报告时间：10月19日（周五）下午15：00-16：00
报告地点：理科大楼A1716
报告题目：Smoothed Spatial Maximum Score Estimation of Spatial Autoregressive Binary Choice Panel Models
报告人：雷敬华 中国人民大学
摘要：
This paper considers spatial autoregressive (SAR) binary choice models in the context of panel data with correlated random effects, where the latent dependent variables are spatially correlated and the individual effects are assumed to be stationary. Without imposing any parametric structure of the error terms, this paper proposes a smoothed spatial maximum score (SSpMS) estimator that consistently estimates the model parameters up to scale. The identication of parameters is obtained when the disturbances are time-stationary and the explanatory variables vary enough over time, along with an exogenous and time-invariant spatial weight matrix. Consistency and the asymptotic distribution of the proposed estimator are also derived in this paper. Finally, a Monte Carlo study indicates that the SSpMS estimator performs quite well in finite samples.
报告人简介：雷敬华，2008年于中国人民大学获得经济学-数学学士学位，2011年于荷兰蒂尔堡大学经济学硕士学位，2014年于荷兰蒂尔堡大学经济学博士学位。2015年1月至今，在中国人民大学财政金融学院财政学院任讲师，主要研究方向是空间计量经济学和财政学，是Papers in Regional Science, Regional Science and Urban Economics, Journal of International Trade & Economic Development的审稿人，曾获得中国人民大学优秀班主任称号。曾在journal of Econometrics等知名金融经济领域刊物上发表多篇学术论文。