Macro Roundup

Just an FYI, NBER with some good statistics on the state of American infrastructure, at the end of 2018 net stock of private/government fixed assets was about $63 trillion, and depreciation was about $3.3 trillion.

Some factoids according to paper real gross infrastructure investment, (2012 prices) peaked at $340 billion in 1968, declined slightly during the next decade and a half, and then grew to reach nearly $800 billion in 2017. Though it varies significantly by differences across categories. For example investment in basic infrastructure, roads, bridges, power grids, dams broadly mirrored that path through 2000s. Since then it has been largely flat, while the share of infrastructure investment in other areas has increased.

These areas include “social infrastructure” ie schools, hospitals, and public safety, as well as digital infrastructure. Digital infrastructure, which is largely private, is the fastest-growing area, includes cell towers, computers, communications equipment, software owned by companies in broadcast and telecom, data processing, internet publishing, and information services. Investment in this area rose about tenfold from the 1980s to 2017.

However it’s worth noting that their calculated real net infrastructure investment per capita, which adjusts gross investment for population growth and depreciation measure. They argue this highlights whether infrastructure investment is keeping up with wear and tear as well as population growth currently stands near its lowest level since 1983. Moreover, the remaining useful life of many types of basic infrastructure has moved lower in recent decades. Net investment per capita, “…For total infrastructure, depreciation is sizable and, on a per capita basis, the gap between gross and net investment on a per capita basis in overall infrastructure has widened during the past 20 years as reported in Figure15. This gap had been growing slowly in earlier decades, but more recently, the divergence has opened up more noticeably. Thus, despite gradual increases in real budget resources being allocated to infrastructure (as measured by real gross investment in infrastructure), actual additions to the real capital stock per capita have been considerably weaker. In terms of the components of total infrastructure, for basic infrastructure (Figure 16),real net investment per capita has drifted downward since the financial crisis and stands at its lowest level since the series hit bottom in 1983. For social infrastructure (Figure 17), real net investment per capita trended up from the mid-1980s through 2007, but then dropped back considerably after the financial crisis (though with a slight pickup in recent years)….”

Jennifer Bennett, Robert Kornfeld, Daniel Sichel and David Wasshausen, "Measuring Infrastructure in BEA's National Economic Accounts," National Bureau Of Economic Research, June 2020, https://www.nber.org/papers/w27446

What’s happening with digital Infrastructure, “…Investment in digital infrastructure rose from about $25 billion annually in the 1980s to almost $250 billion in 2017 (Figure 14). The sharp increase in digital infrastructure since the 1990s arose because of increases in investment in private communications equipment in NAICS 513 and 514 as well as investment in software and computers in these industries.These increases in real investment partly reflect work by BEA and others to quality-adjust the prices of these assets. Interestingly, the pattern of investment in communications structures since the 1990s has been more mixed. This category—which accounted for a modest share of digital investment—includes cell towers but also includes old-fashioned telephone switching structures. Over these decades, the equipment and intellectual property shares of digital infrastructure have increased, while the structures share has fallen. While the net stocks of these digital assets have increased substantially over time, as one would expect (Table 1), the increase in the net stocks and the net stock shares of equipment, software, and computers is perhaps not as rapid as one might expect because depreciation rates for these assets are far higher than the rates for structures. Note that the assets we have classified as digital infrastructure have always been entirely private(Table 3)...”

Snapshot of real net/nominal net shock shares of infrastructure“…These different trends in investment have led to shifts in the composition of capital stocks of basic infrastructure over time (Table 1). Generally, net stocks of most types of infrastructure have risen over time because, even with periods of flat and declining investment, stocks tend to increase because depreciation rates for these assets (mostly structures) are low. One notable exception is railroad transportation: the US had substantial stocks of rail assets at the end of World War II but limited additional investment since then as the nation turned to roads, airplanes, and other forms of transportation. As a result, net stocks of railroad assets decreased markedly over these decades. Over time, the largest increases in real net stocks of basic infrastructure were in highways and streets, electric power structures and equipment, and water and sewer…..”

