Uncovering Companies Missing from the SABI Database: A Web Scraping Approach

[EN] This study evaluates the completeness and representativeness of the SABI database, a widely used commercial source for firm-level data in Spain and Portugal, by comparing it to BORME, the official Spanish business register. Using web scraping techniques, we collected and processed approximately...

Descripción completa

Detalles Bibliográficos
Autores: Xin-Hui Huang, Domenech, Josep|||0000-0002-7302-5810
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/229479
Acceso en línea:https://riunet.upv.es/handle/10251/229479
Access Level:acceso abierto
Palabra clave:SABI database
Data quality
Web scraping
Database reliability
Descripción
Sumario:[EN] This study evaluates the completeness and representativeness of the SABI database, a widely used commercial source for firm-level data in Spain and Portugal, by comparing it to BORME, the official Spanish business register. Using web scraping techniques, we collected and processed approximately 100,000 BORME publications in PDF format, covering the period from 2010 to 2023. These were transformed into a structured dataset comprising over 1.2 million companies, which we then matched against SABI records from the same period. Our analysis reveals that SABI covers only 38.3\% of newly established companies, with significant underrepresentation of younger firms, small enterprises, specific sectors, and certain regions. Furthermore, we find clear evidence of survivorship bias: the longer a company has been dissolved, the less likely it is to appear in SABI. Sectoral and geographic disparities are also substantial, and the coverage is skewed toward firms with higher initial capital and specific legal forms. These findings suggest that SABI represents a non-random subset of the Spanish business population, and caution should be exercised when using it for empirical research. Adjustments for sample bias are recommended to improve the reliability of analyses based on this database.