Weekend reading: “HQ2” edition

Posted on by Maria Monroe

This is a weekly post we publish on Fridays with links to articles that touch on economic inequality and growth. The first section is a round-up of what Equitable Growth published this week and the second is the work we’re highlighting from elsewhere. We won’t be the first to share these articles, but we hope by taking a look back at the whole week, we can put them in context.

Equitable Growth round-up

In a new blog post in Equitable Growth’s Competitive Edge blog series, former Federal Trade Commission commissioner Terrell McSweeny discusses the rise of pricing algorithms and the implications they raise for competition policy.

In an interview for Equitable Growth’s In Conversation series, Heather Boushey and University of California, Berkeley economist Hilary Hoynes discuss the impact of social safety net programs on economic growth.

Check out Brad Delong’s latest worthy reads from Equitable Growth and around the web.

Will McGrew discusses the implications of the rise of job-matching platforms on economists’ job search and matching theory for understanding how workers transition between jobs and get jobs that are the best matches for their skills.

Links from around the web

New reports highlight regional differences in economic prosperity within the United States. In conjunction with a decline in geographic mobility, this trend suggests poor Americans are stuck in poor places. [the economist]

Reed College economist and Equitable Growth grantee Kimberly Clausing and University of California, Berkeley economist Hilary Hoynes explain the policy implications of rising income inequality, particularly as it relates to social safety net programs and tax policy. [econofact]

Derek Thompson of The Atlantic reports that the rise of expensive, elite traveling youth sports teams explains differential rates of participation in youth sports between high- and low-income families: “Just 34 percent of children from families earning less than $25,000 played a team sport at least one day in 2017, versus 69 percent from homes earning more than $100,000. In 2011, those numbers were roughly 42 percent and 66 percent, respectively.” [the atlantic]

New research finds that hospital consolidation in the United States has increased costs for patients. [nyt]

This week’s announcement by Amazon.com Inc. that its new secondary headquarters will be split between New York City and the Washington, DC suburbs in northern Virginia demonstrates that proximity to already highly skilled workers trumps tax incentives in companies’ location decisions, not that that stops local leaders from offering them. [wapo]

Friday Figure

Figure is from “The intersectional wage gaps faced by Latina women in the United States” by Kate Bahn and Will McGrew

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How job-matching technologies can build a fairer and more efficient U.S. labor market

Posted on by Maria Monroe

Economic theory tells us that there are benefits to a dynamic labor market in which workers are matched with jobs based on their skills, interests, and ambitions so they can earn wages equivalent to the value they contribute to production. “Job search and matching theory” is a framework economists use to understand the mechanisms underlying the process of workers transitioning between jobs, as well as the obstacles to efficient matching of workers with jobs. Since its inception, the theory has been applied in a variety of contexts, and it is a particularly helpful frame both for understanding how the advent of new job search, matching, and recruitment technologies may influence workers’ job opportunities and for shedding light on how these innovations can be crafted to secure fairness and competition in the U.S. labor market.

Despite the rise of online job-matching platforms over the past decade, search frictions and skills mismatch continue to be persistent problems for both employers and employees. While new companies such as LinkedIn Corp. and Indeed Inc. have eased the process of identifying vacancies for job-seekers and attracting applicants for employers, online job boards have also created new frictions by proliferating the average number of applications per job-seeker and per job opening. Costs remain particularly high for low-skill, low-wage job-seekers, who are the least likely to have access to and proficiency in new digital technologies and are simultaneously the most likely to spend substantial amounts of time completing numerous burdensome job applications on their smartphones. Among other factors, these search frictions contribute to a persistent skills mismatch between workers and jobs. According to an employer survey by McKinsey & Co Inc., 40 percent reported lack of skills as the primary reason for job vacancies. In contrast, 37 percent of job-seekers in a LinkedIn study said they were underutilizing their skills in their current positions.

The central theoretical model describing the process of looking for and finding a job in the contemporary economics literature is the search and matching model developed by economists Dale Mortensen, formerly of Northwestern University, Christopher Pissarides of the London School of Economics, and Kenneth Burdett of the University of Pennsylvania. Along with economist Peter Diamond at the Massachusetts Institute of Technology, Mortensen and Pissarides received the Nobel Prize in 2011 for their foundational work with this framework, which describes how search frictions’ lack of information, as well as mismatch between skills and interests offered by workers and wages and benefits provided by jobs, hinder the efficient matching of job-seekers with job openings. These obstacles affect job transitions and depress labor market dynamism, which can lead to prolonged bouts of unemployment, noncompetitive wages and benefits, and stunted productivity growth.

