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Using The Yield Curve To Forecast Economic Growth
Journal of Forecasting ( IF 2.627 ) Pub Date : 2020-03-19 , DOI: 10.1002/for.2676
Parley Ruogu Yang 1
Affiliation  

This paper finds the yield curve to have a well‐performing ability to forecast the real gross domestic product growth in the USA, compared to professional forecasters and time series models. Past studies have different arguments concerning growth lags, structural breaks, and ultimately the ability of the yield curve to forecast economic growth. This paper finds such results to be dependent on the estimation and forecasting techniques employed. By allowing various interest rates to act as explanatory variables and various window sizes for the out‐of‐sample forecasts, significant forecasts from many window sizes can be found. These seemingly good forecasts may face issues, including persistent forecasting errors. However, by using statistical learning algorithms, such issues can be cured to some extent. The overall result suggests, by scientifically deciding the window sizes, interest rate data, and learning algorithms, many outperforming forecasts can be produced for all lags from one quarter to 3 years, although some may be worse than the others due to the irreducible noise of the data.

中文翻译:

使用收益率曲线预测经济增长

与专业预测者和时间序列模型相比,本文发现收益率曲线在预测美国实际国内生产总值增长方面表现良好。过去的研究对增长滞后、结构性断裂以及最终收益率曲线预测经济增长的能力有不同的争论。本文发现此类结果取决于所采用的估计和预测技术。通过允许各种利率作为样本外预测的解释变量和各种窗口大小,可以找到来自许多窗口大小的重要预测。这些看似不错的预测可能会面临问题,包括持续的预测错误。但是,通过使用统计学习算法,可以在一定程度上解决此类问题。总体结果表明,
更新日期:2020-03-19
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