The Ministry of Finance of the People's Republic of China (Chinese: 中华人民共和国财政部; pinyin: Zhōnghuá Rénmín Gònghéguó Cáizhèngbù) is the cabinet-level executive department of the State Council which administers macroeconomic policies and the annual budget. It also handles fiscal policy, economic regulations and government expenditure for the state.The ministry also records and publishes annual macroeconomic data on China's economy. This includes information such as previous economic growth rates in China, central government debt and borrowing and many other indicators regarding the economy of Mainland China.The Ministry of Finance's remit is smaller than its counterparts in many other states. Macroeconomic management is primarily handled by the National Development and Reform Commission (NDRC). State-owned industries are the responsibility of the State-owned Assets Supervision and Administration Commission, and there are separate regulators for banking, insurance and securities. It also does not handle regulation of the money markets or interest rates. These, together with other aspects of monetary policy, are governed by the People's Bank of China (PBC), Mainland China's central bank. The Ministry, NDRC and PBC are equal in status, with their political heads all sitting on the State Council..
Multinational corporations repatriate foreign profits through dividends, royalties, and interest paid by foreign affiliates to their parent firms. International tax rules that govern the taxation of repatriated foreign earnings thus influence decisions on profit repatriation. In 2009, Japan introduced a foreign dividend exemption system (the so-called territorial tax system) that exempted dividends received by Japanese firms from their foreign affiliates from home-country taxation. This paper examines the effects of this tax reform on profit repatriation through dividends, royalties, and interest. The enactment of the foreign dividend exemption system reduced the effective tax rate on foreign income repatriated through dividends by an average of 6.8 percentage points in 2009. We find that, in response to this tax rate reduction, Japanese-owned foreign affiliates increased dividend payments but did not alter royalty or interest payments. As a result, these affiliates increased total payments to their Japanese parents.
Metro stations with high ridership are prone to operational delays due to unforeseen factors, disrupting passenger travel and increasing energy consumption. Traditional methods often prioritize restoring the timetable without considering the impact on energy consumption. Considering this deficiency, a timetable rescheduling model based on deep reinforcement learning is proposed for the effective resolution of the aforementioned problem in this paper. This model takes into account both traction energy consumption and regenerative energy consumption. After a train delay occurs, it reallocates the train operation time for subsequent sections, reducing energy consumption while eliminating delay time. A case study of Nanning Rail Transit Line 5 is used to validate the model, showing a 2.1% reduction in energy consumption compared to traditional methods. Moreover, the comparison with other algorithm proves the effectiveness and robustness of the method. The proposed approach demonstrates significant improvements in both delay management and energy efficiency and can be applied to real-time train scheduling in various metro systems to optimize performance and sustainability.
Nowadays, high-speed rail (HSR) has become an increasingly popular choice for travel. However, delays occasionally occur during HSR trips, and these delays can propagate throughout the network, causing widespread disruptions. Therefore, controlling delay propagation is a critical task in HSR network maintenance. Given the limited resources available for delay control in real-world applications (such as budgets, personnel, and facilities), it is crucial to identify the optimal set of station nodes, of a given size, that can most effectively resist the spread of delays when controlled. In this paper, we formulate an optimization problem for immune node selection to control delay propagation. To solve this problem, we propose a node propagation centrality metric that integrates both the susceptibility and infectivity of a node to quantify the importance of nodes in delay propagation. Furthermore, we develop a genetic algorithm to find an approximately optimal set of immune nodes, using centrality-based initialization and a one-hop neighbor-based variable neighborhood search strategy. Comparative experiments on real-world HSR networks demonstrate the effectiveness of our algorithm. Our work helps identify the most influential nodes in HSR networks for limiting delay propagation, assisting railway personnel in making informed decisions.
The use of manufactured sand (MS) in concrete has become an inevitable choice in parts regions in China with the increasing depletion of natural river sand (RS), however, the study on the cracking resistance of ballastless track slabs prepared with manufactured sand concrete (MSC) is insufficient due to the complexity of chemical composition and mechanical properties. In this paper, the influence of manufactured sand lithology, that is, Basalt, Tuff, Granite as well as Limestone and stone powder (SP) content, that is, 5%, 10% and 15% on the static mechanical properties of concrete were first investigated. A static load experiment for China Railway Track System (CRTS) Ⅲ ballastless track slab prepared with MS was then conducted. The cracks distribution and damage factor of MSC track slab were analyzed by the finite element analysis method. The bending moment of MSC track slab was further evaluated accounting for train loads, temperature loads and subgrade settlement. Results show that the compressive strength and elastic modulus of MSC are generally higher than those of river sand concrete (RSC), which can be attributed to the sharper edges of MS particles. The static cracking resistance of the MSC track slab meets the required standards when qualified MS is used. However, the SP content in MS exhibits a dual effect on prestressed concrete track slabs and is recommended to be limited to within 10%. This study demonstrates a feasible approach for applying MS in high-speed railway ballastless track slab.
In recent years, crashes and bankruptcies among Chinese real estate enterprises have become increasingly frequent, sparking academic reflection on stock price crash risk. Unlike previous studies that emphasize capital market imperfections, this paper examines the impact of the ‘moat’ mechanism on crash risk using panel data from 142 Chinese A-share listed real estate companies from 2012 to 2021. The findings are as follows: (1) ESG performance reduces stock price crash risk. (2) Strong ESG performance functions as a ‘moat’ mechanism by enhancing corporate reputation and attracting long-term investors. (3) It also serves as a defense mechanism by mitigating excessive investor sentiment and lowering risk exposure. (4) Heterogeneity analysis shows that the ‘moat’ effect is stronger among firms with high corporate reputation, high stock turnover, low investor sentiment, and high risk-taking, and is more pronounced among privately owned firms in southern China that have not crossed the ‘three red lines’ and engage in short-term ‘greenwashing’. These conclusions expand the explanatory framework for crash risk and provide new empirical evidence for the ‘moat’ interpretation of ESG performance in China’s real estate sector.
