A composite logistic regression approach for ordinal panel data regression

2008 ◽  
Vol 1 (1) ◽  
pp. 29 ◽  
Author(s):  
Ronghua Luo ◽  
Hansheng Wang
Keyword(s):  
Logistic Regression ◽  
Panel Data ◽  
Panel Data Regression ◽  
Data Regression ◽  
Regression Approach

scholarly journals Determinants of Bond Rating and its Implications to Corporate Bond Yield

2019 ◽  
Vol 9 (2) ◽  
pp. 195-200
Keyword(s):  
Logistic Regression ◽  
Panel Data ◽  
Corporate Bonds ◽  
Corporate Bond ◽  
Company Size ◽  
Bond Yields ◽  
Bond Ratings ◽  
Bond Rating ◽  
Panel Data Regression ◽  
Data Regression

Identifying the factors that affect bond ratings is important in relation to investment decisions in long-term debt securities because they have an impact on corporate bonds. The research objective is to analyze the factors that influence bond ratings and their implications for corporate bond yields, both partially and simultaneously. This study uses a logistic regression model to estimate the determinants of corporate bond ratings and a panel data regression model to estimate the implications for corporate bond yields, by taking samples of corporate bonds listed on the Indonesia Stock Exchange (IDX) during the 2012-2016 period with a number of samples research with as many as 36 corporate bonds. Based on the results of the study, using the logistic regression method, the following research findings were obtained: company size, liquidity, leverage and profitability simultaneously affected bond ratings with a contribution of 33.62% (R2 ). In addition, the size and liquidity of the company have a positive and significant effect on bond ratings. While the results of the panel data regression analysis, it was found that company size, liquidity, leverage, profitability and bond rating simultaneously affected bond yields with a contribution of 70.4% (R2) while 29.6% was influenced by other variables. In addition, the size and leverage of the company has a negative and significant effect on the yield of corporate bonds. This study also shows that the larger the size of the company, the less sensitive the changes in bond yields and vice versa, the smaller the size of the company, the more sensitive it is to changes in corporate bond yields.

scholarly journals Modeling the Effect of Bank Specific Factors on Financial Performance of Commercial Banks in Nigeria: Panel Data Regression Approach

2021 ◽  
Vol 28 (1) ◽  
pp. 40-47
Author(s):  
Y. Yakubu ◽  
S.M. Egopija
Keyword(s):  
Panel Data ◽  
Financial Performance ◽  
Commercial Banks ◽  
Management Quality ◽  
Panel Data Regression ◽  
Data Regression ◽  
Regression Approach ◽  
Specific Factors ◽  
Key Indicators ◽  
Bank Specific Factors

Periodic checking and evaluation of financial performance of the banking sector is a way of sustaining the development of a nation’s economy. The key indicators of the banks’ financial performance are their return on assets (ROA) and return on equity (ROE). A bank’s financial performance is affected by some specific factors like capital adequacy ratio (CAR), credit risk (CRISK), management quality, liquidity ratio (LIQ.RAT.) and bank size. This work first compares average financial performance of some sampled commercial banks in Nigeria (UBA, GTB, ZENITH, FIRST, and ACCESS banks) based on the key indicators and the bank specific factors. It then models the effect of these factors on the overall financial performance of the sampled banks using panel data regression approach. The results showed that the GTB had the highest average ROA, ROE and CAR throughout the period under review while Zenith bank was the best in terms of credit risk, management quality and liquidity ratio. The fitted ROA model accounted for 83% of the total variability in the data and revealed that CAR, CRISK, and LIQ.RAT were significant at both 1% and 5% levels while the ROE model accounted for 69% and revealed that CRISK and LIQ.RAT were significant. Keywords: Financial Performance, Commercial Banks, Evaluation, Panel Data, Economy

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.

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.

Using information from singletons in fixed-effects estimation: xtfesing

2020 ◽  
Vol 20 (4) ◽  
pp. 965-975
Author(s):  
Laura Magazzini ◽  
Randolph Luca Bruno ◽  
Marco Stampini
Keyword(s):  
Panel Data ◽  
Method Of Moments ◽  
Fixed Effects ◽  
Generalized Method Of Moments ◽  
Panel Data Regression ◽  
Data Regression ◽  
Method Of Moments Estimator ◽  
Fixed Effects Estimation

In this article, we describe the xtfesing command. The command implements a generalized method of moments estimator that allows exploiting singleton information in fixed-effects panel-data regression as in Bruno, Magazzini, and Stampini (2020, Economics Letters 186: Article 108519).

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 The double-edged sword of corporatisation in the hospital sector: evidence from Indonesia

2016 ◽  
Vol 12 (1) ◽  
pp. 61-80 ◽  
Author(s):  
Asri Maharani ◽  
Gindo Tampubolon
Keyword(s):  
Regression Analysis ◽  
Panel Data ◽  
Financial Performance ◽  
System Performance ◽  
Hospital Performance ◽  
Public Hospitals ◽  
Health System Performance ◽  
The Past ◽  
Panel Data Regression ◽  
Data Regression

AbstractHoping to improve their health system performance, many countries have corporatised their hospitals in the past 20 years. What this means for hospital performance remains as yet largely unknown. This study looks into the association of corporatisation and hospital performance in Indonesia. We apply panel data regression analysis to survey data on 54 public hospitals in East Java province. Our analysis suggests that corporatisation is associated with higher hospital income and expenditure, but fails to improve efficiency and equity. These findings suggest that hospital corporatisation policy in Indonesia should increase emphasis on efficiency and equity rather than on financial performance alone.

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