Tracking GDP in real-time using electricity market data: Insights from the first wave of COVID-19 across Europe.

This paper develops a methodology for tracking in real-time the impact of shocks (such as natural disasters, financial crises or pandemics) on gross domestic product (GDP) by analyzing high-frequency electricity market data. As an illustration, we estimate the GDP loss caused by COVID-19 in twelve European countries during the first wave of the pandemic. Our results are almost indistinguishable from the official statistics during the first two quarters of 2020 (the correlation coefficient is 0.

Real-Time Estimation of the Short-Run Impact of COVID-19 on Economic Activity Using Electricity Market Data.

In response to the COVID-19 emergency, many countries have introduced a series of social-distancing measures including lockdowns and businesses' shutdowns, in an attempt to curb the spread of the infection. Accordingly, the pandemic has been generating unprecedented disruption on practically every aspect of society. This paper demonstrates that high-frequency electricity market data can be used to estimate the causal, short-run impacts of COVID-19 on the economy, providing information that is essential for shaping future lockdown policy.

On the Use of Nudges to Affect Spillovers in Environmental Behaviors.

Environmental self-identity is considered a promising lever to generate positive spillovers across pro-environmental behaviors: existing evidence shows that it is positively correlated with pro-environmental choices and that it can be easily manipulated, by reminding individuals of their past pro-environmental actions. However, it remains unclear whether it can be successfully used for environmental policy making. In two online, incentive-compatible experiments, we manipulate participants' environmental self-identity and test whether this leads to increased donations to an environmental charity.