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Estimation of Nonlinear Models with Unobserved Heterogeneity

Final Report Summary - ENMUH (Estimation of Nonlinear Models with Unobserved Heterogeneity)

The project deals with identification and estimation of nonlinear models with unobserved heterogeneity using panel data. The main achievement so far has been the development of a general approach based on projection ideas that generalizes the standard within-group method for linear models ("functional differencing"). Other achievements include the development of a technique to allow for time-varying paths of unobserved heterogeneity, the introduction of a general estimation approach based on linear quantile specifications, and a new approach to estimate finite mixture models.