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Title: LIMIT THEOREMS FOR FACTOR MODELS
This paper establishes central limit theorems (CLTs) and proposes how to perform valid inference in factor models. We consider a setting where many counties/regions/assets are observed for many time periods, and when estimation of a global parameter includes aggregation of a cross-section of heterogeneous microparameters estimated separately for each entity. The CLT applies for quantities involving both cross-sectional and time series aggregation, as well as for quadratic forms in time-aggregated errors. This paper studies the conditions when one can consistently estimate the asymptotic variance, and proposes a bootstrap scheme for cases when one cannot. A small simulation study illustrates performance of the asymptotic and bootstrap procedures. The results are useful for making inferences in two-step estimation procedures related to factor models, as well as in other related contexts. Our treatment avoids structural modeling of cross-sectional dependence but imposes time-series independence.  more » « less
Award ID(s):
1757199
PAR ID:
10339705
Author(s) / Creator(s):
;
Date Published:
Journal Name:
Econometric Theory
Volume:
37
Issue:
5
ISSN:
0266-4666
Page Range / eLocation ID:
1034 to 1074
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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