scholarly journals THE IMPACT OF CORONAVIRUS PANDEMIC ON AIRLINE STOCKS: AN APPLICATION OF QUANTILE-ON-QUANTILE REGRESSION MODEL

2020 ◽  
Vol 19 (COVID-19 Special Issue) ◽  
pp. 429-446
Author(s):  
Buğra BAĞCI ◽  
Ferhat ÇITAK ◽  
Muhammet Yunus ŞİŞMAN
Keyword(s):  
Quantile Regression ◽  
Regression Model ◽  
Quantile Regression Model ◽  
The Impact

A nonparametric method for assessment of interactions in a median regression model for analyzing right censored data

2018 ◽  
Vol 28 (4) ◽  
pp. 1170-1187
Author(s):  
MinJae Lee ◽  
Mohammad H Rahbar ◽  
Hooshang Talebi
Keyword(s):  
Quantile Regression ◽  
Regression Model ◽  
Survival Data ◽  
Real Life ◽  
Simulation Studies ◽  
Median Regression ◽  
Right Censored Data ◽  
Censored Quantile Regression ◽  
Quantile Regression Model ◽  
The Impact

We propose a nonparametric test for interactions when we are concerned with investigation of the simultaneous effects of two or more factors in a median regression model with right censored survival data. Our approach is developed to detect interaction in special situations, when the covariates have a finite number of levels with a limited number of observations in each level, and it allows varying levels of variance and censorship at different levels of the covariates. Through simulation studies, we compare the power of detecting an interaction between the study group variable and a covariate using our proposed procedure with that of the Cox Proportional Hazard (PH) model and censored quantile regression model. We also assess the impact of censoring rate and type on the standard error of the estimators of parameters. Finally, we illustrate application of our proposed method to real life data from Prospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study to test an interaction effect between type of injury and study sites using median time for a trauma patient to receive three units of red blood cells. The results from simulation studies indicate that our procedure performs better than both Cox PH model and censored quantile regression model based on statistical power for detecting the interaction, especially when the number of observations is small. It is also relatively less sensitive to censoring rates or even the presence of conditionally independent censoring that is conditional on the levels of covariates.

scholarly journals ON THE IMPACT OF REAL ESTATE PRICES ON THE DEVELOPMENT OF REGIONAL ECONOMY IN CHINA–AN ESTIMATION BASED ON PANEL QUANTILE REGRESSION MODEL

2021 ◽  
Vol 5 (2) ◽  
pp. 51-54
Author(s):  
Baili Zhang ◽  
Yadong Ma ◽  
Mengyue Yin ◽  
Zhengxun Li
Keyword(s):  
Economic Development ◽  
Real Estate ◽  
Quantile Regression ◽  
Regression Model ◽  
Marginal Effect ◽  
Quantile Regression Model ◽  
Panel Quantile Regression ◽  
Real Estate Prices ◽  
Impact Of Urbanization ◽  
The Impact

The paper analyzes the mechanism of real estate prices on economic development with panel quantile regression model. It is found that real estate prices can significantly promote economic development. Generally speaking, the contribution of real estate prices to economic development in regions with higher level of economic development is higher than that in regions with lower level. With the continuous improvement of the quantile, the impact of real estate prices has generally increased gradually, and the impact of urbanization level basically shows the law of diminishing marginal effect.

scholarly journals What Affects The Ability To Accumulate The Best Applicants By Russian Universities? The Application Of Quantile Regression Model

2017 ◽  
Vol 19 (5) ◽  
pp. 81-98
Author(s):  
Edyta Łaszkiewicz ◽  
Stepan Zemstov ◽  
Vera Barinova
Keyword(s):  
Higher Education ◽  
Quantile Regression ◽  
Regression Model ◽  
Higher Education Institutions ◽  
Research Quality ◽  
Related Factors ◽  
Public And Private ◽  
Quantile Regression Model ◽  
The Impact ◽  
Russian Universities

The aim of this paper is to evaluate which university’s characteristics have the greatest impact on the competitiveness of universities in their ability to attract better students in Russia. We examined the impact of three groups of factors,related to teaching, research and entrepreneurial activities of universities. The quantile regression model was applied for the subsample of public and private higher education institutions localized in Russia. The results prove that not only traditional, teaching-related factors affect the attractiveness of the universities. We found that the research quality and entrepreneurial experience both increase the ability to accumulate the best applicants by Russian universities. However, the synergy between training, research and business activities is not always achieved. The importance of science and business-oriented activities varies between public and private institutions. According to the results from the quantile regression the importance of the certain factors differs between the quantiles of the dependent variable distribution. Our findings might be useful for the governmental authorities during the universities’ assessment as well as for the higher education institutions themselves – in order to define their strategic development and attract better students.

