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Forecasting Spanish economic activity in times of COVID-19 by means of the RT-LEI and machine learning techniques

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  • Carlos Poza
  • Manuel Monge

Abstract

The main aim of this paper is to analyse and estimate the behaviour of the Spanish economic activity in the next 12 months, by means of a Real-Time Leading Economic Indicator (RT-LEI), based on Google Trends, and the real GDP. We apply methodologies based on fractional integration and cointegration to measure the degree of persistence and to examine the long-term relationship. Finally, we carry out a forecast using a Machine Learning model based on an Artificial Neural Network. Our results indicate that the Spanish economy will experience a contraction in 1Q-21 and will require strong measures to reverse the situation and recover the original trend.

Suggested Citation

  • Carlos Poza & Manuel Monge, 2023. "Forecasting Spanish economic activity in times of COVID-19 by means of the RT-LEI and machine learning techniques," Applied Economics Letters, Taylor & Francis Journals, vol. 30(4), pages 472-477, February.
    • Handle: RePEc:taf:apeclt:v:30:y:2023:i:4:p:472-477
    DOI: 10.1080/13504851.2021.1994122
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