全球智库信息集成服务系统(G2TT): Comparing Greenbook and Reduced Form Forecasts using a Large Realtime Dataset

G2TT

来源类型	Working Paper
规范类型	报告
DOI	10.3386/w13397
来源ID	Working Paper 13397
	Comparing Greenbook and Reduced Form Forecasts using a Large Realtime Dataset
	Jon Faust; Jonathan H. Wright
发表日期	2007-09-12
出版年	2007
语种	英语
摘要	Many recent papers have found that atheoretical forecasting methods using many predictors give better predictions for key macroeconomic variables than various small-model methods. The practical relevance of these results is open to question, however, because these papers generally use ex post revised data not available to forecasters and because no comparison is made to best actual practice. We provide some evidence on both of these points using a new large dataset of vintage data synchronized with the Fed's Greenbook forecast. This dataset consists of a large number of variables, as observed at the time of each Greenbook forecast since 1979. Thus, we can compare real-time large dataset predictions to both simple univariate methods and to the Greenbook forecast. For inflation we find that univariate methods are dominated by the best atheoretical large dataset methods and that these, in turn, are dominated by Greenbook. For GDP growth, in contrast, we find that once one takes account of Greenbook's advantage in evaluating the current state of the economy, neither large dataset methods nor the Greenbook process offers much advantage over a univariate autoregressive forecast.
主题	Econometrics ; Estimation Methods ; Macroeconomics ; Business Cycles
URL	https://www.nber.org/papers/w13397
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/571069
推荐引用方式 GB/T 7714	Jon Faust,Jonathan H. Wright. Comparing Greenbook and Reduced Form Forecasts using a Large Realtime Dataset. 2007.

条目包含的文件
文件名称/大小	资源类型	版本类型	开放类型	使用许可
w13397.pdf（276KB）	智库出版物		限制开放	CC BY-NC-SA	浏览