Re-measuring International Short-term Capital Flow into China with Varying Methods

This paper.fi＇rst conducts a systematic review of domestic and foreign scholars＇ approaches to predicting short-term capital flows, then employs a combination of both direct and indirect methods to carry out its analysis. Three kinds of indicators, both specific and general, are applied in both methods. Thorough consideration is given to short-term international capital inflow from trade, other current account items, capital account, and errors and omissions, as well as other channels through which short term capital might accrue to a nation＇s balance. Based on a comprehensive comparison of year-on-year data, this paper also estimates monthly data using a simplified, indirect calculation approach. Estimates show that, despite a degree of difference in results between methods, most estimates are highly consistent for a given period. Based on monthly estimates, we conclude that turbulence in international financial markets （i.e., the United States subprime mortgage crisis and the European sovereign debt crisis） has had a major impact on China ＇s short-term capital flow.

ANALYSIS OF CAPITAL FLOW WITH GIS——Two Approaches for Regional Investment in China

GIS technology has been mostly concerned with handling physical data andmodeling physical environment. However, the retirements of GIS for handling socio-economicinformation in many cases are different from those concerning phenomena in the physical environment.Analysis of capital flow among regions requires the transitions both from economic values tophysical landscape and from physical surface to economic explanation. Rapid growth of Chineseeconomy comes mainly from investment. There are two main ways for obtaining high growth ofinvestment. One is government expenditure which usually invests in regional facility and amenityblock, which is regarded as stimulus for attracting investment. The other is the creation ofinvesting center and corresponding capital source areas, both of which need the central city withthe highest growth rate of investment among regions. This paper presents the cluster areas of bothgovernment revenue and total investment, the potential situation of capital flow between centralcity Shanghai and its neighbor provinces by using Classification' and Interpolation' functions ofArcView GIS.

The Policy Effects of Capital Flow on Foreign Trade： An Empirical Analysis

Today, intemational capital flows faster and faster. Thus, the supervision of capital flow becomes one of the key problems need to be solved every country, and how to supervise it is the focus in theoretical circle. Especially, China is currently facing international pressure to revalue the RMB, and a large number of free foreign capitals is flowing into China. So it is much more important to supervise it. By using the theory of foreign trade, we analyze the policy effects of foreign trade in the process of capital flow, and hope that the policy of foreign trade will exert positive effects on the supervision of capital flow.

How Demographic Structure Determines International Capital Flows

This paper investigated the relationship between demographic structure and international capital flows with panel data of 190 countries over the past 60 years＇ and projection data for the 21st century. As found, from a global perspective, the current account balance （CAB） is negatively related to the dependency ratio, and orresponding to continuous change, international eapital flows tend to move from ＂adult countries＂ to ＂aged or young countries.＂ Since the middle of the 20th century, the U.S., Europe, Japan, China, Southeast Asia, Central Asia, South Asia, West Asia and Africa took turns in exporting capital to other countries. In the 2lst century, Europe, the U.S., Australia and Singapore will keep importing capital, while China in the 2030s, and Southeast Asia in the 2050s will in turn become the main capital importers. Given the demographic structure of China and the world, the future pattern of the international capital flows requires more serious concern and responses.

Financial Vulnerability, Capital Flow Reversals, and Divergence Macro-Prudential Policies Posing Challenges to the ASEAN Banking Integration Framework （ABIF）

Against the prevailing background of an unusual capital flow reversal which is posing immense challenges to the integration of the region＇s banking sector, this study measures macro-prudential instruments affecting the implementation of an integrated financial service industry. This study is important at times when domestic and country-based financial policies are directed at competing goals. The interaction of macro-prudential policies with other policies, in particular monetary policies and micro-prudential policies is crucial to address systemic risk involved. There is growing recognition that prudential policies tools interact and coordinate with one another. To utilize multiple instruments seems to provide a greater assurance of effectiveness by tackling risk from various angles. As such, this study also assesses the interactions of the policies. The study also proposes a baseline model to capture systemic risk due to liquidity risk and risk because of currency devaluation.

Global Risk Appetite,US Economic Policy Uncertainties and Cross-Border Capital Flow

Based on the global asset portfolio model,this paper created a panel threshold model using EPFR fund data to empirically test the non-linear spillover effects of US economic policy uncertainties on cross-border capital flow for emerging economies.Our study led to the following findings:(1)When the level of global investor risk tolerance is high,rising US EPU will induce a capital inflow into emerging economies,as manifested in the“portfolio rebalancing effect.”When the level of global investor risk tolerance is below a critical threshold,this gives rise to risk aversion and emerging economies will experience net capital outflow,i.e.the“flight to quality effect”.(2)Equity fund investors have a lower risk tolerance threshold than bond fund investors.(3)According to our heterogeneity analysis,more attention should be paid to monitoring capital flow through actively managed funds,ETF funds,and retail investor funds.The economy should increase financial efficiency and economic resiliency to mitigate capital outflow pressures from the external environment.

