Assessing the Factors Related to a Start-Up’s Valuation Using Prediction and Causal Discovery

Mariia Garkavenko, Tatiana Beliaeva, Eric Gaussier, Hamid Mirisaee, Cédric Lagnier and Agnès Guerraz

Entrepreneurship Theory and Practice, 2023, vol. 47, issue 5, 2017-2044

Abstract: Research indicates that investors rely on various criteria to evaluate early-stage companies. However, past research in this area has focused on subsets of factors and does not distinguish between the predictors and causal determinants of start-up valuation. In our study, we applied machine learning and causal discovery to analyze a comprehensive dataset with 57 independent variables and 2,366 valuations of start-ups in the United Kingdom. The results show a strong relationship between good predictors and causal determinants of valuation. However, noncausal variables may still be useful for prediction, and inversely, some observed causes may not help in the prediction task.

Keywords: start-up valuation; machine learning; prediction; causal discovery (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/10422587221121291 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:entthe:v:47:y:2023:i:5:p:2017-2044

DOI: 10.1177/10422587221121291

Access Statistics for this article

More articles in Entrepreneurship Theory and Practice
Bibliographic data for series maintained by SAGE Publications ().