英文标题：
《Inflation, unemployment, and labour force. Phillips curves and long-term
  projections for Austria》
---
作者：
Ivan Kitov, Oleg Kitov
---
最新提交年份：
2013
---
英文摘要：
  We model the rate of inflation and unemployment in Austria since the early 1960s within the Phillips/Fisher framework. The change in labour force is the driving force representing economic activity in the Phillips curve. For Austria, this macroeconomic variable was first tested as a predictor of inflation and unemployment in 2005 with the involved time series ended in 2003. Here we extend all series by nine new readings available since 2003 and re-estimate the previously estimated relationships between inflation, unemployment, and labour force. As before, a structural break is allowed in these relationships, which is related to numerous changes in definitions in the 1980s. The break year is estimated together with other model parameters by the Boundary Element Method with the LSQ fitting between observed and predicted integral curves. The precision of inflation prediction, as described by the root-mean-square (forecasting) error is by 20% to 70% better than that estimated by AR(1) model. The estimates of model forecasting error are available for those time series where the change in labour force leads by one (the GDP deflator) or two (CPI) years. For the whole period between 1965 and 2012 as well as for the intervals before and after the structural break (1986 for all inflation models) separately, our model is superior to the na\\\"ive forecasting, which in turn, is not worse than any other forecasting model. The level of statistical reliability and the predictive power of the link between inflation and labour force imply that the National Bank of Austria does not control inflation and unemployment beyond revisions to definitions. The labour force projection provided by Statistic Austria allows foreseeing inflation at a forty-year horizon: the rate of CPI inflation will hover around 1.3% and the GDP deflator will likely sink below zero between 2018 and 2034.
---
中文摘要：
我们在菲利普斯/费舍尔框架内对奥地利自20世纪60年代初以来的通货膨胀率和失业率进行了建模。劳动力的变化是菲利普斯曲线中代表经济活动的驱动力。对奥地利来说，这一宏观经济变量在2005年首次作为通货膨胀和失业的预测指标进行了测试，相关时间序列于2003年结束。在这里，我们通过2003年以来提供的九个新读数来扩展所有系列，并重新估计之前估计的通货膨胀、失业和劳动力之间的关系。和以前一样，这些关系中允许出现结构性断裂，这与20世纪80年代定义的许多变化有关。利用边界元法，在观测到的积分曲线和预测的积分曲线之间进行LSQ拟合，并结合其他模型参数，估计出断裂年。由均方根（预测）误差描述的通货膨胀预测精度比AR（1）模型估计的精度高20%到70%。对于劳动力变化领先一年（GDP平减指数）或两年（CPI）的时间序列，可以使用模型预测误差估计值。在1965年至2012年的整个时期内，以及结构突变前后的时间间隔内（所有通胀模型均为1986年），我们的模型优于na\\“反过来，ive预测并不比任何其他预测模型差。统计可靠性的水平和通货膨胀与劳动力之间联系的预测能力意味着奥地利国家银行对通货膨胀和失业的控制不超过定义的修订。奥地利统计局提供的劳动力预测允许在一定程度上预测通货膨胀第三年：2018年至2034年间，CPI通胀率将徘徊在1.3%左右，GDP平减指数可能降至零以下。
---
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：
-->