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First-differencing in panel data models with incidental functions

Koen Jochmans
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Abstract

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 unobserved heterogeneity from the differenced model. Conventional estimation techniques can then be readily applied. Distribution theory for a kernel-weighted GMM estimator under large-n and fixed-T asymptotics is developed. The estimator is put to work in a series of numerical experiments to static and dynamic models.
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hal-01069454 , version 1 (29-09-2014)

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Koen Jochmans. First-differencing in panel data models with incidental functions. 2010. ⟨hal-01069454⟩
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