The Effect of Net Working Capital on Jordanian Industrial and Energy Sectors＇ Net Cash Flows Employed in Operating Activities

The primary objective of the cash flow statement is to provide useful, meaningful, and relevant information about the cash receipts and cash payments of a firm during a given period of time. Decision makers can achieve extra features of the change in net assets, the firms＇ financial position （liquidity and solvency）, and the firm＇s ability to adapt to changing circumstances by affecting the amount and timing of cash flows. Cash flow statements improve comparability as they are not affected by differing accounting policies used for the same type of transactions or events. This study aims to verify the effect of net working capital （NWC）, as an indicator of a company＇s short-term liquidity or its ability to meet short-term obligations, on Jordanian industrial and energy sectors＇ net operating cash flows （NOCF）. A simple liner regression is used to test a period of 2008-2011 in order to conclude the extent of the effect on industrial and energy sectors. The study showed that there is a significant effect of the independent variable NWC on the dependent variable NOCF among industrial and energy sectors in Jordanian market. Whereas the adjusted R-squared of test is 0.854, changes in NOCF in Jordanian industrial and energy sectors have been described by NWC. Also, the study reached that the utilities and energy sector has the lowest NWC, while the mining and extraction sector has the highest. And, electrical industries sector has the lowest NOCF, while the mining and extraction sector has the highest. Moreover, the study showed that the printing and packaging sector has the lowest NWC, while the mining and extraction sector has the highest. And, glass and ceramic industries sector has the lowest NOCF, while the utilities and energy sector has the highest.

The Economic Growth with the Flows of Capital ＆ Technology

The difference of regional economy comes from capital dissymmetry, technology dissymmetry, manpower dissymmetry and the information dissymmetry. In the knowledge-based economic ages, globalization and information exceed any age of the history. It provides the new terrace for the balanced development of global economy. The flows of capital and technology improve the regional dissymmetry of production factor. By establishing circulating channels, the flows of the production factor will be enlarged. This will raise the distribution efficiency of global resources and lead to the global economic growth.

A two-stage short-term traffic flow prediction method based on AVL and AKNN techniques

Short-term traffic flow prediction is one of the essential issues in intelligent transportation systems(ITS). A new two-stage traffic flow prediction method named AKNN-AVL method is presented, which combines an advanced k-nearest neighbor(AKNN)method and balanced binary tree(AVL) data structure to improve the prediction accuracy. The AKNN method uses pattern recognition two times in the searching process, which considers the previous sequences of traffic flow to forecast the future traffic state. Clustering method and balanced binary tree technique are introduced to build case database to reduce the searching time. To illustrate the effects of these developments, the accuracies performance of AKNN-AVL method, k-nearest neighbor(KNN) method and the auto-regressive and moving average(ARMA) method are compared. These methods are calibrated and evaluated by the real-time data from a freeway traffic detector near North 3rd Ring Road in Beijing under both normal and incident traffic conditions.The comparisons show that the AKNN-AVL method with the optimal neighbor and pattern size outperforms both KNN method and ARMA method under both normal and incident traffic conditions. In addition, the combinations of clustering method and balanced binary tree technique to the prediction method can increase the searching speed and respond rapidly to case database fluctuations.

Flow Structure and Short-Term Riverbed Evolution in Curved Flumes

River bending is the major effect responsible for bed topography and bank changes.In this study,fluid velocity(measured by a three-dimensional Doppler advanced point current meter)and bed topographical data have been collected in 40 sections of an experimental model.The whole flume was composed of an organic glass bend,upstream and downstream water tanks,two transition straight sections,a circulation pump,and a connection pipeline.Each section has been found to be characterized by a primary circulation and a small reverse circulation,with some sections even presenting three more or more circulation structures.The minimum circulation intensity has been detected in proximity to the top of the curved channel,while a region with small longitudinal velocity has been observed near the concave bank of each bend,corresponding to the flat bed formed after a short period of scouring.The maximum sediment deposition and scour depth in the presence of a uniform distribution of living flexible vegetation within 10 cm of the flume wall have been found to be smaller than those observed in the tests conducted without vegetation.

