赣审动态

时事聚焦。1月CPI同比上涨5.4%,涨幅比上月扩大0.9个百分点。国家统计局今天发布了2020年1月份全国CPI(居民消费价格指数)和PPI(工业生产者出厂价格指数)数据。从环比看,CPI由上月持平转为上涨1.4%,主要是受春节及新型冠状病毒感染的肺炎疫情因素影响。     

我国金融数据高频收益率波动结构突变的检测研究

本文基于Lavielle和Teyssière(2005)提出的惩罚对照函数,对我国上证综指自2005年7月1日至2010年6月30日的5分钟收益率序列,及其已实现波动进行波动结构变点检测,结果发现有两个结构变点。针对这两个结构变点,本文采用了HAR-RV-J模型对其已实现波动进行分段建模,研究不同期限的投资者对股市波动的影响作用。实证分析的结果表明结构突变发生的时间均能与相应的重大经济事件相对应,而且随着时间的推移,短期投资者对股市波动的影响逐渐加大。     

谨防工业萧条

PPI连续5个月出现同比负增长,是否意味着中国由通胀转入通缩局面?"高通胀、高增速"渐渐远去,中国经济似乎又将面临通货紧缩风险。据国家统计局公布的7月宏观经济数据,消费者物价指数(CPI)同比上涨1.8%,连续4个月同比下滑,且低于3%的通胀警戒线;生产者物价指数(PPI)同比下降2.9%,环比下降0.8%,已连续5个月出现同     

数据

1．8％：7月份CPI同比降幅 国家统计局近日发布的数据显示．7月份,我国居民消费价格指数（CPI）同比下降18％,环比出现了4月份以来的首次持平。同期,工业品出厂价格（PPI）同比下降82％,环比上涨1％,环比已连续4个月上涨。     

邯郸市PPI变化对CPI的影响研究

本文从工业生产者出厂价格指数(PPI)波动对CPI的影响角度,运用一般经济学理论,采用定量分析与定性分析相结合的方法,剖析了PPI与CPI之间的内在关系,探究PPI对CPI的影响程度及影响方式;从历史演变的角度,分析了PPI与CPI之间的传导关系、PPI对CPI影响的着力点及邯郸市PPI与CPI之间的变动关系。     

通胀形势凸显经济深层次矛盾

3月份宏观经济数据再次凸显中国经济深层次调整的巨大压力。一面是生产价格指数(PPI)在28个月以来首现负增长,一面却是消费价格指数(CPI)同比上涨3.6%,PPI与CPI之间的"价格差"越拉越大。PPI的负增长表面,实体经济需求不足,企业难以把上游的成本     

资讯

正数字NUMBERGDP二季度同比增长7.6%7月13日,国家统计局公布,今年上半年我国国内生产总值(G D P)为22.7098万亿元,同比增长7.8%,其中第二季度增长7.6%,是自2009年第二季度以来我国经济增速首次跌破8%。CPI同比上涨2.2%据统计局公布,6月份CPI(全国居民消费价格总水平)为2.2%,同比涨幅创下了自2010年2月份以来29个月的新低。PPI(全国工业生产者出厂价格)同比下降2.1%,显示实体经济情况依然不乐观。     

总体经验模式分解视角下的PPI与CPI波动特征及传导关系研究

本文采用总体经验模式分解（EEMD）和计量分析的方法,对国内PPI和CPI的波动特征和传导关系进行了深入研究。结果显示,二者均由高频分量、低频分量和趋势项构成,其中,高频分量体现的是国内物价中随机波动的信息;低频分量传递的是一定时期内的物价变动信息;趋势项反映的是物价中不轻易变动的信息。对上述结构分量的Granger因果检验表明,PPI和CPI之间的传导关系主要受低频分量和趋势项影响：低频分量中只存在PPI到CPI的单向因果关系;而在趋势项中存在不对称的传导方式,即在1%的水平上CPI到PPI存在单向因果关系,在5%的水平上二者互为因果。     