Mark Perry on the new Census Median Household Income numbers, he adjusts the numbers for household size to account for falling household size, “…Median Household Income, Average Household Size, and Income per Householder. The chart above shows: a) the percentage increase in median US household income (in constant 2019 dollars) since 1967, b) the average household size in each year from 1967 to 2019 and c) the percentage increase in median household income per household member since 1967…”

Mark Perry, "More charts and commentary on last week’s Census Bureau report on income," American Enterprise Institute, September 24, 2020, https://www.aei.org/carpe-diem/more-charts-and-commentary-on-last-weeks-census-bureau-report-on-income/

Ed Fed’s update of SCF was released. Data shows btw 2016-2019 lower income family saw proportionally higher income growth than richer counterparts who saw large gains btw 2013-2016

Just wanted to make sure you saw highlights “…. During the three years between the beginning of the 2016 and 2019 surveys,real gross domestic product grew at an annual rate of 2.5 percent, and the civilian unemployment rate fell from 5.0 percent to 3.8 percent.3 These changes in aggregate economic performance were unevenly reflected in the income of families with different characteristics…Between 2016 and 2019, median family income rose 5 percent, and mean family income decreased 3 percent (figure 1). These changes suggest that the income distribution narrowed slightly over the period, particularly as the decrease in mean income was mainly driven by families in the top 1 percent of the income distribution(see box 1, “The Data Used in This Article”). These patterns stand in contrast to the 2010-16 period, during which mean income growth vastly outpaced median income growth and the income distribution widened considerably…Between 2016 and 2019, families that were high wealth, had a college education, or identified as White non-Hispanic experienced proportionally smaller income growth than other groups of families but continued to have the highest income.

Housing and equity prices had a positive impact on family net worth, “…The improvements in economic activity along with rising house and corporate equity prices combined to support continued increases in median and mean family net worth (wealth) between 2016 and 2019.4The national CoreLogic Home Price Index increased at an annual rate of 5.2 percent between early 2016 and early 2019, exceeding the rate of consumer price inflation. The value of corporate equity holdings, as measured by a broad stock price index, grew at around an 11.5 percent annual rate between the two surveys, leading to large inflation-adjusted increases in equity holdings.5 These price trends contributed to the following changes in the distribution of household net worth…”

Neil Bhutta, Jesse Bricker, Andrew C. Chang, Lisa J. Dettling, Sarena Goodman, Joanne W. Hsu, Kevin B. Moore, Sarah Reber, Alice Henriques Volz, and Richard A. Windle, of the Board’s Division of Research and Statistics, prepared this article with assistance from Kathy Bi, Jacqueline Blair, Julia Hewitt, and Dalton Ruh, "Changes in U.S. Family Finances from 2016 to 2019: Evidence from the Survey of Consumer Finances," Board Of Governors Of Federal Reserve System, September 2020, https://www.federalreserve.gov/publications/files/scf20.pdf

Median net worth grew 18%, mean net worth 2%“…Between 2016 and 2019, median net worth grew 18 percent, and mean net worth rose a modest 2 percent (figure 2). In contrast, the 2010-16 period saw outsized gains in mean net worth relative to median net worth, driven by growth between 2013 and 2016….Families at the top of the income and wealth distributions experienced very little, if any, growth in median and mean net worth between 2016 and 2019 after experiencing large gains between 2013 and 2016…”

New FDES Note looking at wealth concentration using the new SCR numbers find wealth distribution largely unchanged:

“…Overall, the 2019 SCF data mostly showsmall changes between the 2016 and 2019 SCF distributions. Wealth concentration in the top 1 percent of families is still near the high point in the historical 1989-2019 SCF time series, and concentration in the top 10 percent is unchanged. Althoughwealth concentration did not increase between 2016 and 2019, the gains that accrued to the rest of the distribution did little to reduce the large existing disparities. Income concentration in the top 1 percent fell but remained at the typical levels seen since the 2007 SCF. However, some of the income share earned by the top 1 percent shifted to the bottom 90 percent of the income distribution, reversing a nearly decade-long decline in the income share for that group….”

