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Spatial differencing for sample selection models with 'site-specific' unobserved local effects
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DOI：10.1093/ectj/utad025.png)
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This paper proposes an estimator which combines spatial differencing with a two-step sample selection estimator. We derive identification, estimation, and inference results from 'site-specific' unobserved effects. These effects operate at a spatial scale that cannot be captured by administrative borders. Therefore, we use spatial differencing. We show that under justifiable assumptions, the estimator is consistent and asymptotically normal. A Monte Carlo experiment illustrates the small sample properties of our estimator. We apply our procedure to the estimation of a female wage offer equation in the United States and the results show the relevance of spatial differencing to account for 'site-specific' unobserved effects.
Keyword:
Sample selection
site-specific unobserved heterogeneity
spatial difference
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