G2TT
来源类型Publication
Decomposing Differences in Impacts on Survey- and Administrative-Measured Earnings from a Job Training Voucher Experiment
Quinn Moore; Irma Perez-Johnson; and Robert Santillano
发表日期2018-10-16
出版者Evaluation Review (online ahead of print, subscription required)
出版年2018
语种英语
概述Findings underscore the relevance of UI coverage to estimated earnings impacts and suggest assessing employment impacts using both UI- and survey-based measures.",
摘要

Background. Differences in earnings measured using either survey or administrative data raise the question of which is preferred for program impact evaluations. This is especially true when the population of interest has varying propensities to be represented in either source.

Objectives. We aim to study differences in impacts on earnings from a job training voucher experiment in order to demonstrate which source is most appropriate to interpret findings.

Research design. Using study participants with survey-reported earnings, we decompose mean earnings differences across sources into those resulting from (1) differences in reported employment and (2) differences in reported earnings for those who are employed in both sources. We study factors related to these two sources of differences and demonstrate how impact estimates change when adjusting for them.

Results. We find that differences in mean earnings are driven by differences in reported employment, but that differences in impacts are driven by differences in reported earnings for those employed in both data sources. Employment and worker characteristics explain much of the research group differences in earnings among the employed. Out-of-state employment, self-employment, and employment in low unemployment insurance (UI) coverage occupations contribute importantly to research group differences in survey- and UI-based employment levels. Employment in more than one job contributes to treatment group differences in earnings among the employed. All of these factors contribute substantially to the difference between survey- and UI-based earnings impact estimates.

Conclusion. Findings underscore the relevance of UI coverage to estimated earnings impacts and suggest assessing employment impacts using both UI- and survey-based measures.

URLhttps://www.mathematica.org/our-publications-and-findings/publications/decomposing-differences-in-impacts-on-survey-and-administrative-measured-earnings-from-a-job
来源智库Mathematica Policy Research (United States)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/489384
推荐引用方式
GB/T 7714
Quinn Moore,Irma Perez-Johnson,and Robert Santillano. Decomposing Differences in Impacts on Survey- and Administrative-Measured Earnings from a Job Training Voucher Experiment. 2018.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Quinn Moore]的文章
[Irma Perez-Johnson]的文章
[and Robert Santillano]的文章
百度学术
百度学术中相似的文章
[Quinn Moore]的文章
[Irma Perez-Johnson]的文章
[and Robert Santillano]的文章
必应学术
必应学术中相似的文章
[Quinn Moore]的文章
[Irma Perez-Johnson]的文章
[and Robert Santillano]的文章
相关权益政策
暂无数据
收藏/分享

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。