作者机构:
[Zhu, Junpeng] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan, Peoples R China.;[Lin, Boqiang] Xiamen Univ, Sch Management, China Inst Studies Energy Policy, Xiamen 361005, Fujian, Peoples R China.;[Lin, Boqiang] Innovat Lab Sci & Technol Energy Mat Fujian Prov, Xiamen 361005, Peoples R China.
通讯机构:
[Lin, Boqiang] X;Xiamen Univ, Sch Management, China Inst Studies Energy Policy, Xiamen 361005, Fujian, Peoples R China.
作者:
Yan, Yixin;Hu, Jiliang;Chen, Xiding;Kumar, A. P. Senthil
期刊:
Mathematical Problems in Engineering,2022年2022 ISSN:1024-123X
通讯作者:
Hu, J.
作者机构:
[Hu, Jiliang; Yan, Yixin] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan, Peoples R China.;[Chen, Xiding] Wenzhou Business Coll, Sch Finance & Trade, Wenzhou, Peoples R China.;[Kumar, A. P. Senthil] Jigjiga Univ, Sch Social Work, Jigjiga, Somali Reg Stat, Ethiopia.
通讯机构:
School of Economics and Business Administration, Central China Normal University, Wuhan, China
摘要:
Traditionally, economic data of power supply is often analyzed through the count regression model due to the type of empirical data in the decision-making process. However, in reality, it is difficult to use count data model for data with autoregressive features. The main reason is that the time series features and autoregressive attributes cannot be controlled through the count regression model, which violates the assumptions set by the model. Therefore, there may be errors in the empirical analysis results. This letter firstly describes the characteristic of the count regression model and the problem, and then we refine the multiplicative autoregressive count model for dynamic count data. The model has desirable theoretical properties and is trivial to incorporate into existing models for the count data. In this study, the multiplicative autoregressive counting model for dynamic counting data is improved. The model has ideal theoretical properties and can be easily incorporated into existing economic models of counting data, especially for power supply policy analyses.
期刊:
Journal of Mathematics,2022年2022 ISSN:2314-4629
作者机构:
[Ding, Weibin] State Grid Zhejiang Elect Power Co Ltd, Hangzhou 310012, Peoples R China.;[Li, Jie] Jinhua Power Supply Co State Grid Zhejiang Elect P, Jinhua 321000, Peoples R China.;[Jin, Dian; Kong, Jiayang] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;[Jin, Dian; Kong, Jiayang] Cent China Normal Univ, Sch Math & Stat, Wuhan 430079, Peoples R China.;[Kong, Jiayang] Cent China Normal Univ, Res Ctr Low Carbon Econ & Environm Pol, Wuhan 430079, Peoples R China.
摘要:
Researcher and analyst are often interested in estimating the effect of an intervention or treatment, which takes place at the aggregate level and affect one single unit, such as country and region. Thus, comparative case studies would be their first choice in practice. However, comparative case studies could fail to yield an estimate in the effect that is unbiased and consistent, as in some contexts; there are not suitable control units that are similar to the treated. The econometric literature has taken synthetic control methods and panel data approaches to this problem. In this study, we developed a principal covariate regression estimator, which exploits the cross-sectional correlation, as well as the temporal dependency, to reproduce the dynamics of the treated in the absence of an event or policy. From a theoretical perspective, we introduce the statistical literature on dimensional reduction to make a causal inference. From a technique perspective, we combine the vertical regression and the horizontal regression. We constructed an annual panel of 38 states, to evaluate the effect of Proposition 99 on beer sales in California, using the principal covariate regression estimator proposed here. We find that California’s tobacco control program had a significant negative and robust effect on local beer consumption, suggesting that policymakers could reduce the use of cigarette and alcohol in the public using one common behavioral intervention.
期刊:
International Journal of Environmental Research and Public Health,2022年19(18):11643- ISSN:1661-7827
通讯作者:
Xiaomeng Zhao
作者机构:
[Chen, Yang; Dong, Xu] Zhengzhou Univ Aeronaut, Sch Econ, Zhengzhou 450046, Peoples R China.;[Zhuang, Qinqin] Chinese Acad Social Sci, Inst Quantitat & Tech Econ, Beijing 100732, Peoples R China.;[Yang, Yali] Zhengzhou Univ Aeronaut, Sch Informat Management, Zhengzhou 450046, Peoples R China.;[Zhao, Xiaomeng] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.
通讯机构:
[Xiaomeng Zhao] S;School of Economics and Business Administration, Central China Normal University, Wuhan 430079, China<&wdkj&>Author to whom correspondence should be addressed.
关键词:
green total factor productivity;agglomeration of productive services;industrial-structure upgrading;the Yellow River Basin;lean green;sustainability
摘要:
Improving green total factor productivity (GTFP) is the inherent requirement for practicing the philosophy of green development and achieving regional high-quality development. Based on panel data for 68 prefectural-level-and-above cities in the Yellow River Basin of China from 2006 to 2019, we measured their GTFPs and degrees of productive-services agglomeration using the non-radial directional distance function and industrial agglomeration index formulas, respectively. Furthermore, we empirically investigated the interactive relationship between agglomeration of productive services, industrial-structure upgrading, and GTFP using the dual fixed-effects model, the mediating-effect model, and the moderating-effect model. The findings were as follows. (1) Both specialized and diversified agglomeration of productive services significantly improved the GTFPs of cities in the Yellow River Basin, and the promoting effect of specialized agglomeration was stronger than that of diversified agglomeration. (2) The diversified agglomeration of productive services (hereinafter referred to as diversified agglomeration) made a significant contribution to GTFP in all sample cities of the Yellow River Basin, while the specialized agglomeration of productive services (hereinafter referred to as specialized agglomeration) only significantly improved GTFP in the upstream cities and had no significant effect on the midstream and downstream cities. (3) When examined according to city size, specialized agglomeration was found to have a positive impact on the GTFPs of small and medium-sized cities in the Yellow River Basin but a non-significant negative impact on large cities, while the effect of diversified agglomeration on GTFP was found not to be significant. (4) Industrial-structure upgrading played partially mediating and negative moderating roles in the process of specialized agglomeration affecting the GTFPs of cities in the Yellow River Basin, but it did not become a mediating channel and moderating factor that influenced diversified agglomeration in relation to GTFP.
