Macro Roundup

Note polling is from October 2016

Peter Aldhous and Jeremy Singer-Vine, "Which White People Support Trump?"Buzzfeed, October 9, 2016, https://www.buzzfeednews.com/article/peteraldhous/trump-and-the-white-vote

Which White People Support Trump?

Race and ethnicity have been a constant backdrop to the 2016 presidential election, thanks to Donald Trump’s provocative comments on immigrants, black communities, and an American-born judge he called “Mexican.”

Yet in all the slicing and dicing of voting intentions by key demographic groups, the “white vote” has largely been considered as a single ethnic block — until now.

A new poll run for BuzzFeed News, which delves into white voters’ self-reported ancestry, reveals surprising diversity in their political outlook. White voters who identify most strongly with their German or Italian heritage strongly support Trump, whereas those who self-identify as Irish, English, or Scottish are more evenly split between Trump and Hillary Clinton.

Between September 22 and October 2 (notably, before the bombshell video of Trump making lewd comments about women), as part of its regular online political poll, the survey firm Morning Consult asked more than 5,000 registered voters to check which of the most common ancestry categories recorded by the Census Bureau applied to them, and also to pick the one ancestry they identified with most.

As in previous polls, voters were starkly divided along broad racial, ethnic, and gender lines.

Many white Americans simply described their ancestry as “American.” Historically, that has been a label favored by people of Scotch-Irish descent who settled in Appalachia — although it was probably used more widely in our poll.

German is the most common European heritage in the United States, claimed by some 45 million people in 2015, or more than 14% of the U.S. population, according to the Census Bureau. Irish, at more than 10%, and English, at about 7.5%, are the next most common. (These categories overlap because many people identify with more than one ancestry).

Those ancestries also led the way in our poll, although Morning Consult recorded more people who identified as English and American than expected from the Census Bureau numbers. That could reflect differences in sampling, the way in which the ancestry question was asked, or the fact that our poll only included registered voters.

For some groups, sample sizes were small. There were just 211 people who identified most strongly as Italian, for example, giving a wide margin of error that means there's a chance that Trump may not actually be ahead in this group.

So why do ethnic Germans and Italians seem to like Trump and the GOP?

Italian Americans seem to have been among the first aboard the “Trump train” of disaffected white voters that swept him to victory in the Republican primaries.

“Italian heritage was a significant predictor of Trump support,” Patrick Ruffini, a Republican digital strategist and founder of the media firm Engage in Alexandria, Virginia, told BuzzFeed News.

In the primaries, Trump dominated in the Northeast, Appalachia and the South, performing particularly well among a demographic once called “Reagan Democrats.” In the Northeast, many of these voters were Italian Americans.

In favoring Trump, voters with German ancestry are siding with one of their own: Trump’s grandfather, Friedrich Trump, then a 16-year-old barber, sailed in 1885 from Bremen, Germany, to make a new life in New York.

But that seems unlikely to explain their preference for the Republican candidate.

“I'm pretty sure these voters do not see Trump as a friendly co-ethnic,” James Gimpel, a political scientist at the University of Maryland who has studied the persistent influence of European ancestry on voting habits in New England, told BuzzFeed News.

Indeed, when asked about their preferences in a congressional race with a generic Republican and Democrat, voters who identified as most German were more likely than others to prefer the GOP.

Indeed, much of the variation in political views across the country can be explained by looking at the immigrants who settled there, David Shor of Civis Analytics, a data science firm in Chicago and Washington DC, spun out of the 2012 Obama campaign, told BuzzFeed News. Scandinavian immigrants shaped the liberal politics of parts of Minnesota, he said, while Dutch Protestants made parts of Iowa deeply conservative.

The German immigrants who came to the United States in the 1800s were a large and diverse group, including Protestants and Catholics, socialists and conservatives. “For a long time, Germans were seen as a swing demographic,” Shor said.