Jesse Bricker, Sarena Goodman, Kevin Moore, Alice Henriques Volz and Dalton Ruh, "Wealth and Income Concentration in the SCF: 1989-2019," FEDS Notes, September 28, 2020, https://www.federalreserve.gov/econres/notes/feds-notes/wealth-and-income-concentration-in-the-scf-20200928.htm

“…This note provides the first look at the wealth distribution since 2016 (figure B). This note also lays out the best practices for augmenting the SCF wealth concept to characterize—and be more comparable to other measures of—the full U.S. wealth distribution. The data collected in the 2010-2016 SCF surveys indicated that the sustained economic growth that followed the Great Recession had initially accrued primarily to the wealthiest families. These 2019 data were collected at the end of the longest economic expansion on record, when growth spread more equitably to the larger segments of the distribution….”

Jordan Nickerson and David Solomon, “Car Seats as Contraception,” Social Science Research Network, September 22, 2020, https://papers.ssrn.com/sol3/papers.cfm

Bottomline, “…First, when conditioning on women that give birth to a second child, we examine the lifetime probability of having a third child. Each additional year that the two eldest children are required to be in car seats results in a 0.60 percentage point reduction in the lifetime probability of having a third child. Second, we embed our panel data estimations into dynamic simulations which incorporate potential offsetting effects. We estimate that switching from an eight-year-old mandate to a four-year-old mandate would result in the average woman having 0.0076 more children. In 2017, we estimate that car seat laws lead to a permanent reduction of approximately 8,000 births, and have prevented 145,000 births over our sample period, with 60% of this effect being since 2008. By contrast, if current laws had applied over the whole sample, we estimate there would have been a further 350,000 fewer births. When comparing simulated birth decreases with predicted changes in births from our base regressions (which only measure contemporaneous effects), we estimate that approximately 71% of the contemporaneous effect is permanent….”

Here they explain their mechanism, “…These laws can significantly raise the cost of having children for women who already have two young children, and are considering a third. While the particular type of mandated restraining device varies, many cars cannot easily accommodate three child seats in the back row of seats, as would be needed if both front seats are occupied by adults. This especially increases the cost of a third child for many families, by necessitating the purchase of a larger car. The most practical options, like minivans, have additional problems of being expensive and unfashionable. We exploit the specific nature of costs associated with a third child, along with considerable variation in mandated ages over states and years, to identify the impact of state car seat laws on fertility. Using census data on the number and age of children for each woman surveyed,we estimate the effect of these laws on birthrates from 1973 to 2017. We find that when a woman has two children below the car seat age, her chances of giving birth that year decline by 0.73 percentage points. This represents a large decline, as the probability of giving birth for a woman age 18-35 with two children already is 9.36% in our sample…”

But as the same time the associated costs of having to buy a bigger car has lowered fertility“…Using census data and state-year variation in laws,we estimate that when women have two children of ages requiring mandated car seats, they have a lower annual probability of giving birth by 0.73 percentage points. Consistent with a causal channel, this effect is limited to third child births, is concentrated in households with access to a car, and is larger when a male is present (when both front seats are likely to be occupied)…. . Simultaneously, they led to a permanent reduction of approximately 8,000 births in the same year, and 145,000 fewer births since 1980, with 90% of this decline being since 2000….”

Unintended consequences, car seat laws. They did limit child deaths, paper estimates, “…these laws prevented…57 car crash fatalities of children nationwide in 2017…”but their cumulative impact was likely limited, “…To give context, it is worth noting how many children’s car crash fatalities there are in the first place in the U.S. In 1978, the number of fatalities for children age 0-8 was 2,392. By 2017, this had declined 73% to 654 total. However, this is almost exactly the same as the 72% decline in fatalities for children ages 9-12 over the same period from 975 to 273 (who were largely unaffected by these laws). In other words, back of the envelope approximations are consistent with the small numbers we document….”

Benjamin Jones and Lawrence Summers, “A Calculation of the Social Returns To Innovation,” National Bureau of Economic Research, September 2020, https://www.nber.org/papers/w27863

On capital deepening, “…Finally, note that incorporating capital investment doesn’t diminish the society wide gains. Rather it acts to spread the gains over a broader set of investments, beyond R&D. The social returns to capital deepening thus appear much larger than the equilibrium private rate of return to capital investment would suggest. To the extent that embodiment is important, R&D investment and capital investment collectively unlock large social returns. From a policy point of view, supporting R&D and capital deepening together would may then be important to attain the high social returns from innovative investments….”

