Macro Roundup

“…As companies across the U.S. fight to find workers, Amazon is emerging as a de facto wage-and-benefit setter for a large pool of low-skilled workers. Business experts have long researched what is known as the Amazon effect in disrupting traditional retailers. Now Amazon’s every move is causing ripple effects well beyond the retail space in local markets throughout America, including on inflation, regional job markets and labor standards, according to an examination of federal labor data and interviews with economists, researchers, local employment officials and current and former Amazon employees….“If they are not leading, they are reinforcing it,” said Lynn Reaser, a professor at Point Loma Nazarene University and longtime economist at financial institutions that include Bank of America Corp. “Everyone is comparing job offers, and they always have Amazon as a benchmark.” Even Amazon’s own internal employee challenges ripple through the market. The company’s turnover rate has exceeded more than 100% across many of its facilities, according to an analysis by The Wall Street Journal….A 10% increase in Amazon’s advertised hourly wages in 2018 led to an average increase of about 2.6% among other employers in labor markets where Amazon is located, according to a paper this year by researchers from the University of California, Berkeley and Brandeis University. Amazon’s influence on wage increases had a big effect because a large fraction of similar jobs then were below $15 an hour, researchers concluded. In comparison, when Walmart and Target Corp. announced $9 starting pay in 2015, the effect was smaller because there was a larger fraction of employers that were already at or above that pay level. Walmart in September raised its minimum wage to $12 an hour. At the same time, the researchers found Amazon’s increase in pay failed to raise overall employment levels and actually led to a small decline. While some employers that raised wages hired additional workers, others cut back on employment or hours. In Amazon’s case, the company’s increase to $15 an hour led to an average decrease in “probability of employment” by 0.8 percentage point, the paper says. Other research showed similar results….”

Sebastian Herrera, "Amazon Emerges as the Wage-and-Benefits Setter for Low-Skilled Workers Across Industries,"Wall Street Journal, December 7, 2021, https://www.wsj.com/articles/amazon-emerges-as-the-wage-and-benefits-setter-for-low-skilled-workers-across-industries-11638910694

Amazon Emerges as the Wage-and-Benefits Setter for Low-Skilled Workers Across Industries

Max Ramirez knew he had a problem when he found out about the truck.

About two years ago, Amazon.com Inc. employees rigged a vehicle to carry a makeshift billboard advertising starting pay of roughly $16 an hour. They drove the truck all over the small Texas city where Mr. Ramirez helps run a rival warehouse operation.

Within a few months, a handful of the employees at his company, mattress manufacturer Serta Inc., had decamped to Amazon. “We had no choice but to compete,” he said. The company raised its starting pay by roughly $2 to about $15 an hour and has since raised it about another dollar, he said.

As companies across the U.S. fight to find workers, Amazon is emerging as a de facto wage-and-benefit setter for a large pool of low-skilled workers. Business experts have long researched what is known as the Amazon effect in disrupting traditional retailers. Now Amazon’s every move is causing ripple effects well beyond the retail space in local markets throughout America, including on inflation, regional job markets and labor standards, according to an examination of federal labor data and interviews with economists, researchers, local employment officials and current and former Amazon employees.

The nation’s second-largest private employer is planning mock fulfillment centers in high schools to plant the seeds of future careers, sending recruiters to local fairgrounds and bombarding job boards with promises of large sign-on bonuses and pay—in some cases nearly triple the federal minimum wage.

The effect is magnified because Amazon churns through hundreds of thousands of employees each year, creating an even more voracious appetite for labor that often compels the company to push up compensation or improve recruitment in other ways—especially during peak times such as the holiday shopping period now under way.

“Amazon has the economies of scale,” said Jesse McCree, a workforce development official in Harrisburg, Pa., an area of the country where Amazon is competing heavily with other large logistics and warehouse companies. “They are influencing the market because of scale and name recognition and can afford to pay more than the smaller guys. As they go, even the big companies are going to pay attention.”

Similar effects are evident in areas near Austin, Los Angeles, Cincinnati and Louisville, Ky., according to a Journal review of local data and interviews with employers and workforce officials.

At produce distributor Castellini near Cincinnati, Chief Executive Brian Kocher can’t get away from Amazon. The company has wrapped job advertisements around cars, buses and billboards. And recently, when Mr. Kocher went to play his favorite Solitaire game on his iPhone, Amazon ads popped up there, too.

Castellini in the past year has raised wages three times, with its pay now starting around $16 an hour. Since many of its employees in the area are Spanish speakers, Castellini has recently focused on hiring and promoting managers who speak the language to better connect with workers. The company also implemented $750 bonuses for any employee who refers family and friends to work there.

Amazon has had a significant impact on the area since 2017, when the company struck a deal with the Cincinnati/Northern Kentucky International Airport to open a $1.5 billion air hub. Paul Verst, chief executive of Verst Logistics, which provides warehousing, transportation and packaging services for clients such as manufacturers and consumer-goods companies, said construction costs have risen by at least $30 a square foot to a range of about $90 to $100 due to increased demand for building space.

Mr. Verst recently gave employees a $3-an-hour raise to compete with Amazon. Starting pay now ranges from $16 to $19 an hour. He said his family-owned company aims to retain employees by connecting with them personally. He signs a birthday card for each worker. Tenures for many workers have averaged 10 to 15 years, he said. Still, the company has lost a handful of employees to Amazon, which has advertised pay of $20 or more an hour and $1,000 sign-on bonuses in the area.

“It was for economic reasons that they left,” he said.

There have been about two job openings for every unemployed person in Cumberland County, the Harrisburg-area county where several Amazon facilities are located. Warehouse competitors include pet food retailer Chewy Inc., United Parcel Service Inc. and food and agriculture giant Cargill Inc.

Wage wars in the area have been fierce ever since Amazon raised its starting pay nationally by several dollars to $15 an hour in 2018, local officials said. Much of the battle for hourly employees has played out near a stretch of the area’s Interstate 81 highway, where companies have erected billboard after billboard advertising sign-on bonuses and “immediate openings.”

