摘要：
Accurately predicting hydrological runoff is crucial for water resource allocation and power station scheduling. However, there is no perfect model that can accurately predict future runoff. In this paper, a daily runoff prediction method with a seasonal decomposition-based-deep gated-recurrent-unit (GRU) method (SD-GRU) is proposed. The raw data is preprocessed and then decomposed into trend, seasonal, and residual components using the seasonal decomposition algorithm. The deep GRU model is then used to predict each subcomponent, which is then integrated into the final prediction results. In particular, the hyperparameter optimization algorithm of tree-structured parzen estimators (TPE) is used to optimize the model. Moreover, this paper introduces the single machine learning model (including multiple linear regression (MLR), back propagation (BP), long short-term memory neural network (LSTM) and gate recurrent unit (GRU)) and a combination model (including seasonal decomposition–back propagation (SD-BP), seasonal decomposition–multiple linear regression (SD-MLR), along with seasonal decomposition–long-and-short-term-memory neural network (SD-LSTM), which are used as comparison models to verify the excellent prediction performance of the proposed model. Finally, a case study of the Qingjiang Shuibuya test set, which considers the period 1 January 2019 to 31 December 2019, is conducted. Case studies of the Qingjiang River show the proposed model outperformed the other models in prediction performance. The model achieved a mean absolute error (MAE) index of 38.5, a Nash-Sutcliffe efficiency (NSE) index of 0.93, and a coefficient of determination (R2) index of 0.7. In addition, compared to the comparison model, the NSE index of the proposed model increased by 19.2%, 19.2%, 16.3%, 16.3%, 2.2%, 2.2%, and 1.1%, when compared to BP, MLR, LSTM, GRU, SD-BP, SD-MLR, SD-LSTM, and SD-GRU, respectively. This research can provide an essential reference for the study of daily runoff prediction models.
期刊：
International Journal of Machine Learning and Cybernetics,2024年15(3):1055-1073 ISSN：1868-8071
通讯作者：
Zhou, LG
作者机构：
[Zhou, Yuanyuan; Zheng, Chengli] Cent China Normal Univ, Sch Econ & Business Adm, Financial Engn Res Ctr, Wuhan 430079, Peoples R China.;[Wu, Peng] Anhui Univ, Sch Business, Hefei 230601, Peoples R China.;[Zhou, Ligang] Anhui Univ, Sch Math Sci, Hefei 230601, Peoples R China.
通讯机构：
[Zhou, LG ] A;Anhui Univ, Sch Math Sci, Hefei 230601, Peoples R China.
关键词：
Additive trapezoidal fuzzy preference relation;Priority vector;Compatibility;COWA operator;Optimization model
摘要：
Considering the conflicting opinions and different risk attitudes among decision-makers (DMs) in group decision making (GDM), this paper develops a novel compatibility model with additive trapezoidal fuzzy environment based on continuous ordered weighted averaging (COWA) operator to handle the conflicts. First, some concepts of COWA operator-based compatibility index and characteristic preference relation for additive trapezoidal fuzzy preference relation (ATFPR) are discussed. Then a compatibility reaching algorithm is designed to assist each ATFPR in achieving acceptable compatibility. Moreover, the expert weight optimization model based on the criterion of minimum compatibility of preference relation in GDM is established. Furthermore, a GDM process based on compatibility measures with ATFPRs is introduced, and an application of the proposed approach is put forward. The novelties of our approach are that: (1) COWA operator can deal with the compatibility of all arguments by using controlled parameters that consider the risk attitudes of DMs rather than the compatibility of the simply two points in intervals; (2) compatibility improving algorithm makes sure that the original opinions are retained as much as possible because only one pair of preference relation elements are revised in each round; (3) optimal weights model ensures that weights of DMs in group aggregation are determined availably.
