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Individual and Firm Heterogeneity in Labor Markets: Studies of Matched Employee-Employer Data

Individual and Firm Heterogeneity in Labor Markets: Studies of Matched Employee-Employer Data
劳动力市场中的个人和企业异质性:匹配雇员-雇主数据的研究
批准号:
9618111
负责人:
John Abowd
金额:
$24.34万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
1997
资助国家:
美国
项目状态:
已结题
起止时间:
1997-03-15 至 2002-02-28

项目摘要

项目成果

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中文摘要
翻译
调查者已经开发了统计方法和数据来源,可以调查个人和公司在观察到的劳动力市场结果中的异质性的相对重要性。这些方法并不像几乎所有以前的研究那样,假定个人效应和企业效应是不相关的。在NSF和法国国家统计研究所共同支持的研究中,这位研究人员使用了来自法国的数据,表明在决定工资结果方面,人的影响比公司的影响重要得多,但这两种影响是合理相关的。这位研究人员从四个来源收集了美国数据,这些数据现在可以用来估计适用于法国数据的人-效应/公司-效应模型的版本。由于美国数据的性质,模型必须有所修改,但分析的本质特征--可单独识别的个人和企业效应之间的相关性--被保留下来。调查员还得到了劳工统计局(BLS)的赞助,并得到了国家科学基金会先前拨款的资助,为1979年全国青年纵向调查(NLSY)队列创建了一个雇主链接文件。该雇主链接文件包含将有关雇主的外部信息与1986-1994年NLSY 1979年基本数据联系起来所需的识别号。作为与劳工统计局保密协议的一部分,调查员可以访问这些数据,NLSY的其他用户将能够从该局的纵向数据计划中获得数据。调查员将扩展和修改他的基本统计模型,这些模型允许他使用雇主链接文件和有关雇主的相关信息来分析在NLSY上测量的工资、就业和其他劳动力市场结果。调查人员可获得的其他数据来源包括由康奈尔大学高级人力资源研究中心开发的匹配的雇主-雇员管理数据。这些数据包括工资结果、或有薪酬和公司的大量业绩衡量标准。还将提供从匹配的当前人口调查中开发的数据文件,其中包括有限的雇主信息,以及调查员目前研究中使用的工人机构特征数据库。
英文摘要
The investigator has developed statistical methods and data sources that permit investigation of the relative importance of individual and firm heterogeneity in observed labor market outcomes. These methods do not assume, as virtually all previous research has, that the person effects and the firm effects are uncorrelated. Using data from France in research supported collaboratively by NSF and the French National Statistical Institute, the investigator has shown that person effects are much more important in determining wage outcomes than are firm effects, but that these two effects are reasonably correlated. The investigator has assembled American data from four sources that can now be used to estimate versions of the person-effect/firm-effect models applied to French data. Because of the nature of the American data, the models must be somewhat modified but the essential character of the analysis-the possibility of correlation between separately identifiable person and firm effects-is preserved. The investigator has also been sponsored by the Bureau of Labor Statistics (BLS ) and by funding under a previous NSF grant to create an employer-link file for the National Longitudinal Survey of Youth (NLSY) 1979 Cohort. This employer-link file contains the identification numbers required to link external information about the employer to the basic NLSY 1979 data for the years 1986-1994. The investigator has access to these data as a part of a confidentiality agreement with the BLS, and other users of the NLSY will be able to obtain the data from the Bureau's Longitudinal Data Programs. The investigator will extend and modify his basic statistical models that permit him to analyze wage, employment and other labor market outcomes measured on the NLSY using the employer link file and the associated information on the employer. The other data sources available to the investigator include matched employer-employee managerial data developed by the Center for Advanced Human Resource Studies at Cornell University. These data include wage outcomes, contingent pay and a large number of performance measures on the firms. Data files developed from matched Current Population Surveys that include limited employer information and from the Worker-Establishment Characteristics Database used in the investigator's current research will also be available.
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TC: Large: Collaborative Research: Practical Privacy: Metrics and Methods for Protecting Record-level and Relational Data
  • 批准号:
    1012593
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $132.67万
  • 财政年份:
    2010
  • 负责人:
    John Abowd
  • 依托单位:
CDI-Type II: Collaborative Research: Integrating Statistical and Computational Approaches to Privacy
  • 批准号:
    0941226
  • 项目类别:
    Standard Grant
  • 资助金额:
    $40.93万
  • 财政年份:
    2010
  • 负责人:
    John Abowd
  • 依托单位:
Joint NSF-Census-IRS Workshop on synthetic data and confidentiality protection, July 2009 Washington, DC
  • 批准号:
    0922494
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.85万
  • 财政年份:
    2009
  • 负责人:
    John Abowd
  • 依托单位:
ITR-(ECS+ASE)-(dmc+int): Info Tech Challenges for Secure Access to Confidential Social Science Data
海外基金