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A dynamic ordered logit model with fixed effects

Chris Muris, Pedro Raposo, Sotiris Vandoros

arXiv 12 Aug 2020 · Econometrics · publishedThe Review of Economics and Statistics (2020)

arXiv:2008.05517 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We study a fixed-$T$ panel data logit model for ordered outcomes that accommodates fixed effects and state dependence. We provide identification results for the autoregressive parameter, regression coefficients, and the threshold parameters in this model. Our results require only four observations on the outcome variable. We provide conditions under which a composite conditional maximum likelihood estimator is consistent and asymptotically normal. We use our estimator to explore the determinants of self-reported health in a panel of European countries over the period 2003-2016. We find that: (i) the autoregressive parameter is positive and analogous to a linear AR(1) coefficient of about 0.25, indicating persistence in health status; (ii) the association between income and health becomes insignificant once we control for unobserved heterogeneity and persistence.

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1Semiparametric Dynamic Logit Model with Endogenous Networks1.00053
2Dynamic Ordered Panel Logit Models0.90984
3The Projection Solution to the Incidental Parameter Problem0.51121
4Identification of Dynamic Panel Logit Models with Fixed Effects We thank Victor Aguirregabiria, Roger Koenker, Ismael Mourifié and Stanislav Volgushev for useful discussion. We are grateful to numerous seminar participants for their feedback, and are especially grateful to Francesca Molinari and three anonymous referees for their helpful comments. All errors are our own0.40511
5Transition Probabilities and Moment Restrictions in Dynamic Fixed Effects Logit Models0.40511