More recently, they have tended to lean Republican, according to Ruffini.

If ethnic Germans are motivated more by traditional conservative values than specific support for Trump, then the recently publicized tape of the candidate making lewd comments about women may change the picture. (A poll conducted on Saturday for Politico, however, revealed little change in voting intentions among GOP supporters.)

In our poll, ethnic Germans were a little older and more likely to be Protestant than the typical white voter, which could partly explain why they skewed GOP.

Still, Peter Skerry, a political scientist at Boston College who studies race, immigration, and ethnic politics, wondered if the tense racial backdrop to the 2016 election cycle has exaggerated splits among white voters along old ethnic lines.

Ethnic Germans, who were forced to downplay their heritage in two world wars, may be particularly suspicious of more recent immigrants, Skerry speculated: “If immigration is one of the key topics in the campaign, what’s the largest immigrant group in America, and the one that was most suppressed? It’s Germans.”

UPDATE

October 9, 2016, at 7:32 p.m.

This post has been updated to explain how the small sample sizes for some of the groups may affect the results.

Here is the quote you asked about Warren, ...."What it's going to take is real courage to fight back against them. These insurance companies do not have a God-given right to make $23 billion in profits and suck it out of our health care system...."

Tracked down the likely source for the number, seems to be from an industry group, National Association of Insurance Commissioners, which found 23.4 billion in net earnings, with a 3.3% profit margin from 1,010 firms. "... Table 1 below provides a 10‐year snapshot of the U.S. health insurance industry’s aggregate financial results for health entities who file with the NAIC on the health annual statement blank. The number of Health insurers filing the health statement type with the NAIC increased to 1,010 from 981 in 2017.The health insurance industry continued its tremendous growth trend as it experienced a significant increase in net earnings to $23.4 billion and an increase in the profit margin to 3.3% in 2018 compared to net earnings of $16.1 billion and a profit margin of 2.4% in 2017. The combined ratio decreased modestly to 97% from 97.2%. Included in the increase in profitability, health entities reported a $343 million increase in net investment income earned to $5.1 billion from $4.8 billion in 2017...."

Every presidential candidate promises to “reduce income inequality” by raising tax rates on the rich and increasing transfer payments (including tax credits and in-kind benefits) for the middle class. Yet the widely used flawed data from Thomas Piketty and Emmanuel Saez exclude both taxes and transfers. Income measures that exclude taxes and transfers cannot tell us whether taxes or transfers are high or low, and cannot be directly affected by higher taxes on some or higher transfers to others (because such policies are ignored in the data).

A simple table adapted from the 2017 Consumer Expenditure Survey, from the Bureau of Labor Statistics, may be sufficient to show how crucial it is to take account of taxes (including refundable tax credits), and also to adjust average income for the different number of people and workers per household.

Note: The table above is similar to Alan’s, but is based on slightly updated BLS mid-year data for the 3rd quarter of 2017 through the 2nd quarter of 2018 for nearly 131 million consumer units (households) over the most recent year. I’ve also added annual expenditure data (last three rows) to the table above to extend Alan’s analysis. The far-right column shows the ratios of various measures of income, consumer unit characteristics, and expenditures comparing the top quintile (top 20%) to the bottom quintile (bottom 20%). Here’s more of Alan’s post updated with data in the table above:

The last column shows that the highest 20% earned 17.47 times as much as the lowest 20% before taxes, but only 13.29 times as much after taxes. But simply adjusting household income for taxes is not enough. Average incomes cannot be properly compared between the highest and lowest quintiles because there are nearly two times as many people per consumer unit (household) in the highest 20% (3.1) as there are in the lowest (1.6). And there are more than four times as many workers on average in the highest 20% (2.1) as there are in the lowest 20% (0.50).

