A constructive proof of identification of multilinear decompositions of multiway arrays is presented. It can be applied to show identification in a variety of multivariate latent structures. Examples are finite-mixture models and hidden Markov models. The key step to show identification is the...

The aim of this paper is to provide simple nonparametric methods to estimate finitemixture 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...

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In this paper, we document whether and how much the equalizing force of earnings mobility has changed in France in the 1990’s. 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...

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...

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...

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,...

Maximum-likelihood estimation of nonlinear models with fixed effects is subject to the incidental-parameter problem. This typically implies that point estimates suffer from large bias and confidence intervals have poor coverage. This paper presents a jackknife method to reduce this bias and to...

We calculate the bias of the profile score for the regression coefficients in a multistratum autoregressive model with stratum-specific intercepts. The bias is free of incidental parameters. Centering the profile score delivers an unbiased estimating equation and, upon integration, an adjusted...

We propose a jackknife for reducing the order of the bias of maximum likelihood estimates of nonlinear dynamic fixed-effect panel models.