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Nonparametric maximum likelihood methods for binary response models with random coefficients by Roger Koenker

Date: 12:30 16 October 2018 - 13:30 16 October 2018
Type: Seminar
Speaker: Roger Koenker UCL
Venue: Institute for Fiscal Studies
Prices: Free

Description

Single index linear models for binary response with random coefficients have been
extensively employed in many econometric settings under various parametric specifications of
the distribution of the random coefficients.  Nonparametric maximum likelihood estimation
(NPMLE) as proposed by Cosslett (1983) and Ichimura and Thompson (1998) in contrast, has
 received less attention in applied work due primarily to computational difficulties.
 We propose a new approach to computation of NPMLEs for binary response
 models that significantly increase their computational tractability
 thereby facilitating greater flexibility in applications.  Our approach, which relies on
 recent developments involving the geometry of hyperplane arrangements, is contrasted
 with the recently proposed deconvolution method of Gautier and Kitamura (2013).  An application to
 modal choice for the journey to work in the Washington DC area illustrates the methods.

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