@article{Chen:269326,
      recid = {269326},
      author = {Chen, Mingli},
      title = {Estimation of Nonlinear Panel Models with Multiple  Unobserved Effects},
      address = {2016-03-03},
      number = {2068-2018-1286},
      series = {WERP 1120},
      pages = {46},
      year = {2016},
      abstract = {I propose a xed eects expectation-maximization (EM)  estimator that can be applied to a class of nonlinear panel  data models with unobserved heterogeneity, which is modeled  as individual eects and/or time eects. Of particular  interest is the case of interactive eects, i.e. when the  unobserved heterogeneity is modeled as a factor analytical  structure. The estimator is obtained through a  computationally simple, iterative two-step procedure, where  the two steps have closed form solutions. I show that  estimator is consistent in large panels and derive the  asymptotic distribution for the case of the probit with  interactive eects. I develop analytical bias corrections to  deal with the incidental parameter problem. Monte Carlo  experiments demonstrate that the proposed estimator has  good nite-sample properties.},
      url = {http://ageconsearch.umn.edu/record/269326},
      doi = {https://doi.org/10.22004/ag.econ.269326},
}