Abstract
Robert McClelland (1996) "Evaluating
Formula Bias in Various Indexes Using Simulations."
In response to one of the problems described in Reinsdorf
(1994), the Bureau of Labor Statistics (BLS) has recently
implemented a method to reduce 'formula bias'. This bias
occurs when the BLS estimates a Laspeyres price index in
which the quantity weights are measured in a past 'base
period'. Current estimates of its magnitude rely upon either
educated guesswork or strong parametric assumptions about the
distribution of prices. In this paper I examine the bias of
several different indexes without making the strong
parametric assumptions of previous researchers by using Monte
Carlo simulations. I do this by treating the price quotes
collected by the BLS as a representative population from
which price quotes can be sampled. The estimate of the bias
using the old imputation method is lower than previous
estimates, being about 0.20 points per annum for the
commodities and services component of the CPI. The recently
implemented seasoning method reduces the estimated bias to
about -0.02. Although the bias of an index is sensitive to
the base period of the Laspeyres, the simulations suggest
that an index using seasoning is close to the Laspeyres index
for reasonable definitions of the base period.
Last Modified Date: July 19, 2008
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