On occasion, Chewy workers have left the company to work at Amazon almost immediately after receiving new training, according to a former area manager. During the Covid-19 pandemic, a period when Amazon hired workers as aggressively as any company in modern history, Cargill was at times so short of employees that it flew workers in from other locations, according to the company. Both Chewy and Cargill now advertise pay near $20 an hour in the area.

Employee turnover in Cumberland County rose after Amazon’s arrival spurred competition among local firms for workers. Three years ago, around the time when Amazon bumped its starting pay to $15 an hour, wages for warehouse employees in Cumberland averaged from $10.50 an hour to $12.50 an hour. Now, they range between $15 to $21 an hour, according to the Cumberland Area Economic Development Corporation.

“Amazon is the standard-bearer,” said Zach Pasquariello, a former Chewy area manager in the region. “Chewy was always following in Amazon’s footsteps and trying to do what Amazon does, but we were always a little bit behind.” Chewy declined to comment.

Job openings across the U.S. outnumber the people who are unemployed, Labor Department figures have shown, demonstrating an unusual tightness in the labor market that has seen a sharp rise in wages. How much of this is due to Amazon’s influence is difficult to pinpoint, due to limited data and the unique influence of the pandemic.

But as Amazon’s footprint has grown rapidly across the country, the potential for the company to influence wages or other market dynamics has increased, economists say. Amazon, which had around 1.4 million total employees at the end of September, hires hundreds of thousands of people every year, putting it on pace to surpass Walmart Inc. as the nation’s largest employer in a matter of years.

“If they are not leading, they are reinforcing it,” said Lynn Reaser, a professor at Point Loma Nazarene University and longtime economist at financial institutions that include Bank of America Corp. “Everyone is comparing job offers, and they always have Amazon as a benchmark.”

Even Amazon’s own internal employee challenges ripple through the market. The company’s turnover rate has exceeded more than 100% across many of its facilities, according to an analysis by The Wall Street Journal.

Amazon has recorded higher injury rates than the national average, and its speedy delivery requirements can quickly burn workers out. The company has faced lawsuits, union challenges and government intervention related to the treatment of its workforce, which has pushed it to introduce new safety measures such as body mechanics training for employees and vows from its top leaders to better listen to workers.

Amazon has said it is working to better understand the needs of its employees and has opposed unions because it prefers to negotiate with workers directly. The company also has said that many of the people it adds are re-hires, demonstrating that many workers return to the company after having earlier left.

Amazon’s wage increases pass through to workers outside the company, researchers have found, as many employers raise their own pay to combat churn. In September, Amazon announced that its starting wage now averages $18.32 an hour, an amount that’s nearly triple the federal minimum wage of $7.25 an hour.

To fight off Amazon, competitors have tried to offer lighter workloads, more flexible schedules, bonus pay and other perks. But Amazon is rolling out new plans to compete in those areas as well.

Amazon wants to use its size and scale to make its jobs as flexible as possible, J. Ofori Agboka, an Amazon senior human-resources executive, said in an interview. Having hundreds of thousands of employees makes it easier to offer workers different work hours, a perk many have requested, he said. Amazon recently broadened a program that allows some employees to switch schedules and pick their own work hours, or cancel a shift at the last minute. The company also offers a child-care network to employees and flexible hours for a few weeks for employees transitioning back to work.

“What does flexibility mean for each employee, and how can we meet that?” Mr. Agboka said.

Candidates are now essentially being hired on the spot, Mr. Agboka said, with many workers able to see their start date less than half an hour after beginning an application online. Amazon is also working to fix common retention issues, he said, such as employees who are dismissed after a minor incident like missing work due to an emergency.

It is too early to know how well some of Amazon’s new initiatives to increase flexibility will be felt in the labor force, but its pay increases are already having a widespread impact.

LaShay Moran, who lives near Louisville, joined Amazon during its current hiring spree. Ms. Moran, 42, left her job at auto parts distributor Premier Performance LLC in part because Amazon offered more money—$17.50 an hour versus $16 at Premier—and a $3,000 sign-on bonus.

“Everybody knows what it is,” she said of Amazon’s name recognition.

A 10% increase in Amazon’s advertised hourly wages in 2018 led to an average increase of about 2.6% among other employers in labor markets where Amazon is located, according to a paper this year by researchers from the University of California, Berkeley and Brandeis University.

Amazon’s influence on wage increases had a big effect because a large fraction of similar jobs then were below $15 an hour, researchers concluded. In comparison, when Walmart and Target Corp. announced $9 starting pay in 2015, the effect was smaller because there was a larger fraction of employers that were already at or above that pay level. Walmart in September raised its minimum wage to $12 an hour.

At the same time, the researchers found Amazon’s increase in pay failed to raise overall employment levels and actually led to a small decline. While some employers that raised wages hired additional workers, others cut back on employment or hours. In Amazon’s case, the company’s increase to $15 an hour led to an average decrease in “probability of employment” by 0.8 percentage point, the paper says. Other research showed similar results.

In response to its overall effect on employment, Amazon has previously pointed to the billions it has invested in infrastructure and the amount of jobs it creates.

In San Marcos, Texas, Amazon established its first fulfillment center in 2016 and soon approached the nearby Texas State University as the area’s largest employer.

Other warehouse operators in the area quickly felt the company’s presence. Amazon advertised on radio stations hundreds of miles away and attracted workers from competitors in short order.

Amazon staffs more than 4,500 workers in three facilities throughout the surrounding Hays County, and a fourth site recently opened that will employ at least hundreds more. The company has added more than 2,000 employees during the Covid-19 pandemic, according to local data.

Worker churn has been high at the facilities. Turnover in Hays County, which is located southwest of Austin, swelled to 101% in 2017, the first full year Amazon operated there. The rate plunged to 68% by 2019, according to a Journal analysis. That decrease happened after Amazon reduced the number of employees at the San Marcos warehouse, according to the Greater San Marcos Partnership, a local business group.

