**Working Papers, Konjunkturinstitutet - National Institute of Economic Research**
# No 52:

Temporal Aggregation of an Econometric Equation

*Erik Ruist*
**Abstract:** Structural breaks in an economy may make the time period
available for estimation of an econometric equation exceedingly short. To
use the existing information efficiently, it may be profitable to use
high-frequency data, say monthly data, for estimation of a particular
equation, even if the rest of the model is expressed in terms of data of
lower frequency, say quarterly or half-yearly. In order to be included in
the model, this equation has to be transformed to the same data frequency
as the rest of the model. If the variables are of different types, or if
some of the variables are lagged, exact transformations to equations that
produce equivalent predicted values of the dependent variable are not
possible. This note gives approximations and estimates for the varoius
terms of the equations. Linear interpolation estimates as well as estimates
that are optimal in a certain sense are given for the case of aggregation
of monthly variables to semi-annual ones. It turns out that in the exchange
rate equation in the KOSMOS model, the approximations do not increase the
equation error substantially.

**Keywords:** Short time series; Structural breaks; Temporal aggregation; (follow links to similar papers)

48 pages, October 1, 1996

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