# Low-rank approximations of nonseparable panel models

@article{FernndezVal2020LowrankAO, title={Low-rank approximations of nonseparable panel models}, author={Iv{\'a}n Fern{\'a}ndez-Val and Hugo Freeman and M. Weidner}, journal={arXiv: Econometrics}, year={2020} }

We provide estimation methods for panel nonseparable models based on low-rank factor structure approximations. The factor structures are estimated by matrix-completion methods to deal with the computational challenges of principal component analysis in the presence of missing data. We show that the resulting estimators are consistent in large panels, but suffer from approximation and shrinkage biases. We correct these biases using matching and difference-in-difference approaches. Numerical… Expand

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