Unemployment

Cartoon: The Dead Thatchers – Eton Uber Alles

Hi, and here’s another of my cartoons satirising the Tories and their utterly reprehensible politicos and other members. In this case, the cartoon takes the form of a sleeve image for a non-existent punk band, the Dead Thatchers, and an equally non-existent song, ‘Eton Uber Alles’. It shows David Cameron, Iain Duncan Smith, Boris Johnson and George Osborne in front of the gates of Auschwitz, which bears the infamous slogan ‘Arbeit Macht Frei’ and the cartoon’s punchline, as you can see, is ‘You will row for the master race’. It’s a reference to the Eton boating song,which itself got poached and revamped in the 1980s by Paul McCartney into the Frog Chorus.

The cartoon’s inspiration is the American punk outfit, The Dead Kennedys, and their song, ‘Kalifornia Uber Alles’. As punks, the Kennedys really hated hippies, and so the song’s just a rant about how California is some kind of hippy Third Reich. I was never a fan of the Dead Kennedys, but I do remember the song had the lines ‘Hippy Nazis will control you, you will jog for the master race!’ Which in the context of a Britain dominated by Eton would obviously be boating.

Now there’s a lot that can be said about hippies both pro and con, but they definitely weren’t Nazis. There was, apparently, a Hippy Nazi party, but they were in Florida, and from their name sound like a rather tasteless joke. They sound like an attempt to wind up the straights, rather than any serious Fascist organisation. Unfortunately, with the way so many of the British ruling class were initially very sympathetic towards Nazi Germany, flocking to organisations like the Anglo-German Fellowship, it’s probably a fair bet that the fathers or grandfathers of many of the boys now at Eton really were Nazi sympathizers. Though I’m not, of course, claiming that those of the four depicted above were.

And there is a serious point for my placing them in front of the slogan ‘Arbeit Macht Frei’, and it’s the same reason people have scrawled it on the walls of Jobcentres and put up photoshopped images of the same. The pro-Israel fanatics and Tories attacked those images and graffiti as anti-Semitic, claiming that they were somehow turning the Holocaust into a joke. However, as Mike explained in his piece last Saturday about the appearance of the slogan on another Jobcentre, this certainly isn’t a case. The phrase translates into English as ‘Work Makes (You) Free’. According to Tony Greenstein, the slogan was on the gates of all the Nazi camps, including those housing gentile prisoners. It was not used exclusively for the Jews, and first appeared on a concentration camp for non-Jews. It’s been applied to the Tories and their administration of the DWP, particularly by Iain Duncan Smith, because they really do seem to have a very Fascistic attitude to the poor and disabled.

The Tories have a mantra about ‘making work pay’, and have deliberately adopted a policy of ‘less eligibility’ towards the disabled and the unemployed in order to deter and punish them for claiming benefit. It takes five weeks after someone has signed on before they receive their first payment under Universal Credit. This is also less than the amount they would have received under the previous, benefit systems. There is an extensive system of sanctions, in which claimants can be thrown off their benefits on the flimsiest of excuses. The disabled are subjected to work capability tests, in which a certain percentage are always found fit work, even when the poor souls are severely disabled and even in several cases terminally ill. Grieving relatives and friends have even found their loved one’s receiving letters from the DWP informing them that they have been found fit for work, and so no longer liable for incapacity and related benefits after they’ve died. It has also been revealed that Maximus, the organisation responsible for administering the tests, like its predecessor Atos, has regularly falsified the results in order to get claimants thrown off benefits.

See: https://voxpoliticalonline.com/2020/03/14/firms-that-falsified-thousands-of-benefit-assessments-set-to-get-contracts-to-falsify-thousands-more/

Mike in his article on Sunday, 8th March 2020 put up this meme reminding everyone how IDS started an article for the online edition of one of the papers actually praising the slogan and defending it against its use by the Nazis. The offending paragraph disappeared soon after, but not before shocked and horrified people had taken screenshots of it and put them back up so everyone could see just how low Iain Duncan Smith is. Here’s the meme:

As one tweeter, Paula Peters, quoted by Mike in his article points out, the language used by the Tories about the disabled is very much the same the Nazis used in the Third Reich. They’re denounced as ‘useless eaters’ and scroungers. The term ‘workshy’, used to describe the long-term unemployed, is also taken from the Nazis. It’s the English translation of ‘arbeitscheu’. And the habitually or long-term unemployed were also branded ‘asocial’ and placed in the concentration camps.