Since Amazon raised its starting pay in 2018, wages in the San Marcos area are also up substantially. Pay for employees in the warehouse and storage industry in Hays County grew by 12.7% in the two years after Amazon’s move to $15, compared with 4.3% in the two years preceding it, according to labor market research firm Emsi Burning Glass.

Walmart and others matched and sometimes exceeded Amazon’s pay at their facilities to stay competitive, said Jason Giulietti, president of the Greater San Marcos Partnership. A large sign recently hung from a Walmart distribution center south of Amazon’s San Marcos facility advertising pay of up to $20 an hour.

At lighting manufacturing giant Signify, which has a warehouse in Hays County, plant manager Haiver Montenegro said he competes with Amazon using flexible schedules, including usually not requiring employees to work on weekends.

“If we were just to compete with hourly rates with Amazon, we would never get there,” he said. “The biggest discussion around resources in this area has to be around what an employer has to offer as a whole package.”

Still, he is short about 15 production associates, with roughly 120 manufacturing employees at the warehouse, according to the company. Signify recently raised starting wages there to around $15 an hour in part because of Amazon’s wage hikes, and he is considering putting up job advertisements on billboards for the first time.

"...The number of U.S. homes with a married couple and kids fell to a record low, according to new government data, as the pandemic further delayed weddings and more adults don’t plan to have kids at all. The share of the U.S.’s 130 million households headed by married parents with children under age 18 fell to 17.8% in 2021 from 18.6% last year, according to the Census Bureau.That’s down from more than 40% in 1970. By absolute numbers, there are just 23.1 million homes with nuclear families, the fewest since 1959, the data show. The pandemic delayed many marriages over the past two years, adding six months to a woman’s age at first marriage -- the most since 1987 -- to now 28.6 years. In the 1950s and ‘60s, women typically married at 20.4 years of age and 22.8 years for men...."

Alexandre Tanzi, "U.S. Married Couple Households With Children Fall to Record Low," Bloomberg, December 3, 2021, https://www.bloomberg.com/news/articles/2021-12-03/u-s-married-couple-households-with-children-fall-to-record-low

U.S. Married Couple Households With Children Fall to Record Low

The number of U.S. homes with a married couple and kids fell to a record low, according to new government data, as the pandemic further delayed weddings and more adults don’t plan to have kids at all.

The share of the U.S.’s 130 million households headed by married parents with children under age 18 fell to 17.8% in 2021 from 18.6% last year, according to the Census Bureau. That’s down from more than 40% in 1970.

By absolute numbers, there are just 23.1 million homes with nuclear families, the fewest since 1959, the data show.

Casey Mulligan on the natural experiment Chicago is running, “… Figure 1 below shows points-in-time numbers of people in Illinois prisons who were convicted in Cook County and admitted to prison within the past half year. The stock of new convicts had been between 3000 and 4000, until the pandemic when it dropped to 1000. Figure 2 limits the sample to convicted murderers. They had been entering Illinois prisons at a rate of about 130 per year (65 per half year), until the first half of 2020 when the rate dropped to about 40 per year (20 per half year).I hope that Chicago-area activists can work to help maintain this progress. Perhaps they could even lend some expertise to the rest of Illinois (not shown in the charts above), which has missed a social-justice opportunity by continuing to admit convicted murderers to prison at pre-pandemic rates….”

I hope that Chicago-area activists can work to help maintain this progress. Perhaps they could even lend some expertise to the rest of Illinois (not shown in the charts above), which has missed a social-justice opportunity by continuing to admit convicted murderers to prison at pre-pandemic rates.

Formerly experts thought that incarceration enhanced public safety. But that was based on old data, examined by researchers lacking sufficient social-justice training. Especially during a pandemic, there is no reason to worry about adverse consequences until somebody has conducted A study using state-of-the-art empirical methods.

A troublesome skeptic might insist on metrics to indicate when the tradeoff-holiday has ended, when the path to safety might again involve more incarceration rather than less. Could it be dangerous to barrel forward on the social-justice highway, when at any moment we could find ourselves in high-speed reverse?

Such a reactionary critic forgets that social justice is crowd sourced. The overwhelming odds are that one of us will notice the situational shift and promptly alert the polity. In the worst-case scenario, remember: if we want to make an omelette, we must be prepared to break a few eggs.

Social Justice Thrives in Cook County during Tradeoff Holiday

During this terrible pandemic, a silver lining has been that many inconvenient tradeoffs no longer apply. A Yale study showed that paying people not to work does not, for the time being, prevent anyone from working. Perhaps also emptying the prisons can enhance public safety. We can have social justice and safety at the same time.

Figure 1 below shows points-in-time numbers of people in Illinois prisons who were convicted in Cook County and admitted to prison within the past half year. The stock of new convicts had been between 3000 and 4000, until the pandemic when it dropped to 1000. Figure 2 limits the sample to convicted murderers. They had been entering Illinois prisons at a rate of about 130 per year (65 per half year), until the first half of 2020 when the rate dropped to about 40 per year (20 per half year).

Casey Mulligan, “Social Justice Thrives in Cook County during Tradeoff Holiday,” supply and demand (in that order), November 13, 2021, http://caseymulligan.blogspot.com/2021/11/social-justice-thrives-in-cook-county.html

“…the time-series of investment and payouts to shareholders reported inFigure 10reveal an interesting pattern. increase in payouts to shareholders outweighs the increase in investment a.er the recent TCJA-17, but not a.er the Kennedy’s tax cuts..is can be observed both at the aggregate and at the c-corporations level. In fact, payouts does not appear to deviate much from the pre-reform trend, unlike investment which exhibits a clear acceleration. The increase in capital formation is gigantic: aggregate business investment is 50% higher in 1966 than in 1963, and c-corporations’ investment is 80% higher….”

