Estimating Government Worker Skills
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866910139066351616 |
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| author | Frick, Kevin Michael Gathen, Jonas |
| author_facet | Frick, Kevin Michael Gathen, Jonas |
| contents | We propose a new approach to estimate government worker skills, a setting where output is hard to observe and wages may be uninformative about skills. The approach uses wages in comparable jobs in the private sector and machine learning tools to link skills to skill-related observables. We apply the approach to rich Indonesian household-level panel data from 1988-2014, showing two main applications. First, government skills have continuously declined relative to the private sector, driven by the most skilled workers ending up in the private sector. Second, the Indonesian government pays a wage premium of 43% conditional on skills. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_15819 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Estimating Government Worker Skills Frick, Kevin Michael Gathen, Jonas General Economics Economics We propose a new approach to estimate government worker skills, a setting where output is hard to observe and wages may be uninformative about skills. The approach uses wages in comparable jobs in the private sector and machine learning tools to link skills to skill-related observables. We apply the approach to rich Indonesian household-level panel data from 1988-2014, showing two main applications. First, government skills have continuously declined relative to the private sector, driven by the most skilled workers ending up in the private sector. Second, the Indonesian government pays a wage premium of 43% conditional on skills. |
| title | Estimating Government Worker Skills |
| topic | General Economics Economics |
| url | https://arxiv.org/abs/2604.15819 |