The Tories do this because they have a fundamentally eugenicist view of the poor, the unemployed and the disabled. They are biologically inferior, ‘dysgenic’, who threaten the healthy purity of the rest of the human race and particularly the biologically superior. Who are naturally the rich, especially the heads of big business. Hence the Tory policy of forcing them off benefits, even if it means the deaths of hundreds of thousands. It’s estimated that about 120,000 people have been killed by Tory austerity. But there is no apology nor any attempt to alter or improve conditions despite continuing revelations of the hardship inflicted on millions of people. Instead the Tories merely double down, repeated their lies about how, under them, the economy was booming and more people were in work than ever before. As for the deaths, they have done everything they can to hide the figures and prevent disability rights activists and carers, like Mike, from obtaining them. Hence putting the Tories in front of that slogan is very appropriate.

See: https://voxpoliticalonline.com/2020/03/08/hypocrisy-over-language-used-to-describe-dwp-oppression-of-benefit-claimants/

Here’s the cartoon. As always, I hope you enjoy it. And please, don’t have nightmares. It’s only Iain Duncan Smith!

 

3.3 Million!! and other dubious records for the USA

Published by Anonymous (not verified) on Fri, 27/03/2020 - 5:02pm in

Tags 

Unemployment

I for one am getting tired of all the "winning" under the illegitimate Trump regime. Today (March 26) we hit two milestones, neither of which is cause to celebrate.

The first biggie is 3.28 million people filed first-time claims for unemployment in the last week. To put this in perspective, with a labor force of 164.6 million, it means that the unemployment rate rose 2.0% in one week. To look at it another way, the previous record for most unemployment claims in a week came in 1982, during the Reagan administration, and that record was 695,000. So this week we surpassed the previous high by a factor of 4.7. For a visual representation, see the tweet below by Heidi Shierholz, the director of policy at the Economic Policy Institute:

This leaves me pretty speechless. So I'll just move on to the second milestone.

On Thursday, the United States moved into the #1 position on the total number of COVID-19 cases of any country in the world, passing both Italy in China in the last 24 hours. In another record, the number of new cases on March 25 was 18,100, breaking China's one-day new case record of 15,100 from February 12. (For those of you keeping score at home, that's six weeks ago!) And unfortunately, the generally rising pattern of new daily cases is continuing, per the Johns Hopkins website.

(Click on "US" at the top of the list of countries at the left, then click on "Daily Increase" on the chart in the lower right-hand corner.)

For good measure, the number of new cases globally hit a record of 61,900 on March 25, also with a continuing upward trend.

This is a disaster in the making if these trends don't improve soon. I don't have a crystal ball, so all I can say is listen to the scientists.

A letter to the Canadian Prime Minister, with two suggestions for next steps in dealing with #COVID19

Published by Anonymous (not verified) on Mon, 23/03/2020 - 6:58am in

Prime Minister,

I certainly hope you and yours are well.

I was in New York City up until last weekend. Earlier in the previous week the university where I work announced that it was moving all courses online, and closing the campus. There was really no further need for me to stay in the City, but my initial thought was to wait it out, and decide later on when to return to Canada.

I started to have second thoughts when a student emailed me for advice just after President Trump announced that travel from Europe to the United States would be banned. He’s from Mexico, and said that he trusted the Mexican health care system more than the American, and wanted my advice on whether he should return home.

If that wasn’t enough to give me pause, when I saw the twitter feed of the Minister of Foreign Affairs  on Saturday evening recommending “that Canadian travellers return to Canada via commercial means while they remain available” I immediately bought myself a ticket for a next day flight to Canada. I arrived last Sunday evening, and have been in self-isolation since. I’m glad to be home given the events of the last week.

It is certainly time for government to step up, and history will judge the fall out of this pandemic in terms of how well societies govern themselves: professionally and efficiently, scientifically and socially, and with a sense of reciprocity and trust that strengthens community. I hope you and your cabinet take to heart a message that one of my colleagues has written in an article called “The Real Pandemic Danger Is Social Collapse.”

… the main (perhaps even the sole) objective of economic policy today should be to prevent social breakdown. Advanced societies must not allow economics, particularly the fortunes of financial markets, to blind them to the fact that the most important role economic policy can play now is to keep social bonds strong under this extraordinary pressure.

Good governance, not just a good health care system, is one of the reasons I’m glad to be home. I have been watching your daily press briefings with a good deal of admiration. And I am also impressed with both the design and speed with which the government has been able to roll out the package of reforms earlier this week, an effort that has no doubt been supported by legions of professional public servants working around the clock.

You promised that these reforms are just the first step in a fast moving and dynamic situation. I can’t pretend to understand the complete situation, hardly have full information, and can’t offer wide-ranging suggestions on what the next steps might be. But here are two suggestions that come from my limited areas of expertise.

