The authors propose consistent sieve estimators for multidimensional matching models with transferable utility under unrestricted characteristic distributions and apply them to find greater cognitive-biased technological progress in the US than prior parametric studies.
Efficient estimation of average derivatives in NPIV models: Simulation comparisons of neural network estimators
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Semi-nonparametric models of multidimensional matching: an optimal transport approach
The authors propose consistent sieve estimators for multidimensional matching models with transferable utility under unrestricted characteristic distributions and apply them to find greater cognitive-biased technological progress in the US than prior parametric studies.