Estimating the price elasticity of gasoline demand in correlated random coefficient models with endogeneity
提出一种每簇工具变量方法，用于估计存在内生性和双向固定效应的线性相关随机系数模型，并应用于汽油需求价格弹性估计，发现弹性存在显著异质性且平均弹性高于标准估计结果。
Summary We 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.