centre for microdata methods and practice

ESRC centre

cemmap is an ESRC research centre


Keep in touch

Subscribe to cemmap news

Nonparametric maximum likelihood methods for binary response models with random coefficients

Authors: Jiaying Gu and Roger Koenker
Date: 21 November 2018
Type: cemmap Working Paper, CWP65/18
DOI: 10.1920/wp.cem.2018.6518


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 diffi culties. We propose a new approach to computation of NPMLEs for binary response models that signi cantly increase their computational tractability thereby facilitating greater exibility 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.

Download full version

Search cemmap

Search by title, topic or name.

Contact cemmap

Centre for Microdata Methods and Practice

How to find us

Tel: +44 (0)20 7291 4800

E-mail us