作者机构：
[Liu, Botao; Tu, Zhengge; Liu, BT] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;[Liu, Botao; Tu, Zhengge; Liu, BT] Cent China Normal Univ, Res Ctr Low Carbon Econ & Environm Policies, Wuhan 430079, Peoples R China.;[Kong, Jiayang] Qinghai Univ Sci & Technol, Coll Comp & Informat Sci, Xining 810016, Peoples R China.;[Kong, Jiayang] Qinghai Univ, Dept Comp Technol & Applicat, Xining 810016, Peoples R China.;[Sun, Liping] Shandong Normal Univ, Audit Off, Jinan 250014, Peoples R China.
通讯机构：
[Liu, BT ] C;Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;Cent China Normal Univ, Res Ctr Low Carbon Econ & Environm Policies, Wuhan 430079, Peoples R China.;Cent China Normal Univ, Sch Math & Stat, Wuhan 430079, Peoples R China.
关键词：
digital economy;entropy method;internet development;regional development imbalance;rural-urban income gap
摘要：
Currently, the Chinese government is considering two major strategies, namely, developing the digital economy and achieving common prosperity, to address regional development imbalances. Using panel data from 276 Chinese cities spanning from 2011 to 2019, the article first employs the entropy method to measure China’s digital economy development, digital fusion application, and Internet accessibility. Subsequently, the paper evaluates the influence of the digital economy on regional development imbalances, focusing on the rural-urban income gap. The results show a significant reduction in the rural-urban income gap due to digital economy development. Notably, digital fusion applications have a greater impact on reducing the rural-urban income gap than Internet accessibility. In addition, a heterogeneity analysis reveals that the influence of the digital economy on the rural-urban income gap is only reflected in the eastern and western regions, with a more substantial effect observed in the western region. This study, to some extent, helps Chinese government officials distinguish the diverse impacts of different dimensions and regional variations in digital economies on the rural-urban income gap. Such insights can guide the government in strategically advancing digital economy development to accelerate the mitigation of regional disparities and achieve sustainable economic development.
关键词：
Carbon trading market;Synergizing the reduction of pollution and;carbon emissions;Technological progress;DSGE model;Carbon allowance
摘要：
This study introduces three production technology shocks (Energy manufactures, Brown enterprises, and Green enterprises) by constructing different models, namely, the environment sector (baseline) model, the carbon emissions trading scheme (ETS) model, and the carbon emissions rights trading mechanism. The fluctuation trend of China's macroeconomic and environmental quality before and after the establishment of carbon market is compared and analyzed. Additionally, the study examines the welfare of the implementation of carbon market policies. The carbon trading market policy can promote the synergistic efficiency of China's pollution reduction and carbon reduction using energy and green production technologies. From the perspective of social welfare, the optimal range of the initial carbon quota ratio issued by the government to enterprises is [0.7,0.8]. The findings of this study provide theoretical support and contribute toward understanding the impact mechanisms of carbon market and technological progress on synergizing the reduction of pollution and carbon emissions in China.
关键词：
Information exposure;information avoidance;social media;low-carbon behavior;China
摘要：
Social media greatly facilitates people's access to information; however, it can also lead to information overload and exposure to uncomfortable content that may cause individuals to avoid it. As a result, two types of influencing mechanisms emerge: information exposure and information avoidance, which may impact users' behaviors. Currently, there is limited understanding of the simultaneous effects of social media information exposure and avoidance on individuals' behavioral intentions towards climate change mitigation. Using survey data for 1056 Chinese Gen-Z undergraduates and based on the extended theory of planned behavior, this paper utilizes a partial least squares structural equation model to examine the effects of social media information exposure and information avoidance on individual low-carbon behavioral intention. The results show that information exposure on social media has a positive relationship with behavioral attitude, subjective norm, and perceived behavioral control, and then increasing the low-carbon behavioral intention. Information avoidance has a negative association with three factors, respectively, and decreases the low-carbon behavioral intention. Additionally, exposure to social media information has the greatest impact on the subjective norm and the least impact on behavioral attitude; information avoidance has the greatest impact on behavioral attitude, whereas perceived behavioral control is the least affected. Drawing from the results, we propose policy recommendations that facilitate information exposure while addressing avoidance in shaping low-carbon behavioral intentions. Those implications would help reconcile the two opposing effects while promoting public engagement in climate activities.
