Large potential reduction in economic damages under UN mitigation targets
with Marshall Burke and Noah S. Diffenbaugh (2018)
Nature, 557, 549–553
We present an empirical framework for evaluating the economic benefits of the 2015 Paris Agreement’s temperature targets of 1.5°C and 2.0°. Our findings decompose the enormous uncertainty in such forecasting exercises and stress the inequity in impacts: it is a stark result that poorer countries that have historically contributed least to carbon emissions will likely be impacted most.
Citations: New York Times and Guardian fact-checking | Governors of New York, California, and Washington | IPCC Special Report | MSNBC (TV) | “The Uninhabitable Earth” by David Wallace-Wells | Germany’s Rezo ahead of 2019 EP elections | | 2019 US Presidential Candidate Bernie Sanders | US House Committee on Financial Services
Combining satellite imagery and machine learning to predict poverty
with Neal Jean, Marshall Burke, Michael Xie, David B. Lobell, and Stefano Ermon (2016)
Science, 353 (6301), 790-794.
We train a convolutional neural network to identify low-level features of image data useful for classification tasks. We then assign the CNN the related task of condensing high-resolution daytime satellite images into lower-dimensional vectors of features covariant with the areas’ corresponding night-time luminosities, which we consider imperfect proxies for levels of economic activity. Ridge regression models then relate these feature vectors to data from representative household surveys conducted in Uganda, Tanzania, Nigeria, Malawi, and Rwanda to generate fine-scale “poverty maps”, regionally disaggregated estimates of the distribution of consumption expenditure and asset wealth. Cross-validation analyses show that our transfer learning method compares favorably to existing and expensive methods at out-of-sample prediction, suggesting potential applications for interventions targeting poverty in data-scarce areas. We emphasize our pipeline uses only public data and software, enabling cheap replication and potential scalability to complement the infrequency and often-prohibitive expense of household surveys.
Dispersion of temperature exposure and economic growth: panel evidence with implications for climate change and global inequality
Graduate thesis supervised by Elizabeth Baldwin and David F. Hendry (2019)
Oxford’s first ‘exceptional’-class (mark of 80+) economics thesis in at least four years
Preliminary draft available upon request, comments very welcome