汇率货币模型的非线性协整关系检验——基于深度GRU神经网络

本文采用深度门控循环单元（GRU）神经网络探讨三种汇率货币模型（弹性价格、前瞻性和实际利率差模型）的非线性协整关系。GRU技术在深度学习中具有智能记忆、自主学习和强逼近能力等优点。为此，本文运用该技术对6组典型浮动汇率制国别数据进行了非线性Johansen协整检验。结果表明，汇率与宏观经济基本面之间存在非线性协整关系，从而说明了货币模型在非线性条件下的有效性，以及先进的深度学习工具在检验经济理论中的优势。     

资产证券化与金融市场动态关系研究——基于美国CDO产品的证据

文章从产品市场链的视角出发,以美国代表性证券化产品CDO为例,从理论机理和实证检验两个方面研究了资产证券化与广义金融市场的动态关系。结果表明:资产证券化把房地产市场、信贷市场、债券市场和股票市场紧密联系在一起,形成一种独特的市场链结构,该市场链反映出证券化产品与各个金融市场之间的强弱关系以及风险传导顺序;短期内证券化产品与市场链上的远端市场关系很弱,长期内证券化产品与所有金融市场均保持一种稳定正向关系,说明证券化产品如若发生风险暴露,短期内风险只会在市场链的近端市场发生传导而不会影响到远端市场,但在长期,风险则会通过市场链传递给整个金融系统,最终可能引发市场动荡。     

Stationary bootstrapping for panel cointegration tests under cross-sectional dependence

Stationary bootstrapping is applied to panel cointegration tests which are based on the ordinary least-squares estimator and the seemingly unrelated regression (SUR) estimator of the residual unit root. Large sample validity of stationary bootstrapping is established. A finite sample experiment reveals that size performances of the bootstrap tests are much less sensitive to cross-sectional correlation than those of existing tests and a test based on the SUR estimator has substantially better power than existing tests.     

福建科技人力资本、研发资本与经济增长协整关系研究

运用现代动态经济计量分析方法,采用《福建统计年鉴（1987—2012）》数据,对福建省科技人力资本、研发资本与经济增长之间的动态关系进行了实证分析。分析结果表明：福建省科技人力资本、研发资本与经济增长之间存在长期稳定的正向关系,科技人力资本是推动经济长期持续增长的重要因素,福建省经济增长对科技人力资本和研发资本在长期都有明显的正效应。在此基础上提出了稳步发展福建省科技人力资本、研发资本促进经济持续协调快速增长的对策。     

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。     

Testing Wagner's Law in India: A cointegration and causality analysis

The present study empirically analyzes the validity of Wagner's Law for Indian economy. With the use of annual time series data from 1970–71 to 2013–14, all the six versions of Wagner's Law have been analyzed to test the relationship between government expenditure and gross domestic product. Wagner's Law states that the economic growth is the causative factor of the growth of the public expenditure. The study applied the unit root test and cointegration test to find the long-run relationship between government expenditure and gross domestic product. The present study employed the various econometric techniques such as unit root test, cointegration, and causality analysis for empirical analysis. The empirical analysis under study inferred mixed results of Wagner's Law for Indian economy, where four versions, namely Peacock, Gupta, Guffman, and Musgrave, found valid for Indian economy. The study concluded that the Wagner's Law is valid for the Indian economy except the Pryor and Mann Versions of the Wagner's Law.     

Comparison of procedures for fitting the autoregressive order of a vector error correction model

This paper investigates the lag length selection problem of a vector error correction model by using a convergent information criterion and tools based on the Box–Pierce methodology recently proposed in the literature. The performances of these approaches for selecting the optimal lag length are compared via Monte Carlo experiments. The effects of misspecified deterministic trend or cointegrating rank on the lag length selection are studied. Noting that processes often exhibit nonlinearities, the cases of iid and conditionally heteroscedastic errors will be considered. Strategies that can avoid misleading situations are proposed.     

基于非参数 ACE变换的贝叶斯非线性协整检验

针对线性以及非线性协整检验存在模型参数过多、小样本条件下检验功效偏低的问题,提出基于非参数 ACE变换的贝叶斯非线性协整 VAR模型, 运用 ACE算法进行变量变换, 结合参数的完全条件分布设计 Gibbs抽样方案, 进行贝叶斯非线性协整检验, 并利用 MonteCarlo仿真研究了贝叶斯非线性协整方法的检验势, 发现贝叶斯非线性协整比经典 Johansen法具有更高更稳健的检验势;同时, 对中国城市和农村居民消费价格指数序列进行实证分析.研究结果表明:贝叶斯非线性协整方法解决了模型中参数过多、小样本条件下检验功效偏低的问题,提高了估计的精确度和检验的准确性