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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

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