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 Semi- and Non-Parametric Econometric Methods
This short course will provide a survey of the econometrics literature on semiparametric and nonparametric models and estimation methods. After a review of asymptotic theory for estimation (including maximum likelihood and generalized method of moments estimation), the course will cover the basic large sample properties of nonparametric (kernel) estimators of density and regression functions, and then cover semiparametric assumptions and estimation methods for several limited dependent variable models, including binary response, censored regression, and sample selection models. The course will conclude with discussions of more recent literature on semi- and nonparametric models for panel data and endogenous regressors. Click here for a list of topics that will be covered and suggested readings.
If you would like to book a place or have any queries about this event, please contact our events team.
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 The following links should give you any extra information you may need with regard to IFS events. 
James Powell , University of California, Berkeley
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