作者机构：
[Su, Kuangxi] Xinyang Normal Univ, Sch Math & Stat, Xinyang, Peoples R China.;[Yao, Yinhong] Capital Univ Econ & Business, Sch Management & Engn, Beijing, Peoples R China.;[Zheng, Chengli] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan, Peoples R China.;[Xie, Wenzhao] Changjiang Secur Co Ltd, Wuhan, Peoples R China.
通讯机构：
[Chengli Zheng] S;School of Economics and Business Administration, Central China Normal University, Wuhan, China
关键词：
Portfolio selection;Empirical mode decomposition;Correlation coefficient test;Financial data denoising
摘要：
As the relationship between climate change and agricultural production increasingly gains attention, the FAO recommends the adoption of climate-smart agriculture practices (CSAPs) to ensure the stable development of agriculture amidst changing climatic conditions. However, the adoption rate of CSAPs remains low and the effects of livelihood capitals have received little attention. Based on the survey data for 916 farmers in the Jianghan Plain of China, this paper adopts a multivariate Probit model to examine the impact of farmers’ livelihood capitals which are measured by an entropy-TOPSIS approach on their adoption of CSAPs. Our results demonstrate that different livelihood capitals exert various influence on the adoption of CSAPs. Specifically, human, financial, physical, and social capital have positive relationships with pesticide-oriented CSAPs such as integrated pest management (IPM). Natural capital has a positive relationship with seed- and water- oriented CSAPs like tolerant rice varieties (TRV). Natural capital positively relates to soil-oriented CPSPs including rice straw mulching (RSM) while physical capital has a negative effect. Natural and physical capitals have positive relationships with fertilizer-oriented CSAPs like deep placement of fertilizer (DPF). Social and natural capitals have positive relationships with soil-oriented CSAPs such as no-tillage direct seeding (NTDS) while financial capital has a negative effect. Climate factors are also important in the adoption of CSAPs such as TRV and RSM. Finally, policy recommendations are suggested to enhance household livelihood capitals to promote the adoption of each type of CSAP.
摘要：
Technological innovation is crucial for creating sustainable corporate value and shaping competitive advantage in the market. ESG, as an indicator of corporate value practices, plays a significant role in enterprise technological innovation. However, there is little empirical evidence to support this claim. This study analyzes the relationship between ESG performance and technological innovation in Chinese A-share listed enterprises from 2011 to 2021. The statistical data shows that strong ESG performance has a significant positive impact on corporate technological innovation. ESG performance can promote corporate technological innovation through external mechanisms, such as enhancing corporate network location and increasing institutional shareholding. Additionally, internal mechanisms, such as reducing labor costs and easing financing constraints, can also promote corporate technological innovation. The impact of ESG performance on corporations exhibits heterogeneity, with ESG performance promoting innovation more strongly among labor-intensive firms, non-state-owned firms, highly competitive industries, and mature firms. Based on the study results, it is recommended that enterprises actively practice ESG development concepts, optimize their equity structure, strengthen information communication with stakeholders, and alleviate problems such as information asymmetry to improve their technological innovation. The government should focus on enterprise characteristics, improve ESG development policies, and promote enterprise innovation through ESG performance.
作者机构：
[Su, Kuangxi] Xinyang Normal Univ, Sch Math & Stat, Xinyang, Peoples R China.;[Zheng, Chengli; Yu, Xing] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan, Peoples R China.
通讯机构：
[Su, KX ] X;Xinyang Normal Univ, Sch Math & Stat, Xinyang, Peoples R China.
