Macro Roundup

“…High school-aged girls who tested on par with their male peers in math chose not to crunch numbers for a living because of their “verbal advantage,” according to a study published Monday in the journal PNAS. For the study, researchers at the Paris School of Economics reviewed data from 300,000 15-year-old students from 64 countries worldwide. They found that girls’ higher reading and verbal test scores may account for up to 80% why math-related jobs are dominated by men globally, researcher said. It’s likely that social and cultural norms — in which women are expected to be more expressive and better communicators — drive young girls to excel at verbal subjects at school, study author Thomas Breda says…”

Natalie O’Neill, “Why teen girls who are as good at math as male peers pick humanities jobs,”New York Post, July 16, 2019, https://nypost.com/2019/07/16/why-teen-girls-who-are-as-good-at-math-as-male-peers-pick-humanities-jobs/

Why teen girls who are as good at math as male peers pick humanities jobs

Women have the write stuff for both math and communication jobs, according to A study.

Teenage girls are just as good with numbers as boys — but their even-stronger verbal skills often inspire them to pick humanities-centric jobs instead, according to a study published Monday in the journal PNAS.

High school-aged girls who tested on par with their male peers in math chose not to crunch numbers for a living because of their “verbal advantage,” according to a study published Monday in the journal PNAS.

For the study, researchers at the Paris School of Economics reviewed data from 300,000 15-year-old students from 64 countries worldwide. They found that girls’ higher reading and verbal test scores may account for up to 80% why math-related jobs are dominated by men globally, researcher said.

It’s likely that social and cultural norms — in which women are expected to be more expressive and better communicators — drive young girls to excel at verbal subjects at school, study author Thomas Breda says.

On average, male students scored only slightly higher in math than their female peers, according to the study. Girls scored better in the subject of reading.

“The reality is that people aren’t just their gender,” Juniper Simonis, a quantitative ecologist who was not involved in the study, told PBS.org

:… The big picture: The numbers simply do not lie. America, as a whole, and swing states, in particular, are growing more diverse, more quickly. There is no way Republicans can change birth rates or curb this trend — and there's not a single demographic megatrend that favors Republicans….”

Long-term, it seems unambiguous: If you need more African American and Hispanic voters, maligning and marginalizing them strikes even some inside this White House as stupid politics.

Go deeper: A tough time to be a Trump supporter

In less than a decade, the under-30 population will be majority non-white.

Between the lines: Trump clearly thinks this is good short-term politics.

Truth is: It's unknowable, though highly debatable.

Florida and Texas, two of the big electoral giants that voted for Trump, are witnessing the fastest non-white population growth.

This wave is only accelerating, as Stef reported in "America's majority minority future":

Next year, the entire under-18 population will be majority non-white, according to Brookings demographer William Frey.

Hispanic people now make up a quarter of the population in Florida, almost a third of the population in Arizona and 39% of Texas — all Trump states in 2016 that are becoming more winnable by Democrats.

The context, from AP: "Not since George Wallace's campaign in 1968 has a presidential candidate — and certainly not an incumbent president — put racial polarization at the center of his call to voters."

For any Republican thinking past 2020, here are numbers to fear, reported by Axios' Stef Kight:

The Hispanic share of the population has grown in every state since 2000, according to Census data.

Jim VandeHei, Mike Allen, "The GOP's demographic decay,"Axios, July 18, 2019, https://www.axios.com/republican-party-demographics-threat-trump-racism-1524a8a1-c2f1-4183-896f-107420e2d50a.html

The GOP's demographic decay

The single biggest threat to Republicans' long-term viability is demographics.

The big picture: The numbers simply do not lie. America, as a whole, and swing states, in particular, are growing more diverse, more quickly. There is no way Republicans can change birth rates or curb this trend — and there's not a single demographic megatrend that favors Republicans.

About last night: Trump paused while speaking at a "Make America Great Again" campaign rally in Greenville, N.C., to savor supporters' new roar: "Send her back!"

"I have a suggestion for the hate-filled extremists who are constantly trying to tear our country down," Trump said. "They never have anything good to say. That's why I say, 'Hey if you don't like it, let 'em leave, let 'em leave.'"

new NBER reinforces that the "hollowing out" of middle income jobs has been driven by demand for more high wage workers, not previous middle wage workers becoming low wage workers. paper also"....rule out the hypothesis that computerization and automation lie behind rising wage inequality...."

