A Smooth Transition Finite Mixture Model for Accommodating Unobserved Heterogeneity
容纳不可观测异质性的平滑转换有限混合模型AI 解读 ↓
← 返回论文列表与筛选
阅读说明
本页整理公开书目信息，不生成学术质量评分。AI 解读根据题名及所注明的摘要或原文片段生成，未完成全文核验，可能有误；具体假设、证明与结论请核对原文。摘要保留来源文本，未经模型改写。
DOI 首次登记不等于接收或发表日期。部分更正、评论等条目没有独立摘要；缺少可靠材料时保留待补状态。
引用量采用 OpenAlex 单条关联记录，不合计多个记录；关联记录可能包含正式发表版本，不等于此版本单独引用。缺失不视为零，引用指标不代表论文质量。
关注作者按书目中的完整姓名匹配，同名和姓名变体需人工辨别。相关论文先按共享细分方向和具体方法排列，再参考通用方法与发表日期。
分类依据与纠错
AI 根据所提供的论文材料归类：摘要明确在面板数据中估计不可观测异质性与时变效应，并应用于棒球比赛上座人数。
反馈分类问题
正在核对关联版本…
代码、数据与补充材料
正在核对对应版本的资源…
容纳不可观测异质性的平滑转换有限混合模型
- 研究问题
- 研究如何在面板数据中同时刻画随时间变化的解释变量效应与不可观测异质性，避免忽略异质性造成参数估计失真。
- 方法与思路
- 作者结合平滑转换与有限混合模型，使用贝叶斯方法进行设定、估计和模型选择，并讨论状态数量随样本增长时的灵活性。
- 材料陈述的贡献
- 摘要称模型嵌套若干既有转换与门限模型，模拟显示一定稳健性，棒球促销与上座人数应用中的表现优于其嵌套版本。
- 阅读关注点
- 应核对混合组别与转换状态的区分、模型识别和选择标准，以及假设违背的模拟范围、嵌套模型比较指标和促销变量处理。
- 阅读边界
- 仅据所给 RePEc 出版社摘要；未说明稳健性条件和比较指标，促销效应也不能仅凭此摘要解释为因果效应。
原文摘要
While the smooth transition (ST) model has become popular in business and economics, the treatment of unobserved heterogeneity within these models has received limited attention. We propose a ST finite mixture (STFM) model which simultaneously estimates the presence of time-varying effects and unobserved heterogeneity in a panel data context. Our objective is to accurately recover the heterogeneous effects of our independent variables of interest while simultaneously allowing these effects to vary over time. Accomplishing this objective may provide valuable insights for managers and policy makers. The STFM model nests several well-known ST and threshold models. We develop the specification, estimation, and model selection criteria for the STFM model using Bayesian methods. We also provide a theoretical assessment of the flexibility of the STFM model when the number of regimes grows with the sample size. In an extensive simulation study, we show that ignoring unobserved heterogeneity can lead to distorted parameter estimates, and that the STFM model is fairly robust when underlying model assumptions are violated. Empirically, we estimate the effects of in-game promotions on game attendance in Major League Baseball. Empirical results show that the STFM model outperforms all its nested versions. Supplementary materials for this article are available online.