 

First, about information and testing. I appreciate that a good deal of testing has to do with the medical priorities of diagnosis and appropriate triage, only testing those with risk factors, like international travel and showing symptoms. That may be appropriate from a medical stand point in the context of possibility limited test kits and personnel.

But testing only those most likely to be ill is not appropriate as a source of information for broader decision making engaging the Prime Minister’s Office. The Economist magazine had a nice article in its February 29th edition describing the challenges of getting information on the incidence of infection and mortality rates from test samples that are selected in this way. Knowing where you are in flattening the curve is going to much more challenging with selected rather than random samples.


Source: https://www.economist.com/briefing/2020/02/29/covid-19-is-now-in-50-countries-and-things-will-get-worse

You might consider a way to randomly test samples of individuals in the provinces and health areas to get data representative of the population, information from a continually rolling daily sample of thousands of Canadians. This will become all the more important in understanding the degree to which there is community spreading, and give your office more accurate estimates of incidence and how it is changing. As you well know, good information is the first ingredient in a professional scientific approach to taking the next steps.

Second, let me restrict particular policy suggestions to Employment Insurance, because that is what I know about. In a sense the need for these reforms shows us where our social safety net is knitted most thinly, and next steps should be conducted not just for short term patch-ups, but with an eye toward making the system more effective in the longer term.

As I mentioned, I was impressed with the package that came out, particularly the attempt to cover people who will not be EI eligible through the new Emergency Support Benefit. A sad failing of the EI program has long been the relatively small fraction of unemployed population who are actually covered. In 2018 only about 64% of the unemployed had contributed to the program, and were potentially eligible to receive benefits. There used to be provisions in the program for labour market re-entrants and job quitters, and you might rethink their eligibility.

A lack of coverage hurts, and will continue to hurt into the future when you are likely to unroll the Emergency Support Benefit.

Unemployment Insurance was always meant to be an insurance program for big social risks, exactly of the kind we are now facing. In the early 1970s Canadians had a much more generous program, broader coverage, more generous and longer benefits, but it was progressively chipped away at in the name of deficit fighting and work incentives.

In normal times, when jobs are to be had, the program’s design certainly does need to keep work incentive effects in mind. That is why we have a waiting period. That is why there is a maximum insurable earnings set modestly at around the overall average earnings. That is why benefits are only paid to 55% of insurable earnings. That is why the duration of benefits is limited.

But all of these design features intended to keep work disincentives in check, now hamper the program’s effectiveness in being an income replacement tool when there is no work to be had, or in fact to be discouraged.

These are not normal times, and in some sense we want Canadians to work less while giving them timely and generous income support. The government has recognized this by eliminating the waiting period. So what is the logic of holding on to the other co-insurance features of the program?

You should significantly increase the maximum insurable earnings—which is currently just above $54,000–by at least half to $75,000 so that more Canadians will see all or a larger fraction of their earnings covered.

You should increase the benefit rate from 55% to at least 75% or even higher. In fact, there is a precedent to be found in the unemployment insurance in the 1970s, which had a replacement rate as high as 75% for certain lower income populations.

You should move the eligibility rule for all regions to the least stringent requirement that now exists for any region. This is important because the eligibility rule adjusts relatively slowly to fast changing conditions, as it is determined by an average of the past three months of unemployment rates in the region. So it is inherently backward looking, and won’t pick up the dramatic changes that are occurring now for at least a couple of months.

For now you should continue to maintain the maximum duration of benefits, and adopt a wait-and-see approach. When people come close to exhausting benefits you will know about it, and can increase the duration at that time if necessary.

Finally, in the last recession during 2008 the work-sharing part of EI worked well to help reduce layoffs. This could be leaned on more aggressively, and relaxed to recognize that we want workers to be attached to their employers, but don’t necessarily want as much work sharing as we normally would.

I hope in some small way this is of help. You, yourself, said in one of your first press briefings this past week that these new reforms should be particularly addressed to the least advantaged. To be without work raises insecurity, and even questions dignity, and good governance is, in the first instance, about reinforcing a grand insurance scheme, that shares risks, binds us together, and gives us all the assurance that together we are taking the right steps in the right direction.

Keeping Business Alive: The Government as a Payer of Last Resort

Published by Anonymous (not verified) on Sun, 22/03/2020 - 1:21pm in

by Emmanuel Saez & Gabriel Zucman* The coronavirus threatens the world’s economic life. The most important message that needs to come from heads of state immediately, even before any new law or complete implementation details are provided, is: “Do not … Continue reading →

Affordable housing, homelessness and the upcoming federal budget

Published by Anonymous (not verified) on Fri, 20/03/2020 - 10:14am in

I’ve written a ‘top 10’ overview of things to know about affordable housing and homelessness, as they relate to Canada’s upcoming federal budget. The overview is based on the affordable housing and homelessness chapter in the just-released Alternative Federal Budget.

