Use of Ratios for Estimation of Official Statistics at a Statistical Agency
by James R. Knaub, Jr.
The US Energy Information Administration (EIA) has made good use of available auxiliary data over a
number of years, for a variety of surveys on energy sources and consumption, for estimating the
statistics that the EIA mission requires. Such use of already available data reduces data collection
burden for a given level of accuracy. Many of these instances relate to a single auxiliary variable,
and involve some type of ratio. The many uses of ratios at the EIA are both disparate and unifying:
disparate in that the applications can appear to be fairly distinct, but unifying in that there are
interrelationships between these methods that may be esthetically pleasing, and of practical importance.
Better communication and future improvements may be achieved by considering what is different between
these methods, and what they have in common. Here we will explore these ideas.
Classical ratio estimator (CRE), model-based estimation, design-based estimation, chain ratio-type
estimator, alternative ratio models, regression through the origin, regression weights, survey design
weights, calibration weights, raking, price
James R. Knaub, Jr., Knaub1977@comcast.net
Richard G. Graf, email@example.com
READING THE ARTICLE: You can read the article in
portable document (.pdf) format (672462 bytes.)
NOTE: The content of this article is the intellectual property of the authors, who retains all rights to future publication.
This page has been accessed 1947 times since May 25, 2012.
(There is an ADENDDUM to this article submitted 6/10/13): You can read the article in
portable document (.pdf) format
Return to the Home Page.