Financial analysis of rural tourism in Catalonia and Galicia pre- and post COVID-19

Other authors

Agencia Estatal de Investigación

Publication date

info:eu-repo/date/embargoEnd/2026-08-03

2024-08-03



Abstract

This article analyses the financial health of Catalan and Galician rural tourism businesses between 2019 and 2021 by examining their profitability and solvency, in order to assess their survivability over the period affected by the COVID-19 pandemic. To this end, we classify firms into groups with similar financial health. The article uses accounting data from the SABI (Iberian Balance Sheet Analysis System) database and the Compositional Data (CoDa) methodology, which offers a reliable analysis of sectoral financial statements, and is immune to the statistical problems of classical ratios (skewness, non-normality, non-linearity, and outliers, among others). The classification with the k-means method reveals three groups with distinct financial profiles. None have a positive return on equity. One cluster is under special financial distress, with high indebtedness, low liquidity and an extremely negative margin. The size of this cluster increases during the 2020 lockdown but returns to normal in 2021


Research funding: Spanish Ministry of Science and Innovation and ERDF-a way of making Europe. Grant Number: PID2021-123833OB-I00 Department of Research and Universities of Generalitat de Catalunya. Grant Numbers: 2021SGR01197, 2021SGR00403, 2021SGR00612 AGAUR of Generalitat de Catalunya. Grant Number: 2023-CLIMA-00037 Spanish Ministry of Health. Grant Number: CIBERB06/02/1002

Document Type

Article


Accepted version


peer-reviewed

Language

English

Publisher

Wiley

Related items

info:eu-repo/semantics/altIdentifier/doi/10.1002/jtr.2698

info:eu-repo/semantics/altIdentifier/issn/1099-2340

info:eu-repo/semantics/altIdentifier/eissn/1522-1970

PID2021-123833OB-I00

info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-123833OB-I00/ES/GENERATION AND TRANSFER OF COMPOSITIONAL DATA ANALYSIS KNOWLEDGE/

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