A link to the ‘top 10’ overview is here.

Affordable housing, homelessness and the upcoming federal budget

Published by Anonymous (not verified) on Fri, 20/03/2020 - 10:14am in

I’ve written a ‘top 10’ overview of things to know about affordable housing and homelessness, as they relate to Canada’s upcoming federal budget. The overview is based on the affordable housing and homelessness chapter in the just-released Alternative Federal Budget.

A link to the ‘top 10’ overview is here.

How Does Credit Access Affect Job-Search Outcomes and Sorting?

Published by Anonymous (not verified) on Wed, 04/03/2020 - 11:45pm in

Kyle Herkenhoff and Gordon Phillips

How Does Credit Access Affect Job-Search Outcomes and Sorting?

How does access to consumer credit affect the job finding behavior of displaced workers? Are these workers looking for jobs at larger and more productive firms? What is the impact of consumer credit on the amount of time it takes to find a job? In recent work with Ethan Cohen-Cole we explore these questions by building a new data set of individual credit reports (from TransUnion) merged with administrative earnings data. We describe our approach and our results in this post.

To answer these questions convincingly, we have to overcome the problem that a person’s credit is determined endogenously: For example, let’s say two individuals lose their job. Individual A has one credit card and individual B has four credit cards. Why does individual B have more credit? Perhaps individual B earned more before being laid off, or perhaps individual B is simply more responsible. To address these concerns about the endogeneity of credit, we use two natural experiments.

Our main approach is to exploit the fact that credit limits differ as a result of variation in account ages, as originally shown by Gross and Souleles (2002). We use this fact to isolate plausibly exogenous differences in credit limits among workers who are mass-displaced, in the merged data based on methods pioneered by Jacobson et al. (1993). Our results are striking: those with a 10 percent increase in credit access (measured as unused credit to prior annual income) take about 0.33 to 0.53 weeks longer to find a job (.5 is half a week and thus corresponds to 3 to 4 days). Among job finders, they had a 0.61 percent to 1.34 percent greater annual earnings replacement rate (the replacement rate is the ratio of current earnings one year after layoff to earnings in the year before layoff). Moreover, job finders are more likely to work for more productive firms. Here, we define a productive firm to be one that is in the top 25 percent of wages paid per worker (a common proxy for labor productivity).

To provide additional validation for our findings, we exploit regional differences in credit access. We use the fact that some metropolitan statistical areas have different housing supply elasticities, and therefore have different house price growth rates. This empirical approach was popularized by Saiz (2010). When house prices increase in a region, we empirically observe a significant rise in both secured credit access (e.g., mortgages) and unsecured credit access (e.g., credit cards). Of course wealthier households may search differently, so we directly control for access to housing wealth, and therefore isolate the impact of consumer credit access on job search behavior. We find that in response to a 10 percent increase in an individual’s credit limit to income ratio, the typical worker takes 1.8 weeks longer to find a job and finds a job that replaces 1.7 percent more of their prior wage.

What is the intuition behind these results? If someone loses their job and their back is against the wall, for instance, they have taken out a mortgage and maxed out their credit cards, that person is much more likely to take a low paying, low productivity job, immediately, rather than hold out and wait for a better job. Another way of looking at these results is that if an individual has enough credit to buy groceries and maintain their overall consumption, they can take longer to find a better fitting job.

Our findings have several important policy implications. In particular, any type of government policy that affects access to credit will change the search durations, wages, and subsequent types of jobs that individuals take. This is relevant for mortgage modifications, principal reductions, or any type of credit subsidy. One relevant example is that if the central bank lowers the interest rate, this will affect job finding behavior. The idea is that providing some “breathing room" for severely credit constrained individuals will enable them to conduct a more thorough search for a job, and they will, on average, find a better fitting job.

Even though workers will have longer unemployment durations when interest rates are lowered, they are better off on average. A side effect of lowering the interest rate is therefore that workers take longer to find a job, so the unemployment rate may be temporarily elevated when interest rates fall. However, workers are searching for jobs that are a better fit, which is obviously a good thing for them and the economy. As a consequence, our results and our theory imply that rather than focusing on unemployment rates, a central bank attempting to implement maximum sustainable employment should look at the wages of new hires to evaluate the effectiveness of monetary policy on labor markets.

