Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2011.05839

Social Diversity and Spread of Pandemic: Evidence from India

Upasak Das·Udayan Rathore·Prasenjit Sarkhel
View original source ↗Read source document ↗Export metadata ↓

Abstract

Compliance with the public health guidelines during a pandemic requires coordinated community actions which might be undermined in socially diverse areas. In this paper, we assess the relationship between caste-group diversity and the spread of COVID-19 infection during the nationwide lockdown and unlocking period in India. On the extensive margin, we find that caste-homogeneous districts systematically took more days to cross the concentration thresholds of 50 to 500 cases. Estimates on the intensive margin, using daily cases, further show that caste-homogeneous districts experienced slower growth in infection. Overall, the effects of caste-group homogeneity remained positive and statistically significant for 2.5 months (about 76 days) after the beginning of the lockdown and weakened with subsequent phases of the lockdown. The results hold even after accounting for the emergence of initial hotspots before lockdown, broader diffusion patterns through daily fixed effects, region fixed effects, and dynamic administrative response through time-variant lagged COVID-19 fatalities at the district level. These effects are not found to be confounded by differential levels of testing and underreporting of cases in some states. Consistent estimates from bias-adjusted treatment effects also ensure that our findings remain robust even after accounting for other unobservables. We find suggestive evidence of higher engagement of community health workers in caste-homogenous localities, which further increased after the lockdown. We posit this as one potential channel that can explain our results. Our findings reveal how caste-group diversity can be used to identify potential hotspots during public health emergencies and emphasize the importance of community health workers and decentralized policy response.

Explore related subjects

econ.GNq-fin.EC

Keep this discovery

BibTeXRIS

Upasak Das, Udayan Rathore, Prasenjit Sarkhel. 2020-11-11. Social Diversity and Spread of Pandemic: Evidence from India. https://arxiv.org/abs/2011.05839

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Reducing Prescription Errors Through Information Intervention: A Field Experiment in Healthcare Operations

Drug-drug interaction (DDI) errors pose serious risks to patient safety. Existing decision-support systems often require physicians to respond to alerts, disrupting workflows and contributing to high override rates. We examine whether a non-mandatory information intervention can reduce DDI errors and foster learning. Using a randomized field experiment with India's largest electronic medical record platform, we analyze 2.81 million prescriptions from 1,700 physicians using a difference-in-differences design. Treatment physicians received real-time information highlighting DDI errors without being required to respond, while control physicians received no such information. The intervention reduced DDI errors by 8.6%, corresponding to an estimated US$4.8 million in annual hospitalization cost savings and approximately 134 lives potentially saved. We identify two mechanisms: reactive correction, whereby physicians remove errors after they are flagged, and proactive learning, whereby they avoid errors before alerts occur. While early reductions are driven primarily by correction, physicians increasingly avoid errors over time. They also become less likely to repeat previously flagged errors and reduce new errors, suggesting that learning generalizes beyond specific drug pairs. The effects are consistent across physician types and do not compromise productivity or care quality. Our findings show that non-mandatory information interventions can improve patient safety through both immediate error correction and persistent, generalizable learning.

econ.GN↗
arXiv2026

How an Economy Shrinks in Space: Concavity-on-Jobs and Upward Consolidation under Demographic Decline

When a country's population declines, the aggregate economy appears to contract on the intensive margin: industrial diversity intact, every industry a little smaller. At the regional level, contraction is uneven and takes the extensive form: entire industries disappear, one after another. The relevant unit is the city: industries are nested by size - the hierarchy property of industrial location - each viable only above a minimum population. Necessity industries' thresholds bunch at the low end, so a city's industry count - and its jobs - is sharply concave in size (concavity on jobs). A modest loss pushes a small city below many thresholds at once; a large core sheds a few specialized industries, one at a time. Lost industries consolidate upward to the next city large enough to host them; for the worker it means a step down to a lower-paid local job. To recover that income, workers move up to the apex - the only city hosting the full industry range. Studying Japan - two decades ahead of the OECD, Tokyo at its apex - with worker-level panel data on the young workers who carry the migration, a wage regression in real, housing-inclusive wages identifies a Tokyo-bound migration incentive that varies by origin, following concavity on jobs.

econ.GN↗
arXiv2026

Do wind and solar curtail at negative electricity prices? Incentives and evidence across two decades of German renewable support schemes

In many power systems, wind and solar generation increasingly often exceeds electricity demand. Curtailing renewable generation in those hours matters both for prices and for the physical stability of the grid. Turning off wind turbines and solar panels is technically easier than ramping down a large power station, yet support schemes often give renewables an economic incentive to keep producing at negative prices. This paper studies wind and solar energy in Germany. For each cohort of generators it estimates, hour by hour, the incentive implied by two decades of support policy. It then sets those incentives against observed behavior, using a new estimate of market-based curtailment built from reanalysis weather data. I find that in 2025, at prices below -50 EUR/MWh, almost all wind generators had an incentive to stop producing, but only half of them did. Solar is the opposite case: nearly two thirds of the potential had no incentive to curtail at all, mostly because it receives a feed-in tariff that shields it from wholesale prices. Of the exposed remainder, just over a fifth cut production. Low exposure and response rates inflate subsidy payments and make the power system harder to operate safely. I conclude that a further expansion of wind and solar requires them to respond to price signals.

econ.GN↗