Macro Roundup

James Capretta, "CBO presents options for covering the uninsured," American Enterprise Institute, October 5, 2020, https://www.aei.org/articles/cbo-presents-options-for-covering-the-uninsured/

Allison Percy and Karen Stockley, “Who Went Without Health Insurance In 2019, and Why?” Congressional Budget Office, September 2020, https://www.cbo.gov/system/files/2020-09/56504-Health-Insurance.pdf

Jared Maeda and Karen Stockley, “Policies to Achieve Near-Universal Health Insurance Coverage,” Congressional Budget Office, October 2020, https://www.cbo.gov/system/files/2020-10/56620-near-universal-coverage.pdf

Capretta here makes no sense according to CBO“…0 million people are uninsured because they are residing in the U.S. without proper legal status; as such, they are ineligible for subsidized coverage.6 million people are ineligible for employer coverage but have incomes too high to qualify for subsidized premiums through the ACA exchanges; they could enroll in plans offered in the nongroup market but would be required to pay the full premiums themselves. Finally, there are 3.2 million people who have incomes below the federal poverty line and live in states that did not expand Medicaid as allowed by the ACA.This group falls into a “coverage gap” in current law; their incomes are too low to qualify for subsidized premiums in the ACA exchanges and yet too high to qualify for Medicaid. The first priority of any future effort to cover the uninsured should be to ensure this population can enroll in either Medicaid or another alternative that requires no premium payment….”

And only 1/3 of persons not insured not eligible for subsidized coverage“…In 2019, an estimated 30 million people under the age of 65, or 12 percent of that population, were uninsured. One reason for the lack of insurance coverage was a lack of subsidized options. About one-third of uninsured people under the age of 65 did not have access to coverage that was subsidized by the government or an employer: 13 percent were noncitizens who were not lawfully present in this country; 11 percent had income that was less than 100 percent of the FPL and lived in a state that did not expand Medicaid; and 9 percent had income that was too high to qualify for marketplace subsidies(see Figure 1)…”

“…About two-thirds of the 30 million uninsured people under the age of 65 had access to some form of subsidized coverage but were not enrolled, although those options were subsidized to different degrees: 17 percent were eligible for Medicaid or CHIP; 19 percent were eligible for subsidized coverage through the marketplaces established under the ACA; and 31 percent had access to coverage through an employer. Most of those people could have purchased health insurance that cost less than 10 percent of their income, but fewer people had an option that cost less than 5 percent of their income. Those people lacked health insurance coverage because they did not consider it to be worth the cost or because of the complexities of the enrollment process, among other reasons….”

But bottom line according toCBO only 9.8mm people who are currently uninsured are not eligible for subsidized coverage under the current systems, and 4mm are not lawfully present in the country, so only5.8mm peoplearen’t being captured by the current system. The other 20mm people don’t have health insurance because to quote CBO “…Those people lacked health insurance coverage because they did not consider it to be worth the cost or because of the complexities of the enrollment process, among other reasons…”

Peter Orszag, "Maybe Low Interest Rates Won’t Last Forever,"Bloomberg, October 8, 2020, https://www.bloomberg.com/opinion/articles/2020-10-08/maybe-low-interest-rates-won-t-last-forever

Here’s the argument, “….. The authors argue that the era of low rates was fundamentally caused by demographics and the entry of China and Eastern Europe into the global trading system. The result was that, from 1991 to 2018, the effective global labor supply more than doubled, which in turn pushed interest rates down (while also depressing inflation and wages and boosting inequality). As they write, “the rise of China, globalisation and the reincorporation of Eastern Europe into the world trading system, together with … the arrival of the baby boomers into the labour force and the improvement in the dependency ratio, together with greater women’s employment, produced the largest ever, massive positive labour supply shock.” The deflationary pressure caused by this supply produced the era of low nominal and real rates. Goodhart and Pradhan go on to argue that the demographic sweet spot of the past three decades is now reversing, with the ratio of dependents (the elderly and the young) to workers rising in the advanced economies and in China. Indeed, working-age populations are now stagnant or falling across most of the world outside of Africa and India.The underlying tectonic plate of aging, the authors argue, will soon reverse the previous deflationary pressures. The consequences? “The main thesis of this book,” the authors write, “is that the great demographic reversal will shortly raise inflation and interest rates…”

