This article investigates estimation of censored quantile regression (QR) models with fixed effects. Standard available methods are not appropriate for estimation of a censored QR model with a large number of parameters or with covariates correlated with unobserved individual heterogeneity. Motivated by these limitations, the article proposes estimators that are obtained by applying fixed effects QR to subsets of observations selected either parametrically or nonparametrically. We derive the limiting distribution of the new estimators under joint limits, and conduct Monte Carlo simulations to assess their small sample performance. An empirical application of the method to study the impact of the 1964 Civil Rights Act on the black-white earnings gap is considered. Supplementary materials for this article are available online.
This paper investigates the extent to which technology used to automate household responses to time‐of‐use pricing for electricity leads to higher energy savings than simply providing households with information on current prices and quantities. Using a large randomized field trial, we find that informed households with “smart” thermostats achieve impressive reductions in consumption during on‐peak periods of up to 48 percent, but also engage in substantial load shifting to off‐peak hours. We also document the extent to which household responses to time‐of‐use pricing are heterogeneous and vary significantly by demographics, weather, and across the usage distribution.
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