关键词：
Portfolio allocation;Complete EEMD with adaptive noise;Financial data denoising;CEEMDAN denoising
摘要：
Effective denoising strategies are increasingly important for portfolio investors. Considering that the common ensemble empirical mode decomposition (EEMD)-based stepwise denoising algorithms suffer from white noise interference and ignore the effect of low-frequency redundant noise components on the portfolio, a novel complete EEMD with adaptive noise (CEEMDAN) denoising algorithm is proposed to improve the portfolio performance. Specifically, we apply CEEMDAN to decompose noisy prices into a series of intrinsic mode functions (IMFs). Then, a series of tests based on the correlations between the original noisy prices and the decomposed IMFs are performed to identify which IMFs are noisy modes. If the tests accept the null hypothesis, the IMFs are considered as noisy components. Finally, we use the soft-threshold technique to process the noisy components and sum the non-noisy components to construct the denoised prices. The empirical results show that under the dynamic minimum-CVaR framework, the proposed CEEMDAN denoising algorithm is not affected by white noise and outperforms the EEMD denoising and stepwise denoising algorithms in improving out-of-sample portfolio returns. Overall, the proposed CEEMDAN denoising is the optimal denoising algorithm, which can help investors improve portfolio performance to the greatest extent.
作者机构：
[Liu, Chong] Northeastern Univ, Coll Sci, Shenyang 110819, Peoples R China.;[Wu, Wen-Ze] Cent China Normal Univ, Sch Econ, Business Adm, Wuhan 430079, Peoples R China.;[Xie, Wanli] Qufu Normal Univ, Sch Commun, Rizhao 276826, Peoples R China.
通讯机构：
[Wen-Ze Wu] S;School of Economics and Business Administration, Central China Normal University Wuhan 430079, China
关键词：
Grey system theory;Multiobjective grey wolf optimizer;Time series prediction;Weakened accumulation operator
摘要：
As a combination of the differential equation prediction model and intelligent optimiza-tion algorithm, the grey intelligent prediction algorithm has attracted increasing attention due to its outstanding performance in small-sample environments. However, most studies focus only on the improvement of algorithm performance, with little regard to the uni-formity, ill-condition and overfitting of the algorithm. To promote the development of this field, we develop a new grey intelligent prediction algorithm with multiobjective correc-tion strategy based on the new weakened accumulation grey optimization model and the multiobjective grey wolf optimizer. In this new prediction algorithm, the new weakened accumulation operation is utilized to enhance the predictive ability of the algorithm and mitigate the ill-condition of the system, the Bernoulli parameter and a discretization tech-nique are used to activate the uniformity and unbiasedness of the algorithm, respectively, and the multiobjective grey wolf optimizer is employed to alleviate the overfitting of the system. Compared with the previous grey intelligent prediction models, the new prediction algorithm is more perfect and reasonable. Taking two energy datasets as research cases, the evaluation results of a system consisting of six evaluation metrics and the Diebold -Mariano test show that the proposed model outperforms the other six comparative mod-els in terms of prediction performance and stability, which confirms the feasibility and validity of the algorithm. (c) 2023 Elsevier Inc. All rights reserved.
作者机构：
[He, Feifei; Chen, Shu] Minist Water Resources China, Changjiang Water Resources Commiss, Changjiang River Sci Res Inst, Wuhan 430010, Peoples R China.;[He, Feifei; Chen, Shu] Hubei Key Lab Water Resources & Eco Environm Sci, Wuhan 430010, Peoples R China.;[He, Feifei; Chen, Shu] ChangJiang Water Resources Commiss, Res Ctr Yangtze River Econ Belt Protect & Dev Stra, Wuhan 430010, Peoples R China.;[Yang, Yuqi; Zhang, Hairong] China Yangtze Power Co Ltd, Hubei Key Lab Intelligent Yangtze & Hydroelect Sci, Yichang 443000, Peoples R China.;[Wan, Qinjuan] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.
通讯机构：
[Hairong Zhang] H;Hubei Key Laboratory of Intelligent Yangtze and Hydroelectric Science, China Yangtze Power Co., Ltd., Yichang 443000, China<&wdkj&>Author to whom correspondence should be addressed.