Orszag on inflationary prospects, “…Almost no one predicts a large rebound in either nominal or real interest rates. So what might go wrong? First, and just to get this out of the way, I was wrong more than a decade ago to worry about an increase in rates. History has, to put it gently, not been kind to that view. By 2011, I had seen enough to know my initial fears were misplaced, and the lesson, learned the hard way, is to be more skeptical about the conventional wisdom…”

Ufuk Akcigit, Jeremy Pearce and Marta Prato, “Tapping Into Talent: Coupling Education and Innovation Policies for Economic Growth,” September, 2020, https://www.nber.org/papers/w27862

Time lag of investment in human capital versus R&D subsidies“…Fourth, we solve for the transitional dynamics of our model and find that it takes time for all of these policies to show their full effect. We find that R&D policy is the most effective policy for innovation in the short-run. On impact, R&D policy stimulates the purchase of R&D inputs other than human capital (e.g. lab equipment) by the existing researchers, which translates into more innovation. Education policy, on the other hand, has limited effectiveness in the short-run due to time-to-build human capital, but is more effective in the medium to long-run. It takes around five years for educational subsidies to surpass R&D policy in terms of its overall growth effect for equivalent expenditure of 0.5% of GDP….”

Human capital most important factor“….Third, our analysis suggests that education policy is more effective in more unequal societies in stimulating innovation. We analyze the responsiveness of policy under different levels of financial frictions. In an environment with lower financial frictions, fewer individuals are unable to pay for schooling; thus, subsidizing the cost of education is less effective in stimulating economic growth. In an economy where no one is constrained, educational subsidies have no effectiveness, as individuals who want to pursue a career in research will do so regardless. In an economy with full frictions, educational subsidies are the most effective policy tool for innovation….”

Here they look at the utility of the policy toolkit“…Second, there is a pecking order between education and R&D policies. The optimal policy mix depends on the size of the budget the government has to allocate to research. If the government has 0.5% of GDP budget to allocate to research, our framework predicts it should allocate all of its resources towards educational subsidies to improve the talent pool by enabling access to education for financially constrained individuals. With a larger budget, the government should mix subsidies to education, subsidies to R&D, and an expansion in the supply of education slots. Given a budget of 1% of GDP, the optimal allocation is between education and R&D subsidies, with 50% of the budget for R&D subsidies and 50% to educational subsidies. Given a budget of 2.5% of GDP, it is optimal to allocate 58% of the budget to R&D subsidies, 26% to education subsidies, and 16% to expanding the educational slots available. The fact that there is an optimal mix highlights the role of the complementarities of the policies in their contribution to economic growth…”

They have four main findings in terms of human capital’s impact on innovation, “…First, we show that, in steady state, R&D policy has limited effectiveness compared to benchmark models of endogenous growth. R&D policy has even more limited contemporaneous effects. A 10% R&D subsidy only has a contemporaneous effect on the growth rate of about 0.6%, because of the time-to-build component of human capital. Further, the long-run effects of R&D are smaller than standard models due to the fact that the talent pulled into research is restricted by both educational capacity and financial constraints. A 10% R&D subsidy has a long-run effect on the growth rate of 5%, compared to 10% in standard models…”

