How does technological innovation mitigate CO2 emissions in OECD countries? Heterogeneous analysis using panel quantile regression

2021 ◽  
Vol 280 ◽  
pp. 111818
Author(s):  
Cheng Cheng ◽  
Xiaohang Ren ◽  
Kangyin Dong ◽  
Xiucheng Dong ◽  
Zhen Wang
Keyword(s):  
Quantile Regression ◽  
Co2 Emissions ◽  
Technological Innovation ◽  
Oecd Countries ◽  
Panel Quantile Regression

scholarly journals The Shadow Economy-Environmental Quality Nexus In OECD Countries: Empirical Evidence From Panel Quantile Regression

2021 ◽  
Author(s):  
Lan Khanh Chu ◽  
Dung Phuong Hoang
Keyword(s):  
Quantile Regression ◽  
Informal Economy ◽  
Ecological Footprint ◽  
Shadow Economy ◽  
Trade Openness ◽  
Oecd Countries ◽  
Causality Test ◽  
Panel Quantile Regression ◽  
Determining Factors ◽  
The One

Abstract This study explores the determinants of ecological footprint by integrating the influence of the shadow economy. The findings based on the panel quantile regression indicate that the environmental effects of the shadow economy, trade openness, energy intensity, renewable energy, and income are not homogeneous across various levels of ecological footprint. The shadow economy-ecological footprint nexus follows an inverted U-shaped pattern. Initially, the higher size of the informal economy leads to more ecosystem degradation. When the shadow economy increases to certain thresholds, its environmental impact reverts to benefit. Such threshold changes with the evolution of ecological footprint. Specifically, it first rises then decreases along with the degradation of the ecosystem. Moreover, the heterogeneous panel causality test reports the one-way directional running from the shadow economy to the ecological footprint in OECD countries. The significant and heterogeneous relationships between ecological footprint and its determining factors are also established.

scholarly journals The Impact of Technological Innovation, Research and Development, and Energy Intensity on Carbon Emissions: An Experience from BRICS and OECD Countries

2022 ◽  
Vol 11 (1) ◽  
pp. 1-17
Author(s):  
Xu Xiaoyang ◽  
Maurice Balibae Kanaado ◽  
Motswedi Epadile
Keyword(s):  
Research And Development ◽  
Co2 Emissions ◽  
Technological Innovation ◽  
Carbon Dioxide Emissions ◽  
Energy Intensity ◽  
Generalized Method Of Moments ◽  
Oecd Countries ◽  
Innovation Research ◽  
Brics Countries ◽  
The Impact

The impact of technological innovation, research and development, and energy intensity on carbon dioxide emissions is examined in this study. A panel data econometric analysis of relevant variables extracted from the OECD and World Development Indicators databases for 36 OECD and 5 BRICS countries from 2005 to 2018 reveals that the Kao panel cointegration test revealed all countries, BRICS countries, and OECD countries exhibited cointegrated relationships regarding the selected variables. At this point, the correlation matrix shows that none of the independent variables has a strong correlation coefficient with the dependent variable. We also used two regression methods to evaluate the long-run association between the study's variables; the two-stage least square (2SLS) and panel generalized method of moments (GMM) both provide similar results, indicating that they are robust. According to the findings, technological innovation and R&D have a positive association with CO2 emissions, but energy intensity has a negative relationship with CO2 emissions.

scholarly journals International Tourism, Digital Infrastructure, and CO2 Emissions: Fresh Evidence From Panel Quantile Regression Approach

2021 ◽  
Author(s):  
Liu Wei ◽  
Sana ullah
Keyword(s):  
Quantile Regression ◽  
Regression Model ◽  
Co2 Emissions ◽  
Environmental Quality ◽  
Quantile Regression Model ◽  
Digital Infrastructure ◽  
Robust Model ◽  
Tourism Sector ◽  
Panel Quantile Regression ◽  
Regression Techniques

Abstract The main motivation behind this study is the importance of the tourism sector and digitalization in the economic development of a country and their potential effects on the country's environmental quality. For empirical analysis, the study applies FMOLS, DOLS, and quantile regression techniques for Asian economies. The findings of the study confirmed that tourism and digitalization improve environmental quality in FMOLS and DOLS models. In the basic quantile regression model, the estimates attached to tourism arrival are positive 5th quantile to 40th quantile and then turn negative from 60th quantile and onwards. Likewise, the estimates attached to tourism receipts in the robust quantile regression model are positive from quantile 5th to quantile 20 and negative and increasing from quantile 30 and onwards. Conversely, the estimates of digital infrastructure are insignificant in the basic quantile model at all quantiles except 95th. However, the estimated coefficients of digital infrastructure in the robust model are negative and rising from 40th quantile to 70th quantile and negative and declining from 80th quantile to 95th quantile. In general, we can say that as the tourism and digital sectors grow, the CO2 emissions decline.

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