Waxing power, waning pollution: The effect of COVID-19 on Russian environmental policymaking.

Like most countries globally, COVID-19 continues to have a demonstrable health, economic, and environmental impact on Russia. The purpose of this paper is to examine the possible ramifications for environmental quality in Russia during and following the coronavirus pandemic. Our work builds on the framework of Elinor Ostrom, as we argue that the pandemic and subsequent lockdown in Russia has highlighted the need for a more polycentric, de-centralized approach to environmental protection. We provide evidence for this point using a novel econometric strategy: given the tight centralization of environmental policymaking, we proxy for de facto decentralization using the amount of influence a regional governor has at the federal level. Using timely data on pollution in major Russian cities both before and during the pandemic, we employ an instrumental variable analysis which shows that pollution in a particular Russian region is negatively related to the amount of influence a Russian governor has at the federal level. Thus, the more powerful a governor is in their ability to set their own course, the better results they have in environmental quality. We conclude that Russia's environmental policy needs a fundamental rethink - and extensive decentralization - in a post-COVID-19 world.

Portfolio frontier analysis: Applying mean-variance analysis to health technology assessment for health systems under pressure.

The COVID-19 pandemic is challenging how healthcare technologies are evaluated, as new, more dynamic methods are required to test the cost effectiveness of alternative interventions during use rather than before initial adoption. Currently, health technology assessment (HTA) tends to be static and a priori: alternatives are compared before launch, and little evaluation occurs after implementation. We suggest a method that builds upon the current pre-launch HTA procedures by conceptualizing a mean-variance approach to the continuous evaluation of attainable portfolios of interventions in health systems. Our framework uses frontier analysis to identify the desirability of available health interventions so decision makers can choose diverse portfolios based upon information about expected returns and risks. This approach facilitates the extension of existing methods and assessments beyond the traditional concern with pre-adoption data, a much-needed innovation given the challenges posed by COVID-19.