Drivers of Entrepreneurial Activity at Micro and Meso Levels: A Fuzzy Time-Series Analysis

The implications of entrepreneurial conditions, opportunities, and attitudes for total entrepreneurial activity (TEA) are under study. The data is obtained from the Global Entrepreneurship Monitor and Heritage Foundation for ten European Union countries, which had long enough time-series data available. The set of indicators include variables to determine the difficulty to start a business, motivations, ambitions, and attitudes of citizens towards entrepreneurship, and economic freedoms from which 7 key indicators were selected. The target variable is TEA and time-period is 2011–2019. The applied time-series analysis compares firstly linear regression accounting for autoregression by classical crisp model, possibilistic least squares linear model with crisp inputs and fuzzy outputs, and fuzzy multi-objective linear model with fuzzy inputs and outputs; secondly, the analysis is complemented by vector error correction model to study long-run causality of the key drivers of TEA. The results extend studies on the connections of entrepreneurial activity and economic freedoms by accounting for behavioral and attitude factors: entrepreneurial finance, grants and subsidies together with established entrepreneurial community support risk-taking of new entrepreneurs, who have identified business opportunities; further, entrepreneurial female/male ratio showed short-run effects, while statistically significant long-run causalities could not be established.