Nonparametric estimation of non-exchangeable latent-variable models

Stéphane Bonhomme, Koen Jochmans and Jean-Marc Robin

Journal of Econometrics, 2017, vol. 201, issue 2, 237-248

Abstract: We propose a two-step method to nonparametrically estimate multivariate models in which the observed outcomes are independent conditional on a discrete latent variable. Applications include microeconometric models with unobserved types of agents, regime-switching models, and models with misclassification error. In the first step, we estimate weights that transform moments of the marginal distribution of the data into moments of the conditional distribution of the data for given values of the latent variable. In the second step, these conditional moments are estimated as weighted sample averages. We illustrate the method by estimating a model of wages with unobserved heterogeneity on PSID data.

Keywords: Latent variable models; Unobserved heterogeneity; Finite mixtures; Hidden Markov models; Nonparametric estimation; Panel data; Wage dynamics (search for similar items in EconPapers)
JEL-codes: C14 C33 C38 J31 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Related works:
Working Paper: Nonparametric estimation of non-exchangeable latent-variable models (2017)
Working Paper: Nonparametric estimation of non-exchangeable latent-variable models (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:201:y:2017:i:2:p:237-248

DOI: 10.1016/j.jeconom.2017.08.006

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