Core finding, "... the results are reported in Figure 11. In response to the Kennedy’s tax cuts, the model predicts a large increase in GDP and investment, and a small effect on payouts to shareholders: the opposite of Trump’s Tax Cuts and Jobs Act. Similarly, the corporate tax multiplier for Kennedy’s tax cuts is around 2:5 for GDP, 1:85 for investment, and close to zero for payouts to shareholders. For the TCJA-17, the multiplier is around 0:6 for each variable. For every dollar of lost corporate tax revenues, the Kennedy’s corporate tax cuts stimulated GDP four times more than the TCJA-17. The intuition behind these results is the following. In the early 1960s, the corporate tax rate was high and tax depreciation policy was not accelerated as it was mimicking economic depreciation. As a result, the corporate tax wedge was well below one (around 0:72) before the reform. The Kennedy’s tax cuts increased the wedge significantly (to around 0:84), thus providing strong stimulus to the investment of c-corporations. Moreover, since around 75% of economic activity was taking place in the c-corporate sector, the aggregate effect was less diluted than in 2017….”

Evidence from the Trump vs Kennedy Tax Cuts

Mike Pettis Comment, "In this very interesting paper @Furno_Francesco compares the Kennedy corporate tax cuts in the early 1960s with the recent Trump corporate tax cuts, and finds that the former stimulated output roughly four times more than the latter. Put differently, the Kennedy tax cuts seem to have increased business investment while the Trump tax cuts were mostly passed on to shareholders which, as Atif Mian, Ludwig Straub and Amir Sufi have explained elsewhere, was likely in turn to lead to higher household debt. Furno explains that “A large part of this difference can be attributed to differences in pre-reform tax depreciation policy.” As I argued in my book and elsewhere, I think the reasons the Kennedy tax cuts flowed into investment and Trump tax cuts into savings had to do with the very different relationship between savings and investment at the time of the tax cuts. From a macro point of view corporate tax cuts increase business profits, which raise corporate savings. Whether these are used to fund investment or are passed on to shareholders depends on whether the main constraint on business investment is scarce savings or weak demand. In the former case, higher business profits can lead fairly automatically to higher business investment. If savings are abundant and the cost of capital low, however, the constraint is likely to be weak demand. In that case businesses will have little incentive to increase investment, and a cut in their taxes simply increases the after-tax profits they pass on to shareholders or use to acquire other companies. In the early 1960s, much of the world was still in the process of rebuilding itself after the ravages of two world wars. With high global investment needs and low global savings (the war caused income to plummet and, with it, savings), the main economic constraint was a scarcity of savings needed to fund investment. This was a time when the US was exporting so much of its domestic savings to the rest of the world that capital controls were imposed to restrict the outflow of dollars. Under these conditions it is not surprising that any policy that generated an increase in savings was likely - in classic supply-side fashion - to lead to an increase in business investment. In recent decades, however, conditions were dramatically different. The world has become awash in ex ante savings, and the US has become the dumping ground for nearly half of the world’s excess savings. What is more, US businesses are sitting on huge piles of cash and can only use them to buy back shares or purchase other companies. It is weak demand, in other words, and not scarce savings, that has limited business investment. In that case policies that increase in savings have little to no impact on business investment, and in fact could actually reduce business investment if the increase in business savings were balanced by a reduction in household income (and, with it, consumption). To me this is the key difference between the Kennedy and Trump tax cuts. The former provided more savings at a time when American businesses wanted to invest more, but were unable to do so in part because of the fierce global competition for US savings. The latter provided more savings at a time when the world was awash in excess savings and American businesses wouldn’t invest until they saw a rise in demand. As an aside, I am re-reading Charles Arthur Conant’s 1900 book, and it is amazing how similar the problem of excess savings the global economy faced in the 1880s-90s. At one point he proposes establishing a state pension system to help generate the demand needed to absorb excess global savings. This is because “experience has shown that when saved capital accumulates rapidly, the groping after new uses for it causes waste and disaster”.

Core of paper“…In the model, corporate tax changes affect the economy primarily through the investment decision of c-corporations, which is affected not only by the tax rate but also by tax depreciation policy. Specifically, the possibility to deduct investment from the tax base (partially) counteracts the distortion introduced by the tax rate: the faster investment is deducted from the tax base, the smaller the distortion to the rate of return on investment. As a result, when tax depreciation policy is very accelerated - like it was in 2017 - the rate of return on investment is almost unaffected by corporate tax policy, and a reduction in the corporate tax rate is not particularly expansionary……However, irrespective of how much stimulus is provided to investment, a corporate tax cut always entails a transfer of resources from the government to c-corporations. When pre-reform tax depreciation policy is very accelerated, the tax-savings from a rate cut are not used for investment and are distributed to the shareholders. When pre-reform tax depreciation policy is not very accelerated, instead, the extra cash is used for investment. Moreover, since a change to the corporate tax rate affects only c-corporations, the aggregate effect is diluted by the presence of pass-through businesses. After a rate reduction, pass-through entities are not only excluded from the tax cut, but they are also put at a competitive disadvantage. ‘is happens because they compete with c-corporations in the production of (imperfectly) substitutable goods, which further amplifies the shift of economic activity from pass-through businesses to c-corporations and reduces the aggregate effect even more….”

"…We estimate the impact of district-level schooling mode (in-person versus hybrid or distance learning) on test scores. We combine Spring 2021 state standardized test score data with comprehensive data on schooling in the 2020-21 school year across 12 states. We find that pass rates declined compared to prior years and that these declines were larger in districts with less in-person instruction. Passing rates in math declined by 14.2 percentage points on average; we estimate this decline was 10.1 percentage points smaller for districts fully in-person. Changes in English language arts scores were smaller, but were significantly larger in districts with larger populations of students who are Black, Hispanic or eligible for free and reduced price lunch…”

“…Panel A of Figure 2 shows the year-on-year changes in math test scores by group for prepandemic years (left figure) and for the pandemic year (right figure). In most cases, the test score declines in the pandemic year are larger in the districts with less in-person instruction. This difference is largest in Virginia. There is no evidence that this pattern aligns with the pre-pandemic years. Prior year-on-year changes do not seem to systematically vary with 2020-21 schooling mode. Panel B shows the results for ELA. While the overall changes are smaller in ELA as compared to math, the pattern is similar….”

