We introduce multivariate ordered discrete response models with general rectangular structures. From the perspective of behavioral economics, these non-lattice models correspond to broad bracketing in decision making, whereas lattice models, which researchers typically estimate in practice, correspond to narrow bracketing. In these models, we specify latent processes as a sum of an index of covariates and an unobserved error, with unobservables for different latent processes potentially correlated. We provide conditions that are sufficient for identification under the independence of errors and covariates and outline an estimation approach. We present simulations and empirical examples, with a particular focus on probit specifications.

翻译：我们引入了具有一般矩形结构的多元有序离散响应模型。从行为经济学视角来看，这些非格点模型对应于决策制定中的宽框架化，而研究人员在实践中通常估计的格点模型则对应于窄框架化。在这些模型中，我们将潜变量过程设定为协变量指数与未观测误差之和，且不同潜变量过程的未观测项可能存在相关性。我们提供了在误差项与协变量独立条件下足以实现模型识别的条件，并概述了一种估计方法。本文还呈现了模拟实验与实证案例，特别侧重于probit设定形式。