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来源类型Working Paper
规范类型报告
DOI10.3386/w18870
来源IDWorking 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
URLhttps://www.nber.org/papers/w18870
来源智库National Bureau of Economic Research (United States)
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资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/576545
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GB/T 7714
Ulrich Mueller,Mark W. Watson. Measuring Uncertainty about Long-Run Prediction. 2013.
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