Another implication of our research is that credit acts a lot like unemployment insurance (UI). Several other papers, including Chetty (2008) and Nekoei and Weber (2015) have studied the impact of UI on durations and subsequent wages. They find that increased UI protracts unemployment durations and workers generally find higher paying jobs (this is true in the United States and Europe, although European estimates are sometimes insignificant or negative Schmieder et al. (2013)). Our work suggests that consumer credit may, in certain cases, be a viable substitute for unemployment insurance. To evaluate these statements in a scientific way, in follow up work, we are studying whether or not it may be optimal to hand unemployed households a credit card rather than simply giving them a UI check (Braxton et al. 2019). We find that if the U.S. government cuts UI, the credit market will contract, and U.S. households will be worse off. Another way of saying this is that private forms of self-insurance (such as credit cards), are complements to public forms of insurance (e.g. UI).

There is a flip side of increased credit access, however. Those who borrow while waiting to find a job, but do not conduct a successful search, are then in a position in which they still are unemployed and now have debt. Moreover, households may borrow before they lose their job, in which case they move into unemployment with a large amount of existing debt. This may force job seekers to take lower wage jobs more quickly than if they had never borrowed at all. In Herkenhoff (2019) one of us explores the impact of credit access on wage inequality, and finds that through this channel, wage dispersion increases mildly. However, in this context, credit access is still welfare improving.

Related Reading:
LSE Series on Heterogeneity

Kyle_HerkenhoffKyle Herkenhoff is a senior economist in the Federal Reserve Bank of New York’s Research and Statistics Group.

Gordon Phillips is the Laurence F. Whittemore Professor of Business Administration and faculty director of the Center for Private Equity and Venture Capital at Dartmouth’s Tuck School of Business.

How to cite this post:

Kyle Herkenhoff and Gordon Phillips, “How Does Credit Access Affect Job-Search Outcomes and Sorting?,” Federal Reserve Bank of New York Liberty Street Economics, March 4, 2020, https://libertystreeteconomics.newyorkfed.org/2020/02/how-does-credit-ac....



Disclaimer

The views expressed in this post are those of the authors and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the authors.

Is the Tide Lifting All Boats? A Closer Look at the Earnings Growth Experiences of U.S. Workers

Published by Anonymous (not verified) on Wed, 04/03/2020 - 11:15pm in

René Chalom, Fatih Karahan, Brendan Moore, and Giorgio Topa

Is the Tide Lifting All Boats? A Closer Look at the Earnings Growth Experiences of U.S. Workers

The growth rate of hourly earnings is a widely used indicator to assess the economic progress of U.S. workers, as well as the health of the labor market. It is also a measure of wage pressures that could potentially spill over into inflationary pressures in a tightening labor market. Hourly earnings growth, on average, has gradually risen over the course of the current expansion, under way since the end of the Great Recession. But how have different groups of workers fared in this regard? Have hourly earnings risen uniformly at all points of the wage distribution, or have some segments of the workforce been left behind? In this post, we take a close look at earnings growth over the past two decades at different points of the wage distribution and for various demographic groups. Our goal is to examine whether there are any significant patterns in the evolution of the distribution of earnings, as opposed to just looking at the behavior of aggregate earnings growth. We focus primarily on hourly earnings growth, although our findings apply to total earnings as well.

We perform our analysis using data from the Bureau of Labor Statistics’ Current Population Survey (CPS). In particular, we focus on prime-age (25 to 54 years of age) workers who are present in two consecutive CPS March supplements (the Annual Social and Economic Supplement), to compute earnings growth from one year to the next for the same individual. In order to minimize volatility and measurement error in our estimates, we further restrict the sample to look at full-time employees, defined as individuals who worked for at least forty-five weeks and usually worked at least ten hours per week in both years. Hourly earnings are computed as annual labor earnings divided by the product of weeks worked last year and usual weekly hours. Workers with hourly wages below the federal minimum wage are dropped from the sample.

The chart below reports average hourly earnings growth by quartile of the initial hourly earnings distribution in each year. We find that—perhaps surprisingly—average hourly earnings at the bottom of the wage distribution have been consistently growing faster than those at the top of the distribution. This pattern is partly driven by the fact that it is more common for low-wage workers to receive large wage increases in percentage terms than for high-wage workers, even though such increases are not that large in absolute terms. As a consequence, it is worth noting that these results are still consistent with increasing income inequality as measured by the variance of earnings. More importantly, the pattern we observe may also be the result of negative shocks to incomes that turn out to be transitory: a worker may have low earnings today because of an adverse event, but if that event is transitory there is a good chance that the worker’s earnings will recover next year.

The finding reported in the chart holds true even within age groups, so it is not just the result of lifecycle patterns (typically, earnings growth is more rapid at the beginning of one’s career and slows down as the worker becomes more mature). Interestingly, the top and bottom of the earnings distribution have experienced a stronger increase in the rate of earnings growth than the middle portion of the distribution over the past four years: this could be related to the gradual decline of “routine,” middle-skill jobs, a process that might accelerate following recessions, as various researchers have highlighted.

