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This paper examines the roles of digital finance development in household income, consumption, and financial asset holding from an extreme value theory perspective. Three types of extreme pairs (Min to Min, Max to Max, and Max to Min) are constructed, corresponding to the three aspects of the economic welfare of digital finance: fairness, efficiency, and their trade-off. Using panel data from the Peking University Digital Financial Inclusion Index of China (PKU-DFIIC) and China Family Panel Studies (CFPS) over time span 2014–2018, this paper models the block maxima and minima of variables by fitting them with generalized extreme value (GEV) distribution. The binary expansion testing (BET) is used to detect the nonlinear dependence between digital finance and household economic variables. The tail quotient correlation coefficient (TQCC) is used to quantify the tail dependencies. The results show that: (1) digital finance has significant fairness effects in reducing poverty, increasing consumption, and promoting financial asset holding; (2) digital finance shows effects of promoting incentives and efficiency in household income and financial asset holding, but this effect is relatively limited in household consumption; (3) digital finance generally increases efficiency without harming fairness in terms of all cases of household income and consumption, and most of the cases regarding household financial asset holding; (4) the positive spatial externality of digital finance exists for all household economic variables; and, for pairs regarding household income and consumption, the wider the scope, the greater the spatial spillover effect. The result of this paper implies many novel policy implications. [ABSTRACT FROM AUTHOR]

Emission trading scheme (ETS), the most popular market-based instrument, is widely used to solve carbon emission problems in the world. With the development of carbon market, carbon asset has been a popular financial product to invest and the risk management becomes important for government, regulated enterprises and other investors. As carbon prices have tail characteristics, this paper explores the extremal risks between carbon markets in US, Europe and China using tail dependence correlation coefficients. The empirical analysis demonstrates the tail dependence structure between carbon markets in US. and Europe is the same sign, which indicates that it is unwise to hold these two carbon assets as a portfolio. Moreover, the co-movements between European Union Emission Trade Scheme (EU ETS) and China's carbon markets are partly significant, and the operation mechanisms in China should be improved. In addition, the tail dependence test among the carbon pilots in China shows diversity. Hubei carbon trading pilot, located in central China, has extremal dependence with all other selected pilots for its regulatory program operation. The findings give insight to the carbon market regulars to improve the operation mechanism and are also useful for the investors to manage their portfolios, policymakers to make practically applicable regulations, and relevant organizations to develop procedures. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the impact of neutrophil-to-lymphocyte ratio (NLR) and preoperative prognostic nutritional index (PNI) on prognosis of gastric cancer (GC) after adjuvant FOLFOX chemotherapy. Materials and Methods: Data on 749 GC patients who received operation after by adjuvant FOLFOX chemotherapy between January 2013 and December 2015 were enrolled in this study, retrospectively. Receiver-operating characteristic curve analysis was employed to assess optimal cutoff thresholds for PNI and NLR. The GC subjects having a low PNI (<52.8) and high NLR (>1.79) received a score of 2. Any variable that met these standards was scored as 1. If none of the two variables met these standards of the patient was assigned a score of 0. Correlation between PNI-NLR score and GC stage was also evaluated. Results: The mean overall survival (OS) and 5-year OS rate for subjects with PNI-NLR = 2 was lower than those of subjects with PNI-NLR = 1, or 0 (40.9% vs. 52.1%, 76.4% [46.0 vs. 61.0], 68.0 months, p ≤ 0.001). In multivariate analyses, the PNI-NLR score (p ≤ 0.001) and WHO grade (p ≤ 0.001) showed potential to independently influence OS. Conclusions: High PNI-NLR scores can independently affect worse prognosis of GC. Thus, it can be utilized to differentiate low risk from high risk subjects. [ABSTRACT FROM AUTHOR]

This paper seeks to explore the relationship among the large declines in China’s stock market and stock markets in the United States, the United Kingdom, Japan, and Hong Kong, and to forecast future large declines in China’s stock market. We apply mutually exciting marked Hawkes processes—where the occurrences of large declines are regarded as events whose magnitudes follow generalized Pareto distributions—to study the interaction between the different stock markets. We find that these interactions are asymmetric. The occurrences of large declines in the Chinese stock market will stimulate declines in the United States and the United Kingdom, and especially in Japan’s and Hong Kong’s stock markets. However, only large declines in Hong Kong’s market have a substantial influence on the occurrence of big declines in China’s market. Finally, we try to predict the time of occurrence of the next major decline in China’s stock market using information from our empirical results. [ABSTRACT FROM PUBLISHER]

This paper is concerned with the statistical learning of the extreme smog (PM 2.5 ) dynamics of a vast region in China. Differently from classical extreme value modeling approaches, this paper develops a dynamic model of conditional, exponentiated Weibull distribution modeling and analysis of regional smog extremes, particularly for the worst scenarios observed in each day. To gain higher modeling efficiency, weather factors will be introduced in an enhanced model. The proposed model and the enhanced model are illustrated with temporal/spatial maxima of hourly PM 2.5 observations each day from smog monitoring stations located in the Beijing–Tianjin–Hebei geographical region between 2014 and 2019. The proposed model performs more precisely on fittings compared with other previous models dealing with maxima with autoregressive parameter dynamics, and provides relatively accurate prediction as well. The findings enhance the understanding of how severe extreme smog scenarios can be and provide useful information for the central/local government to conduct coordinated PM 2.5 control and treatment. For completeness, probabilistic properties of the proposed model were investigated. Statistical estimation based on the conditional maximum likelihood principle is established. To demonstrate the estimation and inference efficiency of studies, extensive simulations were also implemented. [ABSTRACT FROM AUTHOR]

Traditional Chinese medicine (TCM) plays a major role in preventing and treating the disease, however, it is also facing a slice of challenges as fewer choices of TCM treatment. Although lifestyles and health conditions might be paramount influencing factors for the choice of TCM treatment, the relative evidence is scarce. The current observational study was designed to evaluate this association. A total of 24,173 Chinese individuals with a mean age of 47.3 years from the Chinese Family Panel Studies 2014 were selected. The choice of TCM treatment was acquired by the self-report questionnaire. Latent class analysis was employed to identify clusters of lifestyles and health conditions. The binary logistic regression model was employed to examine the association between lifestyles, health conditions and the choice of TCM treatment. Lifestyles and health conditions were classified into 3 classes with latent class analysis, healthy group, unhealthy behavior group, and physical inactivity group. After controlling for potential confounding factors, the results showed individuals in unhealthy behavior group (odds ratio = 1.51, 95% confidence interval: 1.35-1.68, P < .001) or physical inactivity group (odds ratio = 1.11, 95% confidence interval: 1.02-1.22, P = .019) were more likely to visit TCM doctors than healthy group. Sex-specific difference was observed, the relationship still existed among the males. The current study revealed the relationship between lifestyles, health conditions and the choice of TCM treatment. This will provide evidence for the TCM development and provide support for further research., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc.)