“…Figure 1 illustrates the changes in pass rates across states during the pandemic period (the 2020-21 school year) and in several previous periods (the 2015-16 school year through 2018-19). Panel A shows the scores in math and Panel B presents the scores in ELA. The solid triangles represent the change in pass rates between the 2018-19 school year (the last pre-pandemic year) and the 2020-21 school year. The open circles show prior year-on-year changes. Our analysis finds a decline in pass rates from the 2018-19 school year to the 2020-21 school year in all states. The decline ranges from -31.9 percentage points (Virginia, math) to -2.3 percentage points (Wyoming, ELA). Based on the prior year changes, typical year-on-year variation is very small. The pandemic year is a significant outlier. The changes in pass rates for math (Panel A) are considerably larger than the changes in scores for ELA (Panel B). This is broadly consistent with a larger literature which shows math scores are more responsive to schooling differences(Betts and Tang, 2011; Angrist et al., 2013)….”

The Evidence

Core findings, “…In this paper, we use data on district schooling modes alongside Spring 2021 test score data from 12 states to analyze the relationship between schooling mode and test scores. We estimate the relationship between the share of the year that in-person learning was offered (as opposed to hybrid or virtual learning) and student standardized test scores, both overall and interacted with district demographics. Our main regression specification uses a standard panel data approach, with data at the district-year level, to estimate the impact of the time spent in-person on 2021 test scores. These regressions include district-specific trends and a full set of demographics and year interactions. We demonstrate first that, across all 12 states in our sample, there were large reductions in test scores between 2020-21 and previous years. The average decline in math is 14.2 percentage points, versus 6.3 percentage points in English language Arts (ELA). These changes are well outside typical year-on-year variation. Following this, we show our main finding: the decline in students' 2021 test scores as compared to prior years was significantly larger in districts which offered less access to in-person schooling. For example, we estimate that offering full in-person instruction rather than fully hybrid or virtual instruction reduces test score losses in math by 10.1 percentage points (on the base of 14.2 percentage points). In ELA, the loss is reduced in fully in-person settings by 3.2 percentage points.These interactions between test score losses and schooling mode are highly significant. We demonstrate, as well, that access to in-person learning varied by demographics and baseline test scores. Districts with lower baseline test scores and a higher share of Black students offered less in-person learning. Within states, districts with a higher share of Hispanic students also offered less in-person learning (although across states this effect is reversed). Finally, we observe that the impact of access to in person learning on 2021 test scores also varies by subject and demographics. Specifically, among districts with a larger share of Black and Hispanic students, districts with less in-person schooling saw a greater decline in ELA test scores than those with more in-person schooling. Although the impact of schooling mode on ELA is fairly small for districts which are majority white, it is large for those districts with a majority of students of color. Meanwhile, the impact of access to in-person learning had a similar effect on math scores for all districts, regardless of their racial composition….”

Clare Halloran, Rebecca Jack, James Okun and Emily Oster, “Pandemic Schooling Mode and Student Test Scores: Evidence from US States,” National Bureau Of Economic Research, November 2021, https://www.nber.org/papers/w29497

New NBER takes a look at a world where ideas are the limiting constraint, "...High productivity entrants gradually replace obsolescing incumbents by poaching their workers, a process that is intermediated via a frictional labor market. When the likelihood of entrants imitating technologies in the tail of the distribution falls (ideas are harder to find), so does growth. Consistent with US data over the past 30 years, firm entry, incumbents’ employment response to productivity shocks, and job-to-job transitions decline, while the share of old firms increases. With lower imitation, however, there is less misallocation, because the slower rate of obsolescence induces productive growing firms to invest more in costly hiring...."

The dynamic, "... First, growth slows down. Second, the implications of a growth slowdown via this mechanism is consistent with facts related to firm dynamics. Employment reallocation falls, as entrants are relatively lower productivity and poach less from incumbents, while incumbents obsolesce at a slower rate. The firm entry rate declines, and the share of employment in old firms increases. Following productivity shocks, firms also hire fewer workers, consistent with Decker, Haltiwanger, Jarmin, and Miranda (2020). As we discuss below, a lower rate of obsolescence reduces misallocation, with workers more efficiently sorted across the productivity distribution of firms. Poaching a worker from another firm to fill a new job is more difficult in a less misallocated labor market so firms expand more slowly following a shock to their productivity...."

Impact on labor market, "....Third, we document the implications for worker dynamics. We find that on all dimensions labor market flows slow down: employment-to-unemployment (EU), unemployment-to-employment (UE) and employment-to-employment (EE) transitions rates decrease. Ceteris parabus, the decline in the UE rate would lead to an increase in unemployment, but the decline in the rate of obsolescence reduces the rate of layoffs. On net, the second force is stronger such that unemployment declines. Overall, we find weaker creative-destruction effects of a faster growth rate on unemployment than in canonical matching models without on-the-job search. One important reason is that in our environment, as in the real economy, half of job separations are EE transitions which do not entail any unemployment spell. Fourth, these observations, combined with a decline in job-to-job mobility may suggest that misallocation is worse when growth is slower due to a lower intensity of imitation. Interestingly, however, we find the opposite. As growth slows, the misallocation that exists in the economy improves. The dispersion of the marginal product of labor across firms declines and the correlation between size and productivity increases. This leads to a higher level of output, despite slower growth. We find that this level difference is quantitatively significant..."

