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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.04997 |
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| _version_ | 1866917316003889152 |
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| author | Konrad, Lucas D. Vashold, Lukas Cuaresma, Jesus Crespo |
| author_facet | Konrad, Lucas D. Vashold, Lukas Cuaresma, Jesus Crespo |
| contents | Structural break identification methods are an important tool for evaluating the effectiveness of climate change mitigation policies. In this paper, we introduce a unified probabilistic framework for detecting structural breaks with unknown timing and arbitrary sequence in longitudinal data. The proposed Bayesian setup uses indicator-saturated regression and a spike-and-slab prior with an inverse-moment density as the slab component to ensure model selection consistency. Simulation results show that the method outperforms comparable frequentist approaches, particularly in environments with a high probability of structural breaks. We apply the framework to identify and evaluate the effects of climate policies in the European road transport sector. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_04997 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Bayesian Indicator-Saturated Regression for Climate Policy Evaluation Konrad, Lucas D. Vashold, Lukas Cuaresma, Jesus Crespo Econometrics Structural break identification methods are an important tool for evaluating the effectiveness of climate change mitigation policies. In this paper, we introduce a unified probabilistic framework for detecting structural breaks with unknown timing and arbitrary sequence in longitudinal data. The proposed Bayesian setup uses indicator-saturated regression and a spike-and-slab prior with an inverse-moment density as the slab component to ensure model selection consistency. Simulation results show that the method outperforms comparable frequentist approaches, particularly in environments with a high probability of structural breaks. We apply the framework to identify and evaluate the effects of climate policies in the European road transport sector. |
| title | Bayesian Indicator-Saturated Regression for Climate Policy Evaluation |
| topic | Econometrics |
| url | https://arxiv.org/abs/2603.04997 |