Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/241877 
Year of Publication: 
2020
Series/Report no.: 
cemmap working paper No. CWP2/20
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
We propose an optimal-transport-based matching method to nonparametrically estimate linear models with independent latent variables. The method consists in generating pseudo-observations from the latent variables, so that the Euclidean distance between the model's predictions and their matched counterparts in the data is minimized. We show that our nonparametric estimator is consistent, and we document that it performs well in simulated data. We apply this method to study the cyclicality of permanent and transitory income shocks in the Panel Study of Income Dynamics. We find that the dispersion of income shocks is approximately acyclical, whereas the skewness of permanent shocks is procyclical. By comparison, we find that the dispersion and skewness of shocks to hourly wages vary little with the business cycle.
Subjects: 
Latent variables
nonparametric estimation
matching
factor models
optimaltransport
income dynamics
JEL: 
C14
C33
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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