在美国，谁会成为发明者？接触创新的重要性*

中文摘要

我们刻画了决定谁会在美国成为发明者的因素，重点考察发明能力（“先天”）与环境（“后天”）各自的作用。利用专利记录与税务记录关联形成的120万名发明者的去标识化数据，我们首先表明，儿童成为发明者的概率因其出生时的特征而存在巨大差异，这些特征包括种族、性别和父母的社会经济阶层。例如，高收入（收入最高的1%）家庭的儿童成为发明者的概率，是收入低于中位数的家庭儿童的10倍。即使在童年早期数学测试成绩相似的儿童之间，这些差距仍然存在，而这些成绩对创新率具有很强的预测力。这表明，这些差距可能源于环境差异，而非创新能力差异。我们进一步表明，童年时期接触创新对儿童从事发明的倾向具有显著的因果效应，从而直接确立了环境的重要性。家庭在儿童年幼时迁至高创新地区的儿童，更有可能成为发明者。这些接触效应具有技术类别和性别特异性。在某一技术类别创新率较高的社区或家庭中长大的儿童，更有可能在完全相同的技术类别中获得专利。如果女孩成长的地区有更多在某一技术类别从事发明的女性，她们就更有可能在该类别从事发明；男性发明者较多则没有这种效应。这些具有性别和技术类别特异性的接触效应，更有可能由榜样效应或网络效应等作用范围较窄的机制驱动，而非由学校质量等仅影响一般人力资本积累的因素驱动。与接触效应在职业选择中的重要性相一致，女性和弱势青年在高影响力发明者中的代表性不足程度，与其在发明者整体中的代表性不足程度相当。这些发现表明，存在许多“失落的爱因斯坦”——他们若在童年时期接触过创新，本会做出极具影响力的发明——尤其是在女性、少数族裔和低收入家庭的儿童中。

Abstract

We characterize the factors that determine who becomes an inventor in the United States, focusing on the role of inventive ability (“nature”) versus environment (“nurture”). Using deidentified data on 1.2 million inventors from patent records linked to tax records, we first show that children's chances of becoming inventors vary sharply with characteristics at birth, such as their race, gender, and parents' socioeconomic class. For example, children from high-income (top 1%) families are 10 times as likely to become inventors as those from below-median income families. These gaps persist even among children with similar math test scores in early childhood-which are highly predictive of innovation rates-suggesting that the gaps may be driven by differences in environment rather than abilities to innovate. We directly establish the importance of environment by showing that exposure to innovation during childhood has significant causal effects on children's propensities to invent. Children whose families move to a high-innovation area when they are young are more likely to become inventors. These exposure effects are technology class and gender specific. Children who grow up in a neighborhood or family with a high innovation rate in a specific technology class are more likely to patent in exactly the same class. Girls are more likely to invent in a particular class if they grow up in an area with more women (but not men) who invent in that class. These gender- and technology class-specific exposure effects are more likely to be driven by narrow mechanisms, such as role-model or network effects, than factors that only affect general human capital accumulation, such as the quality of schools. Consistent with the importance of exposure effects in career selection, women and disadvantaged youth are as underrepresented among high-impact inventors as they are among inventors as a whole. These findings suggest that there are many “lost Einsteins”-individuals who would have had highly impactful inventions had they been exposed to innovation in childhood-especially among women, minorities, and children from low-income families.