Work

Inference on Structural Breaks using Information Criteria

Year: 2013

Type: article

Abstract: This paper investigates the usefulness of information criteria for inference on the number of structural breaks in a standard linear regression model. In particular, we propose a modified penalty function for such criteria, which implies each break is equivalent to estimation of three individual regression coefficients. AMonteCarlo analysis compares information criteria to sequential testing, with the modified Bayesian and Hannan–Quinn criteria performing well overall, for data‐generating processes both without and with breaks. The methods are also used to examine changes inEuro area monetary policy between 1971 and 2007.

Source: Manchester School

DOI: 10.1111/manc.12017

Authors: Alastair R. Hall, Denise R. Osborn, Nikolaos Sakkas

Institutions: University of Manchester, University of Bath

Language: English

Topic: Monetary Policy and Economic Impact

Subfield: General Economics, Econometrics and Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $3,350

Funder: Economic and Social Research Council