期刊:
FRONTIERS IN PSYCHOLOGY,2022年13:865258 ISSN:1664-1078
通讯作者:
Deng, H.
作者机构:
[Wan, Qinjuan; Deng, Hongping] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan, Peoples R China.;[Wan, Qinjuan; Deng, Hongping] Real Estate Econ Res Ctr Hubei Prov, Wuhan, Peoples R China.
通讯机构:
[Deng, H.] S;School of Economics and Business Administration, Central China Normal University, Wuhan, China
期刊:
Indoor and Built Environment,2022年32(8):1523-1536 ISSN:1420-326X
通讯作者:
Liu, ZX
作者机构:
[Zhao, Li; Wei, Wei] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan, Peoples R China.;[Liu, ZhongXing] Cent China Normal Univ, Inst Adv Studies Humanities & Social Sci, Luoyu Rd 152, Wuhan, Peoples R China.
通讯机构:
[Liu, ZX ] C;Cent China Normal Univ, Inst Adv Studies Humanities & Social Sci, Luoyu Rd 152, Wuhan, Peoples R China.
关键词:
Industrial agglomeration;energy consumption intensity;firm heterogeneity;low-carbon development
摘要:
The complexity and uncertainty of the financial market mainly stem from the rich market internal transaction information and a wide range effect of external factors. To this end, this paper proposes the combination factors-driven forecasting method to predict realized volatilities of the CSI 300 index and index futures. Based on the volatilities predicted by the proposed method, we further evaluate the ex-ante hedging performance in comparison to the conventional HAR model as well as GARCH-type models. The empirical results indicate that the factors-driven realized volatility model significantly dominates the other commonly used models in terms of hedging effectiveness. Furthermore, the superiority of the proposed method is robust in different market conditions, including significant rising or falling and abnormal market fluctuations in the COVID-19 pandemic, and in different index markets. Therefore, this paper improves the prediction accuracy of volatility by integrating market internal transaction information and external factor information, and the proposed method in this paper can be used by investors to obtain an excellent hedging effect.
摘要:
Improving energy efficiency and lowering carbon emissions are of great importance to realize the "dual carbon" goal of carbon peak and carbon neutrality. Digital economy is a new engine of economic development, but whether or how it affects energy efficiency and carbon emissions are unclear. Utilizing panel data of China's 30 provinces from 2012 to 2019, this study empirically explores the relationships among digital economy, energy efficiency, and carbon emissions. Meanwhile, from the perspective of energy efficiency, applying mediation models and panel threshold model, it analyzes the direct, indirect, and nonlinear influencing mechanisms of digital economy on carbon emissions. The results reflect that the development of digital economy in China intensifies carbon emissions. Energy efficiency serves as a vital partial mediator between the two. The enhancement of energy efficiency can lower carbon emissions. However, the development of digital economy is not conducive to improving energy efficiency, thereby, indirectly increasing carbon emissions. The mediating effect of energy efficiency accounts for 30.58 % of the total effect of digital economy on carbon emissions. Meanwhile, taking energy efficiency into account, the impact of digital economy on carbon emissions has a significant double-threshold effect and presents an N-shaped trend. [0.824, 0.912] is the optimal range of energy efficiency, within which the growth of the digital economy can empower carbon emission abatement to some extent. In addition, the expansion of population size, the coal-based energy consumption structure, and the industrial structure significantly increase carbon emissions. The improvements in living standards and environmental regulations can help to decrease carbon emissions, but the emission abatement effects are not significant. Those conclusions reveal the importance of optimizing the level and quality of digital economy and adopting differentiated digital economy development policies based on energy efficiency to achieve carbon emission reduction.
摘要:
The fractional grey model and its deformation forms have been appealed interest of research in practice due to its strong adaptability by merits of falling from the integer-order form into the fractional. This paper proposes an optimised time power-based grey model by the introduction of conformable fractional derivative into the conventional model. As a result, a newly-designed approach, namely the time power-based grey model with conformable fractional derivative (referred to as CFGM( phi, 1 , t alpha)), is proposed thereby. Specifically, the model establishment, system parameter estimation and explicit expression are comprehensively implemented. In particular, several properties for the proposed approach are emphasized to interpret the superiority of the newly-designed model from a theoretical analysis perspective. The particle swarm optimization technique is then employed to determine the emerging coefficients such as the order of the conformable fractional derivative and time-power coefficient. Finally, four real-world cases are chosen to certify the applicability of the proposed model in contrast with other benchmark models and, the empirical results show that the newly-designed model outperforms other competing models, thus obtaining some managerial insights from these numerical experiments.(c) 2021 Elsevier Ltd. All rights reserved.