Spatial Chow-Lin models for completing growth rates in cross-sections
Growth rate data that are collected incompletely in cross-sections is a quite frequent problem. Chow and Lin (1971) have developed a method for predicting unobserved disaggregated time series and we propose an extension of the procedure for completing cross-sectional growth rates similar to the spat...
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| Format: | UnknownFormat |
| Sprache: | eng |
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Wien
Inst. für Höhere Studien (IHS)
2013
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| Schriftenreihe: | Reihe Ökonomie
295 |
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Tag hinzufügen | Zusammenfassung: | Growth rate data that are collected incompletely in cross-sections is a quite frequent problem. Chow and Lin (1971) have developed a method for predicting unobserved disaggregated time series and we propose an extension of the procedure for completing cross-sectional growth rates similar to the spatial Chow-Lin method of Liano et al. (2009). Disaggregated growth rates cannot be predicted directly and requires a system estimation of two Chow-Lin prediction models, where we compare classical and Bayesian estimation and prediction methods. We demonstrate the procedure for Spanish regional GDP growth rates between 2000 and 2004 at a NUTS-3 level. We evaluate the growth rate forecasts by accuracy criteria, because for the Spanish data-set we can compare the predicted with the observed values. -- interpolation ; missing disaggregated values in spatial econometrics ; MCMC ; spatial Chow-Lin methods ; predicting growth rates data ; spatial autoregression (SAR) ; forecast evaluation ; outliers |
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| Beschreibung: | Parallel als Online-Ausg. erschienen Adresse des Verl.: 1060 Wien, Stumpergasse 56 |
| Beschreibung: | 29 S. graph. Darst. 30 cm |