Conference Agenda

When exposed to heat waves, air conditioning (AC) serves as the primary means of preventing heat-related health risks, including mortality. However, surges in cooling demand can disrupt the balance between electricity supply and demand, potentially leading to large-scale blackouts. This study examines households' cooling demand during an extreme heat wave in California in September 2022. During this period, a 10-day event drove electricity demand to historic highs, bringing the state government close to implementing rotating outages and ultimately leading to the issuance of an emergency alert to conserve electricity. We analyze this event using large-scale, high-frequency data from networked thermostats. We first investigate the sensitivity of AC usage to extremely high outdoor temperatures by regressing AC usage for more than 10,000 households on temperature bins up to 110°F. Our results indicate that cooling demand continues to rise with temperature, even at extremely high temperatures. This increase is likely driven by increased air conditioner operation, rather than by active human behaviors such as setpoint overriding. These patterns suggest that many AC systems are oversized. We then evaluate household responses to the government request to save energy, which targeted hot and populated counties. To credibly compare targeted and untargeted households, we apply a matching difference-in-differences approach. Our estimates indicate that AC usage is not responsive to the government's request, and the reduction in its usage is small. These findings underscore the challenges of maintaining the balance between electricity supply and demand during future, more intense heat waves.

Many European companies face the challenge of lowering CO2 emissions from their company car fleets. A promising lever is to increase the notoriously low electric usage of Plug-in Hybrid Electric Vehicles (PHEVs). This paper examines whether home charging infrastructure can help achieve these goals. We leverage quasi-experimental variation in the delivery and installation of home chargers to quantify the impact of this technology on energy use and CO2 emissions of PHEV company cars held by 856 employees of a large German company. Since fuel and electricity expenditures for these cars are covered by the employer, home charging mainly changes the non-monetary costs to an employee. We find that access to home charging increases electricity consumption by 317.9 kWh per quarter and decreases fuel consumption by 97.97 liters, reducing CO2 emissions by 38%. Moreover, access to home charging increases the employee's propensity to choose a Battery Electric Vehicle (BEV) upon renewal of the lease by 28.4 percentage points.

We use these estimates to compute the private levelized abatement costs of home chargers for a range of scenarios characterizing the diffusion of BEVs and the effect of the program on vehicle choice. With current tax-inclusive energy prices, home chargers break even for the company within eight to 16 years.

The objective of this analysis is to investigate household water affordability across 26 municipalities in the state of Chihuahua, Mexico. This arid region faces significant challenges due to income disparities, diverse municipal pricing structures, and environmental constraints. The analysis is based on unique combination of data, including the National Survey of Household Income and Expenditures (ENIGH) for 2022, collected municipal pricing or rate structures, and a variety of both household level and regional control variables (e.g., weather and temperature). Household-level expenditure functions, for combined water and sewer services, are estimated econometrically, while lacking direct demand (consumption) data, the analysis allows derivation and estimation of both price and income elasticities of water demand. Results reveal that municipal water demand remains relatively price inelastic, as expected, but is approaching unitary elasticity, posing risks for utility revenue generation in raising rates. Consistent with Engel’s Law, expenditures are declining as a share of household income. There are significant affordability challenges, as against a sample median of 1.5%, low-income households spend an average of 4.49% of their income on water services, with some spending as much as 21.32%. These findings underscore the need for targeted policies, such as tiered pricing and subsidies, to reduce the financial burden on vulnerable households while balancing utility revenue, conservation, and sustainability goals.

This paper examines the relative contributions of siting decisions and post-siting demographic shifts to current disparities in exposure to polluting fossil-fuel plants in the United States. Our analysis leverages newly digitized data on power plant siting and operations from 1900-2020, combined with spatially resolved demographics and population data from the U.S Census from 1870-2020. We find little evidence that fossil-fuel plants were disproportionately sited in counties with higher Black population shares on average. However, event study estimates indicate that Black population share grows in the decades after the first fossil-fuel plant is built in a county, with average increases in Black population share of 4 percentage points in the 50-70 years after first siting. These long-run demographic shifts are driven by counties that first hosted a fossil-fuel plant between 1900-1949. We are in the process of extending the analysis of siting and sorting by examining the effects of income at the county level starting in 1900 and the effects of income and race at the census tract level starting in 1940. We close by exploring how these long-run demographic shifts were shaped by the Great Migration, differential sorting in response to pollution, and other factors. We are also in the process of using InMAP, an air transport model, and power plant level fuel consumption, to examine the effects of power plants on air pollution exposure. Our findings highlight that the equity implications of siting long-lived infrastructure can differ dramatically depending on the time span considered.