关键词：
streamflow prediction;Bayesian model averaging;machine learning;hyperparameter optimization
摘要：
Medium-term hydrological streamflow forecasting can guide water dispatching departments to arrange the discharge and output plan of hydropower stations in advance, which is of great significance for improving the utilization of hydropower energy and has been a research hotspot in the field of hydrology. However, the distribution of water resources is uneven in time and space. It is important to predict streamflow in advance for the rational use of water resources. In this study, a Bayesian model average integrated prediction method is proposed, which combines artificial intelligence algorithms, including long-and short-term memory neural network (LSTM), gate recurrent unit neural network (GRU), recurrent neural network (RNN), back propagation (BP) neural network, multiple linear regression (MLR), random forest regression (RFR), AdaBoost regression (ABR) and support vector regression (SVR). In particular, the simulated annealing (SA) algorithm is used to optimize the hyperparameters of the model. The practical application of the proposed model in the ten-day scale inflow prediction of the Three Gorges Reservoir shows that the proposed model has good prediction performance; the Nash-Sutcliffe efficiency NSE is 0.876, and the correlation coefficient r is 0.936, which proves the accuracy of the model.
期刊：
Decision Support Systems,2023年177:114103 ISSN：0167-9236
通讯作者：
Wu, LL
作者机构：
[Deng, Shiming] Huazhong Univ Sci & Technol, Sch Management, Luoyu Rd 1037, Wuhan 430074, Peoples R China.;[Chen, Rachel] Univ Calif Davis, Grad Sch Management, Davis, CA 95616 USA.;[Wu, Lingli; Wu, LL] Cent China Normal Univ, Sch Econ & Business Adm, Luoyu Rd 152, Wuhan 430079, Hubei, Peoples R China.;[Wu, Lingli] Hong Kong Polytech Univ, Dept Logist & Maritime Studies, 11 Yuk Choi Rd, Hong Kong, Peoples R China.
通讯机构：
[Wu, LL ] C;Cent China Normal Univ, Sch Econ & Business Adm, Luoyu Rd 152, Wuhan 430079, Hubei, Peoples R China.
关键词：
Consumer fit uncertainty;Fit revelation;Advertising;Complementarity;Substitutability
摘要：
Consumers are often uncertain about how a product fits their individual preferences before purchase. To resolve such uncertainty, firms can use fit-revelation activities such as sampling, product demonstration, and virtual showrooms. Recently, there is an emerging trend of combining product sampling with advertising (e.g., Amazon’s sampling-advertising initiative). Empirical research has shown that fit-revelation may enhance or weaken the effect of advertising. We contribute to the literature by developing an analytical model that links these interactions with the firm’s strategic decisions. We find that, interestingly, when fit-revelation enhances the effect of advertising, these two instruments are not necessarily complementary. Our study further characterizes the firm’s strategy space of whether to conduct fit-revelation alone, advertising alone, or both. We show that advertising may reverse the firm’s decision on whether to facilitate fit-revelation. Moreover, how complementarity/substitutability affects the optimal strategy depends on the types of ads. While substitutability denies the optimality of the joint strategy under informative ads, it fails to do so under persuasive ads. On the other hand, complementarity is necessary for the joint strategy to be optimal under informative ads, which is not the case under persuasive ads. Finally, we extend our analysis to targeted fit-revelation/advertising with heterogeneous consumers ex ante, in which case the firm may find it optimal to target low-valuation consumers. Given the latest trends and growing interest in the deployment of joint advertising and sampling, our study offers timely insights for practitioners.
作者机构：
[Cui, Chunying] Yiwu Ind & Commercial Coll, Sch Econ & Management, Yiwu 322000, Peoples R China.;[Cui, Chunying] Cent China Normal Univ, Sch Econ & Business Management, Wuhan 430079, Peoples R China.;[Yan, Ziwei] Wenhua Coll, Dept Econ & Management, Wuhan 430073, Peoples R China.
关键词：
digital economy;domestic non-tradable sectors;regional economic growth
摘要：
The impact of the digital economy (DE) has become the important faction of the market volume of domestic non-tradable sectors (DNSs). As rising digitalization supersedes traditional market power as a driving force, there is increasing concern about the volume of trade and economy; however, the literature of how the DE procession changed the DNS's are limited, although the Chinese government is eager to enlarge the scale of the domestic market to be consistent with the trend of digitalization. This paper addressed this issue by employing a series of data from prefecture-level cities between 2010 and 2019 in China. Using panel data methods under fixed effect, synthetic difference-in-differences (SDID), and temporal-spatial econometrics, the paper's hypothesis sheds light on the positive impact of the DE on DNSs. The regression results showed a 14.84% of improvement for the effects of DE development on DNS growth. The policy impact effect increased the average treatment effect by 3.9% average treatment effect, accompanied by temporal and spatial correlations. Further analysis illustrated that a possible intermediary mechanism through which the DE promotes the development of DNSs is the enhancement of the local product market development. It was concluded that policy-makers of developing countries should be devoted to breaking down domestic trade barriers among different regions to enhance the benefits of digitalization.
