The Value of Clean Water: Evidence from an Environmental Disaster

Accesible PDF image
Peer Reviewed icon Peer Reviewed
Author
Gonzalez, Rodrigo Barbone ;
Silva, Thiago Christiano
Date issued
Dec 2023
Subject
Municipal Government;
Water Supply;
Environmental Impact;
Consumer Credit;
Payment System;
Disaster;
Water and Sanitation;
Gross Domestic Product;
Small Business;
Agriculture and Food Security;
Economy;
Service Provider
JEL code
C63 - Computational Techniques • Simulation Modeling;
G01 - Financial Crises;
G20 - Financial Institutions and Services: General;
G21 - Banks • Depository Institutions • Micro Finance Institutions • Mortgages;
G28 - Government Policy and Regulation;
O16 - Financial Markets • Saving and Capital Investment • Corporate Finance and Governance;
O40 - Economic Growth and Aggregate Productivity: General
Country
Brazil
Category
Working Papers
Clean water has a largely unknown economic value, particularly to small communities whose agricultural activities take place on river shores. In November 2015, the rupture of a mining tailings dam in the municipality of Mariana led to a record disposal of toxic residuals in southeast Brazil. A mud avalanche ran out for 600 km (373 miles) until it reached the Atlantic Ocean, leaving behind extreme ecological and economic damage in the Doce River basin. This is the largest environmental disaster in Brazil to date. We quantify the negative externalities using rich, identified, and comprehensive data from firm-to-firm electronic payments and individual-level consumer credit usage. We find that agricultural producers in affected municipalities received cumulatively 41% to 60% fewer inflows (income) from customer firms outside the affected zone three years after the disaster. Effects are driven by municipalities where the river shore is larger relative to the farming area. In these municipalities, individuals also faced an 8% fall in their credit card and consumer finance expenditures. This result is stronger for non-formal and high-risk workers. Thus, water contamination led to (first) production and (later) consumption decline with real effects on municipality-level agriculture and services output, causing a 7% decline in local GDP.
Generative AI enabled