Gender diversity and financial performance in an emerging economy: empirical evidencefrom India

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Santi Gopal Maji ◽  
Rupjyoti Saha
Keyword(s):  
Firm Performance ◽  
Panel Data ◽  
Quantile Regression ◽  
Regression Model ◽  
Financial Performance ◽  
Positive Impact ◽  
Gender Diversity ◽  
Content Type ◽  
Quantile Regression Model ◽  
The Impact

Purpose This paper aims to examine the impact of gender diversity both at operational and leadership levels on the financial performance of firms in India. Design/methodology/approach The study is based on a panel data set of 100 large Indian corporate firms. This study uses the Blau index and Shannon index to compute gender diversity. First, this paper uses system generalized method of moments model to deal with the potential endogeneity issue in the association between gender diversity and firm performance. Second, to unveil heterogeneity in such a relationship, the study applies panel data quantile regression model. Finally, the study adopts a generalized estimating equation model to investigate such relationships for group affiliated and standalone firms. Findings This study finds a significant positive impact of workforce gender diversity and board gender diversity on the financial performance of firms. Further, the results of the quantile regression model indicate that the impact of gender diversity (workforce and board) on firm performance is more pronounced at higher quantiles of the conditional distribution of firm performance. However, the study fails to extricate any significant impact of audit committee gender diversity on firm performance. Finally, the study also finds a significant positive impact of gender diversity at both workforce and board level for a group affiliated, as well as standalone firms. Originality/value The present study makes a novel contribution to the extant literature on the association between gender diversity and financial performance of firms by examining such diversity at both operational and leadership levels in the context of an emerging country such as India that captures the complex realities pertaining to gender issues. Further, the study contributes to the empirical literature regarding the heterogeneous impact of gender diversity on firm performance in the Indian context.

scholarly journals The Heterogeneous Effects of COVID-19 Outbreak on Stock Market Returns and Volatility: Evidence from Panel Quantile Regression Model

ETIKONOMI ◽  
2021 ◽  
Vol 20 (2) ◽  
pp. 225-238
Author(s):  
Noreen Khalid ◽  
Raja Fawad Zafar ◽  
Qasim Raza Syed ◽  
Roni Bhowmik
Keyword(s):  
Stock Market ◽  
Quantile Regression ◽  
Regression Model ◽  
Stock Returns ◽  
Market Returns ◽  
Stock Market Returns ◽  
Quantile Regression Model ◽  
Heterogeneous Effects ◽  
Panel Quantile Regression ◽  
The Impact

The purpose of this study is to probe the impact of the novel coronavirus (COVID-19) outbreak on stock market returns and volatility in developed markets. We employ a panel quantile regression model to capture unobserved individual heterogeneity and distributional heterogeneity. The study's findings reveal that there is a heterogeneous impact of COVID-19 on stock market returns and volatility. More specifically, there is a negative impact of COVID-19 on stock returns in the bearish stock market; however, there is an insignificant impact of COVID-19 on stock returns in the bullish stock market. Furthermore, COVID-19 has a positive impact on stock market volatility across all quantiles.JEL Classification: G24, G30, O16How to Cite:Khalid, N., Zafar, R. F., Syed, Q. R., Bhowmik, R., & Jamil, M. (2021). The Heterogeneous Effects of COVID-19 Outbreak on Stock Market Returns and Volatility: Evidence from Panel Quantile Regression Model. Etikonomi, 20(2), xx – xx. https://doi.org/10.15408/etk.v20i2.20587.

Sign in / Sign up

Export Citation Format

Share Document