Dummy Variable Model
Updated 2026-09-11
INTRODUCTION
English translation pending.
CORE DEFINITION
A dummy variable model is a regression specification in which categorical variables are encoded as 0 and 1, so that qualitative factors such as gender, region or treatment status can enter a quantitative model. Its claim is that the coefficient on a dummy then measures the difference between that group and the omitted baseline, turning group membership into an estimable effect.
SCAFFOLDING EFFECT
Reduce cognitive load
- Group effect: encode the category and read its coefficient as the difference from the baseline. - Control layer: use dummies to hold region or period fixed while estimating the effect of interest. - Trap avoidance: omit one category so the set is not perfectly collinear.
Anchor fast decisions
A 0/1 indicator shifts the intercept for the group it marks while leaving the slope common, so the model separates a level shift from the other covariates' effect. Dropping one category is what keeps the indicators independent of the intercept.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- zh.wikipedia.orghttps://zh.wikipedia.org/wiki/%E8%99%9A%E6%8B%9F%E5%8F%98%E9%87%8Fverified
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