Signaling and Employer Learning with Instruments

• 成果类型: Article
• 署名作者: Aryal, Gaurab; Bhuller, Manudeep; Lange, Fabian
• 署名单位: University of Virginia; University of Oslo; Statistics Norway; McGill University; National Bureau of Economic Research
• 刊物名称: AMERICAN ECONOMIC REVIEW
• ISSN/ISSBN: 0002-8282
• DOI: 10.1257/aer.20200146
• 发表日期: 2022
• 页码: 1669-1702
• 关键词: education; returns; earnings; college; identification; attendance; benefits; premium; average; models

摘要

This paper considers the use of instruments to identify and estimate private and social returns to education within a model of employer learning. What an instrument identifies depends on whether it is hidden from, or transparent (i.e., observed) to, the employers. A hidden instrument identifies private returns to education, and a transparent instrument identifies social returns to education. We use variation in compulsory schooling laws across noncentral and central municipalities in Norway to, respectively, construct hidden and transparent instruments. We estimate a private return of 7.9 percent, of which 70 percent is due to increased productivity and the remaining 30 percent is due to signaling.