Key to their formula, “.. The cost, in the denominator, is the ratio of innovation investment expenditure (𝑥) to GDP (𝑦). The benefit, in the numerator, is the growth rate (𝑔) that results, discounted to the present at the discount rate (𝑟).We are suppressing time in this expression to emphasize that the ratio of innovation investment expenditure to GDP and the growth rate of income are approximately constant over time..Namely, we can think of the cost benefit ratio as the cost of one year’s innovation (𝑥/𝑦) producing a stream of output gains that are𝑔percent higher. The present value of this permanent output gain is𝑔/𝑟.”

Here they explain their core logic, “We present new calculations for the social returns to innovation investment, building on core features of the innovation and growth literatures. Our measures emphasize the advantages of examining the path of GDP, which acts to aggregate and net out complicated spillovers involved in the innovation process. The approach offers a seemingly quite general means of estimating the average social returns. Moreover, the simplicity of the method allows us to transparently examine the influence of other, potentially key features that are not typically addressed in studies of the social returns to R&D. These features include embodied vs. disembodied technological progress, diffusion rates, learning-by-doing, productivity mismeasurement, health benefits, cross-country spillovers, and other dimensions for assessing the social returns….Taking this approach seriously, the average returns to innovative investments are determined by linking the aggregate cost of innovation investments to the aggregate production increase that results. Intuitively, by looking at the net value-added gains in the GDP path, one can implicitly net out the spillover margins. By looking at total innovation investment, one includes both research successes and failures. A simple social returns calculation can proceed as follows. Let income per capita be y, innovation investment per capita be x, and the discount rate be r. If a year's worth of innovation investments creates a g percent increase in productivity, then the ratio of benefits to costs is: p=(g/r)/(x/y) The key idea here, as in endogenous growth theory, is that, by investing a GDP share𝑥/𝑦in innovation today (i.e., once), we permanently raise productivity in the economy by𝑔percent, the present value of which is𝑔/𝑟.* Notably, this approach suggests that the average social returns to innovation may be enormous. For example, if we take an R&D investment orientation, with the R&D share of GDP at its usual level in the U.S.,𝑥/𝑦 ≈ 2.7%, and let these investments drive productivity growth, then we have𝑔 ≈ 1.8%. 1 Standard discount rates then imply that 1$ of R&D investment today on average creates over $10 of economy-wide benefits in today’s dollars.2 This return is extremely large, but it follows from the basic mechanics of growth, as understood in advanced economies. That is, a permanent gain in living standards from a seemingly small investment in innovation will, by the above logic, tend to suggest enormous returns….”

“…Overall, we find that the average social returns to innovation investments appear very large. If formal R&D and new venture creation drive the bulk of productivity gains, then the social returns to these investments appear enormous. If a much broader set of investments, including capital embodiment, are needed to fulfill these productivity gains, then the social returns to these broader activities still appear large. Even under very conservative assumptions, it is difficult to find an average return below $4 per $1 spent. Accounting for health benefits, inflation bias, or international spillovers can bring the social returns to over $20 per $1 spent, with internal rates of return approaching 100%.We further consider how these average returns may relate to the marginal return of additional investment in innovation. Using various perspectives, motivated by the micro and macro literatures on innovation, there are good reasons to believe that the marginal returns are also high. The implication is that policies to support further innovation investment are broadly well motivated. Innovation investments can credibly raise economic growth rates and extend lives, paying for their costs many times over. And because the social returns exceed the private returns, public policy has a central role, and opportunity, in unleashing these gains….”

Looking at the US alone they calculate, “…Overall, it appears that a conservative estimate of theaverage social gains is about $5 in benefit per $1 invested. Considering reasonable amounts of inflation bias or health benefits can easily push the average benefit to $10 or even $20 per $1 invested. These gains are just in terms of the U.S. economy. Incorporating international spillovers extends the benefits further. In sum, analyzing the average returns form a wide variety of perspectives suggests that the social returns are remarkably high….”

New Summers tries to look at social return to innovation (including trying to account for research failures) and finds massive positive spillovers the internal rate approach 100%.