Inaccurate Approximation in the Modelling of Hyperinflations

Inaccurate Approximation in the Modelling of Hyperinflations In time series macroeconometric models, the first difference in the logarithm of a variable is routinely used to represent the rate of change of that variable. It is often overlooked that the assumed approximation is accurate only if the rates of change are small. Models of hyper-inflation are a case in point, since in these models, by definition, changes in price are large. In this letter, Cagan’s model is applied to Hungarian hyper-inflation data. It is then demonstrated that use of the approximation in the formation of the price inflation variable is causing an upward bias in the model’s key parameter, and therefore an exaggeration of the effect postulated by Cagan. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

Inaccurate Approximation in the Modelling of Hyperinflations

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Publisher
Kluwer Academic Publishers
Copyright
Copyright © 2006 by Springer
Subject
Social Sciences; Methodology of the Social Sciences; Social Sciences, general
ISSN
0033-5177
eISSN
1573-7845
D.O.I.
10.1007/s11135-005-5078-2
Publisher site
See Article on Publisher Site

Abstract

In time series macroeconometric models, the first difference in the logarithm of a variable is routinely used to represent the rate of change of that variable. It is often overlooked that the assumed approximation is accurate only if the rates of change are small. Models of hyper-inflation are a case in point, since in these models, by definition, changes in price are large. In this letter, Cagan’s model is applied to Hungarian hyper-inflation data. It is then demonstrated that use of the approximation in the formation of the price inflation variable is causing an upward bias in the model’s key parameter, and therefore an exaggeration of the effect postulated by Cagan.

Journal

Quality & QuantitySpringer Journals

Published: Nov 14, 2005

References

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