"...We reexamine whether U.S. workers are increasingly concentrated in both low and high wage jobs, a phenomenon known as employment polarization. We depart from most previous literature, which equates a job with an occupation, by instead considering jobs at the individual level. By assigning workers in the CPS to real hourly wage bins with time-invariant thresholds and tracking over time the shares of workers in each,we find a steady decline since 1973 in the share of workers earning middle wages, consistent with occupation based analysis. However, we find that both over the business cycle and the longer run, the shares of workers in the top and bottom bins move in opposite directions, inconsistent with employment polarization.....On the one hand, the displacement of workers from middle wage occupations to low wage occupations increases supply of low wage workers; on the other hand, demand for low wage services may rise with the rising numbers of the high wage workers.....Grouping workers into four time invariant bins defined only by workers' wages, we do find a steady decline in the share of workers in the middle two wage groups, but one that belies offsetting forces that vary over time and by gender, variously reflecting either upward mobility (workers moving faster from the middle to the top than from the bottom to the middle) or downward mobility (workers moving faster from the middle to the bottom than from the top to the middle), but not employment polarization....However, the shares of workers in the top and bottom groups generally move in opposite directions over the longer term as well, with the share in the top group rising markedly and the share in the bottom falling slightly. The patterns are very similar with ten wage bins rather than four...The slight downward trend in the share of workers with low wages could in principle coexist with the growing employment share of low wage occupations found in the literature: we show that the share of low wage occupation workers with low wages falls greatly with time. However, we also show that the share of employment in low wage occupations is trending up only from 2002-2012, and that the apparent earlier growth found in the literature is an artifact of unbridgeable changes in occupation codes. The late emergence of occupation based polarization is inconsistent with the explanation that computerization and automation have caused both employment polarization and rising wage inequality, unless underlying occupation based employment polarization in earlier periods was masked by human capital driven occupational upgrading of workers. We demonstrate that even absent breaks in occupation codes, occupation mean wages are unsuitable for the analysis of wage inequality: most of the increase in wage inequality is within and not between occupation; occupation mean wages do not capture the bottom of the individual wage distribution; and middle{wage workers are distributed widely across occupations. Computerization and automation may be increasing wage inequality, but the hypothesis cannot be studied through the lens of occupations and does not find support in our analysis...."

Jennifer Hunt and Ryan Nunn, "Is Employment Polarization Informative About Wage Inequality and Is Employment Really Polarizing?," National Bureau of Economic Research, July 2019, https://www.nber.org/papers/w26064

Research (preliminary) from Brookings using FHA data finds that the cost of building one mile of interstate highway in the 1980s was three times what it cost in the 1960s, adjusted for inflation.

".... There is widespread consensus that US infrastructure investment - and infrastructure quality - has been on the decline. In response, politicians across the ideological spectrum have called for increased infrastructure spending. How much infrastructure we would get depends on how much output is produced per dollar of spending. Yet we know surprisingly little about infrastructure costs across time and place. We help to fill this gap by using data we digitized on the Interstate highway system—one of the nation’s most valuable infrastructure assets—to document spending per mile over the history of its construction. We make two main contributions. First, we find that spending per mile on Interstate construction increased more than three-fold (in real terms) from the 1960s to the 1980s. We date the inflection point of increase to the early 1970s. We further show that neither changes in the observed geography of spending nor increases in material and labor prices explain these changes. Second, we provide suggestive evidence of the determinants of the increase in spending per mile. In particular, the increased spending per mile coincides with the rise of “citizen voice” in government decision-making in the early 1970s. And rising incomes and housing prices nearly completely statistically explain the increase in costs.We also largely rule out several common explanations for rising costs, such as increases in per-unit labor or materials prices.....The first is that the demand for more expensive Interstate highways increases with income, as either richer people are willing to pay for more expensive highways or in any case they can have their interests heard in the political process. The doubling in real median per capita income over the period accounts for roughly half of the increase in expenditures per mile over the period. Also consistent with this, and with the finding that the increased costs are due to increased inputs, not per unit input prices, we show that states construct more ancillary structures, such as bridges and ramps, and more wiggly routes in later years of the program. Controls for home value also account for a large proportion of the temporal increase; taken together, income and home value increases account for almost all the temporal change in costs..."

Leah Brooks and Zachary Liscow, "Infrastructure Costs," Brookings Institution, July 2019, https://www.brookings.edu/wp-content/uploads/2019/07/2019-07-12_infrastructure_costs_v2.pdf

"....China today differs in significant ways from Taiwan, South Korea and Japan at similar stages of development. One is that infrastructure, most of it state-led, and housing, are much more important in China, representing half of total investment, says Dwight Perkins, a China expert at Harvard University. This made sense when the average family’s apartment was just 200 square feet and even its most densely populated regions lacked freeways. Now, though, the average apartment is 800 feet, and new highways and railroads increasingly serve remote areas with less potential payoff. “It’s good for those areas, but the return on that investment has undoubtedly fallen very sharply.” Another difference is China’s reliance on debt, which, according to Mr. Tilton, is, as a share of GDP, two to four times that of its east Asian peers at similar stages of development. The upshot: China invests just as heavily but far less efficiently than its peers did. It shows:The return on capital plummeted from 19% in 2007 to 8.4% in 2017, according to Andrew Batson of Gavekal Dragonomics, a research service. The China Development Research Foundation, a government think tank, says total-factor productivity, which measures how efficiently labor and capital are deployed, began growing faster in 2016, led by services. But some analysts are skeptical of official data and say productivity growth has been negative for years. An inefficient state sector matters less if the private sector grows fast enough. But in recent years, private firms in China have faced multiple headwinds. State-controlled banks prefer to lend to state-owned enterprises, so private firms borrow from less-regulated “shadow banks,” which the authorities have targeted in their crackdown on excess lending. The domestic private sector’s share of total sales has dropped about 5 percentage points since 2016, according to Goldman, while the state sector’s share has risen roughly as much..."

Greg Ip, "China’s State-Driven Growth Model Is Running Out of Gas,"Wall Street Journal, July 17, 2019, https://www.wsj.com/articles/chinas-state-driven-growth-model-is-running-out-of-gas-11563372006