Governments and NGOs worldwide use subsidies to improve the adoption of beneficial domestic technologies. However, these subsidies may be mistargeted if the benefits come from the continued use of the technology, which is not guaranteed by its initial takeup. The government of Mexico City provides 10,000 households annually with a system to collect rainwater for all non-drinking purposes. The technology is distributed for free on a first-come, first-served basis among all residents of selected neighborhoods. Nonetheless, some households do not use the technology after receiving it and thus do not benefit. To investigate this misallocation issue, I collected survey data to estimate the heterogeneous effects of the Rainwater Harvesting Program across households with different levels of unobserved willingness to pay (WTP). I analyze these data econometrically by combining contingent valuation methods with a potential outcomes framework. I find that households'  WTP for the technology predicts its usage and benefits, controlling for sociodemographic characteristics. For high-WTP households, the technology saves up to 8 hours per week in water procurement time and makes them 40 percentage points less likely to postpone daily activities due to lack of water. By contrast, less than 35 percent of low-WTP households use the technology, yielding negligible benefits. Counterfactual policy simulations show that lowering the subsidy rate by about 1 percentage point reduces the abandonment of the RWH system by 20 percent and water restrictions by up to 16 percent by discouraging low-WTP households from enrolling.   

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. 

This project explores different barriers to the long-term adoption of the RWH system. Engineers predict the amount and quality of rainwater collected using this technology to depend on adequate maintenance. Maintenance tasks are time-consuming and may constitute a mental load, preventing some households from engaging in them. We investigate two possible explanations for low maintenance adherence: individuals could have a high cognitive cost of engaging in maintenance or could perceive little returns if they obtain low volumes or low water quality after performing maintenance. For this ongoing pilot intervention, we randomized 100 system owners into a control group and two treatment arms: (i) an SMS service of reminders on maintenance actions and (ii) a free maintenance service provided by trained technicians every two weeks. We periodically collect objective and perceived measures of water volumes and quality and maintenance indicators across treatments. Next year, we expect to scale this intervention to explore specific policy tools to incentivize proper maintenance and adoption.

This paper studies household budgeting decisions related to energy consumption. Specifically, we investigate how overall consumer spending responds to changes in gasoline prices and whether responses vary across the income distribution. For identification, we use the differential impact of abrupt gasoline price changes across geographical areas in Mexico. In early 2019, the government shut down pipelines nationwide as part of its security policy to prevent fuel theft, causing disruptions to gasoline transportation and shortages. Using daily data on inflows and outflows in all storage terminals and prices at the retail station level, we show that gasoline retail prices rose sharply in areas traditionally supplied by pipelines but less so in areas served by tanker boats or trains. Our next step is to gather consumption data using household-based scanner data or point-of-sale data to estimate changes in consumption patterns around this period. 

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.