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Low-rank approximations of nonseparable panel models

Abstract:

We provide estimation methods for nonseparable panel 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-differences approaches. Numerical e...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1093/ectj/utab007

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Institution:
University of Oxford
Division:
SSD
Department:
Economics
Oxford college:
Nuffield College
Role:
Author
Publisher:
Oxford University Press
Journal:
Econometrics Journal More from this journal
Volume:
24
Issue:
2
Pages:
C40-C77
Publication date:
2021-03-18
Acceptance date:
2021-03-04
DOI:
EISSN:
1368-423X
ISSN:
1368-4221
Language:
English
Keywords:
Pubs id:
1176684
Local pid:
pubs:1176684
Deposit date:
2021-05-17

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