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Forecasting Spanish Inflation Using the Maximum Disaggregation Level by Sectors and Geographical Areas

Author

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  • Juan de Dios Tena

    (Universidad Carlos , Getafe, Spain, Università di Sassari and CRENoS, Sassari, Italy, jtena@est-econ.uc3m.es)

  • Antoni Espasa

    (Universidad Carlos , Getafe, Spain)

  • Gabriel Pino

    (Universidad de Concepción, Concepción, Chile)

Abstract

This article evaluates different strategies for forecasting Spanish inflation using information from price series for fifty-seven products and eighteen regions in Spain. We consider vector equilibrium correction (VeqCM) models that include cointegration relationships between Spanish prices and prices in the regions of Valencia, Andalusia, Madrid, Catalonia, and the Basque Country. This approach is consistent with economic intuition and is shown to be of tangible importance after suitable econometric evaluation. It is found that sectoral disaggregate models are useful for forecasting inflation in the five largest Spanish regions. Moreover, aggregate inflation forecasts in Spain can be significantly improved by aggregating projections from different sectors and geographical areas and by considering cointegration relationships between regional and national prices. However, in spite of the existence of long-run relationships between sectoral and national prices, they include deterministic components that are not consistent with the law of one price.

Suggested Citation

  • Juan de Dios Tena & Antoni Espasa & Gabriel Pino, 2010. "Forecasting Spanish Inflation Using the Maximum Disaggregation Level by Sectors and Geographical Areas," International Regional Science Review, , vol. 33(2), pages 181-204, April.
    • Handle: RePEc:sae:inrsre:v:33:y:2010:i:2:p:181-204
    DOI: 10.1177/0160017609336629
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    References listed on IDEAS

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    Cited by:

    1. Espasa, Antoni & Pino, Gabriel & Tena Horrillo, Juan de Dios, 2013. "Forecasting disaggregates by sectors and regions : the case of inflation in the euro area and Spain," DES - Working Papers. Statistics and Econometrics. WS ws130807, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Ligia Topan & César Castro & Miguel Jerez & Andrés Barge-Gil, 2020. "Oil price pass-through into inflation in Spain at national and regional level," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 11(4), pages 561-583, December.
    3. Helena Marques & Gabriel Pino & Juan Dios Tena Horrillo, 2014. "Regional inflation dynamics using space–time models," Empirical Economics, Springer, vol. 47(3), pages 1147-1172, November.
    4. Gabriel Pino & J. D. Tena & Antoni Espasa, 2016. "Geographical disaggregation of sectoral inflation. Econometric modelling of the Euro area and Spanish economies," Applied Economics, Taylor & Francis Journals, vol. 48(9), pages 799-815, February.
    5. Robinson Durán & Evelyn Garrido & Carolina Godoy & Juan de Dios Tena, 2012. "Predicción de la inflación en México con modelos desagregados por componente," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 27(1), pages 133-167.

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