通胀渐显影催逼新调控

10月22日，统计局发布三季度统计数据，数据显示，今年前三个季度，居民消费价格指数（CPI）同比累计下降1，1％，工业品出厂价格指数（PPI）累计下降6．5％。但CPI自从7月环比持平之后。8月、9月都出现了环比上涨。截至9月，PPI环比连续7个月上涨。三季度GDP增速达8．9％。主要统计数据基本都在业界预期之内，但在无惊无险的新统计数字背后，却依然没有解决中国经济发展的老问题。     

基于VAR模型的CPI和PPI实证研究

文章选取了中国2005年1月至2016年12月的CPI和PPI的月度数据,建立VAR模型,并通过格兰杰因果检验和脉冲响应含函数,发现滞后PPI的第1～9期对CPI有显著的影响,其中滞后1～4期CPI对PPI也有影响。方差分解的结果表明,居民消费价格指数的变动80%是由本身引起的,20%是由工业品出厂价格指数引起的;工业品出厂价格指数变动40%是由居民消费价格指数引起的,60%是由自身引起的。     

Testing Integration of Macroeconomic Time Series in Transitional Socialist Economies. A Modification of Perron Test

The presence of structural breaks reduces the power of integration tests. A number of methods were suggested to improve the statistical properties of integration tests in the presence of structural breaks. The most known are Perron tests, which allow to test for the level of integration of time series with one structural break. Perron tests allow for two types of structural breaks: additive outlier an innovative outlier. These tests are, however, not very useful in testing the level of integration of macroeconomic time series in countries in transition from centrally-planned to market economy. In such case one should expect two structural breaks to affect the time series: one at the beginning and one at the end of the transformation process. Test that allows for two additive outlier type structural breaks in time series is developed in this paper. This test has superior power as compared to standard Dickey-Fuller and Perron tests. This paper provides asymptotic distribution as well as finite sample properties of proposed test. Therefore practitioners receive a reliable tool for analyzing macroeconomic processes in transitional economies. This revised version was published online in July 2006 with corrections to the Cover Date.     

Forecasting inflation using commodity price aggregates

This paper shows that for five small commodity-exporting countries that have adopted inflation targeting monetary policies, world commodity price aggregates have predictive power for their CPI and PPI inflation, particularly once possible structural breaks are taken into account. This conclusion is robust to using either disaggregated or aggregated commodity price indexes (although the former perform better), the currency denomination of the commodity prices, and to using mixed-frequency data. In pseudo out-of-sample forecasting, commodity indexes outperform the random walk and AR(1) processes, although the improvements over the latter are sometimes modest.     

通货膨胀国际间传导对我国影响的实证检验

本文运用时间序列分析方法,实证检验了欧盟和美国的价格冲击向我国传导的总体效应.实证结果表明,各国物价存在明显的协整关系,脉冲响应分析和方差分解的结论进一步刻画了外国通胀冲击的特征.协整变结构检验证实了近年来通货膨胀国际传导效应显著增强.本文还利用格兰杰因果检验,考察了通货膨胀的各条跨国传导路径,研究发现,消费品和原材料价格传导路径非常通畅,而通过国际储备影响货币供应量的传导渠道,以及总供给-总需求传导渠道不能得到实证支持.     

What is the globalisation of inflation?

This paper studies the globalisation of CPI inflation by analysing core, energy and food components, testing for structural breaks in the relationships between domestic inflation and a corresponding country-specific foreign inflation series at the monthly frequency for OECD countries. The iterative methodology employed separates coefficient and variance breaks, while also taking account of outliers. We find that the overall pattern of globalisation in aggregate inflation is largely driven by convergence of the mean levels of the core component from the early 1990s, compatible with the introduction of inflation targeting in many countries of our sample. There is less evidence of increased synchronisation of shortrun movements in core than aggregate inflation, but an increased role for shortrun foreign energy inflation often contributes to the globalisation effect.     

