Governments and NGOs worldwide use subsidies to promote the adoption of beneficial household technologies. However, these subsidies may be mistargeted when the benefits depend on continued use, which is not guaranteed by initial take-up. I study this misallocation issue in Mexico City’s Rainwater Harvesting (RWH) Program, which distributes 10,000 free RWH systems annually on a first-come, first-served basis. Using program evaluation methods and instrumenting program participation with contingent valuation responses, I estimate treatment effects along the distribution of unobserved willingness to pay (WTP). I find that households’ ex-ante WTP strongly predicts ex-post system usage and realized benefits, after accounting for sociodemographics. High-WTP households save roughly 5 hours per week in water-collection time and reduce postponements of daily activities due to water scarcity by 25 pp. In contrast, low-WTP households make limited use of the system and experience negligible benefits. Counterfactual simulations show that reducing the subsidy rate from 100% to about 97% would screen out households whose expected usage is 20 pp below average. This simple approach can inform subsidy calibration in settings where incentivized experiments or randomized pricing interventions are infeasible.   

Increasing block pricing schemes represent difficulties for applied researchers who try to recover demand parameters, in particular, price and income elasticities. The Mexican residential electricity tariff structure is amongst the most intricate around the globe. In this paper, we estimate the residential electricity demand and use the corresponding structural parameter estimates to simulate an energy efficiency improvement scenario, as suggested by the Energy Transition Law of December 2015. The simulated program consists of a massive replacement of electric appliances (air conditioners, fans, refrigerators, washing machines, and lights) for more energy-efficient units. The main empirical findings are the following: in the main counterfactual scenario, the overall residential electricity consumption decreases 9.9% and the associated expenditure falls 11.3%. Additionally, the electricity subsidy decreases 7.5 billion of Mexican Pesos per year (i.e., 403 million of USD at the average exchange rate registered in 2017) and there is an annual cut in CO2 emissions of 3.9 million of tons. 

Water scarcity is becoming an increasingly pressing issue, prompting utilities and regulators to explore cost-effective strategies for reducing residential water consumption. While price-based policies are commonly used, empirical evidence suggests that they often have a limited impact. In collaboration with a public water utility in Colorado, we designed and implemented a randomized controlled trial to assess the effectiveness of informational interventions in reducing inefficient lawn irrigation practices. Using real-time data from advanced metering infrastructure (AMI), we identified irrigation episodes among 7,000 households during the summer of 2024. Our intervention delivered targeted alerts to customers who watered their lawns during inefficient daytime hours or exceeded the recommended irrigation frequency. We find that the intervention resulted in a 5% to 10% reduction in daytime irrigation events and a decrease in weekly irrigation frequency, depending on the treatment. Our preliminary evidence also indicates that total water use decreased by 4% among households that received alerts about irrigating too frequently, and remained largely unchanged among those that received alerts about irrigation timing.

We examine whether improving maintenance practices for existing domestic Rainwater Harvesting Systems can reduce household water insecurity and whether subsidies for rainwater collection can decrease water use from overburdened sources. This full-scale RCT builds on two pilots conducted in 2023–2024, which indicate that poor maintenance may be causing households to collect significantly less water than these systems are capable of delivering under ideal conditions. Our experiment, scheduled for 2026 in Mexico City, will randomly assign 750 households to one of four groups: information, hands-on training, professional maintenance, or control. Mid-season, half of the households will be offered a per-liter reward for the rainwater they collect. Our main outcome is the volume of rainwater collected, supplemented by water quality measures to explore behavioral drivers and perceived value. We will also assess impacts on time use and expenses. Outcomes will be measured using water meters installed by our team, at-home quality tests, and surveys. Our findings will evaluate the cost-effectiveness of strategies that lower barriers to effective system use, increasing benefits for households and returns for the city. Additionally, we will determine whether subsidizing sustainable sources can promote substitution away from overused sources as an alternative to politically difficult and often ineffective price changes.

Although forced displacement disproportionately affects low- and middle-income countries, where nearly 75 percent of the world’s refugees live, the bulk of relevant data currently comes from high-income countries. This project built on recent World Bank efforts to collect representative data on forcibly displaced peoples and their hosts in several countries to harmonize representative surveys covering ten countries that hosted displaced people in the 2015-2020 period. 

The resulting harmonized database can be accessed here. 

The findings from the harmonized surveys are summarized in three Policy Briefs.