Using State Administrative Data for Longitudinal Analysis of Education, Employment & Earnings

利用国家行政数据对教育、就业进行纵向分析

• 批准号: 9907454
• 负责人: Michael Podgursky
• 金额: $ 4万
• 依托单位: University of Missouri-Columbia
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-08-01 至 2001-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9907454&HistoricalAwards=false
• 关键词: Using; State; Administrative; Data; Longitudinal

With National Science Foundation support Dr. Michael Podgursky and the University of Missouri will purchase a computer system including a Sun Enterprise 450 Server and 4 Gateway 450 MHz PCs. The system will allow a group of Missouri researchers to store and analyze administrative data from the state's Departments of Economic Development, Labor and Industrial Relations, Elementary and Secondary Education, Social Services, and Higher Education. It includes information on welfare participation, technical and vocational education, two- and four- year public education, job training as well as numerous other programs, both specialized and general, to enhance the employability of Missouri residents. The database also includes quarterly earnings for all individuals employed in Missouri who are covered by the state unemployment insurance program, the overwhelming majority of workers in the state, as well as from other categories. This information provides a powerful base for the examination of many policy relevant questions.Since the mid-1980s researchers and public officials have become increasingly interested in understanding how individuals transit from being out of the labor market into employment and what effects government programs have on these transitions. Two types of transitions that have generated the most interest are the transition from school to work and the transition from welfare to work. Analyses have lead a number of people to question the quality of public schooling in general, and in particular, whether schools are providing children with the skills necessary to move into the modern workplace. In addition, in recent years there has been a dramatic increase in the efforts of both the federal and state governments to move single parents off the welfare roles and into the labor market by providing various forms of training and job search assistance. However questions remain regarding the effectiveness of this assistance and the impacts of these programs. They can be difficult to address because long term data is only rarely available. The Missouri database provides a large systematically collected body of information which can serve this function and this NSF award will provide instrumentation which will permit its effective utilization.

在国家科学基金会的支持下，Michael Podgursky博士和密苏里州大学将购买一个计算机系统，包括一个Sun Enterprise 450服务器和4个Gateway 450 MHz PC。该系统将允许一组密苏里州的研究人员存储和分析来自该州经济发展部、劳工和工业关系部、中小学教育部、社会服务部和高等教育部的行政数据。它包括有关福利参与，技术和职业教育，两年和四年的公共教育，职业培训以及许多其他方案的信息，包括专业和一般，以提高密苏里州居民的就业能力。该数据库还包括在密苏里州就业的所有个人的季度收入，这些人是州失业保险计划的覆盖者，该州绝大多数工人以及其他类别的工人。自20世纪80年代中期以来，研究人员和政府官员越来越有兴趣了解个人如何从劳动力市场过渡到就业，以及政府计划对这些过渡的影响。最受关注的两种过渡类型是从学校到工作的过渡和从福利到工作的过渡。分析导致一些人质疑公立学校教育的总体质量，特别是学校是否为儿童提供了进入现代工作场所所需的技能。此外，近年来，联邦和州政府通过提供各种形式的培训和求职援助，为使单亲父母摆脱福利角色而进入劳动力市场作出了巨大的努力。然而，关于这种援助的有效性和这些方案的影响，仍然存在问题。这些问题可能难以解决，因为长期数据很少可用。密苏里州数据库提供了一个大型的系统收集的信息，可以服务于这一功能，这NSF奖将提供仪器，将允许其有效利用。