The new ecological paradigm and responses to climate change in China

The purpose of this study was to develop and evaluate a Chinese-Mandarin version of the revised new ecological paradigm (NEP-R) scale. In a sample of 515 Mandarin-speaking Chinese nationals, we first assessed the factor structure and internal consistency of the NEP-R and assessed its validity by examining associations with global warming risk perceptions and mitigation behavior. Respondents completed the NEP-R scale, together with measures of risk perception and mitigation behavior. Exploratory and confirmatory factor analyses indicated that a two-factor solution, reflecting ecocentric and anthropocentric worldviews, best fit the data. Multi-group path analysis revealed that respondents with stronger ecocentric and weaker anthropocentric worldviews perceived more risks associated with global warming. In turn, respondents who perceived more risks reported engaging in more global warming mitigation behaviors. But importantly, the path between risk perceptions and behavior was significantly stronger for highly educated respondents than for less educated respondents, suggesting that education may represent an important strategy for bridging the gap between perceived risks about global warming and action.     

Forecasting value at risk and expected shortfall with mixed data sampling

I propose applying the Mixed Data Sampling (MIDAS) framework to forecast Value at Risk (VaR) and Expected shortfall (ES). The new methods exploit the serial dependence on short-horizon returns to directly forecast the tail dynamics of the desired horizon. I perform a comprehensive comparison of out-of-sample VaR and ES forecasts with established models for a wide range of financial assets and backtests. The MIDAS-based models significantly outperform traditional GARCH-based forecasts and alternative conditional quantile specifications, especially in terms of multi-day forecast horizons. My analysis advocates models that feature asymmetric conditional quantiles and the use of the Asymmetric Laplace density to jointly estimate VaR and ES.     

Financial risk taking in the presence of correlated non-financial background risk

This paper characterizes the stochastic deterioration resulting from taking a zero-mean financial risk in the presence of correlated non-financial background risk. We show in particular that it has an equivalent stochastic order as well as a necessary and sufficient “integral condition” that implies and is implied by a particular sense in which the stochastic deterioration can be decomposed into a “correlation increase” and a “marginal risk increase”. We further characterize a measure of aversion to the stochastic deterioration. These characterizations provide for a more general framework for formulating concepts of increases in risk and correlation and for better understanding risk management decisions governed by individuals’ attitudes to them.     

Cooperative game with nondeterministic returns

We study a non-traditional cooperative game where returns from coalitions are nondeterministic. The long-standing concept of core can be generalized to reflect players’ contentment with their allocations. It is now imperative to formalize the restrictions, such as those pertaining to information, on allocations. The latter are also at times more conducive to fractional representations. With probabilistic structures added, nondeterministic returns become random variables, utility functions attain risk-attitude connotations, and the timing of players’ allocation resolutions gains significance. Under various conditions for utility functions, we show how various core concepts of the general game can be related to its traditionally defined auxiliaries. These developments help pave the way for our illustrations, within two distinct settings, that players’ increased risk aversion would promote the formation of the grand coalition.     

Geographies of Algorithmic Violence: Redlining the Smart City

City governments are embracing data-driven and algorithmic planning to tackle urban problems. Data-driven analytics have an unprecedented capacity to call urban futures into being. At the same time, they can depoliticize planning decisions. I argue that this shift calls urban studies scholars to investigate geographies of algorithmic violence—a repetitive and standardized form of violence that contributes to the racialization of space and spatialization of poverty. This article examines this broader phenomenon through the case of a proprietary market value assessment that is being used to guide development in cities across the United States. The assessment employs an algorithm that helps city officials make critical decisions about which neighborhoods to target for investment, disinvestment and public service upgrades or disconnections. I argue that the racial, infrastructural, and epistemological violence associated with this evaluation can potentially lead to a new kind of municipal redlining. The article brings insights from critical race theory into conversation with critical scholarship on algorithms by analyzing how algorithmic violence works through data-driven planning technologies to depoliticize and leverage power while further entrenching racism and inequality.     

Corporates' strategic responses to economic policy uncertainty in China

Using a novel news‐based index of economic policy uncertainty, this paper studies the impact of economic policy uncertainty on corporate strategic positioning and corporate risk in China from 2009 to 2015. The study also investigates the impact of corporate strategic positioning on corporate risk. The results show that corporate strategic positioning and economic policy uncertainty have a significant positive impact on corporate risk. The results also explain that economic policy uncertainty increases the market risk of the firms irrespective of their corporate strategy. However, it increases the business risk of prospector firms and decreases the business risk of defensive firms. The study may help the firms to formulate and improve their strategic positioning while considering economic policy uncertainty. Our results are robust to alternate proxies of economic policy uncertainty and corporate risk.     

Operational excellence in a green supply chain for environmental management: A case study

Nowadays, organizations have started to become more conscious about the environment in their supply chain operations. The greening process has guided supply chain practices into new ways of thinking according to green standards. The assessment of the performance of green supply chain management (GSCM) requires a holistic view for the whole supply chain. In this context, given that becoming green in the operational side of activities is essential, the performance assessment of operational activities also requires a holistic view to be taken. In this paper, an attempt has been made to improve the performance of GSCM by examining and evaluating the green operational excellence of a hot dip galvanizing company. The framework includes several green operational excellence key criteria, namely, quality management, efficiency management, green production/manufacturing, eco‐packaging, and green design. First, the weights of the criteria and the respective measurements were found by fuzzy analytic network process. Then, the overall operational performance score was found by a weighted scoring method. Finally, both managerial and theoretical implications were suggested according to the outcomes and findings of the case study.     

Environmental policies,national culture,and stock price crash risk: Evidence from renewable energy firms

This study investigates the impact of country‐level environmental performance and national culture on the stock price crash risk of renewable energy firms. Employing a large sample of 626 renewable energy firms across 31 countries, we find a significant nonlinear relationship between country‐level environmental performance and crash risk. National culture dimensions are found to strongly predict the crash risk of renewable energy firms, particularly after the global financial crisis. On the contrary, national culture dimensions and environmental policies are observed to not exert any significance in explaining the crash risk of fossil fuel firms. Our results are robust with respect to alternative measures of stock price crash risk and the endogeneity of national culture dimensions. Overall, the findings of this paper contribute to the environmental economics literature by providing new evidence regarding the role of societal and environmental factors in explaining the stock price crash risk of energy firms.     

互联网金融的信用风险评估与预警研究

随着互联网金融的蓬勃发展，用户对消费金融的需求也越来越丰富多样。满足用户的多样化需求与建立健全风险监管体系成为互联网金融发展的重中之重。如何实现数据驱动服务升级、技术辅助市场监管成为研究的热点问题。本文通过数据处理与特征工程实现用户认证信息、金融信息、行为信息的融合，利用深度森林算法建立模型进行信用风险评估。结果表明，该方法能有效挖掘数据潜在价值，提高信用风险评估与预警效果。最后，本文针对互联网金融的信用风险预警与市场监管提出了建议。     

Political risk in private participation projects: The effects of political discretionality and corruption

This article investigates the impact of political risk on the performance of private participation infrastructure projects in emerging markets. Previous studies have shown that firms in regulated sectors are prone to employ political capabilities in their investments overseas. Our analysis of 32,257 projects in 114 emerging countries from 1997 to 2013 shows that higher political discretionality in the host country is negatively associated with project completion. In contrast, a higher level of corruption in the host country is positively associated with project completion. The study makes a contribution to the literature on political risk in foreign direct investments.