Browsing by Author "Jordan, Felipe"

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    The diversity we breath: Community diversity and gas leak management
    (2024) Jordan, Felipe; Di Gregorio, Enrico
    Diversity might reduce the ability of small-scale communities to protect local resources through its adverse impact on collective action and individual attachment. Using geocoded data on more than 1500 Grade-3 gas leaks in 2016 across Boston and Cambridge, MA, we show that when a leak emerges in a narrowly-defined area with higher ethno-racial fractionalization it enjoys lower chances of end-year reparation. After accounting for socio-economic and infrastructural factors, our preferred estimate suggests that moving from the 10th to the 90th percentile of the fractionalization distribution is associated to a 5.7 percentage point decrease in the probability of reparation, compared with an already low average of 3.7%. This result is robust to different definitions of the community surrounding a leak and to the inclusion of competing measures of diversity. Consistent with our framework, social capital appears to be especially lower in communities fragmented across ethno-racial lines. In turn, lower social capital is negatively associated to leak reparation.
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    Using Satellite Images and Deep Learning to Measure Health and Living Standards in India
    (2023) Daoud, Adel; Jordan, Felipe; Sharma, Makkunda; Johansson, Fredrik; Dubhashi, Devdatt; Paul, Sourabh; Banerjee, Subhashis
    Using deep learning with satellite images enhances our understanding of human development at a granular spatial and temporal level. Most studies have focused on Africa and on a narrow set of asset-based indicators. This article leverages georeferenced village-level census data from across 40% of the population of India to train deep models that predicts 16 indicators of human well-being from Landsat 7 imagery. Based on the principles of transfer learning, the census-based model is used as a feature extractor to train another model that predicts an even larger set of developmental variables-over 90 variables-included in two rounds of the National Family Health Survey (NFHS). The census-based-feature-extractor model outperforms the current standard in the literature for most of these NFHS variables. Overall, the results show that combining satellite data with Indian Census data unlocks rich information for training deep models that track human development at an unprecedented geographical and temporal resolution.
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    Varieties of capitalism and environmental performance
    (2025) Jordan, Felipe
    This paper investigates the role of institutions in decoupling economic growth from environmental impacts, employing the Varieties of Capitalism framework. It finds that Northern European countries have achieved more significant decoupling than other Western OECD countries since the 1980s, as measured by the Ecological Footprint of Consumption. Differences in corporatism, as well as the amount and type of public social expenditures, are hypothesized to play a crucial role in explaining this pattern. Multiple regression analysis reveals that larger proportions of GDP allocated to universal social expenditures - not contingent on work status - are robustly associated with stronger decoupling. This suggests that the considerable investments of Northern European countries in universal social benefits have been key for effectively reducing environmental impacts associated with economic growth.