Adjustment of U.S. Merchandise Trade Data
For Price Change
Prepared by Foreign Trade Division
U.S. Bureau of the Census
March 2004
1
Landefeld, J. Steven and Robert P. Parker. “Preview of the Comprehensive
Revision of the National Income and Product Accounts: Bea”s New Featured measures of
Output and Prices”. Survey of Current Business (July 1995): 1-38.
2
Introduction
The U.S. Census Bureau (Census) introduced a new constant dollar series (2000 = 100) in the
April 2003 release of the FT900, “U.S. International Trade in Goods and Services”. The fixed-
weighted series, published since 1990, was discontinued at that time. This paper explains the
chained Fisher methodology, its benefits, and where additional information on the chained Fisher
methodology can be found.
Census adopted the new chained Fisher methodology to improve the quality of the data series
and restore the consistency of the Census Bureau’s constant dollar (real) data with the Bureau of
Economic Analysis’s (BEA) National Income and Product Accounts (NIPA), as required by the
Omnibus Trade and Competitiveness Act of 1988. The chained Fisher methodology improved
the quality of the series by eliminating the substitution bias, that is, the tendency of fixed-
weighted series to misstate growth as one moves further from the base year . This tendency
reflects the fact that the commodities, for which output grows rapidly, tend to be those for which
prices increase less than average or decline. Elimination of the substitution bias was the driving
force behind BEA’s adoption of the chained Fisher methodology.1
The Fisher index consists of two components, the Paasche and Laspeyres indexes. The Paasche
index uses weights based upon the month for which the index is calculated. The Laspeyres
index is base-weighted, so the quantity of the previous month provides the weights. The primary
weakness of the Paasche and Laspeyres indexes is the substitution bias. The chained Fisher
methodology brings the two indexes together in the form of a geometric