作者机构：
[Wang, Yang] Wuhan Univ, Econ & Management Sch, 299 Bayi Rd, Wuhan 430072, Peoples R China.;[Tian, Chenling] Cent China Normal Univ, Sch Econ & Business Adm, 382 Xiongchu Rd, Wuhan 430079, Peoples R China.;[Jiang, Xia] Nanjing Univ, Business Sch, 22 Hankou Rd, Nanjing 210093, Peoples R China.;[Tong, Yang; Tong, Y] Zhejiang Normal Univ, Coll Econ & Management, China Afr Int Business Sch, 688 Yingbin Rd, Jinhua 321004, Peoples R China.
通讯机构：
[Jiang, X ] N;[Tong, Y ] Z;Nanjing Univ, Business Sch, 22 Hankou Rd, Nanjing 210093, Peoples R China.;Zhejiang Normal Univ, Coll Econ & Management, China Afr Int Business Sch, 688 Yingbin Rd, Jinhua 321004, Peoples R China.
关键词：
executive green leadership;scale development;green manager;green person
摘要：
Drawing on the existing research on green leadership, this paper first examines the concept and structure of executive green leadership and develops a preliminary scale to measure executive green leadership. The confirmatory factor analysis is adopted to verify and revise the scale. The results show that green leadership and green person are the two main structures of executive green leadership, and the scale developed in this paper is of good reliability and validity. After data analysis, this paper then explores the antecedents of executive green leadership. The results show that factors such as corporate executives’ internal moral identity, conscientiousness, pro-environmental intention, command-based environmental regulation, market-based environmental regulation, and corporate green image have a significant positive correlation with executive green leadership, while their short-term orientation has a significant negative correlation with the green leadership. This paper defines the concept and structure of executive green leadership and develops the corresponding scale for measuring it, to improve scholars’ and managers’ understanding of executive green leadership.
作者机构：
[Zhao, Keyun; Xie, Wanli; Xu, Zhenguo] Qufu Normal Univ, Sch Commun, Rizhao 276826, Peoples R China.;[Wu, Wen-Ze; Wu, WZ] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;[Xu, Zhenguo] Jiangsu Normal Univ, Coll Intelligent Educ, Xuzhou 221008, Peoples R China.
通讯机构：
[Wu, WZ ] C;Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.
关键词：
Grey system model;Fractional -order accumulation;Grey neural network;Predictive model
摘要：
Recently, grey system, neural network, and fractional order calculus theory have become popular research areas, and an increasing number of scholars have joined these studies, conducted illuminating research, and produced a number of significant results. Numerous research studies have demonstrated that these three strategies are crucial to solving a wide range of practical problems. In this paper, we present a fractional order neural grey system model with a three-layer structure in which the input of the network is a fractional order cumulative sequence, and the output is a predicted value in order to maximize the bene-fits of each of the three elements. The purpose of this research is to present a strategy for reducing the number of conditions in order to improve the stability of parameter estima-tion by using QR decomposition. The order of the models is determined by an intelligent optimization algorithm. Finally, real-world examples are used to validate the model's va-lidity, and experimental results indicate that the newly presented model is more accurate than previous models. (c) 2023 Elsevier Inc. All rights reserved.
期刊：
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING,2023年 ISSN：0219-6220
通讯作者：
Yu, X
作者机构：
[Liu, Chenya; Yu, Xing] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;[Zhang, Weiguo] Shenzhen Univ, Sch Management, Shenzhen 518060, Peoples R China.
通讯机构：
[Yu, X ] C;Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.
