老龄化背景下退休对城镇家庭金融资产选择的影响——基于模糊断点回归设计

随着老龄化程度日益加深,我国退休人口将会呈现增长趋势。本文研究退休作为一种个体工作状态的外生冲击,如何影响家庭的金融资产选择行为。利用中国家庭金融调查微观数据,采用模糊断点回归设计的非参数估计方法,本文发现退休不会造成家庭风险金融资产配置比例发生显著变化,但会引起风险资产种类构成的明显变动,现金、股票和基金在家庭金融资产中所占比重显著下降,银行存款、理财产品和借出款所占比重则显著上升。影响机制检验发现,退休对家庭金融资产选择的这种影响,可能是通过退休之后家庭的风险态度变化、金融知识变化和收入冲击造成的。本文研究表明,对退休人口进行金融知识普及和金融风险教育十分必要。     

HDDA: DataSifter: statistical obfuscation of electronic health records and other sensitive datasets

There are no practical and effective mechanisms to share high-dimensional data including sensitive information in various fields like health financial intelligence or socioeconomics without compromising either the utility of the data or exposing private personal or secure organizational information. Excessive scrambling or encoding of the information makes it less useful for modelling or analytical processing. Insufficient preprocessing may compromise sensitive information and introduce a substantial risk for re-identification of individuals by various stratification techniques. To address this problem, we developed a novel statistical obfuscation method (DataSifter) for on-the-fly de-identification of structured and unstructured sensitive high-dimensional data such as clinical data from electronic health records (EHR). DataSifter provides complete administrative control over the balance between risk of data re-identification and preservation of the data information. Simulation results suggest that DataSifter can provide privacy protection while maintaining data utility for different types of outcomes of interest. The application of DataSifter on a large autism dataset provides a realistic demonstration of its promise practical applications.     

Lassoing the Determinants of Retirement

This article uses Danish register data to explain the retirement decision of workers in 1990 and 1998. Many variables might be conjectured to influence this decision such as demographic, socioeconomic, financial, and health related variables as well as all the same factors for the spouse in case the individual is married. In total, we have access to 399 individual specific variables that all could potentially impact the retirement decision. We use variants of the least absolute shrinkage and selection operator (Lasso) and the adaptive Lasso applied to logistic regression in order to uncover determinants of the retirement decision. To the best of our knowledge, this is the first application of these estimators in microeconometrics to a problem of this type and scale. Furthermore, we investigate whether the factors influencing the retirement decision are stable over time, gender, and marital status. It is found that this is the case for core variables such as age, income, wealth, and general health. We also point out the most important differences between these groups and explain why these might be present.     

金融冲击与中央银行的流动性支持政策研究

本文在DSGE框架下引入金融冲击,比较完整地刻画了包含货币政策、宏观审慎政策以及流动性支持政策的央行“政策工具箱”,并对中央银行的流动性支持政策在不同外生冲击下的经济金融稳定效应进行了系统考察。本文分析得到了三个基本结论:一是在各种典型的金融冲击下,中央银行的流动性支持政策均具有良好的宏观稳定效应;二是从政策实施的角度,中央银行的流动性支持政策可考虑盯住银行存款的变动,并在政策操作上体现“及时反应、力度合理”的原则;三是从社会福利增进的角度,中央银行流动性支持政策的效果受到冲击来源的影响,总体上应对金融冲击的效果较好。分析结果初步显示了流动性支持政策作为中央银行“政策工具箱”一种辅助性金融稳定工具的可行性、针对性和有效性。     

Robust portfolio choice for a defined contribution pension plan with stochastic income and interest rate

This paper considers a robust portfolio choice problem for a defined contribution pension plan with stochastic income and stochastic interest rate. The investment objective of the pension plan is to maximize the expected utility of the wealth at the retirement time. We assume that the financial market consists of a stock, a zero-coupon bond and a risk-free asset. And the member of defined contribution pension plan is ambiguity-averse, which means that the member is uncertain about the expected return rate of the bond and stock. Meanwhile, the member's ambiguity-aversion level toward these two financial assets is quite different. The closed-form expressions of the robust optimal investment strategy and the corresponding value function are derived by adopting the stochastic dynamic programming approach. Furthermore, the sensitive analysis of model parameters on the optimal investment strategy are presented. We find that the member's aversion on model ambiguity increases her hedging demand and has remarkable impact on the optimal investment strategy. Moreover, we demonstrate that ignoring model uncertainty will lead to significant utility loss for the ambiguity-averse member, and the model uncertainty about the stock dynamics implies greater effect on the outcome of the investment than the bond.     

提高缴费率还是推迟退休?

