Spatial Chow-Lin Models for Completing Growth Rates in Cross-sections

Polasek, Wolfgang (April 2013) Spatial Chow-Lin Models for Completing Growth Rates in Cross-sections. IHS Economics Series 295

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Abstract or Table of Contents

Abstract: 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.;

Item Type: IHS Series
Keywords: 'Interpolation' 'Missing disaggregated values in spatial econometrics' 'MCMC' 'Spatial Chow-Lin methods' 'Predicting growth rates data' 'Spatial autoregression (SAR)' 'Forecast evaluation' 'Outliers'
Classification Codes (e.g. JEL): C11, C15, C52, E17, R12
Status: Published
Date Deposited: 26 Sep 2014 10:39
Last Modified: 23 Jul 2017 04:38
URI: http://irihs.ihs.ac.at/id/eprint/2195

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