I discuss the fixed-effect estimation of panel data models with time-varying excess heterogeneity across cross-sectional units. These latent components are not given a parametric form. A modification to traditional first-differencing is motivated which, asymptotically, removes the permanent...

This paper presents simple approaches to deal with sample selection in models with multiplicative errors. GMM estimators are constructed for both cross-section data and for panel data. These estimators build only on a specification of the conditional mean of the outcome of interest and are,...

This note shows that the asymptotic variance of Chen’s [Econometrica, 70, 4 (2002), 1683–1697] two-step estimator of the link function in a linear transformation model depends on the first-step estimator of the index coefficients.

Empirical models for panel data frequently feature fixed effects in both directions of the panel. Settings where this is prevalent include student-teacher interaction, the allocation of workers to firms, and the import-export flows between countries. Estimation of such fixed-effect models is...

We present a constructive identification proof of p-linear decompositions of q-way arrays. The analysis is based on the joint spectral decomposition of a set of matrices. It has applications in the analysis of a variety of latent-structure models, such as q-variate mixtures of p distributions....

The aim of this paper is to provide simple nonparametric methods to estimate finite mixture models from data with repeated measurements. Three measurements suffice for the mixture to be fully identified and so our approach can be used even with very short panel data. We provide distribution...

In this paper, we document whether and how much the equalizing force of earnings mobility has changed in France in the 1990s. For this purpose, we use a representative three-year panel,the French Labour Force Survey. We develop a model of earnings dynamics that combines a flexible specification...

We study linear factor models under the assumptions that factors are mutually independent and independent of errors, and errors can be correlated to some extent. Under factor non-Gaussianity, second to fourth-order moments are shown to yield full identification of the matrix of factor loadings....

In this paper,we construct a nonparametric estimator of the distributions of latent factors in linear independent multi-factor models under the assumption that factor loadings are known. Our approach allows to estimate the distributions of up to L(L+1)/2 factors given L measurements. The...