Bootstrap joint prediction regions

Michael Wolf and Dan Wunderli

No 64, ECON - Working Papers from Department of Economics - University of Zurich

Abstract: Many statistical applications require the forecast of a random variable of interest over several periods into the future. The sequence of individual forecasts, one period at a time, is called a path forecast, where the term path refers to the sequence of individual future realizations of the random variable. The problem of constructing a corresponding joint prediction region has been rather neglected in the literature so far: such a region is supposed to contain the entire future path with a prespecified probability. We develop bootstrap methods to construct joint prediction regions. The resulting regions are proven to be asymptotically consistent under a mild high-level assumption. We compare the finitesample performance of our joint prediction regions to some previous proposals via Monte Carlo simulations. An empirical application to a real data set is also provided.

Keywords: Generalized error rates; path forecast; simultaneous prediction intervals (search for similar items in EconPapers)
JEL-codes: C14 C32 C53 (search for similar items in EconPapers)
Date: 2012-02, Revised 2013-05
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (35)

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Persistent link: https://EconPapers.repec.org/RePEc:zur:econwp:064

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