考虑记忆性质与时间滞后效应的非线性经济周期模型分析

考虑非线性经济周期模型中经济变量存在记忆性质与时间滞后现象,研究随机周期作用激励下Goodwin模型的随机响应,以此研究记忆性质与时间滞后现象对经济周期波动的具体影响。通过随机多尺度方法得到了模型的确定性与随机情形下的稳态响应。结果发现:当考虑非线性投资函数时,经济变量的时间记忆性质和时间滞后现象均可以导致经济波动方式的改变;当考虑非线性消费函数时,经济变量的时间记忆性质与时间滞后现象均可以诱导出经济周期波动的随机跳跃现象,即引发经济系统的突变。同时,随机周期作用也可以诱发系统出现稳态概率密度函数的分岔现象出现,说明外部随机周期作用可以诱发经济系统的突变现象产生。     

山西省经济周期浅析

我国宏观经济运行中存在周期性变动,这已是近些年来理论界的共识。本文拟就山西省经济总体的经济周期作粗浅分析,从而更好地认识山西省经济运行的规律性和特点,为宏观南控提供理论上的依据,保持经济持续、快速、健康地发展。     

诺贝尔经济学奖新鲜出炉

芬恩·基德兰德和爱德华·普雷斯科特(以下简称基-普)用实际因素去解释经济周期波动的根源,开创了实际经济周期理论,并获得了2004年诺贝尔经济学奖,其成就主要集中在两个方面:一是在对实际经济周期的研究中,通过对引起实际经济周期波动的各种因素和各因素间相互关系的分析,使人们对于这一现象的认识更加深入;二是通过对宏观经济政策运用中“时间连贯性难题”的分析研究,为经济政策特别是货币政策的实际有效运用提供了思路。     

改革开放以来中国经济周期波动特征与形成机制分析

经济周期波动特征研究既是现实经济运行状况的真实反应,也是经济危机监测与预警机制的前提与基础。利用CF滤波法对1978—2010年间中国经济中主要宏观经济变量进行去势处理,考察了产出的周期波动特征,并以此参照系对改革开放以来国民经济运行展开分析。研究发现,改革开放以来中国经济的周期性波动特征明显,前后共经历了五轮经济波动。根据市场经济体制的确立时间和经济周期波动特点,可以将1978—2010年划分为改革探索时期和改革深化时期。就前者而言,经济周期波动的核心特征是高增长与通货膨胀,政府调节经济主要依靠行政手段,调控的重点是如何抑制需求的过度扩张;就后者论,经济波动的核心特征是流动性过剩、有效需求不足与通货紧缩,政府对经济的调节以间接宏观经济政策为主,调控的重点转变为启动内需。经济周期波动特征、政府调控方式和调控重点的演变反映了改革开放以来中国国民经济结构、宏观经济环境和经济运行机制的变化。     

基于谱分析的安徽省经济波动研究

科学地测定经济周期,有利于从更深层次理解和把握安徽经济系统的运行状态,对于安徽国民经济实现又好又快地发展具有十分重要的理论定义与现实意义。目前国内学者对安徽宏观经济波动的研究还比较少,故采用增长周期法,剔除安徽省国内生产总值指数长期趋势,生成人工序列,并对其进行加汉宁窗的谱分析,得到相应谱密度曲线;确定安徽省经济波动周期分量的长度与类型,对安徽经济周期波动情况进行回顾,发现固定资产投资的周期波动是造成安徽经济周期波动最直接的内在原因。安徽省应加强宏观经济调控,以减缓经济波动造成的影响。     

论经济周期规律与宏观调控实践

论经济周期规律与宏观调控实践张塞一、如何认识经济周期规律宏观经济在运行中客观上存在周期问题,这是不以人的主观意志为转移的一个客观规律。经济运行从一个高峰到另一个高峰,或者从一个低谷到另一个低谷,形成一个周期。从１９７８年以来,我国经济共经历了三个周期...     