本文在一般均衡OLG模型框架内对比分析了提高养老金缴费率和推迟退休年龄对劳均资本存量、个人和社会统筹账户养老金水平等经济变量的影响。分析结果表明：第一、提高个人账户缴费率除了能增加个人账户养老金和降低私人储蓄外对劳均资本存量等其他经济变量均没有影响。第二、推迟退休和提高社会统筹缴费率都会降低劳均资本存量、单位工资、私人储蓄、第一期消费及效用水平;第三、推迟退休和提高社会统筹缴费率都能提高资本回报率、个人和社会统筹账户养老金收益水平;第四、推迟退休可以提高第二期的消费水平,而提高社会统筹缴费率却会降低第二期的消费水平。上述结果表明,推迟退休的政策选择要优于提高社会统筹缴费率的政策。     

群体分析视角下商业银行对金融体系的风险溢出效应研究

本文基于异质市场假说和高频数据,利用高频数据采样频率高及富含波动信息的特点,构造多银行和系统间多元联合分布过程,并将银行间的动态联系纳入考虑,构建了蕴含丰富经济意义、形式灵活的高频动态多条件CoVaR模型及基于此的群体性系统性风险贡献指标。从群体分析视角出发,研究了不同商业银行群体对金融体系的风险溢出效应。结果显示：就系统性风险贡献度而言,该模型准确刻画了近年不同时期下我国三类商业银行系统性风险贡献度的时变特征,其表现为在次贷危机及欧债危机、我国“钱荒”时期及股票市场异常动荡时期,由于风险的传染性等特征导致三类商业银行的系统性风险贡献度均有所上升,而在其他时期则相对平稳;就单个银行对系统的风险溢出影响而言,工商银行的风险溢出比率最大,与其庞大的资产规模以及在金融体系中的重要地位与作用密不可分;当分析同类型银行群体的风险冲击时,国有商行类的系统性风险溢出比率值最高,其次为股份制商行类,该两类的溢出比率相差无几,且均远大于城商行类,表明股份制商行对金融系统的风险溢出影响不可小觑;当剖析不同类型银行群体时,此模型同样适用。本文所构模型能够实现多个银行对金融系统极端风险贡献的度量,可为监管部门的分类监管及有限能力下银行救助顺序的确定提供一定参考依据。     

利率扭曲、市场分割与深化利率市场化改革

虽然存贷款利率管制已经取消,但在改革过渡期内,目前我国信贷市场中仍然存在一定程度的利率扭曲与市场分割：同时存在商业银行和类银行机构,商业银行利率较低,主要为传统企业等低风险企业贷款,而非传统企业融资更多依赖于利率较高的类银行机构。本文从利率扭曲与市场分割问题入手,构建包含异质性金融部门和企业部门的动态随机一般均衡（DSGE）模型,研究深化利率市场化改革对经济金融的具体效应。结果显示,改革将促使利率回归均衡,消除监管套利,维护金融稳定;同时,优化金融资源配置,降低企业部门杠杆率,推动经济高质量发展。但改革也将对不同类型的金融、企业部门形成差异化影响,在助推产业结构优化升级的同时,驱动商业银行和传统企业加快经营转型。此外,改革后经济体在面对外部冲击时更加稳健。进一步,对比不同改革进程下的政策效果发现,若进程过快,可能增加短期经济金融波动风险。因此,改革应遵循循序渐进的推进原则。     

企业财务风险预测模型实证比较分析

企业财务风险一直是风险管理理论和实务界关心的热点话题。运用判别分析和计量经济方法对重庆市某商业银行的461个样本企业2002-2005年的违约特征进行实证检验和预测。结果发现最重要的决定变量是资产负责率、酸性试验比率、资产净利率等7个财务比率以及企业所处的产业部门,考虑了异方差性的probit模型有更好的预测能力。     

脱实向虚和金融强监管对金融实体行业间极端风险关联的影响

随着金融机构影子银行业务的扩张和部分实体企业“脱实向虚”倾向的加剧,金融与实体经济的联系愈发紧密,对于极端风险的研究不应只局限于金融体系内部。故此,本文首先基于行业指数日度数据与五分钟高频数据测算行业风险价值,其次利用Elastic-Net-VHAR模型构建金融实体极端风险网络进行动态演化分析,最后研究实体与金融行业间风险溢出水平的影响因素。结果显示:第一,基于横截面维度,材料和工业行业在网络中居于中心位置,金融行业的风险净溢出水平为负;第二,2017年金融强监管政策开启后,网络整体密度明显下降,实体行业对金融行业风险输出水平降低,而金融行业对实体行业风险输出水平略有提升;第三,面板回归结果显示,实体行业“脱实向虚” 程度显著提升了实体与金融行业之间双向风险溢出水平,并且在金融强监管与双向风险溢出水平之间起到了正向调节效应。根据上述结论,建议监管层进一步推进金融强监管政策,注意金融监管政策与供给侧结构性改革政策之间的配合,还应特别重视对实体企业金融化规模进行严格监控,更加有效地防范系统性风险。     

