摘要
2008年以来,我国PPI与CPI走势出现了多次背离与分化,从整体上看,两者相关性很弱。但从动态视角来看,由于相关关系可能会因时而变,整体相关性有可能被关系本身的方向和强弱变化所削弱甚至掩盖。为准确反映两者相关性的动态变化,本文放宽时变系数函数的光滑性假设,提出了带跳时变系数模型,并给出一种非参数三步估计方法:①估计系数函数中跳点的位置和个数;②基于估计的跳点和Bootstrap方法选择的窗宽给出系数函数的最终估计;③利用蒙特卡洛模拟评价本文提出的非参数估计和窗宽选择方法的有限样本性质。通过对2008年1月至2017年12月我国PPI和CPI月度同比数据的实证分析,本文发现该模型能较好地刻画PPI与CPI相关性的时变和带跳特征,验证了该模型的应用价值。
Since 2008, the trend of PPI and CPI in China has deviated and split up many times. On the whole, both correlate weakly. However, from a dynamic perspective, because the correlation may change over time, the overall correlation may be weakened or even concealed by the veer and extent of correlations itself. In order to reflect the dynamic changes of the PPI and CPI correlations, this paper propose a time-varying coefficient models with jumps and offers a nonparametric three-step estimation procedure in a hypothesis of smoothness in the eased time-varying coefficient function.①the position and number of jumps are estimated in the coefficient function;②the final estimation of the coefficient function is given based on the estimated jumps and the bandwidth chosen by the bootstrap method;③some Monte Carlo simulations are used to evaluate the finite sample performance of the proposed nonparametric estimation and bootstrap method. By empirically studying the PPI and CPI data in China from January 2008 to December 2017, it is found that the model can well depict the time-varying and band jumping characteristics of PPI and CPI, and furthermore justify the value in applying this model.
作者
苍玉权
赵彦勇
林金官
Cang Yuquan;Zhao Yanyong;Lin Jinguan
出处
《统计研究》
CSSCI
北大核心
2019年第2期101-111,共11页
Statistical Research
基金
国家自然科学基金青年项目"复杂数据下带跳回归模型的统计分析"(11701286)
国家自然科学基金面上项目"一类经济计量模型的统计分析及其应用研究"(11571073)
江苏省自然科学基金青年项目"基于带跳回归模型的高维纵向数据统计分析"(BK20171073)的资助
关键词
非参数估计
跳点
时变系数模型
PPI与CPI
Nonparametric Estimation
Jumps
Time-varying Coefficient Model
PPI and CPI
