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Forecasting Regional Labor Market Developments under Spatial Autocorrelation

Longhi, Simonetta and Nijkamp, Peter (2007) 'Forecasting Regional Labor Market Developments under Spatial Autocorrelation.' International Regional Science Review, 30 (2). pp. 100-119. ISSN 0160-0176

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<jats:p> Because of heterogeneity across regions, economic policy measures are increasingly targeted at the regional level and, therefore, require regional forecasts. The data available to compute regional forecasts are usually a pseudo panel of a limited number of observations over time and a large number of regions strongly interacting with each other. Traditional time-series techniques applied to distinct time series of regional data are probably a suboptimal forecasting strategy. Although both linear and nonlinear models have been applied and evaluated to forecast socioeconomic variables, spatial interactions among regions are often ignored. This article evaluates the ability of spatial error and spatial lag models to correct for misspecifications due to neglected spatial autocorrelation in the data. The empirical application on short-term forecasts of employment in 326 West German regions shows that the superimposed spatial structure that is required for the estimation of spatial models improves the forecasting performance of nonspatial models. </jats:p>

Item Type: Article
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: Faculty of Social Sciences > Institute for Social and Economic Research
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 21 Sep 2013 08:21
Last Modified: 06 Jan 2022 14:38

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