Two-Stage Estimation to Control for Unobservables in a Recreation Demand Model with Unvisited Sites
针对休闲需求模型中未观测站点属性问题，提出在随机效用模型两阶段估计的第二阶段使用截断回归，避免普通最小二乘法因未访问站点无估计常数而产生的不一致参数问题。
The role of unobserved site attributes is a growing concern in recreation demand modeling. One solution in random utility models (RUMs) involves separating estimation into two stages, where the RUM is estimated with alternative specific constants (ASCs) in the first stage, and the estimated ASCs are regressed on the observed site attributes in the second stage. Prior work estimates the second stage with ordinary least squares (OLS) and two-stage least squares regression. We present an application with censored regression in the second stage. We show OLS produces inconsistent parameters when there are unvisited sites with no estimable ASCs and that censored regression avoids this problem. <i></i>