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Point and Density Forecasting of Macroeconomic and Financial Uncertainties of the United States
Journal of Forecasting ( IF 2.627 ) Pub Date : 2020-12-15 , DOI: 10.1002/for.2740
Afees A. Salisu 1 , Rangan Gupta 2 , Ahamuefula E. Ogbonna 3
Affiliation  

We forecast macroeconomic and financial uncertainties of the US over the period of 1960:Q3 to 2018:Q4, based on a large data set of 303 predictors using a wide array of constant parameter and time varying models. We find that uncertainty is indeed forecastable, but while accurate point forecasts can be achieved without incorporating time-variation in the parameters of the small-scale models for macroeconomic uncertainty and large-scale models for financial uncertainty, it is indeed a requirement, along with a large data set, when producing precise density forecasts for both types of uncertainties.

中文翻译:

美国宏观经济和金融不确定性的点和密度预测

我们基于包含 303 个预测变量的大型数据集,使用各种恒定参数和时变模型预测了 1960 年第三季度至 2018 年第四季度期间美国的宏观经济和金融不确定性。我们发现不确定性确实是可以预测的,但是虽然可以在不将时间变化纳入宏观经济不确定性小规模模型和金融不确定性大规模模型的参数中的情况下实现准确的点预测,但这确实是一个要求,以及一个大型数据集,在为两种类型的不确定性生成精确的密度预测时。
更新日期:2020-12-15
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