英文标题：
《Does Banque de France control inflation and unemployment?》
---
作者：
Ivan Kitov, Oleg Kitov
---
最新提交年份：
2013
---
英文摘要：
  We re-estimate statistical properties and predictive power of a set of Phillips curves, which are expressed as linear and lagged relationships between the rates of inflation, unemployment, and change in labour force. For France, several relationships were estimated eight years ago. The change rate of labour force was used as a driving force of inflation and unemployment within the Phillips curve framework. The set of nested models starts with a simplistic version without autoregressive terms and one lagged term of explanatory variable. The lag is determined empirically together with all coefficients. The model is estimated using the Boundary Element Method (BEM) with the least squares method applied to the integral solutions of the differential equations. All models include one structural break might be associated with revisions to definitions and measurement procedures in the 1980s and 1990s as well as with the change in monetary policy in 1994-1995. For the GDP deflator, our original model provided a root mean squared forecast error (RMSFE) of 1.0% per year at a four-year horizon for the period between 1971 and 2004. The rate of CPI inflation is predicted with RMSFE=1.5% per year. For the naive (no change) forecast, RMSFE at the same time horizon is 2.95% and 3.3% per year, respectively. Our model outperforms the naive one by a factor of 2 to 3. The relationships for inflation were successfully tested for cointegration. We have formally estimated several vector error correction (VEC) models for two measures of inflation. At a four year horizon, the estimated VECMs provide significant statistical improvements on the results obtained by the BEM: RMSFE=0.8% per year for the GDP deflator and ~1.2% per year for CPI. For a two year horizon, the VECMs improve RMSFEs by a factor of 2, with the smallest RMSFE=0.5% per year for the GDP deflator.
---
中文摘要：
我们重新估计了一组菲利普斯曲线的统计特性和预测能力，这些曲线表示为通货膨胀率、失业率和劳动力变化之间的线性和滞后关系。对法国来说，八年前就有过几段恋情。在菲利普斯曲线框架内，劳动力变动率被用作通货膨胀和失业的驱动力。嵌套模型集从一个没有自回归项和一个滞后解释变量项的简化版本开始。滞后与所有系数一起由经验确定。模型采用边界元法（BEM）进行估计，并将最小二乘法应用于微分方程的积分解。所有模型都包含一个结构性突破，可能与20世纪80年代和90年代对定义和衡量程序的修订以及1994-1995年货币政策的变化有关。对于GDP平减物价指数，我们最初的模型提供了1971年至2004年期间四年期内每年1.0%的均方根预测误差（RMSFE）。预测CPI通胀率时，RMSFE=每年1.5%。对于原始（无变化）预测，同一时间范围内的RMSFE每年分别为2.95%和3.3%。我们的模型比单纯的模型好2到3倍。通货膨胀关系成功地进行了协整检验。我们已经正式估计了两种通货膨胀指标的向量误差修正（VEC）模型。在四年的时间范围内，估计的向量机对边界元法获得的结果提供了显著的统计改进：GDP平减指数的RMSFE=0.8%，CPI的RMSFE=1.2%。在两年期内，VECM将RMSFE提高了2倍，最小的RMSFE=GDP平减指数每年0.5%。
---
分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：General Finance        一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
--

---
PDF下载：
-->