By adjusting for different household size, we find the highest 20% earned only 6.9 times as much after-tax income per person as the lowest 20%. But income is likely to be higher in households with two or more workers than it is in households with no workers or only one. So, that last row measures average after-tax income per worker in the highest and lowest quintiles (and those in between). By further adjusting for the different number of earners, the highest 20% earned only 3.2 times per worker ($74,701) as much as the lowest 20%, after taxes ($23,616).

Properly understood, the facts about U.S. after-tax income distribution and growth are insufficiently alarming to justify the political misuse of questionable pretax, pre-transfer income statistics as a false argument for redistributing after-tax income.

MP: Extending Alan’s analysis to include average annual expenditures by household quintiles shows even smaller ratios on a per person and per earner basis comparing the top to bottom quintiles. For example, average annual expenditures per person in the top quintile ($38,154) was only 2.35 times greater than the average consumption per person in the bottom quintile ($16,258 — more than twice the average after-tax income per person for that group of $7,380 because of generous government transfer payments, and food, housing, and medical assistance, etc.), and the average annual expenditures per earner in the top quintile ($56,322) was only 1.08 times greater than the average earner in the bottom 20% ($52,024 or more than twice the $23,616 average after-tax income per earner for that group because of generous government transfer payments, etc.).

The bottom chart above shows how the income inequality ratios between the top and bottom quintiles decline from 17.5 to 13.3 times after adjusting for taxes, and from 6.9 to 3.2 times after adjusting after-tax income for the average number of persons and average earners per household. Further, the consumption inequality ratio between the top and bottom quintiles decreases from 2.3 times for the average spending person to only 1.1 times for the average spending per earner.

As Alan Reynolds concludes, the facts about America’s after-tax income and consumption inequalities between the richest and poorest US household quintiles are “insufficiently alarming to justify the political misuse of questionable pre-tax, pre-transfer income statistics as a false argument for redistributing after-tax income.” And my contribution to this analysis is to show that when we consider differences in consumption (“consumption inequality”) — which might be the most relevant and important comparison because it reflects the actual standard of living of Americans — there is a relatively small difference between the richest 20% of Americans and the poorest 20%. Amazingly, the 17.5X ratio between the average before-tax income of top quintile households and bottom quintile households falls to a ratio of only 2.3X when we consider the difference between those quintiles for average consumption expenditures per person and only 1.08 times for average consumption expenditures per earner.

In 2013, President Obama called income inequality “the defining challenge of our time” and most of today’s presidential candidates apparently share Obama’s concern and have pledged to address that challenge by various tax schemes on “the rich.” But if we instead focus on what’s most important: differences between high-income and low-income households in after-tax income per person and per earner, and differences in consumption per person or per earner, the “defining challenge of our time” seems realistically to be much more of an “imaginary hobgoblin” (to quote H.L. Mencken) than a real problem or challenge that needs to be corrected

Mark Perry, "Inequality between high and low income households decreases sharply after adjusting for taxes, household size, earners per household, and consumption," American Enterprise Institute, July 29, 2019, https://www.aei.org/carpe-diem/inequality-decreases-sharply-after-adjusting-for-taxes-household-size-earners-per-household-and-consumption/

Inequality between high and low income households decreases sharply after adjusting for taxes, household size, earners per household, and consumption

"...How do we know that we are close to the end of the recovery phase? Three statistics from the Bureau of Labor Statistics’ employment summaries provide clues. As slack vanishes, job growth slows, the employment rate reaches full-employment levels, and wage growth steadies at rates consistent with productivity growth. All three have occurred....."
Edward Lazear, "The Recovery Is Reaching Its End,"Wall Street Journal, June 18, 2019, https://www.wsj.com/articles/the-recovery-is-reaching-its-end-11560897121