The evidence,"...In summary, we have calibrated a model of endogenous growth at rate g that matches key facts regarding firm and worker dynamics in the US economy over the period 2011-2016.... Figure 1 verifies that the model matches the empirical distribution of firms and employment by firm age and firm size. Most firms are small, but most employment is at large firms. Most firms are old and most employment is at old firms. Second, Figure 2 reveals the dynamics of the distribution of firm size and productivity over the lifecycle that deliver the empirical marginal distributions in Figure 1. The figure shows how misallocation is partially resolved over the lifecycle, with employment and productivity becoming increasingly correlated as firms age. A key feature of the model, which we highlight in BEMV, is that the model can generate small, productive, young firms. Young firms with high productivity are small because they are young and yet to accumulate workers through the frictional labor market. This is a key source of misallocation in the economy, due to search frictions, on which we will return when we discuss our results...."

Adrien Bilal, Niklas Engbom, Simon Mongey and Giovanni Violante, “Labor Market Dynamics When Ideas are Harder to Find,” National Bureau Of Economic Research, November 2021, https://www.nber.org/papers/w29479

Business dynamism

"..Figure 4 shows firm dynamics outcomes as we vary the underlying imitation parameter y. Since the parameter is not of direct interest, we plot these key outcomes as a function of the resulting endogenous growth rate. Not surprisingly, a fall in y (i.e. moving to the right in these figures) is associated with an increase in firm creation (panel A). As imitation from the incumbents is easier, entrants are relatively more productive and firm creation is encouraged. As more entrants attempt to enter and there is more competition for inputs, the price of inputs rises faster. Consequently, incumbent firms exit at a faster pace and the rate of obsolescence increases.This is our counterpart of the creative-destruction effect of Aghion and Howitt (1994). Quantitatively, a fall in the aggregate growth rate of one percentage point annually—broadly consistent with the US experience over the past decades—is associated with a decline in firm entry of about 30 percent. For comparison, the US has experienced a reduction in firm entry of over 40 percent since the early 1980s to now...Also consistent with the US data over the past 40 years, a larger share of firms are old when growth is slower (panel B). This outcome arises naturally in our model in response to a fall in the rate of obsolescence—firms remain in the market for longer, extending the firm life-cycle. The overall job reallocation rate falls with the aggregate growth rate (panel C). The reason is that as the rate of obsolescence declines, firms do not fall behind the market as quickly. Consequently, there is less need to reallocate employment across production units. Quantitatively, as the aggregate growth rate declines by 1 percentage points annually, the job reallocation rate decreases by around 10 percent. For comparison, the US has experienced a decline in job reallocation of roughly 30 percent since the early 1980s to now...."

"...Figure 6 illustrates a surprising result. As growth slows, the misallocation that exists in the economy improves, despite there being less firm and worker turnover.The dispersion of the marginal product of labor across firms falls (panel A) and the correlation between size and productivity increases (panel B). This is consistent with the well documented reallocation of sales in the economy toward larger firms (Autor, Dorn, Katz, Patterson, and Van Reenen, 2017), and leads to a higher level of output, despite slower long-run growth. What explains this finding? Our model is unique in the class of growth models in that firms operate a single product, start small, and then grow via costly hiring of workers. When the rate of economic growth is high, firms’ productivity is quickly slipping behind the productivity of the economy as a whole. High productivity firms are therefore less ambitious with respect to these expansion plans. Hiring is costly and takes time, and has a lower benefit when the firm will be swiftly replaced by better firms. High productivity firms therefore no longer grow as large, which shows up as increased misallocation of labor in the economy. We find that this output loss from misallocation can be quantitatively important. Panel (C) computes a measure of ’lost years’ caused by this level effect. It asks how many years, at the baseline annual growth rate of 1.75 percent, it would take to compensate the downward shift in the level of output caused by misallocation. For example, the additional misallocation that occurs at a growth rate of 4 percent, would be offset by 22 years of economic growth at 1.75 percent. The relation is highly nonlinear: when the economy grows fast, the growth-induced misallocation is weak. Starting from low growth rates, however, a rise in the growth rate of 1 percentage point per year would require over 15 years of baseline-growth to make up for the productivity loss from misallocation. Panel (D) shows that in terms of the present discounted value of output, an improvement in imitation that increases the growth rate to at least 2.9 percent is required to offset the misallocation effects from higher growth. Admittedly, here we do not compute the transition between one balanced growth path and the other, and y is an exogenous parameter. Nonetheless, these calculations suggest that computing the misallocation costs of higher growth may be an important consideration in the formulation of progrowth economic policies that could be implemented to change objects related to diffusion of ideas in the economy...."

Evidence that NAFTA drove working class voters out of democratic party to GOP, “…We begin by showing thatNAFTA had a major, negative effect on employment in areas exposed to Mexican import competition. By 2000, counties in the top quartile of our measure of NAFTA exposure saw a 5-8 log point decline in total employment, relative to the bottom quartile. These losses were concentrated in manufacturing and, importantly, exhibit no pre-trends from the mid 1980s to 1994. While we begin all of our analysis by showing trends with county year raw data, the basic shape of our event-study coefficients are unchanged as we add a large number of controls: pre-period county-level measures (e.g., 1990 manufacturing share of employment, 1990 share with a college degree) interacted with year fixed effects, to control flexibly for other secular changes (e.g., automation, skill biased technological change) that may affect communities differentially across time; the “China shock” measure from Autor et al. (2013) interacted with year fixed effects, to ensure we isolate the NAFTA effect from the rise of Chinese imports; and fixed effects at the state×year level, to pick up any policy or other unobserved variation within states across time... Having documented large, negative local employment effects in communities exposed to Mexican import competition, we then ask how voters in these communities reacted. NAFTA was a major issue in the 1992 U.S. presidential campaign, with Ross Perot making opposition to it a major motivation for his third-party campaign, a third-party campaign that picked up 19 percent of the popular vote, making it the most successful such campaign since Teddy Roosevelt’s run as the Bull Moose Party candidate in 1912....We focus on House election votes in most of our political analysis, as every House seat is up for election every two years, allowing for a balanced panel of years. While NAFTAexposed counties (many in the upper South) begin the sample period more Democratic as measured by House election votes than the rest of the country, they exhibit a sharp change in trend and become increasingly Republican. In contrast to our employment effects, which show no pre-1994 pre-trend regardless of specification, this political turning point occurs in either the 1992 or the 1994 election, depending on the controls we include in the event study analysis. We find this ambiguity unsurprising, given the political salience of NAFTA in the 1992 election, even though its provisions did not go into effect until January 1994. Beyond the ambiguity between 1992 and 1994, there is no political pre-trend in NAFTA exposed counties from 1980 to 1990. The shift we document is large. While these counties are in 1990 the most Democratic of our four quartile groups, by 2000 they are as or more Republican than any of the quartiles. We present a variety of microdata-based evidence that the political shift was indeed due to NAFTA. First, we show that in the areas we define as most vulnerable to NAFTA, survey respondents significantly oppose NAFTA and this opposition continues to the present day. Second, in repeated cross-section data from the American National Election Surveys (ANES) we show that, in each year of survey data from 1986 to 1992, Democrats enjoy a significant and steady advantage among those with protectionist views, but between 1992 and 1996 a significant number of protectionist voters move toward the GOP and remain there. Finally, in an ANES panel dataset from 1992 to 1994, we can look at the same voters over time during this key moment. We indeed find that a significant share of those who in 1992 express protectionist views have moved their party-identification toward the GOP by 1994. We show these effects are robust to flexibly controlling for a variety of demographic variables as well as views on other political and policy questions...This shift among protectionist respondents is larger for whites (especially men and those without a college degree) and those with conservative social views, suggesting an interactive effect whereby racial identity and social-issue positions mediate reactions to economic policies…"

