Show Summary Details

Page of

PRINTED FROM OXFORD HANDBOOKS ONLINE ( © Oxford University Press, 2018. All Rights Reserved. Under the terms of the licence agreement, an individual user may print out a PDF of a single chapter of a title in Oxford Handbooks Online for personal use (for details see Privacy Policy and Legal Notice).

date: 15 November 2019

Abstract and Keywords

Special regressor methods are growing in popularity in econometric theory and applications, particularly in models involving binary and multinomial choice. These methods are used for uncovering features of latent variables, errors, and indices in models with discrete, censored, or otherwise limited dependent variables. Special regressors are particularly useful for obtaining point identification in models where latent errors have unknown distributions that may be heteroskedastic or correlated with regressors in unknown ways. Through a sequence of increasingly richer models, this chapter explains the general theory and application of special regressor methods for identification and estimation.

Keywords: special regressor, binary choice, identification, endogeneity, threshold crossing, linear index, latent index, willingness to pay

Access to the complete content on Oxford Handbooks Online requires a subscription or purchase. Public users are able to search the site and view the abstracts and keywords for each book and chapter without a subscription.

Please subscribe or login to access full text content.

If you have purchased a print title that contains an access token, please see the token for information about how to register your code.

For questions on access or troubleshooting, please check our FAQs, and if you can''t find the answer there, please contact us.