The Gelbach decomposition is a statistical method used to decompose changes in regression coefficients that occur when additional explanatory variables are added to a model. Developed by economist Jonah B. Gelbach in 2016, the technique provides an exact accounting of how omitted variables contribute to differences between coefficients in nested linear regressions.
The Gelbach decomposition is a statistical method used to decompose changes in regression coefficients that occur when additional explanatory variables are added to a model. Developed by economist Jonah B. Gelbach in 2016, the technique provides an exact accounting of how omitted variables contribute to differences between coefficients in nested linear regressions.
Source: Wikipedia "Gelbach decomposition" · CC BY-SA 4.0
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