Predictions in spatial econometric models: Application to unemployment data

Thibault Laurent, Paula Margaretic

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Scopus citations


In the context of localized unemployment rates in France, we study the issue of prediction of spatial econometric models for areal data, by applying the prediction formulas gathered and derived in Goulard et al. (Spatial Economic Analysis, 12(2-3), 304-325, 2017), (2017). To model regional unemployment taking into account local interactions, we estimate several spatial econometric model specifications, namely, the spatial autoregressive SAR and SDM models, as well as the SLX model.We consider both types of predictions, namely, in-sample and out-of-sample prediction. We show that the prediction can be a complementary method to testing procedures for model comparison.

Original languageEnglish
Title of host publicationAdvances in Contemporary Statistics and Econometrics
Subtitle of host publicationFestschrift in Honor of Christine Thomas-Agnan
PublisherSpringer International Publishing
Number of pages18
ISBN (Electronic)9783030732493
ISBN (Print)9783030732486
StatePublished - 14 Jun 2021
Externally publishedYes


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