Since 2014
An eigenvector spatial filtering contribution to short range regional population forecasting
Economics and Business Letters
View Archive Info| Field | Value | |
| Title |
An eigenvector spatial filtering contribution to short range regional population forecasting
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| Creator |
Griffith, Daniel A.
Chun, Yongwan |
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| Description |
Statistical space-time forecasting requires sufficiently large time series data to ensure high quality predictions. The dominance of temporal dependence in empirical space-time data emphasizes the importance of a lengthy time sequence. However, regional space-time data often have a relative small temporal sample size, increasing chances that regional forecasts might result in unreliable predictions. This paper proposes a method to improve regional forecasts by incorporating spatial autocorrelation in a generalized linear mixed model framework coupled with eigenvector spatial filtering. This methodology is illustrated with an application of regional population forecasts for South Korea.
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| Publisher |
Oviedo University Press
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| Contributor |
—
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| Date |
2014-12-30
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| Type |
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion — |
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| Format |
application/pdf
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| Identifier |
http://www.unioviedo.es/reunido/index.php/EBL/article/view/10418
10.17811/ebl.3.4.2014.208-217 |
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| Source |
Economics and Business Letters; Vol 3, No 4 (2014): December - Special Issue Advances in Regional Forecasting; 208-217
Economics and Business Letters; Vol 3, No 4 (2014): December - Special Issue Advances in Regional Forecasting; 208-217 2254-4380 10.17811/ebl.3.4.2014 |
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| Language |
eng
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| Relation |
http://www.unioviedo.es/reunido/index.php/EBL/article/view/10418/10124
http://www.unioviedo.es/reunido/index.php/EBL/article/downloadSuppFile/10418/364 |
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| Rights |
Copyright (c) 2014 Economics and Business Letters
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