全球智库信息集成服务系统(G2TT): Dynamic Prediction Pools: An Investigation of Financial Frictions and Forecasting Performance

G2TT

来源类型	Working Paper
规范类型	报告
DOI	10.3386/w20575
来源ID	Working Paper 20575
	Dynamic Prediction Pools: An Investigation of Financial Frictions and Forecasting Performance
	Marco Del Negro; Raiden B. Hasegawa; Frank Schorfheide
发表日期	2014-10-13
出版年	2014
语种	英语
摘要	We provide a novel methodology for estimating time-varying weights in linear prediction pools, which we call Dynamic Pools, and use it to investigate the relative forecasting performance of DSGE models with and without financial frictions for output growth and inflation from 1992 to 2011. We find strong evidence of time variation in the pool's weights, reflecting the fact that the DSGE model with financial frictions produces superior forecasts in periods of financial distress but does not perform as well in tranquil periods. The dynamic pool's weights react in a timely fashion to changes in the environment, leading to real-time forecast improvements relative to other methods of density forecast combination, such as Bayesian Model Averaging, optimal (static) pools, and equal weights. We show how a policymaker dealing with model uncertainty could have used a dynamic pools to perform a counterfactual exercise (responding to the gap in labor market conditions) in the immediate aftermath of the Lehman crisis.
主题	Econometrics ; Estimation Methods ; Macroeconomics ; Business Cycles
URL	https://www.nber.org/papers/w20575
来源智库	National Bureau of Economic Research (United States)
引用统计
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/578249
推荐引用方式 GB/T 7714	Marco Del Negro,Raiden B. Hasegawa,Frank Schorfheide. Dynamic Prediction Pools: An Investigation of Financial Frictions and Forecasting Performance. 2014.