Spatial Chow-Lin Methods for Data Completion in Econometric Flow Models

Polasek, Wolfgang and Sellner, Richard (September 2010) Spatial Chow-Lin Methods for Data Completion in Econometric Flow Models. IHS Economics Series 255

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Abstract or Table of Contents

Abstract: Flow data across regions can be modeled by spatial econometric models, see LeSage and Pace (2009). Recently, regional studies became interested in the aggregation and disaggregation of flow models, because trade data cannot be obtained at a disaggregated level but data are published on an aggregate level. Furthermore, missing data in disaggregated flow models occur quite often since detailed measurements are often not possible at all observation points in time and space. In this paperwe develop classical and Bayesian methods to complete flow data. The Chow and Lin (1971) method was developed for completing disaggregated incomplete time series data. We will extend this method in a general framework to spatially correlated flow data using the cross-sectional Chow-Lin method of Polasek et al. (2009). The missing disaggregated data can be obtained either by feasible GLS prediction or by a Bayesian (posterior) predictive density.;

Item Type: IHS Series
Keywords: 'Missing values in spatial econometrics' 'MCMC' 'Non-spatial Chow-Lin (CL) and spatial Chow-Lin (SCL) methods' 'Spatial internal flow (SIF) models' 'Origin and destination (OD) data'
Classification Codes (e.g. JEL): C11, C15, C52, E17, R12
Status: Published
Date Deposited: 26 Sep 2014 10:39
Last Modified: 23 Jul 2017 04:22
URI: http://irihs.ihs.ac.at/id/eprint/2016

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