A multiple indicator solution approach to endogeneity in discrete-choice models for environmental valuation

Abstract

Endogeneity is an often neglected issue in empirical applications of discrete choice modelling despite its severe consequences in terms of inconsistent parameter estimation and biased welfare measures. This article analyses the performance of the multiple indicator solution method to deal with endogeneity arising from omitted explanatory variables in discrete choice models for environmental valuation. We also propose and illustrate a factor analysis procedure for the selection of the indicators in practice. Additionally, the performance of this method is compared with the recently proposed hybrid choice modelling framework. In an empirical application we find that the multiple indicator solution method and the hybrid model approach provide similar results in terms of welfare estimates, although the multiple indicator solution method is more parsimonious and notably easier to implement. The empirical results open a path to explore the performance of this method when endogeneity is thought to have a different cause or under a different set of indicators.