波动与增长:基于随机增长模型的认识

在经济周期福利成本研究中,波动对增长的影响是人们争论的焦点之一。虽然大量实证研究表明许多国家的人均GDP增长率的均值与标准差之间存在统计显著的负相关关系,但缺乏理论上的说明。文章通过构建随机增长模型发现,随机冲击的增大不仅会使产出增长率的标准差增大,同时也使增长率均值减小。在数量上这就表现为增长率标准差与均值之间出现反向变化关系,从而为实证研究结论提供了一种说明。     

对非线性经济周期模型分岔的研究

基于Goodwin与Puu的经济周期模型,得到了一个推广的非线性动力学经济周期模型,利用路径积分法计算了系统转移概率密度,通过对不同参数条件下概率密度函数形状的变化分析,结合lyapunov指数图,得出了系统发生分岔和混沌的参数域.     

中国宏观经济周期波动的特征分析

文章利用Markov机制转换状态空间模型的平滑概率对中国经济周期的波动特征进行了分析研究，研究结果表明，经济扩张的平滑概率较好地刻画了中国经济周期波动的特征。通过实证分析我们发现：改革开放前后，经济周期的波动存在明显差异，非对称性特征比较明显；1952—2008年中国共经历了10轮经济周期的波动，平滑概率为我国经济周期的划分提供了一种新的分析方法；2000年以后，中国经济已步入了第10轮经济周期，经济扩张概率始终处于高位运行，到2008年为止，新一轮经济周期波动的低谷尚未出现。     

中国金融经济周期与真实经济周期的动态关联研究

 运用恒常条件相关（CCC）和动态条件相关估计方法（DCC）,本文考察了中国金融经济周期与真实经济周期的动态关系。研究发现,从1999年开始,随着中国金融深化程度和金融市场开放度的提高,金融经济周期与真实经济周期的动态关联程度持续上升。金融因素对经济周期的影响越来越显著,货币政策对真实经济的引导效果进一步强化,金融经济周期在中国表现愈加明显。政府运用宏观经济政策平抑经济波动时,不能仅以真实经济指标作为参考,还应参考金融经济指标。     

Short-Term GDP Forecasting With a Mixed-Frequency Dynamic Factor Model With Stochastic Volatility

In this article, we develop a mixed frequency dynamic factor model in which the disturbances of both the latent common factor and of the idiosyncratic components have time-varying stochastic volatilities. We use the model to investigate business cycle dynamics in the euro area and present three sets of empirical results. First, we evaluate the impact of macroeconomic releases on point and density forecast accuracy and on the width of forecast intervals. Second, we show how our setup allows to make a probabilistic assessment of the contribution of releases to forecast revisions. Third, we examine point and density out of sample forecast accuracy. We find that introducing stochastic volatility in the model contributes to an improvement in both point and density forecast accuracy. Supplementary materials for this article are available online.     

A Bayesian Markov-Switching Correlation Model for Contagion Analysis on Exchange Rate Markets

This article develops a new Markov-switching vector autoregressive (VAR) model with stochastic correlation for contagion analysis on financial markets. The correlation and the log-volatility dynamics are driven by two independent Markov chains, thus allowing for different effects such as volatility spill-overs and correlation shifts with various degrees of intensity. We outline a suitable Bayesian inference procedure based on Markov chain Monte Carlo algorithms. We then apply the model to some major and Asian-Pacific cross rates against the U.S. dollar and find strong evidence supporting the existence of contagion effects and correlation drops during crises, closely in line with the stylized facts outlined in the contagion literature. A comparison of this model with its closest competitors, such as a time-varying parameter VAR, reveals that our model has a better predictive ability. Supplementary materials for this article are available online     

Stochastic properties of the mixed accelerated hazard models

The accelerated hazard model in survival analysis assumes that the covariate effect acts the time scale of the baseline hazard rate. In this paper, we study the stochastic properties of the mixed accelerated hazard model since the covariate is considered basically unobservable. We build dependence structure between the population variable and the covariate, and also present some preservation properties. Using some well-known stochastic orders, we compare two mixed accelerated hazards models arising out of different choices of distributions for unobservable covariates or different baseline hazard rate functions.     

