本文采用动态因子模型测度我国2001年2月至2015年12月的核心通货膨胀,并对测度效果进行了评价。在此基础上,进一步估计我国CPI分类项目的共同成分和特质成分,对我国CPI及其分类项目的动态特征进行了深入剖析。研究发现：拟最大似然法估计的核心通货膨胀在波动性、追踪趋势通货膨胀能力、预测未来通货膨胀能力方面表现优良,是测度核心通货膨胀较好的估计方法;CPI及其分类项目之间的波动性差异并非单独由宏观冲击或特质冲击引起,而是由二者共同作用产生并具有放大效应;我国通货膨胀的持久性确实是由宏观冲击主导,但由于部门异质性的存在,不同分类项目对于宏观冲击的响应并不完全一致。上述结论对我国当前和未来货币政策操作具有重要的启发和借鉴意义。
Abstract
With the help of dynamic factor model, this paper measures the core inflation of China from February 2001 to December 2015, and evaluates its measurement effect. On this basis, the common components and idiosyncratic components of China's CPI classifications are further estimated, and then the dynamic characteristics of China's CPI and its classifications are deeply analyzed. The conclusions are as followed. First, the core inflation estimated by the quasi maximum likelihood method is excellent in terms of volatility, tracking trend inflation ability and prediction of future inflation capacity. It is a better estimation method of core inflation. Second, the difference in volatility between CPI and its classified price index in China is not caused by macroeconomic shocks or sector-specific shocks alone, but produced under the joint effect of both, which has amplifying effects. The persistence of inflation in China is indeed dominated by macroeconomic shocks, , but due to the existence of sectoral heterogeneity, the response of different classifications to macroeconomic shocks is not completely consistent. The above conclusions have important enlightenment and reference significance for China's current and future monetary policy operations.
关键词
动态因子模型 /
核心通货膨胀 /
共同成分 /
特质成分
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Key words
Dynamic Factor Model /
Core Inflation /
Common Components /
Idiosyncratic Components
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中图分类号：
F822.5
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参考文献
[1] 范跃进,冯维江. 核心通货膨胀测量及宏观调控的有效性:对中国1995—2004的实证分析[J]. 管理世界,2005(5):6-13
[2] 高华川,赵娜. 基于多层因子模型的我国核心通货膨胀估计[J]. 统计研究,2016(4):36-43
[3] 侯成琪,龚六堂. 核心通货膨胀理论综述[J]. 经济学季刊,2013(2):549-569
[4] 孔丹凤,张成祥. 中国通货膨胀持续性研究:1994—2011——基于总体CPI及其八大类构成成分视角的实证检验[J]. 金融研究,2012(10):46-59
[5] 吕光明,于学霆,徐曼. 多方法改进视角下的中国核心通货膨胀测算和效果评价[J]. 统计研究,2014(5):41-47
[6] 吕光明,于学霆. 我国食品上涨对总体价格影响的“二轮效应”分析[J]. 经济统计学(季刊),2016(2):102-113
[7] 解瑶姝,刘金全. 中国通货膨胀动态特征及其政策启示[J]. 南开经济研究,2017(5):3-17
[8] 王少平,朱满洲,程海星. 中国通胀分类指数的波动源及其性质[J]. 管理世界,2012(8):5-14
[9] 王宇,李季. 持续性加权核心通货膨胀的测度及其货币政策涵义[J]. 国际金融研究,2012(4):24-31
[10] 徐强,陈华超. 基于波动性-持续性的中国核心CPI测算及其评估[J]. 数量经济技术经济研究,2017(4):92-109
[11] 张成思. 中国通胀惯性特征与货币政策启示[J]. 经济研究,2008(2):33-43
[12] 赵昕东,汤丹. 基于CPI分项目价格指数的中国核心通货膨胀估计及政策选择研究[J]. 统计研究,2012(7):31-36
[13] 中国人民银行课题组,杜金富. 通货膨胀测度与货币政策[J]. 经济学动态,2011(6):63-68
[14] Altissimo F,Mojon B,Zaffaroni P.Can Aggregation Explain the Persistence of Inflation?[J]. Journal of Monetary Economics,2009,56(2):231-241
[15] Bai J,Ng S.Determining the Number of Primitive Shocks in Factor Models[J]. Journal of Business & Economic Statistics,2007,25(1):52-60
[16] Boivin J,Giannoni M P,Mihov I.Sticky Prices and Monetary Policy:Evidence from Disaggregated US Data[J]. Social Science Electronic Publishing,2009,99(1):350-384
[17] Clark,T.Disaggregate Evidence on the Persistence of Consumer Price Inflation[J]. Journal of Applied Econometrics,2006,21(5):563-587
[18] Doz C,Reichlin L.A Quasi-Maximum Likelihood Approach for Large,Approximate Dynamic Factor Models[J]. Social Science Electronic Publishing,2012,94(4):1014-1024
[19] Forni M,Hallin M,Lippi M,et al.The Generalized Dynamic Factor Model:One-Sided Estimation and Forecasting[J]. Computing in Economics & Finance,2003,100(100):830-840
[20] Hansen,B.The Grid Bootstrap and the Autoregressive Model[J]. The Review of Economics and Statistics,1999,81(4):94-607
[21] Khan M,Morel L,Sabourin P.The Common Component of CPI:An Alternative Measure of Underlying Inflation for Canada[J]. Bulletin of the Menninger Clinic,2013,50(3):257-68
[22] Koopman S J,Mesters G.Empirical Bayes Methods for Dynamic Factor Models[J]. Ssrn Electronic Journal,2014,1(6):157-162
[23] Kose M A,Otrok C,Whiteman C H.International Business Cycles:World,Region,and Country-Specific Factors[J]. American Economic Review,2003,93(4):1216-1239
[24] Stock J H,Watson M W. Dynamic Factor Models,Factor-Augmented Vector Autoregressions,and Structural Vector Autoregressions in Macroeconomics[J]. Handbook of Macroeconomics,2016
[25] Wynne,M.A.Core Inflation:A Review of Some Conceptual Issures[R]. ECB Working Paper Series,No.5,1999
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