Hybrid Model for Short-Term Passenger Flow Prediction in Rail Transit

A precise and timely forecast of short-term rail transit passenger flow provides data support for traffic management and operation,assisting rail operators in efficiently allocating resources and timely relieving pressure on passenger safety and operation.First,the passenger flow sequence models in the study are broken down using VMD for noise reduction.The objective environment features are then added to the characteristic factors that affect the passenger flow.The target station serves as an additional spatial feature and is mined concurrently using the KNN algorithm.It is shown that the hybrid model VMD-CLSMT has a higher prediction accuracy,by setting BP,CNN,and LSTM reference experiments.All models’second order prediction effects are superior to their first order effects,showing that the residual network can significantly raise model prediction accuracy.Additionally,it confirms the efficacy of supplementary and objective environmental features.

Traffic flow prediction based on BILSTM model and data denoising scheme

Accurate prediction of road traffic flow is a significant part in the intelligent transportation systems.Accurate prediction can alleviate traffic congestion,and reduce environmental pollution.For the management department,it can make effective use of road resources.For individuals,it can help people plan their own travel paths,avoid congestion,and save time.Owing to complex factors on the road,such as damage to the detector and disturbances from environment,the measured traffic volume can contain noise.Reducing the influence of noise on traffic flow prediction is a piece of very important work.Therefore,in this paper we propose a combination algorithm of denoising and BILSTM to effectively improve the performance of traffic flow prediction.At the same time,three denoising algorithms are compared to find the best combination mode.In this paper,the wavelet(WL) denoising scheme,the empirical mode decomposition(EMD) denoising scheme,and the ensemble empirical mode decomposition(EEMD) denoising scheme are all introduced to suppress outliers in traffic flow data.In addition,we combine the denoising schemes with bidirectional long short-term memory(BILSTM)network to predict the traffic flow.The data in this paper are cited from performance measurement system(PeMS).We choose three kinds of road data(mainline,off ramp,on ramp) to predict traffic flow.The results for mainline show that data denoising can improve prediction accuracy.Moreover,prediction accuracy of BILSTM+EEMD scheme is the highest in the three methods(BILSTM+WL,BILSTM+EMD,BILSTM+EEMD).The results for off ramp and on ramp show the same performance as the results for mainline.It is indicated that this model is suitable for different road sections and long-term prediction.

Evolution of gas kick and overflow in wellbore and formation pressure inversion method under the condition of failure in well shut-in during a blowout

With ongoing development of oil exploration and techniques,there is a significant need for improved well control strategies and formation pressure prediction methods.In this paper,a gas-liquid transient drift flow model was established according to the gas-liquid two-phase flow characteristics during the gas kick.A Roe scheme was used for numerical calculation based on the finite volume method.The changes of bottom-hole pressure,casing pressure,the development law of cross-sectional gas holdup,and gas velocity,along with the vertical well depth,were analyzed through simulation examples.The time-series characteristics of mud pit gain were obtained by adjusting the formation parameter.The complex nonlinear mapping relationship between the formation parameters and the mud pit gain was established.The long short-term memory network(LSTM)of deep learning was used to obtain a formation pressure inversion when the blowout is out of control and the well cannot be shut-in.Experimental data from a well were used to verify the gas-liquid two-phase transient drift flow model based on the finite volume method,demonstrating that this method is reliable,with greatly improved prediction accuracy.This approach provides theoretical support for the early monitoring of gas kick during drilling,and for well-killing design and construction after uncontrolled blowout.

Short-time prediction for traffic flow based on wavelet de-noising and LSTM model

Aiming at the problem that some existing traffic flow prediction models are only for a single road segment and the model input data are not pre-processed,a heuristic threshold algorithm is used to de-noise the original traffic flow data after wavelet decomposition.The correlation coefficients of road traffic flow data are calculated and the data compression matrix of road traffic flow is constructed.Data de-noising minimizes the interference of data to the model,while the correlation analysis of road network data realizes the prediction at the road network level.Utilizing the advantages of long short term memory(LSTM)network in time series data processing,the compression matrix is input into the constructed LSTM model for short-term traffic flow prediction.The LSTM-1 and LSTM-2 models were respectively trained by de-noising processed data and original data.Through simulation experiments,different prediction times were set,and the prediction results of the prediction model proposed in this paper were compared with those of other methods.It is found that the accuracy of the LSTM-2 model proposed in this paper increases by 10.278%on average compared with other prediction methods,and the prediction accuracy reaches 95.58%,which proves that the short-term traffic flow prediction method proposed in this paper is efficient.

