实体经济中的石油价格

Pub Date : 2023-05-21 DOI:10.1002/jae.2986
Haicheng Shu, Peter Spencer
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引用次数: 0

摘要

本文提出了美国经济和石油现货及期货市场的宏观金融模型。通过使用卡尔曼滤波对代表通货膨胀渐近线、实际石油价格和期货曲线斜率的潜在变量进行建模,大大提高了模型的性能。我们发现,这些都是由观察到的期货价格的创新所主导的,反映了市场预期的重要性。使用卡尔曼滤波来捕捉通胀冲击有助于解决臭名昭著的价格难题,即利率上升的趋势预测了这种发展,显然会导致通胀。期货价格还取决于风险溢价,我们发现风险溢价是由代表实际油价的潜在变量而不是通货膨胀和利率等宏观变量主导的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Oil prices in the real economy

This paper presents a macro-finance model of the US economy and the spot and futures markets for oil. The performance of the model is greatly enhanced by using the Kalman filter to model latent variables representing the inflation asymptote, the real price of oil and the slope of the futures curve. We find that these are dominated by innovations in observed futures prices, reflecting the importance of market expectations. Using the Kalman filter to capture inflationary shocks helps solve the notorious price puzzle, the tendency for increases in interest rates to anticipate such developments and apparently cause inflation. Futures prices also depend upon risk premiums, which we find are dominated by the latent variable representing the real oil price rather than macro variables like inflation and interest rates.

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