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Bayesian estimation of the exact affine Stone index demand system: Replicating the Lewbel and Pendakur (2009) results
Author(s) -
RamírezHassan Andrés
Publication year - 2021
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.2814
Subject(s) - censoring (clinical trials) , endogeneity , bayesian probability , bayesian inference , affine transformation , inference , monotonic function , index (typography) , mathematics , econometrics , bayes estimator , computer science , nonlinear system , mathematical optimization , statistics , artificial intelligence , mathematical analysis , physics , quantum mechanics , world wide web , pure mathematics
Summary This paper proposes a Bayesian approach to perform inference in the exact affine Stone index (EASI) demand system that was proposed by Lewbel and Pendakur (2009), while taking into account nonlinearity and endogeneity. A Bayesian approach enables us to easily handle censored data, test and impose inequality restrictions (strict cost monotonicity) and concavity of the cost function, and perform inference of nonlinear functions of the parameter estimates as by‐product of the posterior chains. We compare our proposal with Lewbel and Pendakur (2009)'s results, based on iterative linear three‐stage least squares (3SLS). Although we found no statistically significant differences in point estimates between these two approaches, it seems that ignoring censoring overestimates precision.