关键词：
Salmon price risk hedging;fuzzy copula model;Kullback-Leibler divergence;mixture Gaussian model
摘要：
Copula method can explain the dependent function or connection function which connects the joint distribution and the univariate marginal distribution. Therefore, copula has recently become a most significant important tool in the financial field of risk management, portfolio allocation, and derivative asset pricing. However, it leads to a possibilistic uncertainty in estimating the parameters of copulas because of insufficient historical data, imprecise parameter estimation, and uncertain knowledge of future prices. This paper proposes a fuzzy copula model via Kullback-Leibler (KL) divergence to model the fuzzy relations, and further to investigate the hedging issues of salmon futures. We use a new framework of hedging under fuzzy circumstances, consisting of innovative marginal distributions and fuzzy intervals. By synergizing fuzzy copula and simulations, we use the fuzzy copula-GMM to obtain the hedge ratios of salmon futures. The empirical results show that, compared with traditional probabilistic methods, the fuzzy copula-GMM hedges the salmon spot risk measured by variance more successfully.
作者机构：
[Liu, Botao; Tu, Zhengge; Cao, Yu] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.
通讯机构：
[Botao Liu] S;School of Economics and Business Administration, Central China Normal University, Wuhan 430079, China<&wdkj&>Author to whom correspondence should be addressed.
摘要：
In the context of building a “Beautiful China”, it is imperative to strengthen environmental regulations to restrict industrial pollution emissions. However, there are significant differences of regulations intensity among different regions, which will lead to an increase in the cost of compliance with regulations for polluting industries, so these industries tend to transfer from areas with strong environmental regulations to areas with weak environmental regulations. Based on the panel data of 282 prefecture-level cities and national patent data from 1994 to 2010, this paper constructs a difference in difference model (DID) to empirically study the impact of environmental regulations on regional industrial transfer and its mechanism. We find that, firstly, the “Two-Control Zones” policy has significantly promoted regional industrial transfer, and its effect has gradually increased in the long run. Then, the promotion effect of the “Two-Control Zones” policy on regional industrial transfer is heterogeneous among different regions due to the regional market environment and resource endowment; that is, the promotion effect is the greatest in Central China, then in Eastern China, and finally in Western China. At the same time, the frequency of industrial transfer in areas with high resource dependence is significantly lower than that in areas with low resource dependence. Finally, mechanism studies find that environmental regulation enhances inter-regional industrial liquidity and promotes regional technological innovation, and the role of environmental regulation on technological innovation is more obvious in regions with weak industrial liquidity. This proves that the “Pollution Heaven Hypothesis” and the “Porter Hypothesis” can be established at the same time in the Chinese context, which provides more reliable empirical evidence for the government to formulate environmental regulations, restrict pollution emissions, and balance environmental governance and sustainable economic development.
作者机构：
[Xiang, Jingjie] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan, Peoples R China.;[Guo, Gangzheng] China Construct Bank, Beijing, Peoples R China.;[Li, Jiaolong] Zhongnan Univ Econ & Law, Sch Stat & Math, Wuhan, Peoples R China.
通讯机构：
[Jiaolong Li] S;School of Statistics and Mathematics, Zhongnan University of Economics and Law, Wuhan, China
期刊：
Environmental Science and Pollution Research,2023年30(19):55187-55199 ISSN：0944-1344
通讯作者：
Wei Wei
作者机构：
[Wang, Zhi; Li, Kangjia; Wei, Wei; Huang, Wenmin] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;[Huang, Wenmin] China Chengtong Holdings Grp Ltd, Beijing 100031, Peoples R China.;[Wei, Wei] Cent China Normal Univ, Ctr Low Carbon Econ & Environm Policy, Wuhan 430079, Peoples R China.;[Liu, Zhen] Nanjing Normal Univ, Sch Business, Nanjing 210023, Peoples R China.
通讯机构：
[Wei, Wei] S;School of Economics and Business Administration, Central China Normal University, Wuhan, 430079, China.;Center for Low Carbon Economy and Environmental Policy, Central China Normal University, Wuhan, 430079, China.
关键词：
High-speed rail;COD emission intensity;Firm heterogeneity;Difference in difference model
