TY - JOUR
T1 - Neural Network Modeling as a Tool for Forecasting Regional Employment Patterns
AU - Longhi, S.
AU - Nijkamp, P.
AU - Reggiani, A
AU - Maierhofer, E.
PY - 2005
Y1 - 2005
N2 - This article analyzes artificial neural networks (ANNs) as a method to compute employment forecasts at a regional level. The empirical application is based on employment data collected for 327 West German regions over a period of fourteen years. First, the authors compare ANNs to models commonly used in panel data analysis. Second, they verify, in the case of panel data, whether the common practice of combining forecasts of the computed models is able to produce more reliable forecasts. The technique currently employed by the German authorities to compute such regional employment forecasts is comparable to a simple naïve no-change model. For this reason, ANNs are also compared to this undemanding technique. © 2005 Sage Publications.
AB - This article analyzes artificial neural networks (ANNs) as a method to compute employment forecasts at a regional level. The empirical application is based on employment data collected for 327 West German regions over a period of fourteen years. First, the authors compare ANNs to models commonly used in panel data analysis. Second, they verify, in the case of panel data, whether the common practice of combining forecasts of the computed models is able to produce more reliable forecasts. The technique currently employed by the German authorities to compute such regional employment forecasts is comparable to a simple naïve no-change model. For this reason, ANNs are also compared to this undemanding technique. © 2005 Sage Publications.
U2 - 10.1177/0160017605276187
DO - 10.1177/0160017605276187
M3 - Article
SN - 0160-0176
VL - 28
SP - 330
EP - 346
JO - International Regional Science Review
JF - International Regional Science Review
IS - 3
ER -
