scholarly journals Inequality and Economic Growth: An Analysis of 8-Panels

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

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

scholarly journals IMPLEMENTASI DATA PANEL SPASIAL TERHADAP TINGKAT PRODUK DOMESTIK REGIONAL BRUTO DI PROVINSI BALI

2021 ◽  
Vol 10 (2) ◽  
pp. 46
Author(s):  
NI MADE ARY DHARMA WIDYA ASTUTI ◽  
MADE SUSILAWATI ◽  
NI LUH PUTU SUCIPTAWATI
Keyword(s):  
Economic Growth ◽  
Random Effect ◽  
Random Effect Model ◽  
Economic Indicator ◽  
Fixed Time ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Spatial Lag ◽  
Effect Model ◽  
Spatial Panel Data

Gross Regional Domestic Product (GRDP) is an economic indicator to see the economic movements of a region during a certain period, whether based on current and constant price. Economic activities in a region use the GRDP calculation based on current prices by industrial base year 2010. In 2019, Bali's economic growth increased by , exceeding national economic growth of . Using spatial panel data in analysis consists of common effect model, fixed individual effect model, fixed time effect model, random effect model, and spatial lag fixed effect model. The best model to modeling GRDP Bali Province is spatial lag fixed effect which has a difference in constant values ??at any time, with  of 99.41 percent, the remaining is explained by other variables not examined

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.

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.

Effect of Dividend on Stock Price: A Case of Fuel and Power Industries in Bangladesh

2019 ◽  
Vol 9 (2) ◽  
pp. 87
Author(s):  
Mir Md Nazrul Islam
Keyword(s):  
Stock Price ◽  
Dividend Policy ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Return On Equity ◽  
Share Prices ◽  
Earnings Per Share ◽  
Effect Model

Dividend policy is an extensively researched topic in the arena of investments but still it remains an enigmatic that whether Dividend Policy affects the Stock Prices or not. The consequences of researches conducted in different stock markets are different. In Bangladesh, capital market investment is very essential and significant for the growth and market capitalization of domestic industry, trade and commerce. In current years Bangladesh had faced many precarious situations in its stock market. The Stock price reactions to the declaration of dividend of the fuel and power industry of Bangladesh are empirically examined. This study examines stock price reactions of listed dividend paying fuel and power industries in Dhaka stock exchange, Bangladesh for period of 11 years from of 2008-2018. This study will help us to make effective dividend decisions and effective implementation of dividend policies. In this study, Fixed Effect Model along with Random Effect Model have been used to estimate results. Both Models are implemented on panel data for explaining the association between dividend payments and share prices while controlling logarithm value of Profit after Tax, Earnings per Share and Return on Equity. The research is accompanied with a view to find whether the dividend announcement convey any evidence to the market that results a stock price volatility for adjusting the dividend announcement information while controlling the variables like Profit After Tax Earnings, Per Share and Return on Equity. The study also tested both the Models and found Random Effect Model is more significant than Fixed Effect Model. The result documented on the Random Effect Model shows that there are significant relationship with Retention Ratio, dividend per share and Return on Equity. In addition, Profit after tax shows the negative significant association and Earning per Shares insignificant with the share prices in Bangladesh Fuel and Power sector. 

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

IQTISHODUNA ◽  
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.

scholarly journals Is MGNREG Scheme Complementary to Fishing Activities?

2016 ◽  
Vol 5 (1) ◽  
pp. 47-53
Author(s):  
Chiranjib Neogi ◽  
Kamal Ray ◽  
Ramesh Chandra Das
Keyword(s):  
Freshwater Fish ◽  
Rainwater Harvesting ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Series Data ◽  
Component Part ◽  
Indian States ◽  
Effect Model

Freshwater fish output is taken as a proxy variable for empirical assessment of indirect benefits in terms of enhanced quantity of freshwater fish (output) cultivation. It is not unlikely to assess empirically the productivity of subsidized public scheme when rural development or rural asset generations are underlined in the said scheme, MGNREG Act, 2005. Rainwater harvesting is a major component part of the scheme since about 49.5 per cent of the total fund is already utilized on water conservation and obviously it has an impact on the cultivation of freshwater fish output. Time series data on annual expenditure on MGNREG and corresponding freshwater fish output at the state level are taken during the period 2006-07 to 2013-14 for 16 major Indian states. Fixed effect model and random effect models are being applied and the Hausman specification test suggests that fixed effect model is more appropriate than random effect model. Significant differences among the intercepts of the selected states are revealed as per F test. The results of fixed effect panel regression establish that fish output is enhanced by 0.000257 thousand tones or 0.26 tones if MGNREG expenditure rises by one crore or 10 million rupees. 

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

2020 ◽  
Vol 4 (2) ◽  
pp. 1-1
Author(s):  
Ayaz Zafar ◽  
Muhammad Tariq Majeed
Keyword(s):  
Panel Data ◽  
Knowledge Economy ◽  
Positive Impact ◽  
Panel Data Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Global Knowledge ◽  
Data Set ◽  
Effect Model

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.

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>

Comparative Evaluation of Efficacy of Ritodrine Versus Nifedipine in Prevention of Preterm Labour in Direct Head to Head Randomized Control Trials: A Systematic Review

2018 ◽  
Vol 2 (S1) ◽  
pp. e000153
Author(s):  
Viraj Panchal ◽  
Nishita Darji ◽  
Devang Rana
Keyword(s):  
Preterm Labour ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Mesh Terms ◽  
Effect Model ◽  
Direct Head ◽  
The Difference ◽  
Term Labour

Aims and Objectives: To compare the efficacy of ritodrine versus nifedipine in prevention of preterm labour at day two and seven. Methodology: All randomised control trials which follows PRISMA guidelines 2009 and in which Ritodrine and Nifedipine was compared head to head for the treatment of Pre-term labour. Clinical trial registries,MEDLINE, SCOPUS, EMBASE database were searched for MeSH terms Ritodrine, Nifedipine, pre-term labour and having primary outcome as number of delivery at day 2 and 7. Observational studies, unpublished studies, RCTs not following PRISMA guidelines were excluded. Data was analyzed using RevMan 5.3 version® and Odd’s Ratio was calculated to determine the difference at day 2 and 7. Both fixed effect and Random effect model was utilized to calculate the difference. P value less than 0.05 was considered as statistically significant. The I2 will be used to measure the heterogeneity between studies and a value > 30.0 will be considered to reflect heterogeneity. Results: A total of 6 Head to head RCTs were included in the studies. At day 2, according to fixed effect model, statistically ritodrine was having more likelihood for delivery as compared to nifedipine(Odd’s ratio=1.492, CI=1.013-2.197, P=0.043) but according to random effect model the difference was not statistically significant(Odd’s ratio=1.468, CI=0.919-2.344, P=0.108). At day 7, according to fixed effect model, ritodrine was having more likelihood for delivery as compared to nifedipine(Odd’s ratio=1.196, CI=0.852-1.679, P=0.302) and according to random effect model the difference was not statistically significant(Odd’s ratio=1.143, CI=0.720-1.815, P=0.572). Conclusion: Ritodrine causes more deliveries at day 2 and 7, so nifedipine is a better tocolytic as compared to ritodrine.

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