Is the Tide Lifting All Boats? A Closer Look at the Earnings Growth Experiences of U.S. Workers

Turning to the evolution of earnings growth by education, hourly earnings of more educated workers (with a college or advanced degree) have tended to grow faster than for less educated ones (those with a high school diploma or less). On average between 2010 and 2016, hourly earnings of workers with a bachelor’s degree grew by 7.8 percent annually, whereas wages grew by 6.5 percent for those with a high school diploma or less. This finding is especially evident in the current expansion (2009-16), although the pattern reversed in 2017. This is consistent with increasing returns to education, a trend that has been operating at least since the 1990s.

Is the Tide Lifting All Boats? A Closer Look at the Earnings Growth Experiences of U.S. Workers

Finally, the last chart presents average hourly earnings (in constant 2017 dollars) by race and ethnicity. Here we find that, if anything, hourly earnings of Hispanic and especially African American workers seem to have been catching up with those of Whites, at least in more recent years. Hourly earnings of Asian workers have been growing faster than for any other group.

Is the Tide Lifting All Boats? A Closer Look at the Earnings Growth Experiences of U.S. Workers

Conclusion

In this post, we have focused on the experiences of U.S. workers over the past two decades through the lens of earnings growth. We have investigated the evolution of earnings growth, breaking down the aggregate numbers into a more disaggregated picture. The analysis paints a nuanced picture. While there is some evidence that workers at the bottom of the earnings distribution may be catching up with those at the top of the distribution, we also find some indications that the returns to higher education may be increasing, with hourly earnings growth of college graduates outpacing that of high school graduates. Finally, we also find some evidence that—at least in recent years—hourly earnings of minority workers may be starting to catch up with those of white workers. This, together with the fact that the unemployment rate for African American workers has reached record lows, is an encouraging sign for the broadening of the current economic expansion.

Chart data

Related Reading:

LSE Series on Heterogeneity

René Chalom is an economics Ph.D. candidate at Columbia University.

Fatih KarahanFatih Karahan is a senior economist in the Federal Reserve Bank of New York’s Research and Statistics Group.

Brendan MooreBrendan Moore is a senior research analyst in the Bank’s Research and Statistics Group.

Giorgio Topa
Giorgio Topa is a vice president in the Bank’s Research and Statistics Group.

How to cite this post:

René Chalom, Fatih Karahan, Brendan Moore, and Giorgio Topa, “Is the Tide Lifting All Boats? A Closer Look at the Earnings Growth Experiences of U.S. Workers,” Federal Reserve Bank of New York Liberty Street Economics, March 4, 2020, https://libertystreeteconomics.newyorkfed.org/2020/03/is-the-tide-liftin....




Disclaimer

The views expressed in this post are those of the authors and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the authors.

Women Have Been Hit Hard by the Loss of Routine Jobs, Too

Published by Anonymous (not verified) on Wed, 04/03/2020 - 11:00pm in

Jaison R. Abel and Richard Deitz

Women Have Been Hit Hard by the Loss of Routine Jobs, Too

Technological change and globalization have caused a massive transformation in the U.S. economy. While creating new opportunities for many workers, these forces have eliminated millions of good-paying jobs, particularly routine jobs in the manufacturing sector. Indeed, a great deal of attention

has focused on the consequences

of the loss of blue-collar production jobs
for prime‑age men. What is often overlooked, however, is that

women have also been hit hard
by the loss of routine jobs, particularly administrative support jobs—a type of routine work that has historically been largely performed by women. In this post, we show that the combined loss of production and administrative support jobs since 2000 is actually more than three times as large for prime-age women than prime-age men.

Routine Jobs Disappearing


Jobs that involve procedural or rule-based tasks—such as working on an assembly line in a factory—are commonly referred to as routine jobs. These kinds of jobs were once seen as a pathway to the middle class. However, precisely because of the nature of these jobs, they have been hit particularly hard by automation and outsourcing over the past several decades. While the loss of routine manufacturing jobs gets most of the attention, there are actually two broad categories of routine jobs: routine manual and routine cognitive. The first group tends to emphasize physical skills such as working on an assembly line, and are disproportionately held by men. Many such jobs have been displaced by

less expensive labor overseas

or

robots. By contrast, routine cognitive jobs tend to involve mental tasks such as organizing information and basic number crunching, and include work historically performed by secretaries, bookkeepers, and clerks—most often held by women. Many of these kinds of routine jobs have been
replaced by computers.

Our analysis focuses on production jobs and administrative support jobs—by far, the largest categories of routine jobs. While production jobs are concentrated in the manufacturing sector, administrative support jobs are spread across many industries. We examine employment trends in these two occupation categories over the past several decades separately for prime-age men and prime-age women (those between the ages of 25 and 54), plotted below.