Structural breaks and GARCH models of exchange rate volatility

We investigate the empirical relevance of structural breaks for GARCH models of exchange rate volatility using both in‐sample and out‐of‐sample tests. We find significant evidence of structural breaks in the unconditional variance of seven of eight US dollar exchange rate return series over the 1980–2005 period—implying unstable GARCH processes for these exchange rates—and GARCH(1,1) parameter estimates often vary substantially across the subsamples defined by the structural breaks. We also find that it almost always pays to allow for structural breaks when forecasting exchange rate return volatility in real time. Combining forecasts from different models that accommodate structural breaks in volatility in various ways appears to offer a reliable method for improving volatility forecast accuracy given the uncertainty surrounding the timing and size of the structural breaks. Copyright © 2008 John Wiley & Sons, Ltd.     

Identifying Changes in Mean,Seasonality, Persistence and Volatility for G7 and Euro Area Inflation*

We propose an iterative decomposition that tests and accounts for multiple structural breaks in the mean, seasonality, dynamics and conditional volatility, while also accounting for outliers. Considering each component separately within each iteration leads to greater flexibility compared with joint procedures. Monte Carlo analysis shows the procedure performs well. Applied to monthly CPI inflation in G7 countries and the Euro area, we uncover mean and seasonality breaks for all countries and, allowing for these, changes in persistence are generally also indicated. Further, volatility reductions are widespread in the early to mid 1980s, with some countries exhibiting increases from 1999 onwards.     

Nonparametric simultaneous testing for structural breaks

In this paper we consider a regression model with errors that are martingale differences. This modeling includes the regression of both independent and time series data. The aim is to study the appearance of structural breaks in both the mean and the variance functions, assuming that such breaks may occur simultaneously in both the functions. We develop nonparametric testing procedures that simultaneously test for structural breaks in the conditional mean and the conditional variance. The asymptotic distribution of an adaptive test statistic is established, as well as its asymptotic consistency and efficiency. Simulations illustrate the performance of the adaptive testing procedure. An application to the analysis of financial time series also demonstrates the usefulness of the proposed adaptive test in practice.     

A SURVEY OF MEASUREMENT BIASES IN PRICE INDEXES

Abstract. This paper reviews the literature on measurement error in the major US price indexes—the Consumer Price Index (CPI), the Producer Price Index (RPI), and the Gross Domestic Product (GDP) deflators. We take as our point of departure Triplett's, 1975, survey and focus on the studies of measurement error that have appeared since then. We review the problems of substitution bias, quality bias, new goods bias, and outlet substitution bias that are generally considered to be the main sources of error in price indexes. The bulk of the paper is devoted to problems in the CPI and PPI, as the GDP deflators tend to be based mainly on the components of these series. We find that there has been surprisingly little work on the problem of overall measurement error in any of these price indexes, and we conclude that there is very little scientific basis for the commonly accepted notion that measured inflation at 2 to 3 percent a year is consistent with price stability.     

Price-wage dynamics in a transition economy: The case of Poland

In this paper we analyse the wage-price relationship of an economy in transition characterized by important structural changes. It is known (see Perron, 1989) that structural breaks in stationary time series can induce apparent unit roots. The stationarity analysis of the series employed in the present model is conducted jointly with the assumption that the breakpoint location is unknown. We follow a testing procedure recently proposed by Zivot and Andrews (1992). Cointegration analysis of wages and prices in the presence of structural breaks finds empirical evidence in favour of two cointegrating vectors involving prices and wages. Our analysis focuses on the different structural behaviour of the price-wage dynamic relationship in the short and long term; we also demonstrate the relative importance of import prices as a source of wage-price fluctuations.     

基于我国CPI时间序列的神经网络预测模型

近年来,我国的居民消费价格指数涨幅屡创新高。根据我国1990年-2008年的CPI时间序列,首先利用时间序列分析方法确定输入向量,然后应用改进BP算法的人工神经网络分别预测出2011年和2012年我国CPI将分别为104.9和105.2,实验结果证实了BP神经网络模型用于CPI预测的准确性和可行性。