incentives matter

"...by measuring the effects of workplace competition on labor supply and firm costs using a field experiment in which workers are assigned to competitive and non-competitive payment schemes. Our research design enables us to rule out variation due to productive technology because workers are all hired to perform the same job under identical conditions. The only difference is compensation, where workers in the competitive scheme compete for a bonus prize. We also shut the channel of worker self-selection into competition by assigning workers to schemes and by not informing them in advance of the possibility of a bonus prize. Our main finding is that work time is substantially higher among workers competing for a tournament prize bonus of $30 to the worker with the highest output in their pre-defined 4- person work group. In that treatment, 55% worked the full 40 minutes and only 15% worked less than 11 minutes. Workers in the $30 bonus group also invested more effort per minute of work than those who were not offered the chance to compete for a bonus. However, this intensive margin response had a small impact on overall performance relative to the extensive margin response. Paying a bonus increased total employer costs per work group. To recover these costs, we needed total work time to increase by at least 30%. The average induced increase in effort and performance was greater than 80%. Therefore, our costs per unit of input (work time, effort) or output (task performance) were significantly lower (over 30%) when we paid a bonus....Thus, our results clearly show a strong causal relationship between performance-based incentive pay and work hours....A majority of workers in the treatment without explicit financial incentives worked past the minimum time, but awarding a tournament prize increased work time and effort by over 80% and lowered costs of effort or output by over a third. Effort was similar with alternative (piece rate, low-prize tournament) bonuses. Men worked longer than women in the high-prize tournament, but for the same duration in other treatments.....This implies that the competitive nature of many high-status and high-pay careers, in which workers compete against their colleagues for bonuses and promotions, is likely to be part of the explanation for their long work hours. Workers in these jobs are not typically paid on an hourly basis or for fixed time shifts. Rather, they have flexibility about how long to work, and can voluntarily provide working hours well beyond the standard workweek in order improve their performance rank. Since workplaces typically hire workers of similar ability levels, even the highest ability workers will need to invest long hours to distinguish themselves from (or not fall behind) their equally capable colleagues. Furthermore, our results indicate that competitive compensation schemes can be cost effective and therefore profitable for firms. If they generalize, the induced increase in output that results from the longer working hours (even if only a subset of workers is actively vying for a promotion or bonus) is enough to justify the costs of providing performance-based incentive pay. The profitability of competitive pay is the direct result of the labor supply effects we estimate and can explain its widespread prevalence.... When tournament incentives are cost-effective, it is natural that firms will offer them, and competitive jobs will entail long work hours. Therefore, our findings highlight a fundamental challenge for policy efforts aimed at reducing work hours in order to enhance overall worker well-being or improve gender equality in elite occupations. These policies may be rendered ineffective with pay incentives that encourage workers to voluntarily supply additional labor and circumvent formal hours restrictions.Moreover, policies effective at reducing hours may entail substantial costs to employers and some employees. Our field experiment also revealed a significant gender difference in labor supply, but only in the high-prize tournament. The fact that men worked longer in that tournament hints at a second channel through which high-stakes workplace competition can contribute to gender gaps in labor markets. The first is based on our overall result that indicates that competition can increase the work hours needed to succeed in elite professional careers. This disproportionately deters women, who traditionally have more binding time constraints from greater household obligations. The second channel is through differential effects of high-stakes competition on labor supply, even absent any differences in time constraints...."
Amalia Miller, Ragan Petrie and Carmit Segal, "Does Workplace Competition Increase Labor Supply? Evidence from a Field Experiment," National Bureau of Economic Research, June 2019, https://www.nber.org/papers/w25948

Just an FYI, IMF 2019 External Sector numbers, euro area (largely Germany) is the largest contribute to global imbalances, driven by a rise on corporate net savings (Figure 1.7.1)

