Integrating expenditure and income data: what to do with the statistical discrepancy?

Eric Bartelsman and J. Joseph Beaulieu

No 2004-39, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)

Abstract: The purpose of this paper is to build consistent, integrated datasets to investigate whether various disaggregated data can shed light on the possible sources of the statistical discrepancy. Our strategy is first to use disaggregated data to estimate consistent sets of input-output models that sum to either GDP or GDI and compare the two in order to see where the discrepancy resides. We find a few \"problem\" industries that appear to explain most of the statistical discrepancy. Second, we explore what combination of the expenditure data and the income data seem to produce the most sensible data according to a few economic criteria. A mixture of data that do not aggregate either to GDP or to GDI appears optimal.

Keywords: Gross domestic product; Statistical methods; Income (search for similar items in EconPapers)
Date: 2004
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.federalreserve.gov/pubs/feds/2004/200439/200439abs.html (text/html)
http://www.federalreserve.gov/pubs/feds/2004/200439/200439pap.pdf (application/pdf)

Related works:
Chapter: Integrating Expenditure and Income Data: What to Do with the Statistical Discrepancy? (2006)
Working Paper: Integrating Expenditure and Income Data: What to do with the Statistical Discrepancy? (2004)
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:fip:fedgfe:2004-39

Access Statistics for this paper

More papers in Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.) Contact information at EDIRC.
Bibliographic data for series maintained by Ryan Wolfslayer ; Keisha Fournillier ().