The limiting distribution of the LS estimator in panel models with interactive fixed effects is invariant to over-specifying the number of factors.
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An alternating optimization procedure for high-dimensional generalized latent variable models yields consistent estimators and a debiased covariate-effect estimator with asymptotic normality.
Extends BLP demand model with interactive fixed effects via factor structure and proposes two-step LS-MD estimator for consistent estimation under endogeneity.
Introduces a lag-based OLS estimator for GDFM using static PCA factors, establishes consistency and asymptotic normality, and applies it to European macro data to identify sizeable weak common components.
citing papers explorer
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Linear Regression for Panel With Unknown Number of Factors as Interactive Fixed Effects
The limiting distribution of the LS estimator in panel models with interactive fixed effects is invariant to over-specifying the number of factors.
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Inference on Generalized Latent Variable Models with High-Dimensional Responses and Covariates
An alternating optimization procedure for high-dimensional generalized latent variable models yields consistent estimators and a debiased covariate-effect estimator with asymptotic normality.
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Estimation of random coefficients logit demand models with interactive fixed effects
Extends BLP demand model with interactive fixed effects via factor structure and proposes two-step LS-MD estimator for consistent estimation under endogeneity.
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A Distributed Lag Approach to the Generalised Dynamic Factor Model
Introduces a lag-based OLS estimator for GDFM using static PCA factors, establishes consistency and asymptotic normality, and applies it to European macro data to identify sizeable weak common components.