全球智库信息集成服务系统(G2TT): Measuring Uncertainty about Long-Run Prediction

G2TT

来源类型	Working Paper
规范类型	报告
DOI	10.3386/w18870
来源ID	Working Paper 18870
	Measuring Uncertainty about Long-Run Prediction
	Ulrich Mueller; Mark W. Watson
发表日期	2013-03-08
出版年	2013
语种	英语
摘要	Long-run forecasts of economic variables play an important role in policy, planning, and portfolio decisions. We consider long-horizon forecasts of average growth of a scalar variable, assuming that first differences are second-order stationary. The main contribution is the construction of predictive sets with asymptotic coverage over a wide range of data generating processes, allowing for stochastically trending mean growth, slow mean reversion and other types of long-run dependencies. We illustrate the method by computing predictive sets for 10 to 75 year average growth rates of U.S. real per-capita GDP, consumption, productivity, price level, stock prices and population.
主题	Econometrics ; Estimation Methods ; Macroeconomics ; Macroeconomic Models
URL	https://www.nber.org/papers/w18870
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/576545
推荐引用方式 GB/T 7714	Ulrich Mueller,Mark W. Watson. Measuring Uncertainty about Long-Run Prediction. 2013.