Despite its widespread impact, the search and matching model has faced criticism for failing to fully account for several empirical phenomena in contemporary labor markets, notably the cyclicality and persistence of vacancies, unemployment, and job creation, as well as the persistence of inflation in response to monetary shocks. As economist John Quiggin of the University of Queensland explains, one of the key criticisms of the search and matching theory has focused on its failure to accurately predict the effects of the internet on unemployment. Since the dominant framework models unemployment as a function of search and matching frictions, unemployment should have declined with the rise of the internet, which increased the information available to both employers and employees. Yet this empirical prediction did not materialize. Indeed, over the past two decades, despite sustained innovations involving the internet, unemployment spiked twice—in the early 2000s, after the dot-com bust and again in the Great Recession beginning in December 2007. In the latter case, the spike was particularly durable, as unemployment has only recently returned to healthy levels.

While these empirical critiques call into question the implications of the job search and matching model for key macroeconomic labor market variables, this model may nevertheless be helpful for understanding the internal dynamics of the job search process itself—and particularly the role of technological innovation in this process. Indeed, the centrality of transaction costs in terms of search and matching in the mainstream model is a logical frame in which to analyze the effects of technological innovations, which presumably have the capacity to reduce various types of frictions.

Instead of discarding this model, a future research agenda should build on it while incorporating important structural frictions in the contemporary U.S. labor market, notably monopsony (or the dominance of a small number of employers), occupational segregation (the disproportionate concentration of women and ethnic minorities in certain fields), and labor market polarization (the recent increase in low-skill, low-wage and high-skill, high-wage jobs at the expense of middle-class employment). Including both structural and informational frictions in the Mortensen-Burdett model also sheds light on points of intervention where innovators and policymakers can help facilitate a more efficient and more equitable job search and matching process. For example, in Alan Manning’s book, Monopsony in Motion, the economist describes how lack of information, among other frictions, is pronounced when there are too few employers in a single labor market, underlying the importance of public intervention to prevent labor market concentration.

At the very least, better matching technologies could help reduce informational search frictions and the related skills mismatch—with positive implications for both inequality and growth. With the goal of improving existing job boards and similar platforms as a starting point, companies—including Alphabet Inc’s Google unit and Indeed—have begun to use artificial intelligence and machine learning to narrow down the most relevant jobs for job-seekers. Indeed also uses natural language processing to help employers identify the best candidates for vacancies by analyzing language from applicants’ resumes and other submitted materials. These technologies and further innovations in this vein would enhance both the equity and efficiency of labor markets by reducing the inequality associated with skills mismatch and search frictions, driving down unemployment given shorter search times and increasing labor force participation and work hours in response to improved matching to jobs consistent with workers’ skills and interests. A report by the McKinsey Global Institute estimates that these advances could add 2 percent to global GDP in the next decade.

Innovative job-matching platforms, especially those integrated with training programs, can also strengthen workers’ human capital, as well as their bargaining power in the labor market. Companies such as CodeSignal (formerly CodeFights Inc.), for example, are creating online platforms that allow job-seekers to practice their skills and earn credentials, which they can use to be matched with employers and job opportunities. If programs such as those offered by CodeSignal are successful in helping applicants develop the skills required for particular job opportunities, then the credentials they provide could become strong signals giving credentialed job applicants increased leverage in the recruitment process. In essence, these technologies could help create digital apprenticeships of the future, which combine training programs with pathways to gainful employment.

These platforms can further increase workers’ human capital, exit options, and bargaining power in their current jobs by providing them with opportunities for professional development and notifying them of relevant job postings as they open up. In particular, with the help of artificial intelligence, these services can keep workers informed of how their salaries and benefits compare to those of new vacancies, further solidifying their bargaining position without taking time and energy from their job responsibilities. The combined effects of innovations in this vein may reduce the search frictions workers face in transitioning between jobs in search of higher pay and a better overall fit. Program evaluation and further research on how job training and greater comparative information on wages and benefits impacts both matching and bargaining power are needed to ensure that technology is addressing the needs of workers and reducing structural inequality in labor market outcomes.

In addition to mitigating power imbalances between workers and firms, matching services powered by AI and machine learning can be crafted to reduce occupational segregation by race, gender, and socioeconomic class. This is important because segregation remains one of the most important factors leading to wage discrepancies faced by workers based on their demographic identity and not their productive capacity. From the labor demand side of the equation, job-matching services can bring more objective standards and processes to the recruitment pipeline, thereby reducing the influence of implicit biases and social networks in hiring decisions. Well-known research from Harvard University economist Claudia Goldin and Princeton University Woodrow Wilson School Dean and economist Cecilia Rouse finds that concealing demographic information of job applicants increased gender representation among orchestras, demonstrating the need for matching by observable skill rather than demographic characteristics that may reinforce discrimination.

