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Addressing Household Water Vulnerabilities in U.S. Cities


Term:

Fall

Department:

11: Urban Studies and Planning

Faculty Supervisor:

Gabriella Carolini and Lawrence Susskind

Faculty email:

carolini@mit.edu

Apply by:

September 13th, 2020

Contact:

Winn Costantini, Graduate Research Assistant, winncos@mit.edu

Project Description

Steeply rising water rates have outpaced low-income customers’ ability to pay, especially in cities with aging infrastructure. Mass water disconnections and spatial concentrations of water poverty are signaling the worsening of a water affordability crisis in urban America, particularly in communities of color. Advocates have asserted a human right to water, and criticized utilities’ use of water shutoffs, tax sales, and foreclosures as tools for collecting unpaid bills. We propose to work with all the relevant stakeholders to invent alternatives to shutoffs. Our aim is to promote socially equitable and financially sustainable solutions that will make drinking water affordable for all urban residents, regardless of their income, class and race. Our research seeks to understand the relationship between shut-offs, water tax sales, and foreclosures across different U.S. cities, as well as what segments of the population are affected by each element in this cycle. Additionally, our research will address if and how COVID-19 exacerbated trends in these three phenomena across urban micro-geographies (e.g., neighborhoods) and communities (e.g., by race/ethnicity/income). Our research is conducted using information from interviews, document reviews, policy and program evaluation, Freedom of Information Act requests, and spatial statistical analysis.

Pre-requisites

This is a remote research assistant position. No prior experience or coursework is required. We are particularly interested in students with a demonstrated interest in racial and social justice, public health, and/or municipal finance. Experience with spatial statistical analysis and/or social science research methods is preferred. Experience with GIS and/or R would also be helpful. Students will be expected to work X hours per week.