A Dynamic Model of Entrepreneurial Learning
将创业学习建模为迭代选择问题的校准算法，创业者根据过往经验更新知识积累，重复有前景的选择并放弃失败的选择。模型强调失败与成功同样具有信息价值，并允许创业者具有短视预见性。
We model entrepreneurial learning as a calibrated algorithm of an iterated choice problem in which entrepreneurs learn by updating a subjective stock of knowledge accumulated on the basis of past experiences. Specifically, we argue that entrepreneurs repeat only those choices that appear most promising and discard the ones that resulted in failure. The contribution of the paper is twofold. First, we provide a structural model of entrepreneurial learning in which failure is as informative—though clearly not as desirable—as success. Second, to complement standard economic models in which agents are rational, we allow our entrepreneurs to have myopic foresight. Our entrepreneurs process information, make mistakes, update their decisional algorithms and, possibly, through this struggle, improve their performance.