The purpose of this study is to investigate the importance of economic, social, political, and environmental factors in determining green technology diffusion. We use a unique annual panel dataset covering 58 nations from 1990 to 2019. Based on dynamic panel data models estimated using system generalized method of moments (GMM), we test whether the technological achievement of nations, general technology diffusion trends, environmental performance, democratic accountability, income distribution, foreign direct investment, income level, and socioeconomic conditions are significant determinants. Our findings indicate that green technology diffusion has a significant relationship with all of these factors. We obtain new evidence that general or brown technological innovation, diffusion, and achievement trends in a country are significant drivers of environmental technology diffusion. The findings of our paper have significant implications for sustainable development, given the importance of green products and technologies. The results of the study suggest that policies aimed at promoting the diffusion of green technologies may not be successful in the presence of unfavorable economic, social, political, or environmental conditions.

The primary objective of this paper is to investigate the extent to which climate change adaptation and green technology diffusion serve as key drivers for green growth. Additionally, the study examines the influence of various economic, environmental, and social factors on green growth. Utilizing an annual panel dataset comprising 38 OECD member countries from 1990 to 2020, a series of dynamic panel data models are estimated using the system generalized method of moments (GMM) approach. The empirical results provide novel and robust evidence that the diffusion of green technology and climate change adaptation exert a significant positive influence on green growth. Furthermore, the findings highlight the significant role played by macroeconomic, institutional, social, and government policy-related factors in promoting green growth. These insights have substantial policy implications for the development and implementation of strategies that encourage climate change adaptation and green innovation. As a result, policymakers should prioritize the integration of green technology and climate change adaptation measures in their sustainable development agendas to foster a greener, more resilient future.

This study examines the effect of the COVID-19 pandemic on major agricultural commodity prices (cattle, cocoa, coffee, corn, cotton, hog, rice, soya oil, soybeans, soybean meal, sugar and wheat) using daily data from 1 January 2016 to 25 February 2022. We measured COVID-19 effect using a news-based sentiment index. A robust nonparametric Granger causality-in-quantiles test is used to test the effect of the COVID-19 sentiment on agricultural commodity prices and price volatility. We find significant Granger causality from the news-based COVID-19 sentiment to mean of the agricultural commodity prices in the lower and upper ranges of the quantiles. Moreover, findings show that the COVID-19 sentiment is also causal for variance of agricultural commodity prices, but only above the quantile ranges above the first quarter. Thus, COVID-19 is causal for large volatility changes in agricultural commodity prices. Accordingly, the extremely negative sentiment associated with COVID-19 has not only caused a price crash in agricultural markets, but also significantly increased market risk. Policymakers should be wary of the risks and vulnerabilities of agricultural commodities to extreme events, as well as the ramifications for producers and consumers throughout the economy.