A mechanism to improve the allocation of public investment funds

2020 ◽  
Vol 26 (7) ◽  
pp. 1522-1533
Author(s):  
A.V. Larionov
Keyword(s):  
Panel Data ◽  
Random Effects ◽  
Public Investment ◽  
Allocative Efficiency ◽  
Investment Funds ◽  
The Public ◽  
Panel Data Regression ◽  
Data Regression ◽  
Efficiency And Effectiveness ◽  
Effective System

Subject. This article deals with the issue of improving the public investment allocative efficiency. Objectives. The article aims to develop an approach to improve the efficiency and effectiveness of public investment in the economy. Methods. The study is based on a panel data regression with random effects. Conclusions and Relevance. All sectors of the economy have different demand for investment resources attracted, determined by operational and technological aspects. The results of the study can be used to develop an effective system of public investment.

scholarly journals Efficiency and Effectiveness of Government Expenditure on Education at Districts/Cities Level in East Java Indonesia

2017 ◽  
Vol 13 (8) ◽  
pp. 91
Author(s):  
Achmad Solihin ◽  
Djoko Mursinto ◽  
Lilik Sugiharti
Keyword(s):  
Panel Data ◽  
Local Government ◽  
Government Expenditure ◽  
Educational Outcome ◽  
Household Expenditure ◽  
Panel Data Regression ◽  
Data Regression ◽  
Efficiency And Effectiveness ◽  
Local Government Expenditure ◽  
Regional Product

The purpose of this study is to investigate and analyze the efficiency and effectiveness of local government expenditure on education sector in districts and cities level of East Java, during the periods 2007-2014. Furthermore, this study will evaluate the impacts of local government expenditure, household expenditure for education, and regional product domestic bruto or (PDRB) on the educational outcomes, namely education index.Data Envelopment Analysis (DEA) is selected as the methodology for analyzing the efficiency of local government expenditure on educational outcome. The model assumes constant return to scale (CRS) and variable return to scale (VRS). Measurement of the effectiveness of government spending is done by using panel data regression. Data for supporting the analyses is panel data from 38 districts and cities in East Java for the periods of 2007 – 2014. The results show that government expenditure in educational sector is relatively inefficient. Government Expenditure for Education (PPP) has no significant impact on educational index, while Household expenditure for education (PPRT) and GRDP per Capita positive has significant impact on the Education Index (IP). This imply that government expenditure for educational sector is not effective improving educational index.

scholarly journals Trends in COVID-19 Infected Cases Based on Panel Data Regression Modelling

2021 ◽  
Author(s):  
A. RAJARATHINAM ◽  
P TAMILSELVAN
Keyword(s):  
Panel Data ◽  
Regression Model ◽  
Random Effects ◽  
Tamil Nadu ◽  
Random Effects Model ◽  
Infected Case ◽  
Panel Data Regression ◽  
Data Regression ◽  
Tamil Nadu State ◽  
The Government

Abstract Background and Objective: The novel coronavirus pandemic, known as COVID-19, could not have been more predictable; thus, the world encountered health crises and substantial economic crises. This paper analysed the trends in COVID-19 cases in October 2020 in four southern districts of Tamil Nadu state, India, using a panel regression model. Materials and Methods: Panel data on the number of COVID-19-infected cases were collected from daily bulletins published through the official website www.stopcorona.tn.gov.in maintained by the Government of Tamil Nadu state, India. Panel data regression models were employed to study the trends. EViews Ver.11. Software was used to estimate the model and its parameters. Results: In all four districts, the COVID-19-infected case data followed a normal distribution. Maximum numbers of COVID-19-infected cases were registered in Kanniyakumari, followed by Tirunelveli, Thoothukudi and Tenkasi districts. The fewest COVID-19 cases were registered in Tenkasi, followed by Tirunelveli, Thoothukudi and Kanniyakumari districts. A random effects model was found to be an appropriate model to study the trend.Conclusion: The panel data regression model is found to be more appropriate than traditional models. The Hausman test and Wald test confirmed the selection of the random effects model. The Jarque-Bera normality test ensured the normality of the residuals. In all four districts under study, the number of COVID-19 infections showed a decreasing trend at a rate of 1.68% during October 2020.

scholarly journals Analisis Faktor-Faktor yang Memengaruhi Perolehan Surplus Underwriting pada Asuransi Jiwa Syariah di Indonesia (Periode 2015-2020)

