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A quantile-based nonadditive fixed effects model
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DOI：10.1080/07474938.2025.2587645.png)
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Abstract
En 中文
I propose a quantile-based nonadditive fixed effects panel model to study heterogeneous causal effects. This model connects to both the standard fixed effects model and the structural quantile regression model. It uncovers the heterogeneous causal effects as functions of the unobserved rank variable. The rank is assumed stable over time, which is often more economically plausible than the panel quantile studies that assume individual rank is iid over time. I provide identification and estimation results, establishing uniform asymptotics of the heterogeneous causal effect function estimator. Simulations show reasonable finite-sample performance and show my model complements fixed effects quantile regression. Finally, I illustrate the proposed methods by examining the causal effect of a country's oil wealth on its military defense spending.
Keywords:
Rank variable
structural model
panel data
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