Women Have Been Hit Hard by the Loss of Routine Jobs, Too

Production jobs among prime-age men, represented by the red line, fell from 6.4 million in 1970 to under 4 million by 2019, a decline of more than 35 percent. While this occupation category employs fewer women than men, the pace of decline for prime-age women was even steeper, falling from a peak of around 3.2 million in the late 1980s to 1.6 million in 2019, a 50 percent decline. Administrative support jobs, while growing slightly for prime-age men in recent decades, declined substantially for women. These jobs used to employ more than 10 million women in the 1990s and early 2000s, but now employ around 7.5 million, a decline of more than 25 percent. Looking at these two types of jobs combined, between 2000 and 2019, about one million jobs were lost among prime‑age men, compared with a decline of 3.5 million jobs among prime‑age women.

These declines have had profound consequences for the types of job opportunities available for men and women alike, as shown in the chart below. Over 20 percent of prime‑age men used to be employed in production jobs, but now these jobs employ just 7 percent; among prime‑age women, the share declined from 17 percent to just 3 percent. The share of prime-age women working in administrative support jobs declined from over 30 percent to just 16 percent over the past several decades, while the share among prime-age men held fairly steady at between 5 and 6 percent. All in all, these two categories of routine jobs employed close to half of all working prime-age women in the 1970s, a share that plummeted to less than one-fifth by 2019. Among prime-age men, these jobs employed around a quarter in the 1970s compared with just 13 percent in 2019. Thus, it appears that the loss of these kinds of routine jobs may have been even more consequential for women than men.

Women Have Been Hit Hard by the Loss of Routine Jobs, Too

Labor Market Changes


As routine jobs have disappeared, workers have shifted into other types of jobs, and there has been an increasing number not participating in the labor force at all. The chart below identifies labor market shifts between 2000, roughly when employment in routine jobs began to decline in earnest, and 2019. The chart shows the change in the distribution of all prime-age men and women between occupations and labor market status, including whether they were unemployed or not in the labor force. Each bar shows the percentage-point change in the share for each job category or labor market status. For example, among all prime-age men (working or not), the share in production jobs was 9.7 percent in 2000 and 6.4 percent in 2019, a decline of 3.3 percentage points—shown by the first blue bar. Note that the sum of all bars for each gender necessarily equals zero, since increases in the shares of some sectors must be offset by decreases in the shares of others. As such, these data present a comprehensive view of how job types and the employment status of all prime-age men and women has evolved over time.

Women Have Been Hit Hard by the Loss of Routine Jobs, Too

In addition to the shrinking share of prime-age men employed in production jobs, there were also declines in the shares of prime-age men working in other traditional blue-collar jobs, such as repair, transportation, and construction. On the flip side, a higher proportion of prime-age men worked in business services and engineering jobs in 2019, like chemical engineers, lawyers, and software developers, and in low‑skilled service jobs, which have seen significant growth in recent decades. Notably, there was a nearly 3-percentage-point increase in the share of prime-age men not in the labor force, a trend which has been highlighted in a number of recent research studies.

Among prime-age women, there was a 4.6-percentage-point decline in the share working in administrative support jobs, and also a significant decline in the share working in production jobs, though this decline was less than it was for men. Unlike prime-age men, there was a large increase in the share of women working in healthcare jobs, particularly as nurses and healthcare aides—jobs that men have been reluctant to move into
for a number of reasons. Like prime-age men, there was a significant increase in the share of prime-age women working in low-skilled service jobs and an increase of about 2 percentage points in the share of prime-age women not participating in the labor force.

Conclusion


Contrary to conventional wisdom, men seem not to have been disproportionately affected by the decline of routine jobs. While the loss of blue-collar production jobs in the manufacturing sector has been quite steep among men, such losses have been even steeper in percentage terms for women. Further, there has been a significant loss of administrative support jobs among women, but not among men. The ability of workers to respond to the economic forces that have eliminated these kinds of routine jobs is more important than ever before. So far, women have shifted into health care jobs more than men, while men have shifted into business services and engineering jobs more than women. One troubling trend is that a larger share of both prime-age men and women now work in low‑skilled service jobs, or have left the labor force altogether.

Related Reading:

LSE Series on Heterogeneity

Jaison R. Abel

Jaison R. Abel
is an assistant vice president in the Federal Reserve Bank of New York’s Research and Statistics Group.

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Richard Deitz

Richard Deitz

is an assistant vice president in the Bank’s Research and Statistics Group.