Al-Muzara ah ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 185-196
Author(s):  
Amelia Nadiah Wahyu Putri ◽  
Jaenal Effendi
Keyword(s):  
Panel Data ◽  
Life Insurance ◽  
Public Interest ◽  
Regression Method ◽  
Insurance Company ◽  
The Public ◽  
Panel Data Regression ◽  
Data Regression ◽  
Reserve Fund ◽  
Islamic Insurance

In Islamic insurance, if at the end of the period there is a surplus from the substraction result between total insurance income in the tabarru’ fund and insurance expenses, the surplus will be called as underwriting surplus. A good Islamic insurance company can be seen when the company succeeds in obtaining an underwriting surplus, because it is a proof when the company has managed the participant funds well. The underwriting surplus can be used as a reserve fund when an underwriting deficit occurs or when insurance expenses exceed insurance income, thereby it can improve the public interest in Islamic insurance. Therefore, this study aims to analyze the development of the underwriting surplus in Islamic life insurance in Indonesia and the factors that influence it by using panel data regression method. The estimation results using the REM model show that the variables of total assets and GDP have a positive and significant effect. Meanwhile, the contribution allowance, claim allowance, and inflation variables have a negative and significant effect.

scholarly journals The Effect of Local Taxes and Retribution on Economic Growth in Indonesia

2020 ◽  
Vol 18 (1) ◽  
pp. 14-23
Author(s):  
Bayu Rhamadani Wicaksono
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Random Effects ◽  
Secondary Data ◽  
Random Effects Model ◽  
Good Strategy ◽  
Local Taxes ◽  
Panel Data Regression ◽  
Data Regression ◽  
The Government

The purpose of the study is to analyze the effect of local taxes and retributions on the economic growth in Indonesia. The data used are secondary data from provinces in Indonesia 2014-2017 using panel data regression with Random Effects Model (REM). The results are as follows, first, the local taxes has a negative and significant impact on the economic growth in Indonesia. Second, the retributions have a positive and significant effect on the economic growth in Indonesia. The government should evaluate and plan a good strategy for the next period so that the potential revenues of local taxes and retributions can increase economic growth gradually.

scholarly journals THE INFLUENCE OF THE CEO POPULARITY ON PERFORMANCE OF BANKING COMPANIES AT THE EARLIER STAGES OF COVID-19

2021 ◽  
Vol 18 (1) ◽  
pp. 1-14
Author(s):  
Dian Wardhani ◽  
◽  
Wiwik Supratiwi ◽  
Keyword(s):  
Panel Data ◽  
Mass Media ◽  
Banking Sector ◽  
Stock Exchange ◽  
Company Performance ◽  
The Public ◽  
Influence Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
Model Approach

This study aims to obtain empirical evidence about the influence of CEO popularity on banking performance at the earlier stages of the COVID-19 pandemic in Indonesia. The CEO popularity significantly improve based on their achievements in the public mass media. The study sample consisted of 108 banking companies listed on the Indonesia Stock Exchange in Q1 - Q3 2020. Panel data regression with a common influence model approach was used for analysis, while the company performance was measured using Tobin's Q. The result showed that CEO popularity in the banking sector positively affects company performance. Therefore, hiring popular CEO helps obtain better company performance.

scholarly journals Estimating Trends in COVID-19 Infected Cases Based on Panel Data Regression Modelling

2021 ◽  
Author(s):  
RAJARATHINAM ARUNACHALAM ◽  
TAMILSELVAN PAKKIRISAMY
Keyword(s):  
Panel Data ◽  
Regression Model ◽  
Random Effects ◽  
Tamil Nadu ◽  
Random Effects Model ◽  
Infected Case ◽  
Panel Data Regression ◽  
Data Regression ◽  
Tamil Nadu State ◽  
The Government

Abstract Background and Objective: The novel coronavirus pandemic, known as COVID-19, could not have been more predictable; thus, the world encountered health crises and substantial economic crises. This paper analysed the trends in COVID-19 cases in October 2020 in four southern districts of Tamil Nadu state, India, using a panel regression model. Materials and Methods: Panel data on the number of COVID-19-infected cases were collected from daily bulletins published through the official website www.stopcorona.tn.gov.in maintained by the Government of Tamil Nadu state, India. Panel data regression models were employed to study the trends. EViews Ver.11. Software was used to estimate the model and its parameters. Results: In all four districts, the COVID-19-infected case data followed a normal distribution. Maximum numbers of COVID-19-infected cases were registered in Kanniyakumari, followed by Tirunelveli, Thoothukudi and Tenkasi districts. The fewest COVID-19 cases were registered in Tenkasi, followed by Tirunelveli, Thoothukudi and Kanniyakumari districts. A random effects model was found to be an appropriate model to study the trend.Conclusion: The panel data regression model is found to be more appropriate than traditional models. The Hausman test and Wald test confirmed the selection of the random effects model. The Jarque-Bera normality test ensured the normality of the residuals. In all four districts under study, the number of COVID-19 infections showed a decreasing trend at a rate of 1.68% during October 2020.

