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The actual, adjusted gap is estimated by a wage regression controlling for the same covariates as in the separations equation.
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The second step is a wage regression.
These wage gaps are conventionally estimated from a wage regression using individual-level data.
This figure is derived from a wage regression using Jamaican census data.
Starting from 1976, we estimate a wage fixed effect from a Mincerian wage regression.
Under that assumption, estimation of a Mincer wage regression typically requires inclusion of location fixed effects.
Our goal is to quantify the impact of the unemployment misperception by the respondent on his labor income, in the spirit of a worker-level wage regression.
For comparison, column 1 contains the estimation results of a standard quadratic wage regression model.
Individual level PIAAC data for the US are then used to estimate the weight of each dimension in the human capital composite by running Mincerian wage regressions.
The top panel of Table 1 reports wage regression results using a standard set of controls.
Hence, including the migrant variable in the wage regression will show whether migrants experience an earnings penalty or earnings premium and whether this differs by components of human capital endowment.
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