金融危机和地产调控冲击下地产板块和整体股市的波动性研究

本文采用股票指数数据，通过BEKK—GJR—GARCH模型考察了地产板块和整体股市之间的均值溢出和波动溢出效应，并在此基础之上，进一步考察了在金融危机发生的特定时间窗口下，两者之间的波动溢出效应。此外，本文在引入表征危机事件和地产调控冲击的虚拟变量之后，考察了冲击对地产板块和整体股市波动性的影响。本文的实证模型考虑了非对称性因素并采用广义误差分布（GED）处理“厚尾”问题，是对现有研究范式的有益探索。本文的实证结果认为，地产板块和整体股市之间存在着显著的波动溢出效应，均值溢出效应的存在不甚稳健，但两种溢出效应都存在明显的非对称性。地产板块对整体股市的波动溢出持续性很小，但冲击会加剧波动，反之整体股市对地产板块的则具备持续性，冲击更强烈。波动溢出在2008年金融危机和2015年股灾期间存在变化，尤其是一方对另一方的直接冲击作用都更弱了，可能由两市场联结减弱导致，但非对称性依旧突出。引入表征事件冲击的虚拟变量后，估计结果能够显示出危机和地产调控对于地产板块和整体股市的波动性存在明确影响：直接来看，2010年的房市调控影响幅度最大，超过2015年股灾和2008年金融危机，这一点值得房市调控政策制定者注意；间接来看，六次事件中的五次均对地产板块和整体股市之间的相关性有影响，普遍性很高，由此，风险监管层有必要关注不同冲击下股市内部相关性的变化。     

A new financial risk ratio

Randomness in financial markets has been recognized for over a century: Bachelier (1900), Cowles (1932), Kendall (1953), and Samuelson (1959). Risk thus enters into efficient portfolio design: Fisher (1906), Williams (1936), Working (1948), Markowitz (1952). Reward versus risk decisions then depend upon utility to the investor: Bernoulli (1738), Kelly (1956), Sharpe (1964), and Modigliani (1997). Returns of a portfolio adjusted to risk are measured by a number of ratios: Treynor, Sharpe, Sortino, M2, among others. I will propose a refinement of such ratios. This possibility was mentioned in my recent book: Antieigenvalue analysis, World-Scientific (2011). The result is a new set of growth-to-return risk-based financial ratios of ratios.     

Conditional Extremes in Asymmetric Financial Markets

ABSTRACT

The global financial crisis of 2007–2009 revealed the great extent to which systemic risk can jeopardize the stability of the entire financial system. An effective methodology to quantify systemic risk is at the heart of the process of identifying the so-called systemically important financial institutions for regulatory purposes as well as to investigate key drivers of systemic contagion. The article proposes a method for dynamic forecasting of CoVaR, a popular measure of systemic risk. As a first step, we develop a semi-parametric framework using asymptotic results in the spirit of extreme value theory (EVT) to model the conditional probability distribution of a bivariate random vector given that one of the components takes on a large value, taking into account important features of financial data such as asymmetry and heavy tails. In the second step, we embed the proposed EVT method into a dynamic framework via a bivariate GARCH process. An empirical analysis is conducted to demonstrate and compare the performance of the proposed methodology relative to a very flexible fully parametric alternative.     

Selecting treatments: a decision theoretic approach

The paper looks at the problem of comparing two treatments, for a particular population of patients, where one is the current standard treatment and the other a possible alternative under investigation. With limited (finite) financial resources the decision whether to replace one by the other will not be based on health benefits alone. This motivates an economic evaluation of the two competing treatments where the cost of any gain in health benefit is scrutinized; it is whether this cost is acceptable to the relevant authorities which decides whether the new treatment can become the standard. We adopt a Bayesian decision theoretic framework in which a utility function is introduced describing the consequences of making a particular decision when the true state of nature is expressed via an unknown parameter θ (this parameter denotes cost, effectiveness, etc.). The treatment providing the maximum posterior expected utility summarizes the decision rule, expectations taken over the posterior distribution of the parameter θ.     

