Quantile factor models (QFM) represent a new class of factor models for high-dimensional panel data. Unlike approximate factor models (AFM), which only extract mean factors, QFM also allow unobserved factors to shift other relevant parts of the distributions of observables. We propose a quantile...

This paper investigates the identification and parametric estimation of marriagematching models. We first extend the identification result for the empirical dynamicmarriage matching model proposed in Choo (2015) by allowing the unobserved het-erogeneities to be drawn from more general...

Quantile factor models (QFM) represent a new class of factor models for high-dimensional panel data. Unlike approximate factor models (AFM), which only extract mean factors, QFM also allow unobserved factors to shift other relevant parts of the distributions of observables. We propose a quantile...