"...The IMF’s multilateral approach suggests that about 35-45 percent of overall current account surpluses and deficits were deemed excessive in 2018.Higher-than-warranted balances remained centered in the euro area as a whole (driven by Germany and the Netherlands) and in other advanced economies (Korea, Singapore), while lower-than-warranted balances remained concentrated in the United Kingdom, the United States, and some emerging market economies (Argentina, Indonesia). China’s external position was assessed to be in line with fundamentals and desirable policies, as its current account surplus narrowed further, although achieving a lasting external rebalancing will require gradual reining in expansionary macroeconomic policies and adopting further structural reforms.....Despite the narrowing of global current account imbalances, stock imbalances have continued to widen to reach record levels.At 40 percent of world GDP, the world’s net international investment position—the sum of net creditor and net debtor positions—is now at a historical peak and four times larger than in the early 1990s (Figure 1.8, panel 1). Among the top debtors (Table 1.2), the net international investment position of the United States is now close to -50 percent of GDP, down about 40 percentage points since 2007. Other large debtor economies include Australia and Spain, while the largest creditors include Japan, Germany, and China. The wider stock positions reflect, generally, the increased concentration of current account deficits (surpluses) in debtor (creditor) countries (with a few exceptions, such as most euro area debtor countries), which has been partly mitigated by valuation effects in most cases, both in the form of exchange rate and asset price movements (Figure 1.8, panel 2). A notable exception to this pattern has been the United States, with cumulative current account deficits and valuation losses over the same period, primarily linked to the cumulative US dollar appreciation and relatively higher equity prices...."

IMF Staff, " External Sector Report: The Dynamics of External Adjustment," July 2019, International Monetary Fund, https://t.co/QKX8oRWhwb

Great paper that finds Germany's overseas investment returns are anemic"....Germany is world champion in exporting capital ("Exportweltmeister"). No other country invests larger amounts of savings outside its borders. However, Germany plays in the third division when it comes to investment performance, as we show in this paper. We study the returns on German foreign investments from 1950 to 2017 and find that:(1) Germany's annual returns on foreign assets were 2 to 5 percentage points lower than those of comparable countries. Germany ranks last among the G7 countries, also in the last decade; (2) Domestic returns on German assets have outperformed foreign returns abroad by about 3 percentage points per year; (3) Germany's external wealth provides very little consumption insurance as foreign returns are highly correlated with domestic activity; (4) The capital exports do little to diversify demographic risks as Germany mainly invests in countries with similar demographics. Taken together, these facts raise substantial doubts whether German households, firms, and banks allocate their savings in a beneficial way...."

. new study from National Academy of Sciences reinforcing the 2016 Fryer findings

"...Despite extensive attention to racial disparities in police shootings, two problems have hindered progress on this issue. First, databases of fatal officer-involved shootings (FOIS) lack details about officers, making it difficult to test whether racial disparities vary by officer characteristics. Second, there are conflicting views on which benchmark should be used to determine racial disparities when the outcome is the rate at which members from racial groups are fatally shot. We address these issues by creating a database of FOIS that includes detailed officer information. We test racial disparities using an approach that sidesteps the benchmark debate by directly predicting the race of civilians fatally shot rather than comparing the rate at which racial groups are shot to some benchmark. We report three main findings: 1) As the proportion of Black or Hispanic officers in a FOIS increases, a person shot is more likely to be Black or Hispanic than White, a disparity explained by county demographics; 2) race-specific county-level violent crime strongly predicts the race of the civilian shot; and 3) although we find no overall evidence of anti-Black or anti-Hispanic disparities in fatal shootings, when focusing on different subtypes of shootings (e.g., unarmed shootings or “suicide by cop”), data are too uncertain to draw firm conclusions. We highlight the need to enforce federal policies that record both officer and civilian information in FOIS...."

