Data Projects

Climate Impacts for Social Science Computing Platform

There are two sets of barriers that currently limit the ability of scholars across the social sciences to study the socioeconomic impacts of climate change. The first is the absence of high-quality, harmonized and georeferenced survey data. Of the six major barometers in political science, for example, only one, the Afrobarometer, includes coordinates that precisely locate respondents. The second set of barriers is primarily computational: researchers must generate valid estimates of climate exposures for tens or hundreds of thousands of locations for up to 30 years. This requires both facility with extremely large datasets (upwards of 150GB per product) and modern geospatial computing. These constraints are especially strong for scholars who lack access to cloud computing and the necessary background in climate econometrics.  

Our goal with this project is to solve both sets of challenges simultaneously by building two databases — one containing survey data, the other climate data — that work seamlessly together, allowing researchers to quickly find pre-harmonized survey data for their area of study and generate corresponding exposure measures without doing any user-side computation of any kind. A prototype version of the survey database, made possible by a previous King Seed grant, currently contains more than 1.1 million survey responses from 84 countries spanning nearly 30 years. To build out this database, we have developed a set of tools that leverages advances in natural language processing to provide unsupervised algorithmic solutions to the problem of geolocating, harmonizing and thematically grouping survey responses. 

Along with documentation that gives practical, accessible guidance to beginner users in the selection of competing climate products and the application of new approaches to dealing with measurement error bias in remotely sensed data, we intend to publish all tools used in the development of the databases as companion R packages, complete with an R-based API lookup that will allow users to query, download and save data directly from a console. Our goal is to build not just a single, static product but an ecosystem of connected products, complete with an online dashboard and a regularly updated list of survey locations, administrative units, and climate products.

Spatially Referenced Social Safety Net Program Database

The first wave of climate change funding in the developing world was focused around mitigation efforts. However, recognizing the amount of unavoidable warming and the slow pace of mitigation efforts, the international community has begun to build funding mechanisms explicitly designed to foster adaptation and resilience to climate change. As adaptation and resilience financing increases, there is a growing need to understand what policies are likely to be climate protective in a developing-country context. Yet the evidence base that policymakers can draw on in designing climate change adaptation policies is surprisingly small, with many of the most cited studies considering only a single government program in a single country. Our initiative addresses this gap and helps policymakers address what we view as the two most important questions in this space: what kinds of adaptation and resilience programs should national governments and international donors invest in? And at whom should these programs be targeted? 

There are two major challenges researchers face in answering these questions. The first is a problem of scale: the class of potentially climate-protective adaptation policies is enormous3, ranging from individual-level unconditional cash transfers to targeted local interventions to national-level welfare programs. The second is a problem of external validity: while researchers have recently begun to analyze the climate-protective effects of large government programs, such as PROGRESA in Mexico and NREGA in India, it is unclear whether those findings generalize to other countries with different levels of state capacity and baseline levels of development. Nonetheless, researchers and policymakers urgently need evidence that can inform how to craft optimal adaptation and resilience strategies. 

To address the scope and scale problem, we look backward rather than forward, utilizing existing databases from the World Bank, AidData and the Social Protection Project to identify thousands of already completed or currently active programs that may plausibly be climate protective. We then produce novel spatial extent data — essentially, digitized, time-varying maps that show where and when a project is active — that allow us to credibly estimate their climate-protective effects. The resulting database, which will be made publicly available for researchers and policymakers, will comprise thousands of projects that cover the entire spectrum of adaptation programs, allowing us for the first time to estimate global effects of specific types of programs on three critical outcomes: economic growth and agricultural output, political stability and conflict, and public health.