Do Value-Added Estimates Add Value? Accounting for Learning Dynamics

• 成果类型: Article
• 署名作者: Andrabi, Tahir; Das, Jishnu; Khwaja, Asim Ijaz; Zajonc, Tristan
• 署名单位: The World Bank; Harvard University; National Bureau of Economic Research; Claremont Colleges; Pomona College
• 刊物名称: AMERICAN ECONOMIC JOURNAL-APPLIED ECONOMICS
• ISSN/ISSBN: 1945-7782
• DOI: 10.1257/app.3.3.29
• 发表日期: 2011
• 页码: 29-54
• 关键词: panel-data; specification; TECHNOLOGY; QUALITY

摘要

This paper illustrates the central role of persistence in estimating and interpreting value-added models of learning. Using data from Pakistani public and private schools, we apply dynamic panel methods that address three key empirical challenges: imperfect persistence, unobserved heterogeneity, and measurement error. Our estimates suggest that only one-fifth to one-half of learning persists between grades and that private schools increase average achievement by 0.25 standard deviations each year. In contrast, value-added models that assume perfect persistence yield severely downward estimates of the private school effect. Models that ignore unobserved heterogeneity or measurement error produce biased estimates of persistence. (JEL I21, J13, O15)