Jiwon Choi, Ilyana Kuziemko, Ebonya Washington and Gavin Wright, “Local Economic and Political Effects of Trade Deals: Evidence from NAFTA,” National Bureau Of Economic Research, November 2021, https://www.nber.org/papers/w29525

“…We show the results of estimating the event-study equation (5) in Figure 13. The first series shows the coefficient estimates from an equation with no controls (so the vector Xi is omitted), so the plotted points are just raw differences. We see that pre-NAFTA, those with protectionist views were less supportive of the GOP. Sometime between 1992 and 1996 (the protectionist question is not asked in 1994) a significant number of protectionist voters moved toward the GOP, so that the raw difference disappears. In Appendix Figure?? we show this result as two separate series instead of as a difference, and we also include 2016, which shows that in that year there was yet again another movement of protectionist voters toward the GOP, consistent with Trump's anti-trade message. In the second series, we add standard demographic and socioeconomic controls: race, sex, age, education, and income. The same 1992-1996 shift toward the GOP among protectionist voters remains, even after allowing these characteristics to have their own effect each year. In the final series, we add controls for trust in the federal government, views (a thermometer" going from cold to warm) toward African Americans (given the importance of race in U.S. politics), views on abortion, and weekly religious attendance. We are limited somewhat by wanting to use questions that are asked each or most years in our sample. For example, questions on gay rights and regulations on _rearms purchases are missing in our pre-period (we are able to add a richer set of controls in our panel-data analysis in the next subsection). As the final series of the figure shows, the large shift between 1992 and 1996 remains even after flexibility controlling for views toward the other salient issues available over our sample period….”

“…Figure 12 makes clear that, throughout the 1980s, NAFTA-vulnerable counties exhibited a steady Democratic lean in House elections, but beginning in 1994 shift in the Republican direction….”

Evidence, “…Our first set of political results takes the same county-level event-study approach we have used for our local-economic analysis, except that our dependent variable occurs every other year, as we focus on House election outcomes. Because of the important role of NAFTA in the 2016 election, we extend our post-period to 2016, though readers are free to discard evidence this far from the original 1994 event. Except for the extension of the sample period and our observing the dependent variable biennially instead of annually, the analysis remains identical to those in the previous sections. Figure 12 shows the House election outcomes using our standard event-study specifications. Unlike the employment and other economic outcomes, which had a clear break beginning in 1994 (the year of NAFTA implementation), our baseline specification shows a break beginning in the 1992 election. Given the large role that the debate over whether to ratify NAFTA played in the 1992 election, it is not clear that 1994 as opposed to 1992 is the most legitimate start of the post-period" for the political analysis. Adding state-year fixed effects generally does not change the event-study coefficients, though now 1994 appears more like the break in trend than does 1992. It appears that within states, NAFTA-exposed counties break from their pre-period trend in 1994, even if the break occurs in 1992 when both within- and between-state variation in NAFTA exposure is considered. As we have found throughout the previous analysis, adding the ADH CZ-level measure interactions with year fixed effects (the second series in Figure 12) makes no appreciable difference to the event-study coefficients. Nor does 1990 county-level manufacturing interacted with each year. Again, as with previous outcomes, the set of covariates that most attenuates the implied effects of NAFTA are the 1990 college share interacted with year fixed effects. But even with this specification, we find a visually compelling shift in the two-party Democratic share of vote in House races. In this specification, there is a at pre-trend with no coefficient’s confidence interval exclude zero, but in the post-period an average coefficient value of roughly -0.75 (compared to the other specifications, where the post-period coefficient values are more like -1.5). What do these magnitudes suggest in terms of actual political outcomes? Taking our preferred specification (the second series, with state_year _fixed effects) the average of the coefficients in the late 1990s and early 2000s is roughly 0.60, suggesting that the most exposed quartile increase its share of GOP House votes by roughly 4.8 percentage points relative to the least exposed. As Table?? shows, the baseline for this group was only 0.38, so the 4.8 percentage point swing is very large. Appendix Figure A.12, which presents the data in completely raw form, shows that by 1998, these once-solidly Democratic counties voted as or more Republican in House elections as did any other county quartile…”