David Johnson, Trevor Tress, Nicole Burkel and Carley Taylor, "Officer characteristics and racial disparities in fatal officer-involved shootings,"Proceedings of the National Academy of Sciences, July 2019, https://www.researchgate.net/publication/334633566_Officer_characteristics_and_racial_disparities_in_fatal_officer-involved_shootings

Klein on the new IMF numbers

"...Faced with a stagnant domestic market, German companies flush with cash refused to invest domestically. These dynamics were exacerbated by government policies that limited worker bargaining power, lowered taxes on the rich, and cut infrastructure investment. The net effect was to strangle consumption and companies’ capital expenditures, which grew far more slowly than German production. The widening gap between what Germans make and what they can afford to buy for themselves is now responsible for the largest trade surplus in the world. The IMF found an almost perfect correlation between the change in Germany’s trade balance and the change in the share of German national income going to the rich and the companies they control....German wages have risen since the financial crisis, which has helped lift workers’ share of national income, but this has done little to reduce either overall income inequality or Germany’s trade surplus. The reason is that the German government has effectively leaned against the improving economy by raising taxes and strangling infrastructure investment. The government now has a budget surplus of 2% of GDP even as its bridges and ports continue to deteriorate from lack of maintenance...."

Matt Klein, "No, Sen. Warren, Germany Is Not a Model for the U.S.,"Barrons, July 19, 2019, https://www.barrons.com/articles/no-sen-elizabeth-warren-germany-is-not-a-model-for-u-s-51563566459

Dartmouth economist adjust the death of despair numbers for comp-shift in educational attainment and find that mortality increases among whites have been driven almost entirely by changes in the bottom 10% of the education distribution.

"....Changing mortality rates among less educated Americans are difficult to interpret because the least educated groups (e.g. dropouts) become smaller and more negatively selected over time. New partial identification methods let us calculate mortality changes at constant education percentiles from 1992-2015. We find that middle-age mortality increases among non-Hispanic whites are driven almost entirely by changes in the bottom 10% of the education distribution. Drivers of mortality change differ substantially across groups......First, among middle-aged non-Hispanic white (hereafter referred to as white) men and women, the group most widely discussed in the recent literature, mortality increases are driven almost entirely by the bottom 10% of the education distribution (the part of the distribution represented by high school dropouts in 2015). From 1992 to 2015, age-adjusted mortality for whites in the least educated 10% has risen by 59-90% for women and 32-49% for men (respectively 2.2-3.1% and 1.3-1.9% per year).Mortality change in percentiles 10-45 (approximately high school completers in 2015) is considerably less dramatic, and is rising unambiguously only for white women below the age of 50 and white men under 35. The mortality increases described by Case and Deaton (2015, 2017) are thus both more severe and more focused in a narrow population subgroup than has previously been recognized. Second, non-Hispanic blacks have experienced large improvements in mortality in all education groups except for the least educated 10%. Blacks in the least educated 10% have close to zero mortality change from 1992-2015; age-adjusted middle-age mortality for blacks is marginally rising for women and marginally declining for men. This has led to a substantial convergence between black and white outcomes at the bottom of the education distribution. Conditional upon being in the least educated 10% of the national distribution, white men over the age of 50 now have higher mortality than similarly-aged black men.The same holds for white women relative to black women over the age of 40. Finally, a single proximate cause cannot expain these divergent death rates. The change in deaths from despair, which has been widely discussed in prior research and in the media, accounts for a large share of mortality increases for young whites, but a very small share of rising mortality among older whites and none of the divergent mortality rates of blacks. Further, deaths of despair have increased more uniformly across the education distribution than deaths from other causes. The least educated middle-aged white women, in particular, are now at higher risk of dying from cancer, heart diseases and respiratory diseases, among other causes, even as mortality from these causes has declined sharply for those outside of the bottom 10%. Note that earlier unadjusted estimates were particularly difficult to interpret for women, for whom education has risen considerably more than among men, creating a larger selection bias.....Deaths of despair explain a large share of mortality change among young non-Hispanic whites, but a small share among older whites and almost none among non-Hispanic blacks...."

Paul Novosad and Charlie Rafkin, "Mortality Change Among Less Educated Americans," Dartmouth College, April 2019, https://www.dartmouth.edu/~novosad/novosad-rafkin-mortality.pdf

interesting, new Guzman finds that state level R&D tax credits work, with a 5 year time lag.....

