Forecasting multivariate time series under present-value-model short- and long-run co-movement restrictions

Osmani Guillén, Alain Hecq, João Issler and Diogo Vinícius Menezes Saraiva

No 763, FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) from EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil)

Abstract: Using a sequence of nested multivariate models that are VAR-based, we discuss different layers of restrictions imposed by present-value models (PVM hereafter) on the VAR in levels for series that are subject to present-value restrictions. Our focus is novel - we are interested in the short-run restrictions entailed by PVMs (Vahid and Engle, 1993, 1997) and their implications for forecasting. Using a well-known database, kept by Robert Shiller, we implement a forecasting competition that imposes different layers of PVM restrictions. Our exhaustive investigation of several different multivariate models reveals that better forecasts can be achieved when restrictions are applied to the unrestricted VAR. Moreover, imposing short-run restrictions produces forecast winners 70% of the time for the target variables of PVMs and 63.33% of the time when all variables in the system are considered.

Date: 2015-02-26
New Economics Papers: this item is included in nep-ets and nep-for
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Citations: View citations in EconPapers (5)

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Related works:
Journal Article: Forecasting multivariate time series under present-value model short- and long-run co-movement restrictions (2015)
Working Paper: Forecasting Multivariate Time Series under Present-Value-Model Short- and Long-run Co-movement Restrictions (2014)
Working Paper: Forecasting multivariate time series under present-value-model short- and long-run co-movement restrictions (2013)
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