Public environmental attention, media coverage, and corporate green innovation: evidence from heavily polluting industries in China.

Against the background of building a multi-environmental co-governance system, it is of great importance to systematically explore how public environmental attention (PEA) affects corporate green innovation (GI). Based on the panel data of Chinese A-share listed enterprises of heavily polluting industries from 2013 to 2020, this paper empirically explores the role of PEA in GI and examines the moderating impacts of media visibility and media favorability. The results indicate that the higher degree of public environmental attention, the more corporate green innovation.

How does China's stock market react to supply chain disruptions from COVID-19?

As a once-in-a-century global pandemic, COVID-19 severely hit the global economy and disrupted the worldwide supply chain. Based on 505 Chinese firms, we use the event study method to explore the effect of COVID-19 on the financial performance of firms. The findings show that COVID-19 has an immediate impact on Chinese firms.

The local-neighborhood effects of low-carbon city pilots program on PM in China: A spatial difference-in-differences analysis.

Using the balanced panel of 260 cities in China from 2005 to 2018, this study explores the local-neighborhood effects of the low-carbon city pilots (LCCPs) program on PM concentration by utilizing the spatial difference-in-differences (SDID) method. The results show that the LCCPs program can not only reduce the local PM concentration but also effectively alleviate the smog pollution in neighboring cities. The reduction effect of LCCPs on PM in local cities is more significant in central and western areas, second-tier and above cities and resource-based cities.

COVID-19 pandemic, limited attention, and analyst forecast dispersion.

This paper investigates the effect of the COVID-19 pandemic on analysts' forecast dispersion. We find that analysts' exposure to the COVID-19 lockdown reduces the dispersion of their forecasts. Along with the forecast dispersion, the number of earnings forecasts issued by treated analysts decreases, supporting the channel of attention distraction.

Investigating the Applicability of Alignment-A Monte Carlo Simulation Study.

Traditional multiple-group confirmatory factor analysis (multiple-group CFA) is usually criticized for having too restrictive model assumption, namely the scalar measurement invariance. The new multiple-group analysis methodology, alignment, has become an effective alternative. The alignment evaluates measurement invariance and more importantly, permits factor mean comparisons without requiring scalar invariance which is usually required in traditional multiple-group CFA.

The predicted trend of COVID-19 in the United States of America under the policy of "Opening Up America Again".

COVID-19 virus has been spreading worldwide for more than a year. At present, the situation of the new crown pneumonia epidemic remains full of tension and uncertainty. It is of concern is that the worst outbreak in the world is in the United States.