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Replication: Spatial Heterogeneity and Historical Persistance

This is a partial replication of the main body of the following paper, enriched with sample selection evaluations and coded in Python:

Pepinsky TB, Goodman SW, Ziller C. Modeling Spatial Heterogeneity and Historical Persistence: Nazi Concentration Camps and Contemporary Intolerance. American Political Science Review. 2024. 118(1). 519-528. https://doi.org/10.1017/S0003055423000072

Since the article is open access, it is included in the repository. Additionally, the openly accessible supplementary materials and replication archive are provided.

Link to the Replication Archive: https://doi.org/10.7910/DVN/0PY9EA

This replication is rather a showcase of possibilities of resampling and linear model selection than a precise paper replication. The main analysis though is an exact replica of the paper's main analysis - except for the models using the g-estimator.

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Replication of a scientific paper in python, focused on acyclic graphs, post-treatment bias and fixed effects. Enriched with resampling and linear model selection techniques.

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