Is More Information a Good Thing? Bias Nonmonotonicity in Stochastic Difference Equations

10 Pages Posted: 27 Sep 2000 Last revised: 15 Jan 2012

See all articles by Karim M. Abadir

Karim M. Abadir

Imperial College Business School

Kaddour Hadri

Durham Business School

Abstract

It is shown that the bias of estimated parameters in autoregressive models can increase as the sample size grows. This bias is also a nonmonotonic function of the largest autoregressive root, contrary to what asymptotic approximations had indicated so far in the literature. These unusual results are due to the effect of the initial sample observations that are typically neglected in theoretical asymptotic analysis, in spite of their empirical relevance. Implications for practical economic modelling are considered, including a comparison of the likely inaccuracies of parameter estimates in alternative models based on competing macroeconomic theories.

JEL Classification: C10

Suggested Citation

Abadir, Karim M. and Hadri, Kaddour, Is More Information a Good Thing? Bias Nonmonotonicity in Stochastic Difference Equations. Bulletin of Economic Research, Vol. 52, Issue 2. Available at SSRN: https://ssrn.com/abstract=231648

Karim M. Abadir (Contact Author)

Imperial College Business School ( email )

South Kensington Campus
Exhibition Road
London SW7 2AZ, SW7 2AZ
United Kingdom

HOME PAGE: http://www3.imperial.ac.uk/portal/page?_pageid=61,629646&_dad=portallive&_schema=PORTALLIVE

Kaddour Hadri

Durham Business School ( email )

Mill Hill Lane
Durham, Durham DH1 3LB
United Kingdom

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