“…Starting in 2002, the Danish government required universities to double PhD enrollment in the span of 10 years, with the goal of expanding the pool of scientists and inventors. As highlighted in Fact 9, the increase in PhD enrollment was associated with a decline in average IQ of enrolled PhDs. This empirical finding illustrates constraints the government faces when attempting to expand the pool of researchers and inventors due to the scarcity and heterogeneity of talent, which is a key determinant of innovation outcomes. It also stresses the importance of tapping into other sources of talent in the economy: attracting into research those talented individuals who are financially constrained or work in other sectors….“…Figure 14 shows that as the number of slots for PhDs increases, the average IQ of the enrolling students falls. This indicates that there is heterogeneous quality of enrollees and expanding slots may draw in a marginal researcher less talented than the average researcher from the existing pool. Thus, even though policy can increase the supply of researchers, there is a trade-off between expanding the pool of PhDs and the average talent of PhDs in the economy….In order to speak to innovation and the effects of policies, we match the dataset to external patent data from the European Patent Office (EPO) and policy data from the Danish Ministry of Education. A unique feature of this dataset is detailed information on an innovation and education policy change implemented in 2002, which introduced new R&D subsidies and dramatically increased funding to universities and the level of PhD enrollment. We exploit this variation to better isolate the links between talent, education and innovation. We stress ten facts in our framework made possible by the extensive Danish dataset that shape our analysis:Fact 1 Individuals with higher IQ are more likely to obtain a PhD.Fact 2 Individuals with higher parental income are more likely to obtain a PhD. Fact 3 Individuals’ IQ is correlated with parental income, but not perfectly.Fact 4 Only a fraction of people with high IQ and high parental income obtain a PhD. Fact 5 PhDs are 20-times more likely to become inventors compared to the average person in society.Fact 6 Conditional on education level, higher IQ people are more likely to innovate.Fact 7 Inventors work in teams and team size is heterogeneous.Fact 8 The probability of innovating as a team leader over an inventor’s life-cycle follows an inverted-U shape. Fact 9 An increase in the number of PhD slots is associated with a decline in the average IQ of PhDs.Fact 10 The economy is open in the goods market but closed in the skills market: import and export accounted for 44% and 51% of GDP in 2010, but foreign migrants make up only 10% of inventors in Denmark…”

New Akcigit using a unique natural experiment/Danish dataset looks at the links btw higher education policy, R&D subsidies and innovation. His data suggests that talent is the limiting constraint.

David Cutler and Lawrence Summers, “The COVID-19 Pandemic and the $16 Trillion Virus,” Journal of the American Medical Association, October 12, 2020, https://jamanetwork.com/journals/jama/fullarticle/2771764

“…. The Congressional Budget Office projects a total of $7.6 trillion in lost output during the next decade…. In addition toCOVID-19deaths, studies suggest increased deaths from other causes, amounting to almost 40% of COVID-19-related deaths. Thus, if the current trajectories continue, an estimated 625 000 cumulative deaths associated with the pandemic will occur through next year in the US…. In environmental and health policy,3 for example, a statistical life is assumed to be worth $10 million. With a more conservative value of $7 million per life, the economic cost of premature deaths expected through the next year is estimated at $4.4 trillion… Data from survivors ofCOVID-19suggest that long-term impairment ccurs for approximately one-third of survivors with severe or critical disease.4Because there are approximately 7 times as many survivors from severe or critical COVID-19 disease as there are COVID-19 deaths, long term impairment might affect more than twice as many people as the number of people who die… an estimated loss from long-term complications of $2.6 trillion for cases forecast through the next year… The proportion of US adults who report symptoms of depression or anxiety has averaged approximately 40% since April 2020; the comparable figure in early 2019 was 11.0%.5 These data translate to an estimated 80 million additional individuals with these mental health conditions related to COVID-19…. the valuation of these losses could reach approximately $1.6 trillion….. related to the lost output and health reduction are shown in the Table. The total cost is estimated at more than $16 trillion, or approximately 90% of the annual gross domestic product of the US. For a family of 4, the estimated loss would be nearly $200 000. Approximately half of this amount is the lost income from the COVID-19-induced recession; the remainder is the economic effects of shorter and less healthy life

The residual are long term health/mental health impact of the pandemic.

The largest component of that is lost GDP,he’s using CBO estimates at $7.6T over the next decade. The second largest component is deaths (they value a life a $7mm) and are estimating 625,000 excess deaths for $4.4 Trillion (though they are estimating 450,000 directly from Covid)

Just an FYI, Summer’s tacks a whack at estimating Covid’s economic impact. Bottom line is $16 Trillion (90% of a years GDP)