Template-Type: ReDIF-Paper 1.0
Title: Temporal Aggregation of an Econometric Equation
Author-Name: Ruist, Erik
Author-Workplace-Name: Stockholm School of Economics
Author-Workplace-Postal: Stockholm School of Economics, Box 6501, SE-113 83 
    Stockholm, Sweden
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
Creation-Date: 1996-10-01
Length: 48 pages
Series: Working Paper
Number: 52
Handle: RePEc:hhs:nierwp:0052
