Measuring Uncertainty about Long-Run Prediction

Ulrich Mueller and Mark Watson

No 18870, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: 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.

JEL-codes: C22 C53 E17 (search for similar items in EconPapers)
Date: 2013-03
New Economics Papers: this item is included in nep-for
Note: AP EFG ME
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Published as Ulrich K. Müller & Mark W. Watson, 2016. "Measuring Uncertainty about Long-Run Predictions," The Review of Economic Studies, vol 83(4), pages 1711-1740.

Downloads: (external link)
http://www.nber.org/papers/w18870.pdf (application/pdf)

Related works:
Journal Article: Measuring Uncertainty about Long-Run Predictions (2016)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nbr:nberwo:18870

Ordering information: This working paper can be ordered from
http://www.nber.org/papers/w18870

Access Statistics for this paper

More papers in NBER Working Papers from National Bureau of Economic Research, Inc National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.. Contact information at EDIRC.
Bibliographic data for series maintained by ().