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.     

On stochastic behaviors of load-sharing parallel systems

Abstract

This paper mainly investigates a general load-sharing parallel system having two units. First, we construct some comparisons among a load standby system, a warm standby system, a hot standby system and a cold standby system. Moreover, some stochastic comparisons between the load-sharing parallel system and one of its two components are obtained in the sense of the usual stochastic order. Finally, the residual life of this system and its properties are examined.     

Preservation properties of stochastic orders by transformation to the transmuted-G model

Abstract

The transmuted-G model is a useful technique to construct some new distributions by adding a parameter. This paper considers stochastic comparisons in the transmuted-G family with different parameters and different baseline distributions in the sense of the usual stochastic, shifted stochastic, proportional stochastic and shifted proportional stochastic orders. Also, we present a necessary and sufficient condition for existence of the moments of the transmuted-G model and then we obtain some bounds for the survival and aging intensity functions of the transmuted-G model conditioned on its parameter and its baseline distribution.     

Some stochastic properties of conditionally dependent frailty models

The frailty approach is commonly used in reliability theory and survival analysis to model the dependence between lifetimes of individuals or components subject to common risk factors; according to this model the frailty (an unobservable random vector that describes environmental conditions) acts simultaneously on the hazard functions of the lifetimes. Some interesting conditions for stochastic comparisons between random vectors defined in accordance with these models have been described in the literature; in particular, comparisons between frailty models have been studied by assuming independence for the baseline survival functions and the corresponding environmental parameters. In this paper, a generalization of these models is developed, which assumes conditional dependence between the components of the random vector, and some conditions for stochastic comparisons are provided. Some examples of frailty models satisfying these conditions are also described.     

经济周期波动的函数型时序分解方法——基于CPI的实证分析

建立一个函数型时序分解模型,根据交叉验证方法将数据分为趋势项、周期项和随机项,因而提取出的趋势项具有较好的泛化能力;提出的基于调节粗惩系数的转折点选取法,通过优化粗惩系数较好地分割了CPI的扩张期和收缩期,可判断经济指数的转折点。另外利用傅里叶变换(FFT)提取数据主频,改进了周期型基函数,相比于传统的傅里叶基函数,新的周期基函数对周期项的拟合精度较高。通过对近十年和近两年的CPI数据进行分析,结果表明季节影响较为明显,而且最后的组合模型预测精度较高。     

ULM,a software for conservation and evolutionary biologists

Matrix models for population dynamics have recently been studied intensively and have many applications to theoretical and applied problems (conservation, management). The computer program ULM (Unified Life Models) collects a good part of the actual knowledge on the subject. It is a powerful tool to study the life cycle of species and meta-populations. In the general framework of discrete dynamical systems and symbolic computation, simple commands and convenient graphics are provided to assist the biologist. The main features of the program are shown through detailed examples: a simple model of a starling population life cycle is first presented leading to basic concepts (growth rates, stable age distribution, sensitivities); the same model is used to study competing strategies in a varying environment (extinction probabilities, stochastic sensitivities); a meta-population model with migrations is then presented; some results on migration strategies and evolutionary stable strategies are eventually proposed.     

随机波动HJM框架下信用利差模型及实证研究

将随机波动引入到具有违约风险的HJM模型中,基于无套利条件推导得出随机波动HJM模型框架下信用利差的漂移项限制条件,从而构建了随机波动HJM框架下的信用利差模型,并基于波动率结构的适当设定对模型进行马尔科夫简化,进而利用该模型对中国可违约债券市场信用利差的动态特性进行实证分析。结果发现：短期信用利差的动态特性具有显著的随机波动特征,而随机波动HJM框架下的信用利差模型可以很好地刻画中国可违约债券市场信用利差的动态特性。