价格压力的衡量标准

Laura Jackson Young, Kevin L. Kliesen, Michael T. Owyang
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引用次数: 7

摘要

美联储投入了大量资源来预测关键的经济变量,如实际国内生产总值增长、就业和通货膨胀。这些变量的前景对企业和金融市场参与者也非常重要。作者提出了一个因子增强贝叶斯向量自回归预测模型,该模型显著优于基准随机游走模型和纯时间序列模型。然后,他们在有序概率模型中使用这些因素来开发12个月范围内的概率分布。一个分布评估了明年通货膨胀超过2.5%的可能性;他们把这种可能性称为价格压力指标。这一价格压力指标将为政策制定者和市场提供一种定量评估未来12个月平均通胀率高于美联储2%长期通胀目标的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Measure of Price Pressures
The Federal Reserve devotes significant resources to forecasting key economic variables such as real gross domestic product growth, employment, and inflation. The outlook for these variables also matters a great deal to businesses and financial market participants. The authors present a factor-augmented Bayesian vector autoregressive forecasting model that significantly outperforms both a benchmark random walk model and a pure time-series model. They then use these factors in an ordered probit model to develop the probability distribution over a 12-month horizon. One distribution assesses the probability that inflation will exceed 2.5 percent over the next year; they term this probability a price pressure measure. This price pressure measure would provide policymakers and markets with a quantitative assessment of the probability that average inflation over the next 12 months will be higher than the Fed’s long-term inflation target of 2 percent.
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