商业银行信贷投资传导机制的统计分析

本文利用4家商业银行1992～2006年经济数据,根据协整理论和VAR模型等方法,从不同角度研究了我国大、中、小型商业银行信贷投资之间的动态关系,定量刻画了大、中型商业银行在小型商业银行信贷投资额波动中作用的大小。实证结果表明:大、中型商业银行与小型商业银行的信贷投资额之间具有长期均衡关系,且大、中型商业银行信贷投资的取向均是小型商业银行信贷投资取向的Granger原因,但大型商业银行之间的信贷传导力度比较微弱;大、中型商业银行信贷投资对小型商业银行投资波动的贡献度都表现出正向效应,相比而言,中型商业银行对小型商业银行信贷投资的传导力度要更大些。     

银行信贷与股票价格动态关系研究

本文采用五变量VAR模型对我国银行信贷与股票价格之间的动态关系进行实证分析,发现股票价格的上涨会导致银行信贷的扩张,但银行信贷扩张不是股票价格上涨的原因。基于此,本文提出对银行信贷的调控要考虑股票市场的影响。在股票市场繁荣的时候应该通过增加股票供给、丰富投资产品等措施防止股市泡沫的扩大,降低市场对股价升幅的预期,同时密切关注银行信贷资金的流向,防止资金由实体经济大量流向股票市场;而在股票市场萧条的时候,放松银行信贷并不能阻止股票价格下跌,稳定股票市场的关键是增强投资者信心,改善投资者对未来股票价格的预期。     

Data visualization and forecast combination for probabilistic load forecasting in GEFCom2017 final match

This paper describes the methods used by Team Cassandra, a joint effort between IBM Research Australia and the University of Melbourne, in the GEFCom2017 load forecasting competition. An important first phase in the forecasting effort involved a deep exploration of the underlying dataset. Several data visualisation techniques were applied to help us better understand the nature and size of gaps, outliers, the relationships between different entities in the dataset, and the relevance of custom date ranges. Improved, cleaned data were then used to train multiple probabilistic forecasting models. These included a number of standard and well-known approaches, as well as a neural-network based quantile forecast model that was developed specifically for this dataset. Finally, model selection and forecast combination were used to choose a custom forecasting model for every entity in the dataset.     

非现金支付的发展及其规律性的分析

本文分析了2013年至2017年我国非现金支付发展情况及其规律性,建立了关于非现金支付工具选择偏好的模型。数据分析发现,在这段时间传统的非现金支付业务出现了较大幅度的下降,而新型的电子化支付工具迅速发展,特别是网上支付和移动支付业务规模出现爆发性增长。理论研究表明,非现金支付工具的选择主要决定于安全性、便利性和使用成本,而这三项因素又受到交易规模的影响。交易规模越大,人们对支付工具的安全性要求越高,对便利性要求越低,也可以接受付费和较高的使用成本;交易规模越小,人们对支付工具的便利性要求越高,对安全性要求降低,也不可以接受付费和较高的使用成本;在交易规模一定的情况下,越安全、越便利、使用成本越低的支付工具越能得到使用。本文建议,应将非银行支付机构的账户余额纳入M1范围,加强对非现金支付工具的统计分析,加快开发中央银行主导的新型非现金支付工具。     

Macroeconomic Drivers of Loan Quality in Turkey

We analyze the drivers of nonperforming loans in the Turkish banking system after the 2000–01 Turkish banking crisis. By constructing a vector autoregression model, we perform dynamic out-of-sample forecasts, which yield quite accurate results compared to the actual data. Since forecasting is a very crucial tool for both policy makers and market players, these results are some of the main strengths and contributions of this study. This article shows various patterns between the economic and financial indicators and the nonperforming loans. One important message obtained from the results is that policy makers should be concerned about the status of the economy and the market expectations to maintain stability in the banking system.     

