SummaryWe propose a per‐cluster instrumental variable (PCIV) approach for estimating linear correlated random coefficient models in the presence of contemporaneous endogeneity and two‐way fixed effects. This approach estimates heterogeneous effects and aggregates them to population averages. We demonstrate consistency, showing robustness over standard estimators, and provide analytic standard errors for robust inference. In Monte Carlo simulation, PCIV performs relatively well in finite samples in either dimension. We apply PCIV in estimating the price elasticity of gasoline demand using state fuel taxes as instrumental variables. We find significant elasticity heterogeneity and more elastic gasoline demand on average than with standard estimators.

中文翻译：

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具有内生性的相关随机系数模型估计汽油需求的价格弹性

摘要我们提出了一种每簇工具变量（PCIV）方法，用于在同时存在内生性和双向固定效应的情况下估计线性相关随机系数模型。这种方法估计异质效应并将其汇总为总体平均值。我们展示了一致性，显示了相对于标准估计器的稳健性，并为稳健推理提供了分析标准误差。在蒙特卡罗模拟中，PCIV 在任一维度的有限样本中都表现相对较好。我们使用 PCIV 来估计汽油需求的价格弹性，并使用州燃油税作为工具变量。我们发现，与标准估算相比，弹性异质性显着，平均汽油需求弹性更大。