关键词：
Trade policy uncertainty;Precious metal markets;China-US trade Conflict;Time-varying spillovers
摘要：
Using a time-varying vector autoregressive (TVP-VAR) model combined with a spillover index, we study the dynamic spillovers between trade policy uncertainty (TPU) and precious metal markets during the Sino-US trade war. The results show obvious spillover effects between the Chinese TPU and American TPU and the precious metal markets, and the strength and direction of the spillover effects are time-varying and asymmetrical. The uncertainty of the Sino-US trade policy has a heterogeneous impact on the precious metal markets. American TPU dominates the markets, followed by Chinese TPU. In the face of trade war conflict, the spillover fluctuation of American TPU to Chinese TPU is very significant. In addition, in the face of trade policy uncertainty, gold and silver have strong self-adjustment abilities and stabilities, making them highly suitable for hedging investments. International investors and policymakers should consider the impacts of international trade policy uncertainty when conducting risk monitoring and building portfolios in precious metal markets.
作者机构：
[Wu, Liang; Peng, Yuting; Li, Zhijuan] Wuhan Univ, Dept Econ & Management, Wuhan 430072, Peoples R China.;[Zhang, Zemin; Chen, Rui] Wuhan Univ, Dong FuReng Econ & Social Dev Sch, Wuhan 430072, Peoples R China.;[Jiang, Wen; Jiang, Yinjuan] Hunan Agr Univ, Econ Coll, Changsha 410125, Peoples R China.;[Zheng, Kaixin] Wuhan Univ, Acad Dev, Wuhan 430072, Peoples R China.
关键词：
carbon emission;construction sector;green development;industrial green transformation;entropy method
摘要：
In the context of the commitment to peak carbon emissions by 2030, specific sectors in China should take responsibility to change their energy consumption patterns. In China and across the globe, the construction sector is a major source of carbon dioxide emissions, as well as an indicator of economic growth and structural transformation. In this study, we examine panel data for 30 provinces or regions from 2008 to 2019 to dissect which macro-factors contribute to growth in carbon emissions, and which will lead to carbon emission reductions. Derived by the entropy method, the Green Finance Index is a comprehensive environmental regulation index related to reduction in emissions in each province. It presents an N shape for construction emissions, and provinces are currently striving to cross the first inflection point, which will help to curb emissions. Judging from the combined effects of this and other structural factors, the Green Finance Index can promote the decarbonization of production by playing the role of guiding and screening capital allocation. Population expansion, income levels, and financial development initially stimulate demand for construction, but their effects eventually level off. This paper can serve as a reference for developing countries that are experiencing industrialization and urbanization processes and handling gas discharge pressure at the same time.
关键词：
image processing;quality of agricultural products;image denoising;LSTM network
摘要：
Farmers should provide high-quality agricultural products and companies should receive high-quality agricultural products, which is the purpose and pursuit of the business model of "companies plus farmers". In order to increase the stability of the cooperation mode between companies and farmers, it is necessary to detect the quality of agricultural products accurately, objectively and efficiently. Therefore, this article studies the quality inspection method of agricultural products based on image processing. Firstly, the traditional threshold calculation method and threshold function are improved to obtain more ideal denoising effect of agricultural products images. Aiming at the problem that the traditional image processing model cannot obtain fine-grained feature information of image objects, a multi-level feature dependence extraction network is constructed, and the structure and working principle of the network model are introduced in detail. Experimental results verify the effectiveness of the proposed algorithm and model for agricultural product quality inspection.
