Partial Effects in Ordered Response Models with Factor Variables
针对包含虚拟变量的非线性回归模型，推导了有序Probit模型中计算各分类与所有其他分类之间差异的偏效应公式，并用主观幸福感数据展示了其应用价值。
Interpretation in nonlinear regression models that include sets of dummy variables representing categories of underlying categorical variables is not straightforward. Partial effects giving the differences between each category and the reference category are routinely computed in the empirical economics literature. Yet, partial effects yielding the differences between each category and all other categories are not calculated, despite having great interpretative value. We derive the correct formulae for calculating these partial effects for an ordered probit model. The results of an application using data on subjective well-being illustrate the usefulness of the alternative partial effects.