This paper considers the estimation and inference procedures for the case of a logistic panel regression model with interactive fixed effects, where multiple individual effects are allowed and the model is capable of capturing high-dimensional cross-section dependence. The proposed model also allows for heterogeneous regression coefficients. New Bayesian and non-Bayesian approaches are introduced to estimate the model parameters. We investigate the asymptotic behaviors of the estimated parameters. We show the consistency and asymptotic normality of the estimated regression coefficients and the estimated interactive fixed effects when both the cross-section and time-series dimensions of the panel go to infinity. We prove that the dimensionality of the interactive effects can be consistently estimated by the proposed information criterion. Monte Carlo simulations demonstrate the satisfactory performance of the proposed method. Finally, the method is applied to study the performance of New York City medallion drivers in terms of efficiency.

本文考虑了具有交互固定效应的逻辑面板回归模型的估计和推理过程，其中允许多个个体效应并且模型能够捕获高维横截面依赖性。所提出的模型还允许异质回归系数。引入了新的贝叶斯和非贝叶斯方法来估计模型参数。我们研究估计参数的渐近行为。当面板的横截面和时间序列维度都趋于无穷大时，我们展示了估计的回归系数和估计的交互固定效应的一致性和渐近正态性。我们证明了交互效果的维数可以通过所提出的信息标准一致地估计。蒙特卡罗模拟证明了所提出方法的令人满意的性能。最后，将该方法应用于研究纽约市奖章车手在效率方面的表现。