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Coronavirus disease 2019 (COVID-19) vaccine development and manufacturing have proceeded at a historically unprecedented pace. This speed may be accounted for by the unprecedented scale of resources being devoted to addressing COVID-19; an unusual intensity of cooperation, encompassing the public and private sectors and occurring both within and across national borders; and innovation with respect to both technologies (for example, new vaccine platforms) and processes (for example, vaccine clinical trials). In this article we describe and analyze how resources, cooperation, and innovation have contributed to the accelerated development of COVID-19 vaccines. Similar levels and types of public investment, models of cooperation, and harnessing of innovative processes and technologies could be applied to future epidemics and other global health challenges. P rogress toward the successful development and manufacture of effective coronavirus disease 2019 (COVID-19) vaccines has taken place with remarkable speed. In early December 2020 several national regulatory authorities, including the Food and Drug Administration (FDA), granted emergency or full authorization for a messenger RNA (mRNA) vaccine developed by BioNTech and Pfizer, following review of results from Phase III clinical trials. These determinations were quickly followed by FDA Emergency Use Authorization for a second mRNA vaccine developed by Moderna and the National Institutes of Health (NIH) in the US. Top US public health officials have predicted that hundreds of millions of doses of multiple COVID-19 vaccines will be available to the US population by the second half of 2021. 1 The World Health Organization (WHO) has also suggested that widespread vaccination could take place internationally on a similar timeline, 2 although initial delivery has progressed slowly in a number of high-income settings, including the US. Considering the potential for further delay in remaining clinical trials, regulatory approval, manufacturing, and distribution, it is perhaps more reasonable to project that substantial global access to COVID-19 vaccination may be achieved sometime between 2022 and 2024. Competition among (wealthy) countries to secure sufficient supplies of vaccine for their populations with ample room for contingencies may also contribute to slowing global access. Even so, the rapidity with which both development and, likely, access to COVID-19 vaccines has occurred or is anticipated to occur is entirely without precedent. By comparison, development of the mumps vaccine, which holds the current speed record, took four years from isolation of the mumps virus to licensure in 1967. 3 Indeed, vaccine research and development, manufacturing, and delivery typically involves a long, deliberate process that takes a decade or more (see

New technologies and unprecedented public investment have transformed vaccine development and allowed fast delivery of safe and efficacious COVID-19 vaccines, mitigating the impact of the pandemic on health and the economy. A quantum change in public investment for vaccine development and widespread vaccine distribution are necessary to achieve global pandemic preparedness.

I compare unemployment expectations from the Michigan Survey of Consumers to VAR forecastable movements in unemployment. I document three key facts. First, onehalf to one-third of the population expects unemployment to rise when it is falling at the end of a recession even though the VAR is able to predict the fall in unemployment. Second, more people expect unemployment to rise when it is falling at the end of a recession than expect it to rise when it is rising at the beginning of a recession even though these movements are predictable with the VAR. Finally, the lag change in unemployment is as important as the VAR prediction of the future unemployment change in predicting the fraction of the population that expects unemployment to rise. Least squares learning or real time expectations do little to help explain these facts. However, delayed updating of expectations can addresses some of these puzzles and extrapolative expectations addresses these puzzles the best. Individuals with higher income or education are only slightly less likely to make these expectational errors and those who makes these errors are 8-10 percent less likely to believe it is a good time to make a major purchase.

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Over the past two decades, China's R&D intensity has surged. The institutional arrangements underlying this surge remain unclear. We study the notable restructuring of the country's 5,000 research institutes, begun in 1999. This study first reviews the evolution of China's research institute sector over the period 1995–2010. Then applying OLS, fixed effects, event study and propensity score analysis to institute level data, we find the restructuring programme has accomplished some of its goals. The converted Science and Technology enterprises shifted towards a more commercial mission, the institutes converted to non‐profit research institutes have focused on a more research‐oriented mission.

All papers in the Holy Cross Working Paper Series should be considered draft versions subject to future revision. Comments and suggestions are welcome.