Leveraging federalism for flexible and robust management of social-ecological systems

Managing social-ecological systems (SES) requires balancing the need to tailor actions to local heterogeneity and the need to work over large areas to accommodate the extent of SES. This balance is particularly challenging for policy since the level of government where the policy is being developed determines the extent and resolution of action.We make the case for a new research agenda focused on ecological federalism that seeks to address this challenge by capitalizing on the flexibility afforded by a federalist system of governance. Ecological federalism synthesizes the environmental federalism literature from law and economics with relevant ecological and biological literature to address a fundamental question: What aspects of SES should be managed by federal governments and which should be allocated to decentralized state governments?This new research agenda considers the bio-geo-physical processes that characterize state-federal management tradeoffs for biodiversity conservation, resource management, infectious disease prevention, and invasive species control.Read the free Plain Language Summary for this article on the Journal blog.

Opening of hotels and ski facilities: Impact on mobility, spending, and Covid-19 outcomes.

This paper investigates how reopening hotels and ski facilities in Poland impacted tourism spending, mobility, and COVID-19 outcomes. We used administrative data from a government program that subsidizes travel to show that the policy increased the consumption of tourism services in ski resorts. By leveraging geolocation data from Facebook, we showed that ski resorts experienced a significant influx of tourists, increasing the number of local users by up to 50%. Furthermore, we confirmed an increase in the probability of meetings between pairs of users from distanced locations and users from tourist and non-tourist areas. As the policy impacted travel and gatherings, we then analyzed its effect on the diffusion of COVID-19. We found that counties with ski facilities experienced more infections after the reopening. Moreover, counties strongly connected to the ski resorts during the reopening had more subsequent cases than weakly connected counties.

Socio-economic and demographic factors influencing the spatial spread of COVID-19 in the USA

As the COVID-19 pandemic progressed in the USA, ‘hotspots' shifted geographically over time to suburban and rural counties showing a high prevalence of the disease. We analyse population-adjusted confirmed case rates based on daily US county-level variations in COVID-19 confirmed case counts during the first several months of the pandemic (1 March 2020 through 23 May 2020) to evaluate the spatial dependence between neighbouring counties and quantify the overall spatial effect of socio-economic and demographic factors on the prevalence of COVID-19. We indeed find strong evidence of county-level socio-economic and demographic factors influencing the spatial spread such as sex, race, ethnicity, population density, pollution, health conditions, and income. The relevance of the spatial factors suggests that neighbouring counties have a significant and positive effect on the prevalence of COVID-19. Copyright © 2022 Inderscience Enterprises Ltd.

Socio-economic and demographic factors influencing the spatial spread of COVID-19 in the USA

As the COVID-19 pandemic progressed in the USA, 'hotspots' shifted geographically over time to suburban and rural counties showing a high prevalence of the disease. We analyse population-adjusted confirmed case rates based on daily US county-level variations in COVID-19 confirmed case counts during the first several months of the pandemic (1 March 2020 through 23 May 2020) to evaluate the spatial dependence between neighbouring counties and quantify the overall spatial effect of socio-economic and demographic factors on the prevalence of COVID-19. We indeed find strong evidence of county-level socio-economic and demographic factors influencing the spatial spread such as sex, race, ethnicity, population density, pollution, health conditions, and income. The relevance of the spatial factors suggests that neighbouring counties have a significant and positive effect on the prevalence of COVID-19.

State-Level Economic Policy Uncertainty

We quantify and study state-level economic policy uncertainty. Tapping digital archives for nearly 3,500 local newspapers, we construct three monthly indexes for each state: one that captures state and local sources of policy uncertainty (EPU−S), one that captures national and international sources (EPU−N), and a composite index that captures both. EPU−S rises around gubernatorial elections and own-state episodes like the California electricity crisis of 2000-01 and the Kansas tax experiment of 2012. EPU−N rises around presidential elections and in response to 9-11, Gulf Wars I and II, the 2011 debt-ceiling crisis, the 2012 fiscal cliff episode, and federal government shutdowns. Close elections elevate policy uncertainty much more than the average election. VAR models fit to pre-COVID data imply that upward shocks to own-state EPU foreshadow weaker economic performance in the state, as do upward EPU shocks in contiguous states. The COVID-19 pandemic drove huge increases in policy uncertainty and unemployment, more so in states with stricter government-mandated lockdowns.

Air Pollution Exposure and Covid-19 in Dutch Municipalities.

In light of the existing preliminary evidence of a link between Covid-19 and poor air quality, which is largely based upon correlations, we estimate the relationship between long term air pollution exposure and Covid-19 in 355 municipalities in the Netherlands. Using detailed data we find compelling evidence of a positive relationship between air pollution, and particularly P M 2.5 concentrations, and Covid-19 cases, hospital admissions and deaths. This relationship persists even after controlling for a wide range of explanatory variables. Our results indicate that, other things being equal, a municipality with 1 µg/m3 more P M 2.5 concentrations will have 9.4 more Covid-19 cases, 3.0 more hospital admissions, and 2.3 more deaths. This relationship between Covid-19 and air pollution withstands a number of sensitivity and robustness exercises including instrumenting pollution to mitigate potential endogeneity in the measurement of pollution and modelling spatial spillovers using spatial econometric techniques.

Spatial spillover and COVID-19 spread in the U.S.

BACKGROUND: This research estimates the effects of vulnerability on the spread of COVID-19 cases across U.S. counties. Vulnerability factors (Socioeconomic Status, Minority Status & Language, Housing type, Transportation, Household Composition & Disability, Epidemiological Factors, Healthcare system Factors, High-risk Environments, and Population density) do not only influence an individual's likelihood of getting infected but also influence the likelihood of his/her neighbors getting infected. Thus, spatial interactions occurring among individuals are likely to lead to spillover effects which may cause further virus transmission. METHODS: This research uses the COVID-19 community index (CCVI), which defines communities likely vulnerable to the impact of the pandemic and captures the multi-dimensionality of vulnerability. The spatial Durbin model was used to estimate the spillover effects of vulnerability to COVID-19 in U.S. counties, from May 1 to December 15, 2020. RESULTS: The findings confirm the existence of spatial spillover effects; with indirect effects (from neighboring counties) dominating the direct effects (from county-own vulnerability level). This not only validates social distancing as a strategy to contain the spread of the pandemic but also calls for comprehensive and coordinated approach to fight its effects. By keeping vulnerability factors constant but varying the number of reported infected cases every 2 weeks, we found that marginal effects of vulnerability vary significantly across counties. This might be the reflection of both the changing intensity of the pandemic itself but also the lack of consistency in the measures implemented to combat it. CONCLUSION: Overall, the results indicate that high vulnerability in Minority, Epidemiological factors, Healthcare System Factors, and High-Risk Environments in each county and adjacent counties leads to an increase in COVID-19 confirmed cases.

The spatial econometrics of the coronavirus pandemic.

In this paper we use spatial econometric specifications to model daily infection rates of COVID-19 across countries. Using recent advances in Bayesian spatial econometric techniques, we particularly focus on the time-dependent importance of alternative spatial linkage structures such as the number of flight connections, relationships in international trade, and common borders. The flexible model setup allows to study the intensity and type of spatial spillover structures over time. Our results show notable spatial spillover mechanisms in the early stages of the virus with international flight linkages as the main transmission channel. In later stages, our model shows a sharp drop in the intensity spatial spillovers due to national travel bans, indicating that travel restrictions led to a reduction of cross-country spillovers.