Shift Restrictions and Semiparametric Estimation in Ordered Response Models
提出一种半参数有序响应模型的估计量，在误差与解释变量独立的假设下，可一致且渐近正态地估计回归系数和阈值点，适用于存在系统性误报的调查数据，如新电信服务需求预测中的夸大偏差评估。
We develop a √n-consistent and asymptotically normal estimator of the parameters (regression coefficients and threshold points) of a semiparametric ordered response model under the assumption of independence of errors and regressors. The independence assumption implies shift restrictions allowing identification of threshold points up to location and scale. The estimator is useful in various applications, particularly in new product demand forecasting from survey data subject to systematic misreporting. We apply the estimator to assess exaggeration bias in survey data on demand for a new telecommunications service.