THE 2013 LAWRENCE R. KLEIN LECTURE: BEHAVIORAL AND DESCRIPTIVE FORMS OF CHOICE MODELS†
形式化描述了选择模型中的描述性形式，从行为模型推导而来，可用于量化预期偏差，并研究了考虑近似误差和内生性的离散选择模型估计量。
Empirical work on choice models, especially on relatively new topics or data sets, often starts with descriptive, or what is colloquially referred to as “reduced form,” results. Our descriptive form formalizes this process. It is derived from the underlying behavioral model, has an interpretation in terms of fit, and can sometimes be used to quantify biases in agents' expectations. We consider estimators for the descriptive form of discrete choice models with interacting agents that take account of approximation errors as well as unobservable sources of endogeneity. We conclude with an investigation of descriptive forms for two‐period entry models.