Forecast Comparison in L2

Departmental Working Papers from Rutgers University, Department of Economics

Abstract: This paper provides a comprehensive framework for comparing predictors of univariate time series in the mean square norm. Initially, the forecast errors are assumed to be unbiased, independent, and normally distributed. Each of these is progressively relaxed. A new heteroscedasticity and autocorrelation consistent statistic for forecast comparison is derived. Finite sample distributions are tabulated in a sequence of Monte Carlo exercises. Power is examined by comparing forecast errors from a moving average model with misspecified autoregressive alternatives.

Keywords: Mean squared prediction error; robust forecast comparison (search for similar items in EconPapers)
JEL-codes: C52 C53 (search for similar items in EconPapers)
Date: Written 1996-08-01
View list of references View citations in EconPapers

Downloads: (external link)
ftp://snde.rutgers.edu/Rutgers/wp/1995-24.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Access Statistics for this paper

More papers in Departmental Working Papers from Rutgers University, Department of Economics
Contact information at EDIRC.
Series data maintained by ().