Least Squares Estimation of Large Dimensional Threshold Factor Models

56 Pages Posted: 29 Jul 2015 Last revised: 17 Apr 2017

Date Written: November 13, 2016

Abstract

This paper studies large dimensional factor models with threshold-type regime shifts in the loadings. We estimate the threshold by concentrated least squares, and factors and loadings by principal components. The estimator for the threshold is super consistent, with convergence rate that depends on the time and cross-sectional dimensions of the panel, and it does not affect the estimator for factors and loadings: this has the same convergence rate as in linear factor models. We propose model selection criteria and a linearity test. Empirical application of the model shows that connectedness in financial variables increases during periods of high economic policy uncertainty.

Keywords: Large Threshold Factor Model, Least Squares Estimation, Model Selection, Linearity Testing, Connectedness

JEL Classification: C12, C13, C33, C52, G10

Suggested Citation

Massacci, Daniele, Least Squares Estimation of Large Dimensional Threshold Factor Models (November 13, 2016). Available at SSRN: https://ssrn.com/abstract=2636801 or http://dx.doi.org/10.2139/ssrn.2636801

Daniele Massacci (Contact Author)

King's College London ( email )

United Kingdom

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