互联网金融、存款竞争与银行风险承担

本文通过构建纳入互联网金融的银行环形城市模型,推演了“互联网金融→存款结构/付息成本→银行风险承担”的传导机制。在此基础上,以2003-2016年我国83家商业银行为样本,建立多重中介效应模型进行实证检验。研究结果表明:(1)互联网金融发展经由恶化存款结构和抬高付息成本两种渠道显著加重了银行风险承担水平,其中,恶化存款结构效应的相对贡献为50%左右,抬高付息成本效应的相对贡献为35%左右;(2)相较于互联网渠道构筑业态,互联网支付结算、互联网资源配置和互联网财富管理业态对银行存款结构和付息成本的不利影响更为强烈;(3)相对于国有、大规模、低流动性和低资本充足率商业银行,面对互联网金融的冲击,非国有、小规模、高流动性和高资本充足率商业银行的客户存款流失更快,平均付息成本上涨更多。     

货币政策、消费品和投资品通货膨胀——基于金融加速器视角

本文建立一个包含消费品和投资品生产的两部门新凯恩斯DSGE模型,并且引入金融加速器以分析货币政策对消费品和投资品通货膨胀的影响机制,同时使用1999Q1至2015Q4的中国宏观经济数据对模型进行贝叶斯估计。估计结果表明,两个部门的菲利普斯曲线都具有较高的价格粘性。外部融资溢价对两个部门企业投资的影响存在异质性,投资品部门的金融加速器效应更加明显。脉冲响应分析表明货币政策扩张时,投资品部门的产出和通胀膨胀上升幅度比消费品部门更大。理论模型的脉冲响应与VAR实证分析得到的经验事实相一致。金融摩擦导致的消费品和投资品部门需求结构的异质性是解释货币政策对两个部门影响差异的关键。数值模拟分析发现金融加速器机制主要改变货币政策对投资品产出和通货膨胀的影响,对消费品部门影响改变较小。方差分解结果表明加总技术冲击、投资边际效率冲击和货币政策冲击是经济波动的主要来源。     

风险资产配置与货币政策规则——黏性价格均衡下的宏观资产配置模型初探

本文将一个基于动态新凯恩斯理论的连续时间黏性价格一般均衡模型与随机动态资产配置模型相结合,进而研究基于内生宏观经济动态和货币政策规则进行资产配置的问题。在最优配置策略下,投资者相对风险偏好随无风险名义利率的增大而单调减小,而随通胀率的变化呈“U”型,说明投资者在通胀偏离稳态幅度较大时配置风险资产的相对意愿较高。此外,本文也给出了使用该模型讨论投资者最大化跨期效用对经济反作用这一宏观审慎问题的方式。     

城镇化、收入分配与进口贸易

城镇化是中国经济持续发展的重要战略平台,影响着个人收入水平的变动及收入分配差距的变化,从而对进口贸易规模及结构产生影响。本文通过VAR模型的构建、Granger因果检验和脉冲图,对城镇化发展影响个人收入分配差距、个人收入分配差距影响中国进口贸易进行分析。研究结果表明：城镇化发展对个人收入分配差距具有长期、相互的影响作用,个人收入分配差距变化对进口贸易增长具有正态效应。应采取相应措施,通过个人收入分配媒介,发挥城镇化对进口贸易的刺激效能。     

Rater Rating‐Level Bias and Accuracy in Performance Appraisals: The Impact OF Rater Personality,Performance Management Competence,and Rater Accountability

We studied the problem of rating‐level bias and rating accuracy among retail managers of a Fortune 500 retailer. Hypotheses were tested regarding the relationship among managers’ Five‐Factor Model (FFM) personality characteristics, their competence in performance management, and their levels of bias and accuracy in appraisals made in situations differing on levels of rater accountability. Associate store managers (N = 125) rated subordinates, peers and managers under conditions of high and low rater accountability. We found support for the stability of rating‐level bias across rating situations. Raters’ levels of agreeableness and assertiveness were related to mean rating levels across situations, and U‐shaped relationships were found in predicting one measure of rating accuracy such that high and low levels of these two traits were related to greater rating inaccuracy. Conscientiousness scores were significantly (and negatively) correlated with highly accountable mean ratings of subordinates. Performance management competence was related to rating‐level bias in both high‐ and low‐accountability conditions and contributed incremental validity in the prediction of rating level and rating accuracy. Our results indicate that the most lenient raters are more agreeable, less assertive, and less competent in performance management. These raters may also be less accurate. © 2015 Wiley Periodicals, Inc.