Modelo de previsão de crescimento de empreendedores no Brasil usando cadeias de Markov

Abstract

This study analyzes the evolution of entrepreneurship in Brazil between 2000 and 2024 through the application of Markov Chains to data from the Global Entrepreneurship Monitor (GEM). The main objective was to examine the transition dynamics between different entrepreneurial states and to identify the stationary distribution that describes long-term behavior. The results indicate that most probabilities are concentrated in intermediate scenarios, characterized by stability or slight negative fluctuations, which confirms the sensitivity of Brazilian entrepreneurship to economic and political factors. The critical analysis, compared with the literature, reinforces that the country has a resilient but unstable entrepreneurial ecosystem, marked by high business mortality rates and the prevalence of necessity-driven entrepreneurship. The implications discussed include economic and social challenges, emphasizing the importance of public policies aimed at reducing informality, expanding access to credit, and fostering opportunity-driven entrepreneurship. It is concluded that the Markov Chain model is a useful tool for understanding the trajectory of Brazilian entrepreneurship and can support strategic decision-making in both academic and governmental contexts.