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The correlation between Chinese green finance markets and climate risks remains unknown, although the association between climate risks and finance markets has been extensively examined in earlier research. Therefore, this study analyzes the relationship among physical risk, transition risk, green bonds, green stocks, clean energy, and carbon markets across time, frequencies, and quantiles. To this end, the wavelet-based quantile Granger causality test and the time-frequency spillover based on the QVAR method are employed. We find that, at most frequencies and quantiles, both physical risk and transition risk are Granger causes of the green finance markets. Furthermore, the spillovers between climate risks and the green finance markets intensify as the quantile increases, with short-term spillovers predominating over medium- and long-term spillovers. Interestingly, these spillover dynamics exhibit notable crisis leaps in response to important occurrences, for instance, the COVID-19 crisis. Consequently, asymmetric spillover patterns are observed at different times, frequencies, and quantiles. In addition, as spillover transmitters and receivers encompass multiple quantiles and frequencies, physical risk and transition risk perform contradictory roles. Clean energy and green stocks are highly favorable investments against climate risks in turbulent markets. Notably, extreme climate events like the 2021 Henan rainstorm occurrences can reinforce spillovers between climate risks and green finance markets. Our discoveries present important information to market participants in Chinese green finance markets regarding portfolio diversification and risk governance. • Investigated the time-frequency spillovers between Chinese green finance markets and climate risks across quantiles. • The spillovers become more significant with the increasing quantile, whereas short-term spillovers predominate. • Both physical risk and transition risk are Granger causes of green finance markets at most frequencies and quantiles. [ABSTRACT FROM AUTHOR]

• The carbon price within the DICE model is adjusted to generate climate change scenarios. • Global physical costs increase by 5x under a 4.2°C versus a 2°C warming scenario. • Carbon pricing alone is not sufficient to reach 2°C by 2100. • Global carbon price currently estimated at $2.79 per ton of CO 2. Global carbon pricing has been recognized as one of the most efficient mechanisms that can be used to reduce CO 2 emissions, but questions remain about the magnitude of the price and the speed of implementation. We examine this important issue by extending the Dynamic Integrated Climate and Economy (DICE) model to estimate global carbon prices that will be required to reach various warming scenarios. Our analysis suggests that while carbon pricing can play a critical role in reducing greenhouse gas emissions and limiting global warming, it must be supported by other policy measures and innovations in order to reach the Paris Agreement targets. In particular, we found there was no feasible carbon pricing scenario that was high enough to limit emissions sufficiently to achieve anything below 2.4°C warming on its own. We project significant differences in global physical costs due to climate change across various warming scenarios, which range from a total (to 2100) of $152tr under a 1.5° scenario to $765tr under 4.2° warming. [ABSTRACT FROM AUTHOR]

In recent years, scholars have published numerous studies dealing with the consequences of climate change for businesses’ activity. However, a more holistic understanding of companies’ perceptions of and responses to physical, regulatory, and market-related climate risks across a wider range of sectors is still missing. To address this gap, this paper provides an empirical analysis of corporate climate risk perception and countermeasures for companies in industries regulated and not regulated by climate policy. Drawing on data from the Carbon Disclosure Project of a size-matched sample of 126 European-based companies, it is shown that most firms feel less exposed to physical and market risks than to regulatory risks. This is because physical risks are expected to materialize in the more distant future and the realization of market risks is considered rather unlikely. Moreover, the results indicate that firms in regulated industries implement more regulatory response measures than firms that are part of non-regulated industries, while, interestingly, there are no significant differences between the two groups in exposure and responses to physical and market risks. By discussing climate-related risks and highlighting the significant role of regulation in spurring corporate action in the context of climate change, this paper holds important implications for corporate managers and policy makers. [ABSTRACT FROM AUTHOR]

• The DICE model is customized specifically to estimate costs to the Canadian economy. • Physical costs due to climate change double under a 5°C versus 2°C warming scenario. • Inflection points occur in 2050 and 2070 when climate damage costs accelerate. • Investments to curb warming more than pay for themselves in terms of avoided costs. The Office of the Superintendent of Financial Institutions, the Bank of Canada, and several key financial institutions recently published a report examining transitional risks to the Canadian economy under various climate change scenarios. However, their results leave an important void with respect to the impact of physical risks and the associated costs of climate change for Canada, such as the loss of biodiversity, sea-level rise, and infrastructure damage due to fires and floods, etc. We fill this void by updating the Dynamic Integrated Climate and Economy model developed by 2018 Nobel Laureate William Nordhaus to project physical damages due to climate change for Canada. Our results illustrate stark differences in physical costs under various warming scenarios, highlighting the importance of taking action to mitigate climate change. We find that undertaking the required investments to reduce greenhouse gas (GHG) emissions more than pays for itself in terms of avoided physical damage alone. [ABSTRACT FROM AUTHOR]

Augmented reality (AR) has become a promising technology in the gaming industry. However, few research studies have examined users' perspectives towards mobile AR games. To address this issue, the present study proposed a research model to better understand the factors determining and shaping users' behavioral intention to adopt mobile AR games from a developing country environment. Based on a literature review, nine factors have been expected to determine and shape individuals' intention towards the acceptance and adoption of mobile AR games. Using WarpPLS software, the model was empirically tested with a survey of 240 non-adopter respondents collected via an online survey questionnaire. The model was found statistically robust in terms of measurement quality criteria: reliability, validity, multicollinearity, and goodness of fit. The analysis revealed that perceived ease-of-use, social norms, privacy, perceived enjoyment, perceived competition, perceived inspiration, perceived image, and perceived innovativeness affect users' behavioral intention to adopt mobile AR games. However, the hypothesized moderating impact of perceived physical risk on the relationships connecting perceived ease-of-use, perceived enjoyment, perceived competition, and perceived inspiration with the intention to adopt was found to have little statistical significance. The result showed that perceived innovativeness was the strongest criterion to affect intention, and perceived ease-of-use was found to be the least important criterion in impacting users' intention. Interestingly, the model explains 76% of the variance in behavioral intention to adopt mobile AR games. This study offers theoretical and practical implications for its findings. • Augmented reality has the potential to revolutionize gaming practices and mobility. • This study is one of the first attempts to explore the adoption of mobile AR games from a developing country perspective. • This study proposed a model to understand the factors determining the intention to adopt mobile AR games. • Ease-of-use, social norms, privacy, enjoyment, competition, inspiration, image, and innovativeness affect intention. • The model explains a staggering 76% of the variance in behavioral intention to adopt mobile AR games. [ABSTRACT FROM AUTHOR]