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Unformatted text preview: Estimating and Testing a Quantile Regression Model with Interactive Effects Matthew Harding 1 and Carlos Lamarche 2 1 Stanford University 2 University of Oklahoma California Econometrics Conference, Sept 24, 2010 1 / 50 Estimating and Testing a Quantile Regression Model with Interactive Effects Motivation Motivation Classical least squares methods for panel data are often inadequate for empirical analysis. They deal with individual heterogeneity, but fail to estimate effects other than the mean. Koenker (2004), Lamarche (2010), Harding and Lamarche (2009), Abrevaya and Dahl (2008) suggest approaches but their use is limited under general conditions. Limitation They assume that latent heterogeneity has the classical additively separable, timeinvariant structure. 2 / 50 Estimating and Testing a Quantile Regression Model with Interactive Effects Motivation Motivation Classical least squares methods for panel data are often inadequate for empirical analysis. They deal with individual heterogeneity, but fail to estimate effects other than the mean. Koenker (2004), Lamarche (2010), Harding and Lamarche (2009), Abrevaya and Dahl (2008) suggest approaches but their use is limited under general conditions. Limitation They assume that latent heterogeneity has the classical additively separable, timeinvariant structure. 2 / 50 Estimating and Testing a Quantile Regression Model with Interactive Effects Motivation Motivation Classical least squares methods for panel data are often inadequate for empirical analysis. They deal with individual heterogeneity, but fail to estimate effects other than the mean. Koenker (2004), Lamarche (2010), Harding and Lamarche (2009), Abrevaya and Dahl (2008) suggest approaches but their use is limited under general conditions. Limitation They assume that latent heterogeneity has the classical additively separable, timeinvariant structure. 2 / 50 Estimating and Testing a Quantile Regression Model with Interactive Effects Motivation Motivation Classical least squares methods for panel data are often inadequate for empirical analysis. They deal with individual heterogeneity, but fail to estimate effects other than the mean. Koenker (2004) , Lamarche (2010) , Harding and Lamarche (2009) , Abrevaya and Dahl (2008) suggest approaches but their use is limited under general conditions. Limitation They assume that latent heterogeneity has the classical additively separable, timeinvariant structure. 2 / 50 Estimating and Testing a Quantile Regression Model with Interactive Effects Motivation Motivation Classical least squares methods for panel data are often inadequate for empirical analysis. They deal with individual heterogeneity, but fail to estimate effects other than the mean....
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This note was uploaded on 12/26/2011 for the course ECON 245a taught by Professor Staff during the Fall '08 term at UCSB.
 Fall '08
 Staff
 Econometrics

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