scholarly journals What Contributes to Regional Disparities of Energy Consumption in China? Evidence from Quantile Regression-Shapley Decomposition Approach

2018 ◽  
Vol 10 (6) ◽  
pp. 1806 ◽  
Author(s):  
Feng Dong ◽  
Bolin Yu ◽  
Jixiong Zhang
Keyword(s):  
Energy Consumption ◽  
Quantile Regression ◽  
Regional Disparities ◽  
Decomposition Approach ◽  
Shapley Decomposition

scholarly journals Wavelet decomposition approach for understanding time-varying relationship of financial sector variables: a study of the indian stock market

2020 ◽  
Vol 15 ◽  
pp. 36-65
Author(s):  
Indranil Ghosh ◽  
◽  
Tamal Datta Chaudhuri ◽  
Keyword(s):  
Stock Market ◽  
Quantile Regression ◽  
Wavelet Decomposition ◽  
Cross Correlation ◽  
Time Varying ◽  
Multiple Correlation ◽  
Decomposition Approach ◽  
Market Sentiment ◽  
Cross Correlation Analysis ◽  
Time Periods

In this paper, we study the effect of overall stock market sentiment in India on sectoral indices and on individual stock prices in terms of co-movement, dependence and volatility transmission along with the magnitude and persistence of the effects. The study uses wavelet decomposition framework for breaking down different financial time series into time-varying components. Quantile Regression, Wavelet Multiple Correlation and Cross-Correlation analysis, and Diebold-Yilmaz spillover analysis are then applied to investigate the nature of dependence, association, and spillover dynamics. For further focus, we have considered different time periods separately to identify the effect of market phases. Interesting results are obtained with respect to persistence of shocks, both across and within time periods. These have implications with respect to understanding market behavior and also perception of sectors and stocks. Keywords: Wavelet Decomposition, SENSEX, Quantile Regression, Wavelet Multiple Correlation, Wavelet Multiple Cross Correlation, Diebold-Yilmaz Spillover.

Driving forces of Iran's CO2 emissions from energy consumption: An LMDI decomposition approach

2017 ◽  
Vol 206 ◽  
pp. 804-814 ◽  
Author(s):  
Babak Mousavi ◽  
Neil Stephen A. Lopez ◽  
Jose Bienvenido Manuel Biona ◽  
Anthony S.F. Chiu ◽  
Markus Blesl
Keyword(s):  
Energy Consumption ◽  
Co2 Emissions ◽  
Driving Forces ◽  
Decomposition Approach

scholarly journals The Impacts of Non-Fossil Energy, Economic Growth, Energy Consumption, and Oil Price on Carbon Intensity: Evidence from a Panel Quantile Regression Analysis of EU 28

2018 ◽  
Vol 10 (11) ◽  
pp. 4067 ◽  
Author(s):  
Cheng Cheng ◽  
Xiaohang Ren ◽  
Zhen Wang ◽  
Yukun Shi
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Quantile Regression ◽  
Oil Price ◽  
Carbon Intensity ◽  
Fossil Energy ◽  
Empirical Results ◽  
Panel Quantile Regression ◽  
Growth Energy ◽  
Quantile Regression Method

This study investigates some determinants of carbon intensity in 28 countries in the European Union (EU), including non-fossil energy, economic growth, energy consumption, and oil price. A panel quantile regression method, which considers both individual heterogeneity and distributional heterogeneity, is applied in this paper. The empirical results imply that the influences of these determinants on carbon intensity are heterogeneous and asymmetric across different quantiles. Specifically, non-fossil energy can significantly decrease carbon intensity, but shows a U-shaped relationship. Economic growth has a negative impact on carbon intensity, especially for medium-emission and high-emission countries. The effects of heating degree days on carbon intensity are positive, although the coefficients are not significant at low quantiles, they become significant from medium quantiles. Besides, we find an inverse U-shaped relationship between crude oil price and carbon intensity. Finally, several relevant policy recommendations are proposed based on the empirical results.

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