Econometric Methods for Understanding Matched Employer-Employee Data and Intergenerational — NSF Award to University of Chicago (I
This award will fund a research program that will use three projects to develop improved econometric methods for understanding earnings heterogeneity in matched employer-employee data and intergenerational mobility in large administrative registers. The first project will re-examine understanding of the role firms and
| Award title | Econometric Methods for Understanding Matched Employer-Employee Data and Intergenerational |
|---|---|
| Award ID | 2419008 |
| Awardee | University of Chicago |
| City | CHICAGO |
| State | IL |
| Amount obligated | $428,460 |
| Principal investigator | Azeem Shaikh |
| Program | Economics, Methodology, Measuremt & Stats |
| Start date | 08/15/2024 |
| Abstract | This award will fund a research program that will use three projects to develop improved econometric methods for understanding earnings heterogeneity in matched employer-employee data and intergenerational mobility in large administrative registers. The first project will re-examine understanding of the role firms and worker differences play in earnings heterogeneity -- the idea that earning heterogeneity stems from differences in wages across firms as well differences in worker productivity. Th |
| Source | NSF Awards |
$799/mo
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