Researching the dynamics of residential electricity consumption at finely-resolved
timescales is increasingly practical with the growing availability of high-resolution data and …

We estimate consumer response to the first large-scale real-time electricity pricing (RTP)
program. In 2015, RTP became the default tariff for residential customers in Spain, exposing …

Demand-side flexibility which reacts to hourly price signals is expected to play an essential
role in balancing intermittent electricity generation in the future carbon-neutral power …

This study examines a field experiment in Texas that includes pricing and informational
interventions to encourage energy conservation during summer peak load days when the …

The residential sector's electricity consumption during peak hours is significant. Reducing it
would be valuable in economic and environmental terms, particularly for isolated grids and …

The success of time-of-use (TOU) pricing, where consumers are charged higher rates during
peak usage windows, depends on consumer flexibility—an assumption that may not be true …

Addressing climate change requires full decarbonization of our economies. Whether this
objective is achieved at least cost for society hinges on good policy design. In turn, this calls …

This article reviews recent endeavors to incorporate big data and machine learning
techniques into energy and environmental economics research. We find that novel datasets …

This paper proposes a quantile regression estimator for a heterogeneous panel model with
lagged dependent variables and interactive effects. The paper adopts the Common …

I apply and extend a new machine-learning method to estimate heterogeneous electricity
demand responses to time-varying prices in an experiment on Irish households. The most …