经济增长目标调整促进了资本流动吗——基于企业跨地区投资的视角

地方政府“为增长而竞争”的发展模式是造成市场分割的重要因素,那么经济增长目标下调能否缓解这一局面、促进要素资源自由流通?为了回答这一问题,本文以上市公司在异地设立子公司的行为衡量资本要素的流动性,系统考察经济增长目标下调对企业跨地区投资的影响。研究发现,经济增长目标下调能够促进资本流动,表现为经济增长目标下调显著提升了辖区内上市公司设立异地子公司的比例;影响机制分析表明,经济增长目标下调提高了政府放权意愿,降低了市场分割程度,进而促进了企业跨地区投资;进一步的异质性分析揭示,在地区行政壁垒较低、行业竞争程度较高及民营企业样本中,经济增长目标下调对企业跨地区投资的促进作用更加明显。本文丰富了制度性政府行为影响资源配置的相关研究,为当前推进全国统一大市场建设提供了直接的政策思路。

全球经济政策不确定性对国际资本异常流动的影响

全球经济政策不确定性上升会提高国际投资的风险和成本,加上“外国劣势”的影响,投资者会减少对外投资,从而使国际资本出现本土化倾向的异常流动。采用24个发达经济体、25个新兴和发展中经济体2005年第三季度至2022年第四季度的跨国面板数据,将国际资本异常流动分为外逃、撤回、激增、中断4种类型,运用Probit模型分析发现:在样本期间,发达经济体的资本异常流动少于新兴和发展中经济体;全球经济政策不确定性上升会降低资本外逃和激增的概率,并增加资本撤回和中断的概率;全球经济政策不确定性对发达经济体4种异常流动的影响都显著,而对新兴和发展中经济体只显著影响了资本外逃和激增;全球经济政策不确定性会显著影响其他投资的4种异常流动,并显著影响直接投资的外逃和激增、证券投资的外逃和撤回;金融开放水平较低时,金融开放会强化全球经济政策不确定性对国际资本异常流动的影响,但当金融开放水平较高时,全球经济政策不确定性的影响不再显著。因此,应建立国际资本异常流动监测平台,完善国际投资监管机制,并积极推进高水平金融开放。

资金流对乡村产业振兴的影响

基于2006—2019年全国722个脱贫县和1058个非贫困县的非平衡面板数据,构建乡村产业振兴指数,实证检验了金融资金流动对乡村产业振兴的影响效果及作用机制。研究发现:金融资金流入能显著促进乡村产业振兴,且对脱贫县的促进效果强于非贫困县;金融资金流动主要通过带动“实物流”“技术流”和“人才流”发挥促进作用,实现乡村生产体系、经营体系及产业体系的现代化,进而推动乡村产业振兴;新产业新业态发展的需求端、普惠金融发展的供给端和精准扶贫政策实施的政策端均能对促进作用产生正向效应。

企业数字化转型促进了资本跨区域流动吗——基于异地并购视角的研究

加快资本跨区域流动对构建以国内大循环为主体、国内国际双循环相互促进的新发展格局具有重要的战略意义。本文以2008—2022年中国A股上市公司为样本,借助异地并购这一重要的资本跨区域流动形式,考察新发展格局下企业数字化转型对资本跨区域流动的影响。研究发现:企业数字化转型通过降低并购交易成本和提高集团管控能力,有效地促进了异地并购决策,尤其对跨省并购决策的促进作用更显著。异质性分析结果表明,当并购企业所在地区市场化程度更高、税负水平更低、数字金融发展水平更高以及目标企业所在地区营商环境更好时,企业数字化转型对异地并购决策的促进作用更强;同时,这一促进作用在民营企业、非高新技术企业以及高管具有金融背景或海外背景的企业中更显著。本研究丰富了数字经济时代资本跨区域流动驱动因素的研究,从异地并购视角提供了企业数字化转型促进资本跨区域流动的微观证据。

数字金融是否促进了县域产业结构升级?——基于网商银行进入农村市场的准自然实验

近年来,数字金融在农村市场发展迅猛,有望成为推动县域产业结构升级的新动能,为推动我国县域产业结构升级提供了新的思路。本文以网商银行进入农村市场作为一项准自然实验,利用2013—2020年的县域数据构建多期双重差分模型,实证分析数字金融对县域产业结构升级的影响。研究发现:(1)数字金融显著促进了县域产业结构升级;(2)数字金融通过发挥数字技术优势,引导资金更多地流向第三产业来促进县域产业结构升级;数字金融通过促进消费结构升级来促进县域产业结构升级;(3)数字金融对南方县、非贫困县、传统信贷投入高的县产业结构升级的促进效果更大。上述研究结论为数字金融时代促进县域产业结构升级、推进乡村振兴战略的实现提供了重要的经验证据和政策启示。