TY - JOUR
AU - MÃ¼ller,Ulrich K.
AU - Stock,James H.
TI - Forecasts in a Slightly Misspecified Finite Order VAR
JF - National Bureau of Economic Research Working Paper Series
VL - No. 16714
PY - 2011
Y2 - January 2011
DO - 10.3386/w16714
UR - http://www.nber.org/papers/w16714
L1 - http://www.nber.org/papers/w16714.pdf
N1 - Author contact info:
Ulrich Mueller
Department of Economics
Princeton University
Princeton, NJ 08544-1013
E-Mail: umueller@princeton.edu
James H. Stock
Department of Economics
Harvard University
Littauer Center M26
Cambridge, MA 02138
Tel: 617/496-0502
Fax: 617/495-7730
E-Mail: James_Stock@harvard.edu
AB - We propose a Bayesian procedure for exploiting small, possibly long-lag linear predictability in the innovations of a finite order autoregression. We model the innovations as having a log-spectral density that is a continuous mean-zero Gaussian process of order 1/√T. This local embedding makes the problem asymptotically a normal-normal Bayes problem, resulting in closed-form solutions for the best forecast. When applied to data on 132 U.S. monthly macroeconomic time series, the method is found to improve upon autoregressive forecasts by an amount consistent with the theoretical and Monte Carlo calculations.
ER -