Parameter identification for the discretely observed geometric fractional Brownian motion

This paper deals with the problem of estimating all the unknown parameters of geometric fractional Brownian processes from discrete observations. The estimation procedure is built upon the marriage of the quadratic variation and the maximum likelihood approach. The asymptotic properties of the estimators are provided. Moveover, we compare our derived method with the approach proposed by Misiran et al. [Fractional Black-Scholes models: complete MLE with application to fractional option pricing. In International conference on optimization and control; Guiyang, China; 2010. p. 573–586.], namely the complete maximum likelihood estimation. Simulation studies confirm theoretical findings and illustrate that our methodology is efficient and reliable. To show how to apply our approach in realistic contexts, an empirical study of Chinese financial market is also presented.     

Estimation for seasonal fractional ARIMA with stable innovations via the empirical characteristic function method

Seasonal fractional ARIMA (ARFISMA) model with infinite variance innovations is used in the analysis of seasonal long-memory time series with large fluctuations (heavy-tailed distributions). Two methods, which are the empirical characteristic function (ECF) procedure developed by Knight and Yu [The empirical characteristic function in time series estimation. Econometric Theory. 2002;18:691–721] and the Two-Step method (TSM) are proposed to estimate the parameters of stable ARFISMA model. The ECF method estimates simultaneously all the parameters, while the TSM considers in the first step the Markov Chains Monte Carlo–Whittle approach introduced by Ndongo et al. [Estimation of long-memory parameters for seasonal fractional ARIMA with stable innovations. Stat Methodol. 2010;7:141–151], combined with the maximum likelihood estimation method developed by Alvarez and Olivares [Méthodes d'estimation pour des lois stables avec des applications en finance. Journal de la Société Française de Statistique. 2005;1(4):23–54] in the second step. Monte Carlo simulations are also used to evaluate the finite sample performance of these estimation techniques.     

信息化在“四化”发展中的贡献度研究——基于中国省际面板数据

构建“四化”发展水平指标体系,基于2006-2013年中国省际面板数据,运用全局主成分分析法得出“四化”发展水平得分,在此基础上,对“四化”耦合发展互动关系进行计量分析.结果显示:“四化”之间存在长期均衡的协整关系;信息化对于农业现代化边际贡献度为0.231 8,弱于工业化的边际贡献;信息化对于城镇化的边际贡献度为0.702 3,强于工业化对城镇化的贡献;信息化对于工业化的边际贡献不显著.基于实证分析结果,提出加强城镇信息化建设和提升城镇化人口素质的政策建议.     

我国居民文化消费影响因素探析

运用我国1983—2012年的数据,通过实证分析考察了可支配收入、教育水平、金融发展和政府文化事业支出对我国居民文化消费的影响。长期均衡分析结果表明,教育水平和金融发展对我国居民文化消费具有显著的促进作用;教育水平提高1%,居民文化消费增加0.454%;金融机构信贷提高1%,居民文化消费增加0.363%;可支配收入和政府文化事业支出对居民文化消费的影响不显著。脉冲响应分析结果表明,可支配收入冲击对居民文化消费的影响在短期由正向转为负向,教育水平冲击和金融发展冲击对居民文化消费短期具有正向影响,政府文化事业支出冲击对居民文化消费短期具有负面影响。根据实证分析的结论,文章提出了扩大我国居民文化消费的政策建议。     

The Comparison of Performances of Widely Used Cointegration Tests

The aim of this study is to compare performances of commonly cointegration tests used in literature in terms of their empirical power and type I error probabilty for various sample sizes. As a result of the study, it has been found that some tests are not appropriate in testing cointegration in terms of empirical power and type I error probability. As a result of simulation study, λ_max test for any values of ρ and sample sizes have been found most appropriate test in conclusion.     

长江流域的消费函数:基于非稳定面板数据的分析

运用面板单位根与面板协整方法研究长江流域的消费函数。基于10省(市)1981-2003年的宏观消费与收入的面板数据,研究发现消费与收入存在显著的面板协整关系,边际消费倾向也非常稳定,稳定在0.7-0.85之间。为此,应采取鼓励消费的政策,从而促进经济长期增长。     

国债收益率协整关系研究

通过对中国国债收益率与央票利率、基准利率和CPI的协整关系研究,揭示出我国国债市场的收益率走势与各宏观经济变量之间的互动关系。研究结果表明:在不施加任何约束的条件下,我国国债市场的风险长期来看是可以规避的,而国债与央票之间具有互动关系,二者的利率风险具有一定的互补性。     

金融发展与区域经济增长研究——基于重庆市的实证分析

金融对经济的促进作用往往会受到其他因素的影响,而使得结果大打折扣,其主要原因是因为目前资金的流动受到很多制度和人为因素的影响,导致资源不能及时从低效率部门流入高效率部门。本研究从现有理论出发,通过收集重庆市1986—2010年有关经济增长和金融发展的数据,利用计量经济学软件,通过误差修正模型,得出二者之间的协整关系。在此基础之上,结合重庆现状分析回归结果并提出有关政策建议。     

固定资产投资与国内生产总值的误差修正模型研究

运用协整理论和误差修正模型研究固定资产投资和国内生产总值之间的关系,可以发现它们之间存在长期均衡的协整关系,使用误差修正模型比普通的单变量方程更能反映两者长期和短期的关系,还可以避免谬误回归问题。