Regression over Timescale Decompositions: A Sampling Analysis of Distributional Properties

James Ramsey

Economic Systems Research, 1999, vol. 11, issue 2, 163-184

Abstract: In two previous papers, Ramsey and Lampart demonstrated that regression analyses between timescale decompositions provided important insight into the properties of economic relationships. The idea in those papers was that the relationship between any two variables, say consumption and income, was the union of the individual relationships between consumption and income at each timescale and that the regression relationship might, differ across timescales. This paper is dedicated to discovering the approximate distributional properties of the regression estimators and of the residuals in the context of such models. Sampling procedures are used to verify the distributional properties of the regression estimators at each timescale and those of the residuals. This analysis is necessary to provide the appropriate distributional information required to specify tests of hypotheses and confidence intervals.

Keywords: Timescale; wavelets; consumption function; income velocity (search for similar items in EconPapers)
Date: 1999
References: View complete reference list from CitEc
Citations: View citations in EconPapers (16)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/09535319900000012 (text/html)
Access to full text is restricted to subscribers.

Related works:
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:taf:ecsysr:v:11:y:1999:i:2:p:163-184

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CESR20

DOI: 10.1080/09535319900000012

Access Statistics for this article

Economic Systems Research is currently edited by Bart Los and Manfred Lenzen

More articles in Economic Systems Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().