Oaxaca_6

# Oaxaca_6 - Oaxaca Decomposition The common coefficient...

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1 Oaxaca Decomposition Ch12 pp. 397-400 Oaxaca Decomposition The common coefficient model implicitly assumes that β , the rate at which productive characteristics increase wages, is the same for males and females. The Oaxaca decomposition relaxes this assumption. It allows for productive characteristics to be rewarded differentially in the market. Why is this important? Oaxaca Decomposition - Method The Oaxaca decomposition requires running two separate regressions, one for males and one for females. For each gender, log wages are regressed on productive characteristics. Males only: ln W i = α M + β M *X i + ε i Females only: ln W i = α F + β F *X i + ε i Where, W i is the wages of individual i and X i is a vector of productive characteristics of individual i Example - Common Coefficient Suppose that we have the following data. A dot represents an (education, wage) pair for a female. A triangle represents an (education, wage) pair for a male. Female Male Education α + X i * β α + X i * β γ Notice that by including only a single β for both males and females, the slopes of these lines are assumed to be equal. ^ ^ ^ Log wage ^ ^ α γ α ^ ^ ^ ^ Example - Oaxaca The common coefficient model does not tell the whole story. It appears that the discrimination is more severe at high levels of education than at low levels. Female Male Education α M + X i * β M α F + X i * β F ^ Log wage ^ ^ α F ^ α M ^ ^ Oaxaca Decomposition For males: ln W M = α M + β M *X M For females: ln W F = α F + β F *X F The log wage gap, Δ , is: Δ = ln W M – ln W F Consider the following expression: ln W MXF = α M +

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