我们应该多频繁地重新估计DSGE模型?

Marcin Kolasa, Michał Rubaszek
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引用次数: 7

摘要

政策制定机构使用DSGE模型进行预测的一个常见做法是,只是偶尔而不是每次预测都重新估计它们。在本文中,我们询问这种做法如何影响基于DSGE模型的预测的准确性。为此,我们使用了一个典型的中等规模新凯恩斯模型,并比较了其对美国经济的季度实时预测如何随着连续重新估计的间隔而变化。我们发现,每年只更新一次模型参数通常不会导致点预测精度的显著下降。另一方面,如果对密度预测的质量感兴趣,增加重新估计的频率会有一些好处。
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How Frequently Should We Re-Estimate DSGE Models?
A common practice in policy making institutions using DSGE models for forecasting is to re-estimate them only occasionally rather than every forecasting round. In this paper we ask how such a practice affects the accuracy of DSGE model-based forecasts. To this end we use a canonical medium-sized New Keynesian model and compare how its quarterly real-time forecasts for the US economy vary with the interval between consecutive re-estimations. We find that updating the model parameters only once a year usually does not lead to any significant deterioration in the accuracy of point forecasts. On the other hand, there are some gains from increasing the frequency of re-estimation if one is interested in the quality of density forecasts.
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