A Short Term Forecasting Model for the Spanish GDP and itsDemand Components

Ana Arencibia Pareja, Ana Gómez-Loscos, Mercedes de Luis López and Gabriel Perez-Quiros
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Ana Arencibia Pareja: Banco de España
Mercedes de Luis López: Banco de España
Gabriel Perez-Quiros: European Central Bank and CEPR
Authors registered in the RePEc Author Service: Gabriel Perez Quiros

Revista Economía, 2020, vol. 43, issue 85, 1-30

Abstract: This paper proposes a new version of the Spain-STING (Spain, Short-Term INdicator of Growth), a dynamic factor model used by the Banco de España for the short-term forecasting of the Spanish economy. The extended and revised version of the Spain-STING presented in this document includes a forecast for each of the demand components of the National Accounts. In order to select the indicators that best estimate the Spanish GDP and its demand components, several models are considered. Following this strategy, the selected models are those in which the common factor explains the highest proportion of the variance of the GDP. These models allow us to forecast GDP, private consumption, public expenditure, investment in capital goods, construction investment, exports and imports in a consistent way. We assess the predictive power of the models for GDPand its demand components for the period 2005–2017. With regard to the GDP forecast, we find some improvement of the predictive power compared to the previous version of Spain-STING. As for the demand components, we show that our proposal has better predictive power than other possible time series models.

Keywords: Business cycles; Spanish economy; Dynamic Factor models (search for similar items in EconPapers)
JEL-codes: C22 E27 E32 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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