Welfare Gains of the Poor: An Endogenous Bayesian Approach with Spatial Random Effects

Abstract

We introduce a Bayesian instrumental variable procedure with spatial random effects that handles endogeneity, and spatial dependence with unobserved heterogeneity. We find through a limited Monte Carlo experiment that our proposal works well in terms of point estimates and prediction. Then, we apply our method to analyze the welfare effects on the poorest households generated by a process of electricity tariff unification. In particular, we deduce an Equivalent Variation measure where there is a budget constraint for a twotiered pricing scheme, and find that 10% of the poorest municipalities attained welfare gains above 2% of their initial income.JEL Classification: C11, C15, D11, D12, D60

Semi-parametric estimation of the EASI model: Welfare implications of taxes identifying clusters due to unobserved preference heterogeneity

“…There are remarkable welfare analysis due to price changes using demand systems, for instance, Banks et al (1997) and Lewbel and Pendakur (2009). In particular, previous studies analyzing implications associated with electricity price changes are Schulte and Heindl (2017); Tovar and Wölfing (2018); Pereira et al (2019); Ramírez-Hassan and Montoya-Blandón (2019). The latter two use univariate demand approaches, whereas the former two use demand systems.…”