Clearing up Trash Mountains: Measuring Willingness to Pay and Mortality Effects

SHREYA CHANDRA

India generates 277 million tonnes of waste each year, about 77% of which is left unprocessed and dumped in landfill sites. In most Indian mega-cities, these landfills, while originally intended to be located in the outskirts, are now well within city boundaries because of rapid urban expansion. Unsurprisingly, poor communities occupy these areas within cities. Most of the largest landfills were established many years before the Indian Government formally proposed Municipal Solid Waste (MSW) disposal guidelines in 2000. Due to poor regulation, these sites have been growing much beyond their planned volumes, continuing to impose immense environmental and economic damage for many years. In this project, we propose to ask two questions: first, we propose to estimate a new measure of willingness to pay that incorporates residential and firm re-sorting due to the location of the landfill and a spatial equilibrium model to estimate welfare gains from removing or re-locating the landfill. Second, we want to empirically quantify the health and economic impacts of these landfill sites on neighboring localities, and measure how (or whether) impacts decay with distance for a larger set of cities in India.

The Aerial History Project

SIMON GREENHILL

The Aerial History Project is digitizing and analyzing an archive of 1.6 million aerial images taken between 1940 and 1990. The archive includes images from large swaths of Africa, Asia, and islands in the Caribbean, Atlantic, and Pacific. We use machine learning techniques to combine the images into high-resolution mosaics similar to the images taken by modern-day satellites. We then develop and apply machine learning techniques to extract structured information from the images, such as road length, population density, forest cover, or land use. For many of the locations in the archive, contemporaneous records are sparse or nonexistent. For example, measures of forest cover at a comparable level of granularity are only available starting in 2000; measures of the spatial evolution of human settlement start in 1975; spatially resolved estimates of wealth, such as nighttime lights, begin only in 1992; and household surveys such as the Demographic and Health Surveys (DHS) and Living Standards Measurement Survey (LSMS) begin no earlier than 1985 and have sparse spatial and temporal coverage. In many cases, the information we extract from our images is the only information available on that place at that time.

We will use these data to conduct research on the long-run effects of various natural and economic phenomena on human development and environmental outcomes. Proposed topics include natural disasters such as hurricanes and droughts, infrastructure development, and decolonization. Importantly, because these data cover areas that were poor at the time the images were taken, and in many cases remain poor today, our work will have particular relevance for understanding the experience of disadvantaged populations.

The Impact of Different Roll-outs of Prepaid and Smart Meters on Consumers: Evidence from Senegal

ABDOULAYE CISSE

In order to reduce energy production losses, cope with delinquency losses and improve energy reliability, utility providers in developing countries have been rolling out new electricity technologies, including smart and prepaid meters. This project studies the welfare impact of the voluntary roll-outs of smart and prepaid meters in developing countries. It focuses on whether: (i) customers’ decision to adopt or not to adopt these technologies aligns with their welfare gains/losses from switching, (ii) customers delay adoption even when they could have benefitted from an early adoption, and (iii) adverse selection plays a role on the meter type that customers choose. To answer these questions, we rely on evidence from the adoption of smart and prepaid meters in Senegal. We use primary data and disaggregated electricity consumption and expenditures data from the Senegalese utility provider, Société Nationale d’Electricité du Senegal (SENELEC). We leverage various roll-outs and deployment strategies that the company has tested over the last 15 years.

How are Timber Farmers Adapting to the New Wildfire Landscape? Evidence from California’s Public Timber Auctions

KALEB JAVIER

In conversations with forestry professionals, a common narrative is that farms a decade ago were willing to bear the risk of wildfires, but now farmers are reluctant to own assets and work on timber stands that they view as being highly susceptible to wildfire damages. Currently there is little rigorous economic evidence to assess this claim. This research looks to fill this gap and provide the evidence needed to inform policymakers and forest managers about how the timber industry is changing their business decisions in the face of our new wildfire reality.

The Impact of Floods on Women’s Empowerment and Female Labor Force Participation in Rural India in the Age of Climate Change

Elena stacy

Catastrophic floods are becoming more common as a result of climate change, and globally vulnerable populations are particularly at risk for their adverse effects. In the context of rural India, pervasive gender norms may lead women to be pushed out of the labor market and into the home more strongly following a flood event than during a typical economic shock, due to school closures and infrastructure damage related to flooding. This project proposes to investigate this hypothesis using satellite data to identify flood impacted villages, and subsequent time use survey data to measure how women are spending their time in the days following a flood compared to a typical day. This study aims to help prevent the female labor force from falling through the cracks as governments consider necessary coping mechanisms for the changing climate.