Inference after discretizing time-varying unobserved heterogeneity
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866909851238531072 |
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| author | Beyhum, Jad Mugnier, Martin |
| author_facet | Beyhum, Jad Mugnier, Martin |
| contents | Approximating time-varying unobserved heterogeneity by discrete types has become increasingly popular in economics. Yet, provably valid post-clustering inference for target parameters in models that do not impose an exact group structure is still lacking. This paper fills this gap in the leading case of a linear panel data model with nonseparable two-way unobserved heterogeneity. Building on insights from the double machine learning literature, we propose a simple inference procedure based on a bias-reducing moment. Asymptotic theory and simulations suggest excellent performance. In the application on fiscal policy we revisit, the novel approach yields conclusions in line with economic theory. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_07352 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Inference after discretizing time-varying unobserved heterogeneity Beyhum, Jad Mugnier, Martin Econometrics Approximating time-varying unobserved heterogeneity by discrete types has become increasingly popular in economics. Yet, provably valid post-clustering inference for target parameters in models that do not impose an exact group structure is still lacking. This paper fills this gap in the leading case of a linear panel data model with nonseparable two-way unobserved heterogeneity. Building on insights from the double machine learning literature, we propose a simple inference procedure based on a bias-reducing moment. Asymptotic theory and simulations suggest excellent performance. In the application on fiscal policy we revisit, the novel approach yields conclusions in line with economic theory. |
| title | Inference after discretizing time-varying unobserved heterogeneity |
| topic | Econometrics |
| url | https://arxiv.org/abs/2412.07352 |