Determinants Of Capital Structure For Multinational And Domestic Companies In India: Panel Data Regression Model

2019 ◽  
Vol 118 (7) ◽  
pp. 147-154
Author(s):  
K. Maheswari ◽  
Dr. J. Gayathri ◽  
Dr. M. Babu ◽  
Dr.G. Indhumathi
Keyword(s):  
Panel Data ◽  
Capital Structure ◽  
Regression Model ◽  
Business Risk ◽  
Return On Assets ◽  
Panel Data Regression ◽  
Data Regression ◽  
Return On Capital ◽  
Domestic Companies ◽  
The Capital Structure

The capital structure refers to the components of capital needed to establish and expand its business activities. The study was made with an objective to examine the determinants of capital structure of multinational and domestic companies listed in S&P BSE automobile sector. The study concluded that there is significant impact on capital structure determinants such as size, business risk, non debt shield tax, return on assets, tangibility, profit, return on capital employed and liquidity on the capital structure of multinational and domestic companies of Indian Automobile Sector.  

FAKTOR DETERMINAN PEMBENTUK STRUKTUR MODAL PADA PERUSAHAAN SEKTOR FARMASI PERIODE 2012 - 2016

2017 ◽  
Vol 2 ◽  
pp. 241-250
Author(s):  
Neng Ria Kanita ◽  
Hendryadi Hendryadi
Keyword(s):  
Panel Data ◽  
Capital Structure ◽  
Firm Size ◽  
Stock Exchange ◽  
Pharmaceutical Manufacturing ◽  
Manufacturing Companies ◽  
Purposive Sampling ◽  
Panel Data Regression ◽  
Data Regression ◽  
Partial Effects

This study aims to examine the simultaneous and partial effects of profitability, liquidity, and firm size on capital structure. The sample is 10 pharmaceutical manufacturing companies listed in Indonesia Stock Exchange period 2012-2016, using purposive sampling. The technique of analysis used is panel data regression (pooled regression). The results showed that the selected model is the fixed effect. Simultaneously NPM, CR, and Firm Size have a significant effect on capital structure. Partially NPM has a negative and significant effect on capital structure. CR partially have a negative and not significant effect on capital structure. Partially Firm Size have a positive and significant effect on capital structure. Variables that have a significant effect on capital structure are NPM and Firm Size. While CR does not significantly affect the capital structure. Keywords: Capital Structure, Profitability, Liquidity, Firm Size

A Study of Multilayered Profitability Analysis by Using DuPont Model: Evidence from Indian Pharmaceutical Industry

2021 ◽  
pp. 097215092199305
Author(s):  
Pinku Paul
Keyword(s):  
Panel Data ◽  
Pharmaceutical Industry ◽  
Profit Margin ◽  
Pharmaceutical Firms ◽  
Sustainable Performance ◽  
Profitability Analysis ◽  
Panel Data Regression ◽  
Data Regression ◽  
Negative Effect ◽  
Positive Effect

Profitability is used as a prime indicator to measure the sustainable performance of an organization. The current study made an attempt to apply the DuPont model to investigate the multilevel profitability determinants for the pharmaceutical industry of India. The study also estimates an empirical model to predict the association of profitability with factors such as profit margin, asset utilization, leverage, interest load and tax load of firms in the pharmaceutical industry of India. For this purpose, a dataset for 170 companies from 2010–2011 to 2018–2019 was analysed initially by using panel data regression followed by stepwise panel data regression. The study successfully applied and tested the DuPont model with respect to the firms of the pharmaceutical industry in India. It was found that the factors such as profit margin, asset utilization and leverage had a significant positive effect on the firms’ profitability and the factor interest load had a significant negative effect on the firms’ profitability. The tax load does not have an impact on the profitability of the pharmaceutical firms in India. These findings are expected to provide a guide for understanding the profitability of the firms in a better way.

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