DSGE Forecasts of the Lost Recovery

Michael D Cai, Marco Del Negro, M. Giannoni, Abhijit Sen Gupta, Pearl Li, Erica Moszkowski
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引用次数: 24

Abstract

The years following the Great Recession were challenging for forecasters. Unlike other deep downturns, this recession was not followed by a swift recovery, but instead generated a sizable and persistent output gap that was not accompanied by deflation as a traditional Phillips curve relationship would have predicted. Moreover, the zero lower bound and unconventional monetary policy generated an unprecedented policy environment. We document the actual real-time forecasting performance of the New York Fed dynamic stochastic general equilibrium (DSGE) model during this period and explain the results using the pseudo real-time forecasting performance results from a battery of DSGE models. We find the New York Fed DSGE model’s forecasting accuracy to be comparable to that of private forecasters, and notably better for output growth than the median forecasts from the FOMC’s Summary of Economic Projections. The model’s financial frictions were key in obtaining these results, as they implied a slow recovery following the financial crisis.
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DSGE对失去的复苏的预测
大衰退(Great Recession)之后的几年对预测者来说充满挑战。与以往的深度衰退不同,这次衰退之后并没有出现迅速复苏,而是产生了相当大且持续的产出缺口,而且没有像传统的菲利普斯曲线关系所预测的那样伴随着通缩。此外,零利率下限和非常规货币政策形成了前所未有的政策环境。我们记录了纽约联储动态随机一般均衡(DSGE)模型在此期间的实际实时预测性能,并使用一系列DSGE模型的伪实时预测性能结果来解释结果。我们发现纽约联储DSGE模型的预测精度与私人预测者相当,对产出增长的预测明显优于联邦公开市场委员会经济预测摘要的中位数预测。该模型的金融摩擦是获得这些结果的关键,因为它们暗示了金融危机后的缓慢复苏。
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