Variations in technical efficiency of farmers with distinct land size across agro-climatic zones: Evidence from India

Dagar, Vishal; Khan, Muhammad Kamran; Alvarado, Rafael; Usman, Muhammad; Zakari, Abdulrasheed; Rehman, Abdul; Murshed, Muntasir; Tillaguango, Brayan

doi:10.1016/j.jclepro.2021.128109

Cited by 126 publications

(43 citation statements)

References 57 publications

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“…Integrating environmental regulations into the analytical framework of export trade can help transform the development mode of trade and thus contribute to solving the contradiction between export trade and the ecological environment. Many evidences show that there is a close relationship between environmental regulation and export Responsible Editor: Ilhan Ozturk trade in the country (Xu 2000;Dagar et al 2021;Fang et al, 2019;Kamal et al 2021).…”

Section: Introductionmentioning

confidence: 99%

The impact of environmental regulations on export trade at provincial level in China: evidence from panel quantile regression

Ouyang

Wang

Deng

et al. 2021

Environ Sci Pollut Res

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Based on panel data from 30 provinces in China from 2008 to 2017, this paper constructs a quantile regression econometric model to analyze whether China's environmental regulation has an impact on export trade and to verify whether the Porter hypothesis has been valid in China in recent years. The results show that in the short term, environmental regulations have a restraining effect on export trade, while in the long run, due to the existence of innovation efficiency, environmental regulations will change from having a restraining effect to a promoting effect on export trade. Strict environmental regulations will reduce the production cost of Chinese products, further improve the export competitiveness of Chinese enterprises, and promote export trade. The empirical results verify the conclusion that the Porter hypothesis is confirmed in China. The following three suggestions are proposed for China's exports to promote the win-win of China's green development and export trade: promote the realization of international and domestic double circulation, avoid becoming "pollution shelters" and support technological innovation in environmental protection industries.

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Section: Introductionmentioning

confidence: 99%

The impact of environmental regulations on export trade at provincial level in China: evidence from panel quantile regression

Ouyang

Wang

Deng

et al. 2021

Environ Sci Pollut Res

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“…Among them, some scholars believe that economic development will have an impact on environmental quality and that economic, financial, and trade development will lead to environmental degradation (Khan et al, 2021;Sharma et al, 2021a;Islam et al, 2021;Sharma et al, 2021b;Shahbaz et al, 2020). Other scholars believe that environmental changes will in turn play an important role in economic factors such as production technology, consumption structure, and economic progress (Dagar et al, 2021;Sinha and Shahbaz, 2018;Zakari et al, 2021;Rehman et al, 2021). These studies have laid an important foundation for the construction of environmental regulation and the optimization of enterprises' multinational investment under environmental regulation, and inspired the relevant research on enterprises' multinational investment risk preference under environmental regulation.…”

Section: Theory and Research Hypothesesmentioning

confidence: 99%

The Influence of Host Country’s Environmental Regulation on Enterprises’ Risk Preference of Multinational Investment

Cheng

Jiang

2021

Front. Environ. Sci.

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At present, China is in an important period of promoting high-quality economic development. In order to promote enterprises to “go global” and realize high-quality foreign investment, China advocates enterprises to abide by the environmental protection laws and regulations of the host country and standardize their environmental protection behaviors in foreign investment cooperation. However, the impact of the host country’s environmental regulation on Chinese enterprise’s multinational investment risk preference has not been paid enough attention. This paper makes an empirical analysis on how the host country’s environmental regulation affects the enterprises’ risk preference of multinational investment (MIRP) by using the samples of A-share listed companies in China from 2010 to 2018 and emphatically examines the moderating effects of enterprise’s green technology innovation and social responsibility on the relationship between host country’s environmental regulation and enterprises’ MIRP. It is found that, on the whole, the environmental regulation of the host country will significantly promote the enterprises’ MIRP. The green technology innovation will positively moderate the impact of the environmental regulation of host country on enterprises’ MIRP, while the engagement of corporate social responsibility will inhibit this positive impact.

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“…GP predictions have been commonly employed in geo-statistics (Journel and Huijbregts 1978;Matheron 1973). The application of Gaussian process in predication can be seen in various fields such as in meteorology (Daley 1991), in spatial prediction (Whittle 1963) and in spatial statistics (Ripley 1981;Cressie 1993), etc. Researchers realized that Gaussian process can be applied in the general regression context (O'Hagan 1978;Zhao et al 2020).…”

Section: Related Workmentioning

confidence: 99%

Forecasting CO2 Emissions Due To Electricity Power Generation In Bahrain

Qader

Khan

Kamal

et al. 2021

Preprint

Self Cite

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Global warming is one of the biggest challenges among the leaders and scientists from developed and developing countries. Rapid industrialization and urbanization have given the boost to the amount of greenhouse gases’ emission. Carbon dioxide (CO2) is a significant of greenhouse gases and is the major contributing factor for global warming. CO2 emissions concentrations in the atmosphere have increased by 47% over the past 170 years due to human activities. As per Doha amendment of the Kyoto protocol in 2012, the target for maximum CO2 emission per capita for Bahrain was set to 20.96 metric ton for 2020. However, the current amount of CO2 emission per capita is 21.64 metric ton as of 2019. This research has applied multiple methods such as neural network time series nonlinear autoregressive, Gaussian Process Regression and Holt’s methods for CO2 emission forecasting. It attempts to forecast the CO2 emission of Bahrain. These methods are evaluated for performance. Neural network model has the RMSE of merely 0.206 while the GPR-RQ model has RMSE of 1.0171 and Holt’s method has RMSE of 1.4096. Therefore, it can be concluded that neural network time series nonlinear autoregressive model has performed better for forecasting the CO2 emission of Bahrain.

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Variations in technical efficiency of farmers with distinct land size across agro-climatic zones: Evidence from India

Cited by 126 publications

References 57 publications

The impact of environmental regulations on export trade at provincial level in China: evidence from panel quantile regression

The impact of environmental regulations on export trade at provincial level in China: evidence from panel quantile regression

The Influence of Host Country’s Environmental Regulation on Enterprises’ Risk Preference of Multinational Investment

Forecasting CO2 Emissions Due To Electricity Power Generation In Bahrain

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