The Vector Floor and Ceiling Model

Gary Koop and Simon Potter

No 04/15, Discussion Papers in Economics from Division of Economics, School of Business, University of Leicester

Abstract: This paper motivates and develops a nonlinear extension of the Vector Autoregressive model which we call the Vector Floor and Ceiling model. Bayesian and classical methods for estimation and testing are developed and compared in the context of an application involving U.S. macroeconomic data. In terms of statistical significance both classical and Bayesian methods indicate that the (Gaussian) linear model is inadequate. Using impulse response functions we investigate the economic significance of the statistical analysis. We find evidence of strong nonlinearities in the contemporaneous relationships between the variables and milder evidence of nonlinearity in the conditional mean.

Keywords: Nonlinearity; Bayesian; Vector Autoregression (search for similar items in EconPapers)
JEL-codes: C32 C52 E30 (search for similar items in EconPapers)
Date: 2000-01
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.le.ac.uk/economics/research/RePEc/lec/leecon/dp04-15.pdf (application/pdf)

Related works:
Chapter: The Vector Floor and Ceiling Model (2006)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:lec:leecon:04/15

Ordering information: This working paper can be ordered from
https://www2.le.ac.u ... -1/discussion-papers

Access Statistics for this paper

More papers in Discussion Papers in Economics from Division of Economics, School of Business, University of Leicester School of Business, University of Leicester, University Road. Leicester. LE1 7RH. UK Provider-Homepage: https://le.ac.uk/school-of-business. Contact information at EDIRC.
Bibliographic data for series maintained by Abbie Sleath ().