Predicting Formality in Micro and Small Enterprises in Peru: A Model Based on Structural and Strategic Factors

Business informality represents a structural challenge in emerging economies, limiting productivity, access to credit, and the inclusion of micro and small enterprises (MSEs) in formal networks. This study develops a predictive model to estimate the probability of formality in Peruvian MSEs, using data from the V National Economic Census 2022. With a sample of 29,950 companies, binary logistics regression was applied considering structural variables (legal organization, size, sector, location, ownership of the premises) and strategic variables (sales, production, remuneration). The results reveal that larger companies, constituted as legal entities, with greater production and operating in rented premises have a higher probability of formality. On the other hand, high levels of sales are not necessarily associated with formalization, which suggests deliberate strategies of regulatory evasion. The model showed an accuracy of 74.9% and an acceptable discriminative capacity (AUC = 0.772). These findings offer a useful tool to focus public policies on segments with a higher risk of informality. It is recommended to expand the analysis with longitudinal data and qualitative variables to better capture the complexity of the phenomenon.