Trouble in the Tails? What We Know about Earnings Nonresponse 30 Years after Lillard, Smith, and Welch

• 成果类型: Article
• 署名作者: Bollinger, Christopher R.; Hirsch, Barry T.; Hokayem, Charles M.; Ziliak, James P.
• 署名单位: University of Kentucky; University System of Georgia; Georgia State University; IZA Institute Labor Economics
• 刊物名称: JOURNAL OF POLITICAL ECONOMY
• ISSN/ISSBN: 0022-3808
• DOI: 10.1086/701807
• 发表日期: 2019
• 页码: 2143-2185
• 关键词: current population survey; SAMPLE SELECTION BIAS; ROTATION GROUP BIAS; Gender Wage Gap; measurement error; UNITED-STATES; response error; match bias; TRENDS; INEQUALITY

摘要

Earnings nonresponse in household surveys is widespread, yet there is limited knowledge of how nonresponse biases earnings measures. We examine the consequences of nonresponse on earnings gaps and inequality using Current Population Survey individual records linked to administrative earnings data. The common assumption that earnings are missing at random is rejected. Nonresponse across the earnings distribution is U-shaped, highest in the left and right tails. Inequality measures differ between household and administrative data due in part to nonresponse. Nonresponse biases earnings differentials by race, gender, and education, particularly in the tails. Flexible copula-based models can account for nonrandom nonresponse.