Estimation of the Preference Heterogeneity within Stated Choice Data Using Semiparametric Varying- Coefficient Methods.
Estimation of the Preference Heterogeneity within Stated Choice Data Using Semiparametric Varying- Coefficient Methods.
复制标题
使用半参数变系数方法估计指定选择数据中的偏好异质性。
DOI：
10.1007/s00181-012-0646-5
复制
发表时间：
2012
影响因子：
3.2
通讯作者：
Tadao
中科院分区：
文献类型：
--
作者：
Hoshino;Tadao
本研究提出使用半参数变系数方法估计偏好异质性内规定的选择数据。半参数变系数方法有可能克服传统随机参数模型和潜在类模型的缺点。特别是对于变系数的二进制概率模型，本研究提出了一种易于计算的局部迭代最小二乘（LILS）方法，基于期望最大化算法。有限样本性质的LILS估计使用Monte Carlo实验进行评估。为了证明半参数变系数方法的实用性，我们提出了一个实证研究，进行经济评估的景观与二分法选择条件估值。
This study proposes the use of semiparametric varying-coefficient methods to estimate the preference heterogeneity within stated choice data. Semiparametric varying-coefficient methods have the potential to overcome the disadvantages of conventional random parameter models and latent class models. For binary probit models with varying coefficients, in particular, this study proposes an easy-to-compute local iterative least squares (LILS) approach, based on the expectation–maximization algorithm. The finite sample properties of the LILS estimator are assessed using Monte Carlo experiments. In order to demonstrate the practical usefulness of semiparametric varying-coefficient methods, we present an empirical study, conducting an economic valuation of a landscape with dichotomous choice contingent valuations.