A Comparative Study of Parametric and Nonparametric Regressions

This paper evaluates inflation forecasts made by parametric and nonparametric models. The results revealed that the neural network model yields better estimates of inflation rate than do parametric autoregressive integrated moving average (ARIMA) and linear models. Furthermore, the neural network model outperformed nonparametric models (except MARS).

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Year of publication:	2011
Authors:	Fattahi, Shahram
Published in:	Iranian Economic Review. - Faculty of Economics. - Vol. 16.2011, 3, p. 19-43
Publisher:	Faculty of Economics
Subject:	ARIMA \| AM \| MARS \| PPR \| NN \| Inflation Forecast

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Extent:	application/pdf
Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010928050