Bruno, Giancarlo (2009): Non-linear relation between industrial production and business surveys data.
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n this paper I compare different models, a linear and a non-linear one, for forecasting industrial production by means of some related indicators. I claim that the difficulties associated with the correct identification of a non-linear model could be a possible cause of the often observed worse performance of non-linear models with respect to linear ones observed in the empirical literature. To cope with this issue I use a non-linear non-parametric model. The results are promising, as the forecasting performance shows a clear improvement over the linear parametric model.
|Item Type:||MPRA Paper|
|Original Title:||Non-linear relation between industrial production and business surveys data|
|Keywords:||Forecasting; Business Surveys; Non-linear time-series models; Non-parametric models|
|Subjects:||C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods; Simulation Methods
C - Mathematical and Quantitative Methods > C2 - Single Equation Models; Single Variables > C22 - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
|Depositing User:||Giancarlo Bruno|
|Date Deposited:||01. Nov 2012 07:42|
|Last Modified:||19. Feb 2013 11:40|
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