Extremal dependence tests for contagion

A new test for financial market contagion based on changes in extremal dependence defined as co-kurtosis and co-volatility is developed to identify the propagation mechanism of shocks across international financial markets. The proposed approach captures changes in various aspects of the asset return relationships such as cross-market mean and skewness (co-kurtosis) as well as cross-market volatilities (co-volatility). Monte Carlo experiments show that the tests perform well except for when crisis periods are short in duration. Small crisis sample critical values are calculated for use in this case. In an empirical application involving the global financial crisis of 2008–2009, the results show that significant contagion effects are widespread from the US banking sector to global equity markets and banking sectors through either the co-kurtosis or the co-volatility channels, reinforcing that higher order moments matter during crises.     

“丝绸之路经济带”背景下中国对哈萨克斯坦资本流动风险评价及预测

从投资环境的稳定性、资本流动的合理性及金融市场的有效性三个层次构建三角模型,考察中国对哈萨克斯坦资本流动可能存在的风险问题。研究结果认为:中国对哈萨克斯坦资本流动的整体风险容易受到国际环境及哈萨克斯坦内部环境变化的影响,2008年以后整体风险开始上升。采用GM(1,1)模型对2015—2020年资本流动的风险状态进行预测,结果显示:未来几年中国对哈萨克斯坦资本流动的风险状态主要处于弱安全区,哈萨克斯坦的投资环境、资本流动结构、金融市场稳定性均存在不同程度的恶化,存在较大的资本流动风险。     

预期引导、政策冲击与股市波动——基于文本分析法的异质性诊断

防范股票市场异常波动是维护金融稳定和防控金融风险的关键一环。货币政策实践中,预期引导与政策冲击对股市波动的实际影响和传导机制迥然不同。现有文献对两者之于股票市场波动 的异质性影响多有讨论,但分歧明显。基于2005年到2019年中国人民银行各季度《货币政策执行报告》和《货币政策大事记》,本文分别构建表征货币政策预期引导强度和实际操作频度的代理变量,对上述指标之于同期A股市场主要行业指数的波动性影响做了多维诊断和系统梳理。研究发现,第一,预期引导效应和政策冲击效应对于股票市场波动性的影响存在显著异质性特征,预期引导有助于平抑市场波动,而频繁调控则会放大股市波动。第二,预期引导的明确性会制约其对股市波动的平缓作用,货币调控意愿的表达越明确,越有助于平抑股票市场波动;而更坚决的“严厉型”表述比态度相对温和的“温和型”表述能够更显著地平抑股票市场波动。第三,实际操作频度对股市波动的放大作用受制于具体调控方向,宽松型调控的频率上升仅会小幅放大股市波动,而紧缩型货币调控则会大幅抬升股市波动性。由此,从平抑股市异常波动、维持金融稳定的角度出发,强化货币政策的预期引导比相机抉择的频繁调控更为重要;在预期引导过程中,应当增强调控意愿表达的明确性和坚决性,以限制其对金融市场运行带来的扰动。     

The Increasingly Mixed Proportional Hazard Model: An Application to Socioeconomic Status,Health Shocks,and Mortality

We introduce a duration model that allows for unobserved cumulative individual-specific shocks, which are likely to be important in explaining variations in duration outcomes, such as length of life and time spent unemployed. The model is also a useful tool in situations where researchers observe a great deal of information about individuals when first interviewed in surveys but little thereafter. We call this model the “increasingly mixed proportional hazard” (IMPH) model. We compare and contrast this model with the mixed proportional hazard (MPH) model, which continues to be the workhorse of applied single-spell duration analysis in economics and the other social sciences. We apply the IMPH model to study the relationships among socioeconomic status, health shocks, and mortality, using 19 waves of data drawn from the German Socio-Economic Panel (SOEP). The IMPH model is found to fit the data statistically better than the MPH model, and unobserved health shocks and socioeconomic status are shown to play powerful roles in predicting longevity.     

长寿风险对教育和退休决策的影响

本文在三阶段世代交叠及两部门经济模型的框架下研究长寿风险对劳动者受教育年限、退休年龄及长期收入的影响。个人的一生分为教育、工作及退休三个阶段,同时劳动者采用经验-工资的倒U型曲线,在此条件下分析劳动者的工作-闲暇决定和消费-储蓄决定。根据模型显示,长寿风险会增加个人的受教育年限、延长退休年龄以及增加劳动者的长期收入。同时,根据模型的敏感性分析,政府对劳动者征收的税率也会对劳动者个人决策产生影响,而且这种影响的程度超过了长寿风险的影响。最后,根据模型的结论提出了相应的政策性建议。     

韩国的金融政策与金融危机及对我国的警示

金融危机的爆发对经济发展的危害是巨大的,受这次金融风暴直接冲击的国家,其经济实力普遍倒退７至１０年。其中韩国因货币贬值五成,其经济规模已由世界排名第１２位降至第１７位,人均国民生产总值由１９９６年的１０５４８美元降至目前的６６６４美元,经济实力倒退了...