"....The acceleration of start-up activity is often cited as a rationale for the R&D tax credit, a key innovation policy instrument adopted increasingly by US states over the past quarter century. While there is a strong empirical base linking the R&D tax credit to increased R&D expenditures and innovation, prior work has not provided causal evidence that this policy effects the rate of formation and growth potential of new businesses. This paper combines data from the US Startup Cartography Project with the Panel Database on Incentives and Taxes to implement a difference-in-differences estimate of the impact of the R&D tax credit on the quantity and quality-adjusted quantity of entrepreneurship. Our key finding is that the R&D tax credit is associated with a significant long-term impact on both the overall quantity and quality-adjusted quantity of entrepreneurship, with the bulk of the effect materializing more than five years after the policy is enacted........Accounting for county and year fixed effects, as well as lagged state GDP,we find that the introduction of state R&D tax credits is associated with around 7% increase in the rate of net new business formation (both in terms of raw quantity and accounting for the heterogeneous firm potential for growth). Moreover, this effect may underestimate the incentive’s actual long-term impact. While state-level R&D tax credits have little to no effect on the rate or composition of new firm formation in the first few years following their introduction, these incentives lead to a 20% increase in the quantity and quality-adjusted quantity of entrepreneurship over a ten year period (in the absence of any meaningful pre-adoption trend).Notably, these impacts stand in sharp contrast to the effects of other contemporaneous state fiscal incentives supporting established firms - state-level investment tax credits.2 For the investment tax credit, we see at best a neutral impact in terms of the overall quantity of entrepreneurship, and a longer-term decline in the quality-adjusted quantity of new firms founded, suggesting that, by enhancing the competitiveness of established businesses, the investment tax credit might serve to deter growthoriented entrepreneurship over time..... These findings stand in contrast to an analysis of the adoption of state-level investment tax credits. There, we observe no long-term impact on the quantity of entrepreneurship but a marked decline in the rate of formation of growth-oriented startups over time. Combined with other evidence regarding the efficacy of R&D tax credits in spurring innovative investment, our results shed light on the potential for this fiscal policy to also stimulate the formation of growth-oriented start-ups....."
Catherine Fazio, Jorge Guzman and Scott Stern, "The Impact of State-Level R&D Tax Credits on the Quantity and Quality of Entrepreneurship," National Bureau of Economic Research, July 2019, https://www.nber.org/papers/w26099

Ernie Tedeschi updated his charts last friday after the jobs report, he sees the labor market decelerating,

"...Big move down in part-time for economic reasons -- -24bp of employment -- and slight rise in EPOP and LFPR. Household survey very good. But there's little doubt now that the labor market, which was a source of comfort for the Fed & policymakers for so long, is decelerating. Deceleration in jobs growth could in principle just be a sign that we've hit full employment, but the deceleration in wages isn't consistent with that hypothesis. Interestingly -- this doesn't happen often -- while prime-age EPOP and LFPR declined slightly, my demographically-adjusted series, which covers all ages, rose, because we've seen sharp increases in EPOP and LFPR for the 55+ population over the last 2 months..."

Ernie Tedeschi, "Jobs Day, July 2019," August 2, 2019, https://twitter.com/ernietedeschi/status/1157274423508000769

Warren really doesn't like PE. This reads to me as effectively taking limited liability away from the PE industry, ".... My plan would transform the private equity industry and end this looting with a comprehensive set of legal changes,including: Putting private equity firms on the hook for the debts of companies they buy, making them responsible for the downside of their investments so that they only make money if the companies they control flourish. Holding private equity firms responsible for certain pension obligations of the companies they buy, so that workers have a better shot of getting the retirement funds they earned...."

Elizabeth Warren, "End Wall Street’s Stranglehold On Our Economy," Medium, July 18, 2019, https://medium.com/@teamwarren/end-wall-streets-stranglehold-on-our-economy-70cf038bac76