How to cite this post:

Jaison R. Abel and Richard Deitz, “Women Have Been Hit Hard by the Loss of Routine Jobs, Too,” Federal Reserve Bank of New York Liberty Street Economics , March 4, 2020, https://libertystreeteconomics.newyorkfed.org/2020/03/women-have-been-hi....




Disclaimer

The views expressed in this post are those of the authors and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the authors.

Introduction to Heterogeneity Series II: Labor Market Outcomes

Published by Anonymous (not verified) on Tue, 03/03/2020 - 11:00pm in

Rajashri Chakrabarti

 Labor Market Outcomes

While average outcomes serve as important yardsticks for how the economy is doing, understanding heterogeneity—how outcomes vary across a population—is key to understanding both the whole picture and the implications of any given policy. Following our six-part look at heterogeneity in October 2019, we now turn our focus to heterogeneity in the labor market—the subject of four posts set for release tomorrow morning. Average labor market statistics mask a lot of underlying variability—disparities that factor into labor market dynamics. While we have written about labor market heterogeneity before, this series is an attempt to pull together in a cohesive way new insights on the labor market and highlight details that are not immediately obvious when we study aggregate labor market statistics.

Here is a brief look at each post in the series:

Women Have Been Hit Hard by the Loss of Routine Jobs

1. Women Have Been Hit Hard by the Loss of Routine Jobs, Too

Technological change and globalization have eliminated many “routine jobs”—positions that center on physically intensive activities, such as assembly line work, or on certain cognitively intensive tasks, such as number-crunching. Jaison Abel and Richard Deitz investigate whether the repercussions have differed for male and female workers. Here’s what they found:

  • While both men and women have experienced a decline in routine jobs, the decline was markedly steeper for women.
  • As routine jobs have disappeared, men and women have sorted into different occupations: men are more likely to take engineering positions while women are more likely to take healthcare jobs.
  • In addition, an increasing share of both men and women sorted into low-skilled service jobs or left the labor force altogether.

Is the Tide Lifting All Boats? A Closer Look at the Earnings Growth Experiences of U.S. Workers

2. Is the Tide Lifting All Boats? A Closer Look at the Earnings Growth Experiences of U.S. Workers

Rene Chalom, Fatih Karahan, Brendan Moore, and Giorgio Topa look at the pace of earnings growth across the wage distribution.

  • Average hourly earnings have grown considerably faster at the bottom of the wage distribution than at the top over the past two decades.
  • Workers in the top and bottom quartiles of the earnings distribution have experienced a stronger increase in the rate of earnings growth than those in the middle of the distribution, a pattern that may be related to the decline of routine jobs referenced above.
  • Earnings of more educated workers have grown faster than those for less educated ones. Earnings of Hispanic and African American workers have moved closer to those of white Americans, particularly in the past few years.

Searching for Higher Job Satisfaction

3. Searching for Higher Job Satisfaction

Gizem Kosar, Leo Goldman, and Kyle Smith explore the role of job satisfaction in job search and job-to-job mobility, examining differences by gender and other characteristics.

  • Regardless of race, age, or income level, lower job satisfaction is associated with a higher likelihood of searching for a job.
  • However, differences exist in the job components that men and women care about when choosing whether to search for a new position.
  • Different factors also determine job-to-job mobility for men and women. Compensation is the strongest driver for women while men primarily care about satisfaction with the experience and skills attached to their current job.

How Does Credit Access Affect Job-Search Outcomes and Sorting?

4. How Does Credit Access Affect Job-Search Outcomes and Sorting?

Kyle Herkenhoff, Gordon Phillips, and Ethan Cohen-Cole investigate the effects of credit access on job searches by displaced workers.

  • Displaced workers who have greater credit access take longer to take a new job.
  • Additionally, workers with greater credit access have higher annual earnings a year after losing their jobs, and are more likely to work for more productive firms.
  • The findings suggest that individuals with enough credit have the ability to prolong their search to look for a better job match.

As these posts will demonstrate in greater detail tomorrow, the average outcome doesn’t provide a full picture of the labor market, where outcomes are determined by a range of factors, including differences in race, gender, and credit access, among others. We will continue to study and write about the importance of heterogeneity in the labor market and other segments of the economy.

Related Reading:
LSE Series on Heterogeneity

Chakrabarti_rajashriRajashri Chakrabarti is a senior economist in the Federal Reserve Bank of New York’s Research and Statistics Group.

How to cite this post:

Rajashri Chakrabarti, “Introduction to Heterogeneity Series II: Labor Market Outcomes,” Federal Reserve Bank of New York Liberty Street Economics, March 3, 2020, https://libertystreeteconomics.newyorkfed.org/2020/02/introduction-to-he....



Disclaimer

The views expressed in this post are those of the author and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the author.

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