Demand Estimation with Flexible Income Effect: An Application to Pass‐Through and Merger Analysis*
提出一个半参数离散选择模型，灵活估计收入效应和需求曲率，应用于日本汽车市场分析补贴传导和合并效应，发现比参数模型更高的传导率和更显著的合并影响。
This article proposes a semiparametric discrete choice model that incorporates a nonparametric specification for income effects. The model allows for the flexible estimation of demand curvature, which has significant implications for pricing and policy analysis in oligopolistic markets. Our estimation algorithm adopts a method of sieve approximation with shape restrictions in a nested fixed‐point algorithm. Applying this framework to the Japanese automobile market, we conduct a pass‐through analysis of feebates and merger simulations. Our model predicts a higher pass‐through rate and more significant merger effects than parametric demand models, highlighting the importance of flexibly estimating demand curvature.