An Integrated Model of the Data Measurement and Data Generation Processes with an Application to Consumers' Expenditure

K D Patterson

Economic Journal, 1995, vol. 105, issue 428, 54-76

Abstract: An integrated model is defined as one that not only models the data generation process (DGP) but also models the data measurement process. A natural framework for such an integrated model is the state space approach, with the optimal combination of preliminary vintages of data and predictions from the data generation process model being obtained by application of the Kalman filter. The author shows that substantial reductions in the mean square error of preliminary vintages of data on consumers' expenditure can be obtained from this approach. This provides further evidence that preliminary vintages are not efficient forecasts of the final vintage. Copyright 1995 by Royal Economic Society.

Date: 1995
References: Add references at CitEc
Citations: View citations in EconPapers (23)

Downloads: (external link)
http://links.jstor.org/sici?sici=0013-0133%2819950 ... 0.CO%3B2-G&origin=bc full text (application/pdf)
Access to full text is restricted to JSTOR subscribers. See http://www.jstor.org for details.

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:ecj:econjl:v:105:y:1995:i:428:p:54-76

Ordering information: This journal article can be ordered from
http://www.blackwell ... al.asp?ref=0013-0133

Access Statistics for this article

Economic Journal is currently edited by Martin Cripps, Steve Machin, Woulter den Haan, Andrea Galeotti, Rachel Griffith and Frederic Vermeulen

More articles in Economic Journal from Royal Economic Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing () and Christopher F. Baum ().