The political response in areas vulnerable to NAFTA

Evidence, “…Figure 4 shows our four groups of counties, with data unadjusted except for each group's (log) employment level being normalized to zero in 1993. While in the event-study analysis we weight by 1990 county population (both to match past work as well as to better match to the political results, where counties are essentially weighted by population of voters) in this raw analysis we do not. The four series are nearly on top of one another in the years leading up to NAFTA. But they begin to diverge thereafter. By 2000, the most-exposed quartile has roughly five to ten log-points less than other counties relative to the 1994 baseline. Note also that the second-most-exposed quartile also shows a slowing of employment growth relative to the least-exposed half of counties, suggesting that the effect is not entirely driven by a few counties in the most-exposed quartile… As shown in Table A, counties that would be more exposed to NAFTA were already different on important dimensions in 1990: for example, they had higher reliance on manufacturing employment and lower rates of college-degree completion. The fourth series in Figure 5 adds 1990 manufacturing share of county employment interacted with year fixed effects, which barely moved the coefficients. The final series is the same, but instead adds 1990 share of adults with a college degree interacted with year fixed effects. Of all the controls we add, this one has the most appreciable effect. Nonetheless, the effects are large, negative and highly significant..."

China). While growing before NAFTA, Mexican imports enjoy more rapid growth beginning in 1994. Interestingly, despite the larger focus on China in the empirical labor economics literature, it is not until 2004 that China supplants Mexico as the most important low income source of imports (though its rise since 2004 is indeed more rapid than any period for Mexico)….”

Good factoid, “…Figure 1 shows the value of imports to the US from Mexico (and, for context, also includes

“…Ladd made one criticism that will have a familiar ring today: “In recent years, election polls have frequently overestimated the Democratic share of the vote. Since the 1980s, exit pollsters have tended to overstate Democratic candidates’ strengths.” “Frequently” may have been too strong, but the problem was and is significant. A Pew Research Center analysis of 2020 polls conducted after September 15, 2020, found that “93 percent of national polls overstated the Democratic candidate’s support among voters.” Eighty-eight percent of polls did so in 2016….”

Karlyn Bowman, "The pollsters’ Waterloo,"Forbes, November 18, 2021, https://www.aei.org/articles/the-pollsters-waterloo/

The pollsters’ Waterloo

Twenty-five years ago today, The Wall Street Journal excerpted an article written by the political scientist Everett Carll Ladd with the title, “The Pollsters’ Waterloo.” Ladd didn’t pull any punches. “Election polling,” he said, “had a terrible year in 1996. The entire enterprise should be reviewed...” The reaction to the article from some pollsters was swift and severe. Some clearly saw his criticisms as a threat to their livelihood, while others said his description of final poll results on which he based his criticism was erroneous. A quarter century later, however, the pollsters are thriving, but the criticisms Ladd raised continue to cast a shadow over their work.

Ladd made one criticism that will have a familiar ring today: “In recent years, election polls have frequently overestimated the Democratic share of the vote. Since the 1980s, exit pollsters have tended to overstate Democratic candidates’ strengths.” “Frequently” may have been too strong, but the problem was and is significant. A Pew Research Center analysis of 2020 polls conducted after September 15, 2020, found that “93 percent of national polls overstated the Democratic candidate’s support among voters.” Eighty-eight percent of polls did so in 2016.

Ladd urged the pollsters to convene a blue-ribbon commission like their predecessors did after the polling debacle in the 1948 election. After all, as the late Andrew Kohut, one of the giants in the field who was a principal at both Gallup and Pew said, the survey business should not be judged solely on the performance of election polls, but these polls are the “most visible expression of the validity of the survey research method.” In both 2016 and 2020, under the auspices of the American Association for Public Opinion Research (AAPOR), a distinguished group of practitioners and academics reviewed publicly available national and state-level results. The big takeaway from the new report: the polling error in 2020 “was the highest in 40 years for the national popular vote and the highest in at least 20 years for state-level estimates of the vote in presidential, senatorial, and gubernatorial contests.” The polling error that favored Biden over Trump was consistent across different survey modes.

In 1948, the reviewers concluded that the pollsters stopped conducting their polls too early, and that voters made up their minds late in that campaign. In 2016, the AAPOR task force pointed to several factors: a large number of late deciders who broke disproportionately for Donald Trump and incorrect weighting for voter education levels in many key states. The 2020 report ruled out those factors and a number of others.

The 2020 task force could not say with certainty given available data why polls overstated the Democratic margin. But they advanced a number of possible explanations. One is that Trump’s strongest supporters simply chose not to respond to pollsters, while those who did voted more Democratic, thereby skewing results. They speculated that nonresponse could have contributed, as could weighting measures and a large infusion of new voters.

If it is a key explanation, the nonresponse problem may be specific to Trump. His criticisms were harsh, but they certainly weren’t new. Others have tried to undermine the poll participation as well. In 1984, the popular Chicago Tribune columnist Mike Royko urged his readers to join him in what he called a “noble pursuit,” to “lie” to the pollsters in the Illinois primary that year. And after the 2000 election, a blue-ribbon panel, with honorary cochairs Gerald Ford and Jimmy Carter, “strongly encourage citizens not to participate in exit polling.”

Ladd lodged other criticisms as well: he believed the sheer volume of pre-election polling activity and relentless media coverage of the horse race distorted elections. As a friendly critic, I would add other criticisms. With the possible exceptions of Gallup and Pew, pollsters incessant chasing of headlines and focus on polarization has caused them to abandon many old questions that gave us a fuller sense of who we are. They have given short shrift to ordinary life in favor of politics, politics, politics and the negativity it conveys. Pollsters shouldn’t abandon political coverage. It is essential. But other subjects should be given their due.

Ladd was a long-time friend and mentor. Despite his criticism, it was always clear to me that he wanted the survey business, which he loved and thought vital to our understanding of America and democracy, to perform better. He would no doubt appreciate the impressive efforts of the 2016 and 2020 task forces. He would applaud the extraordinary work pollsters have done on COVID. But he would be saddened that there is neither a clear answer to a problem he identified a quarter century ago, nor an obvious way to fix it, nor an effort to provide a fuller picture of American life.