Intrapreneurs, entrepreneurial employees, constitute an important force behind innovations in the economy. Yet, what factors that promote intrapreneurship at the country level are an underdeveloped research area. This paper provides an important contribution regarding the methodological approach and the broad set of potential explanatory factors studied. Based on machine-learning techniques (Least Absolute Shrinkage and Selection Operator (LASSO) and Extreme Bounds Analysis (EBA)), we investigate the influence of over 60 factors capturing institutional, demographic, cultural, and developmental factors. We find that the quality of government measured as impartiality, i.e. that the public institutions treat the citizens in a non-discriminatory fashion and do not favor some groups or individuals, and the level of human capital, measured as the average years of schooling, are the most important factors predicting the level of intrapreneurship across countries. Instrumental variable results support a causal interpretation. The findings emphasize the importance of policy to establish well-functioning and impartial institutions as well as to promote higher education.

中文翻译：

---

内部创业的沃土：公正的制度和人力资本

内部企业家、企业家雇员构成了经济创新背后的重要力量。然而，在国家层面促进内部创业的因素是一个欠发达的研究领域。本文提供了有关方法论方法和所研究的广泛的潜在解释因素的重要贡献。基于机器学习技术（最小绝对收缩和选择算子 (LASSO) 和极限边界分析 (EBA)），我们调查了 60 多个捕获制度、人口、文化和发展因素的因素的影响。我们发现衡量政府质量的公正性，即公共机构以非歧视的方式对待公民，不偏袒某些群体或个人，以及人力资本水平，以平均受教育年限衡量，是预测各国内部创业水平的最重要因素。工具变量结果支持因果解释。调查结果强调了建立运作良好和公正的机构以及促进高等教育的政策的重要性。