The work constructs projections till 2030 for health care expenditures of Italian Regional Health Care Systems. Three different schemes of financing are hypothesised, with three different levels of solidarity between Regions. Financing is always supposed to cover the entire exigency of...

Productivity research is Canada has traditionally focused on narrow economic issues. In our view, it has given inadequate attention to the broader ramifications of productivity, both in terms of shedding light on the importance of productivity for the advancement of various aspects of social...

Background: Significant health expenses can force households to reduce consumption of items required for daily living and long-term well-being, depriving them of the capability to lead economically stable and healthy lives. Previous studies of out-of-pocket (OOP) and other health expenses have...

America’s COVID-19 pandemic has both devastated and disparately harmed minority communities. How can the allocation of scarce treatments for COVID-19 and similar public health threats fairly and legally respond to these racial disparities? Some have proposed that members of racial groups who...

We present a multi-city economic model to study the endogenous choice of migration and to evaluate various policy alternatives during a pandemic. We combine a traditional epidemic dynamic model with endogenous migration decisions between cities and provide analytical solutions under two...

The Covid-19 pandemic has brought renewed attention to rationing guidelines for scarce medical resources. This paper describes the benefits of using a reserve system over a priority system in operationalizing compromises between certain ethical goals. In the last two years, more than a dozen...

We develop a theory that addresses the problem of the existence of stable vaccine allocations in a political economy. These are allocation policies that a political leader can enforce without losing their popularity. Our analysis distinguishes between contexts where vaccination has positive...

We study how a regulator can best target inspections. Our case study is a US Occupational Safety and Health Administration (OSHA) program that randomly allocated some inspections. On average, each inspection averted 2.4 serious injuries (9%) over the next five years. We use new machine learning...