial, and temporal perspective. The purpose of this paper is to assess the selected economic and demographic variables’ impact on the volume of Romanian emigration to the European Union (EU) during 2010-2017. The analysis was done using a gravity model. The models used in this study are the fixed effect model (FEM) and the random effect model (REM), both applied to panel data. The results show that the economic and demographic factors have a significant influence on the emigration’s destination, and the socio-economic and demographic situation in the host country determines the flow migration from Romania. The paper strengthens the literature through an empirical analysis of the economic and demographic determinants of Romanian emigration to the EU from the perspective of the country of origin.

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Pengaruh Profitabilitas, Leverage, dan Growth Terhadap Kebijakan Deviden Pada Perusahaan Property, Real Estate, and Building Contruction yang Terdaftar di Bursa Efek Indonesia

Jurnal Benefita ◽

10.22216/jbe.v4i3.3938 ◽

2019 ◽

Vol 4 (3) ◽

pp. 399

Author(s):

Afriyeni Afriyeni ◽

Kartika Deas

Keyword(s):

Panel Data ◽

Real Estate ◽

Random Effect ◽

Random Effect Model ◽

Fixed Effect Model ◽

Dividend Payout ◽

Common Effect ◽

Effect Model ◽

Equity Ratio ◽

Asset Growth

The purpose of this research is to test the influence of Profitability variable by using Return On Asset (ROA), Leverage by using Debt to Equity Ratio (DER), and Growth variable by using Asset Growth (AG), to the Dividend Payout Ratio (DPR) on companies Property, Real Estate, and Building Construction 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 explanatory research using a quantitative approach. The data analysis method used is regression analysis in 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 result of the estimation model, it is found that REM is the best model in this study. The result showed that the profitability has a positive and significant effect on Dividend Payout Ratio, Leverage has a positive and significant effect on Dividend Payout Ratio, while Growth has a negative and hasn’t significant effect on Dividend Payout Ratio<div> </div><div>Tujuan dari penelitian ini adalah untuk menguji pengaruh variabel Profitabilitas dengan menggunakan Return On Asset (ROA), Leverage dengan menggunakan Debt to Equity Ratio (DER), dan variabel Growth dengan menggunakan Asset Growth (AG), terhadap Kebijakan Deviden dengan menggunakan Dividend Payout Ratio (DPR) pada perusahaan Property, Real Estate, and Building Contruction 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 8. Data panel regresi dapat diperkirakan menggunakan tiga model, yaitu Common Effect Model (CEM), Fixed Effect Model (FEM), dan Random Effect Model ( REM). Dari hasil model estimasi, ditemukan bahwa REM adalah model terbaik dalam penelitian ini. Hasil penelitian menunjukkan bahwa profitabilitas berpengaruh positif dan signifikan terhadap Kebijakan Deviden, leverage berpengaruh positif dan signifikan terhadap Kebijakan Deviden, sedangkan pertumbuhan berpengaruh negatif dan tidak signifikan terhadap Kebijakan Deviden</div>

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Do Government Expenditures Subject to Law of Diminishing Returns? A Panel Data Application

International Conference on Eurasian Economies 2018 ◽

10.36880/c10.02212 ◽

2018 ◽

Author(s):

Menşure Kolçak ◽

Ali Yasin Kalabak

Keyword(s):

Economic Growth ◽

Panel Data ◽

Empirical Analysis ◽

Random Effect ◽

Random Effect Model ◽

Government Expenditure ◽

Fixed Effect Model ◽

Public Expenditures ◽

Effect Model ◽

Diminishing Returns

The effect of government expenditure on economic growth has attracted attention of economist for long time. In this context, this paper aims to understand that government expenditure subjects to whether constant, decreasing or increasing yield. For this reason, countries were classified as with low government expenditure, medium government expenditure and high government expenditure, and were added into empirical analysis in the paper. The number of countries included in the analysis is 138 and the analysis covers the period between years 1980 and 2016. In this context, empirical analysis consists of fixed effect model, random effect model, hausman test and unbalanced panel data technique was applied. According to results of analysis, when government expenditure increases as quantitative, it’s effect on economic growth decreases but it still affects economic growth positively. To make public expenditures lately subject to law of diminishing returns, it may come into question that public expenditures is canalized to technology intensive areas. In order to increase productivity in the public expenditures and to shift out diminishing returns, level of spendings on human capital can be increased.

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