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

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.

ETIKONOMI ◽  
2021 ◽  
Vol 20 (2) ◽  
pp. 225-238
Author(s):  
Noreen Khalid ◽  
Raja Fawad Zafar ◽  
Qasim Raza Syed ◽  
Roni Bhowmik

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.


2018 ◽  
Vol 28 (4) ◽  
pp. 1170-1187
Author(s):  
MinJae Lee ◽  
Mohammad H Rahbar ◽  
Hooshang Talebi

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.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rabia Muhammad Amjad ◽  
Abdul Rafay ◽  
Noman Arshed ◽  
Mubbasher Munir ◽  
Maryam Muhammad Amjad

Purpose The Financial Action Task Force defines money laundering as “processing of these criminal proceeds to disguise their illegal origin”. This is the major portion of financial crime that has ties across borders and like all financial crimes which are well planned and camouflaged, this crime is difficult to detect and deter. Over the years, on one side, globalization has provided development opportunities, it has also become one reason for the pervasiveness of money laundering. This has led to a disturbance in the global financial system and social unrest as proceeds from money laundering are being used in terrorism. The purpose of this study is to explore the non linear effect of globalization on financial crime in the form of money laundering. Design/methodology/approach An investigation based on 119 developing countries from the time period of 1985 till 2015 is conducted in this study. The panel quantile regression model was used to estimate antecedents of money laundering. Findings The study confirmed that globalization follows an inverted U-shaped relationship with money laundering. Furthermore, indicators such as investment portfolio and socioeconomic conditions have a significant effect on money laundering. Originality/value The panel quantile regression model was used to estimate antecedents of money laundering.


2017 ◽  
Vol 19 (5) ◽  
pp. 81-98
Author(s):  
Edyta Łaszkiewicz ◽  
Stepan Zemstov ◽  
Vera Barinova

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.


2021 ◽  
Vol 7 (2) ◽  
pp. 1
Author(s):  
Shahram Fattahi ◽  
Zainab Moridi ◽  
Rasoul Moridi

OPEC countries are heavily dependent on oil dollar revenues through which impact on exchange rates. The purpose of this study is to investigate the effect of oil shocks on the real exchange rates for selected OPEC countries for the period 1980-2018. The oil shocks are first obtained using the vector auto-regression model and then their effects on the exchange rates are estimated using a panel quantile regression model. The results show that effect of oil shocks on exchange rates varies across quantiles. The oil specific-demand shock and global demand shock have a negative and significant effect on the real exchange rates while the oil supply shock has a positive and significant effect on the real exchange rates in OPEC countries. Furthermore, oil specific-demand shock has the most impact on the real exchange rates.


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

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