Along with the training and credentialing efforts discussed above, other startups, among them the recruitment and talent assessment company Harver, have partnered with employers to create job-specific assessments along these lines that identify the most qualified candidates for a given position based solely on the actual skills required for the role. In turn, on the labor supply side, job-matching services can expand the horizons of job applicants from underrepresented gender, racial, and educational groups to occupations and industries they may not have traditionally considered. Specifically, these services could match workers to jobs that are higher paying but require skills these workers may have already gained or could acquire without much difficulty in a training program.

Despite these promising developments, recent research has documented that AI, machine learning, and other innovations can often be inadvertently programmed to reproduce existing biases in labor market institutions. Job-matching technologies undoubtedly have the potential capacity to reduce labor market inequalities—both between employers and firms and among various groups of workers. But in order to realize these objectives, technology developers and policymakers must recognize that labor market monopsony, occupational segregation, and job polarization create frictions in the contemporary U.S. labor market that are arguably as significant as those created by informational inefficiencies. As such, any truly efficient matching system must be intentionally calibrated with the help of rigorous social science research to reverse all three trends.

Beyond their potential role in reducing unemployment and improving workers’ human capital and bargaining power, public and private efforts to reduce search frictions and skills mismatch stand to strengthen aggregate productivity growth and thus the overall health of the economy by providing workers with more fulfilling opportunities, incentivizing employers to innovate and compete for talent, and ensuring workers have the skills necessary to help firms thrive.

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Brad DeLong: Worthy reads on equitable growth, November 9–15, 2018

Posted on by Maria Monroe

Worthy reads from Equitable Growth:

  1. The most important thing: The deadline for Equitable Growth’s next set of grant proposals is January 31, 2019: “Request for Proposals.” Also read Korin Davis, our academic programs director, who presents the backdrop to the new request for proposals: “Our grantmaking is organized around key drivers of economic growth, allowing us to ask questions to better understand the mechanisms through which inequality may be affecting growth. After 5 years of funding research, we have, for the first time, altered how we organize our grantmaking. While the underlying questions have not changed, the reorganization captures what we’ve learned about what makes the U.S. economy grow. The updated funding channels are: macroeconomic policy, market structure, the labor market, and human capital.”
  2. A great interview with my University of California, Berkeley colleague, the wise Hilary Hoynes, “In conversation with Hilary Hoynes,” in which she says: “Our social safety net … very much moved toward work-contingent types of activity … Some quantification or estimation of the question: Does providing more assistance through the social safety net, particularly aimed at children, lead to differences in where children end up in adulthood?”
  3. We have a new blog at Equitable Growth! Hooray! Read this week’s “Competitive Edge,” featuring former Commissioner of the Federal Trade Commission Terrell McSweeney, who writes in “Competitive Edge: Antitrust Enforcers Need Reinforcements to Keep Pace with Algorithms, Machine Learning, and Artificial Intelligence” that: “Algorithmic price fixing isn’t science fiction. The U.S. Department of Justice’s Antitrust Division and the United Kingdom’s Competition and Markets Authority have already brought their first case in which competitors agreed to use specific pricing algorithms for the sale of posters online. This particular case did not stretch the traditional antitrust framework for price fixing because humans were involved. But as technology becomes more powerful and autonomous, some competition experts are raising concerns about whether analog antitrust doctrines can keep pace.”
  4. Read Delany Crampton, “Veterans in the U.S. Labor Market Face Barriers to Success That Can and Should Be Addressed,” in which he writes: “Anna Zogas of the University of Washington observes in her 2017 research that the U.S. military does an extremely effective job of training veterans to operate within the military and an extremely poor job of preparing them, especially young servicemembers, for post-military jobs.”
  5. Watch the video via Equitable Growth’s Twitter feed of its event on Capitol Hill, “Building a New Consensus on Antitrust Reform.”

 

Worthy reads not from Equitable Growth:
 

  1. Read Ken Kuttner, “Outside the Box: Unconventional Monetary Policy in the Great Recession and Beyond,” in which he writes: “A preponderance of evidence nonetheless suggests that forward guidance and quantitative easing succeeded in lowering long-term interest rates. Studies using micro data have documented tangible effects of quantitative easing on firms and financial intermediaries. Macro models suggest that the interest rate reductions are likely to have had a meaningful impact. The adverse side effects appear to have been mild, and are dwarfed by the costs of the more protracted recession in the United States that likely would have occurred in the absence of the unconventional policies. The benefits of unconventional policy therefore probably outweighed the costs.” My read of the evidence is somewhat different here: My view is that forward guidance did something, but quantitative easing did very, very little. And the idea that quantitative easing made forward guidance more credible? I do not see that. Yes, quantitative easing was a big deal for the financial professionals who otherwise would have held the Treasury bonds that the Federal Reserve bought. But I do not see any channels through which their attempt to compensate had large effects on the real economy of production and demand.
  2. Since 2008, it is clear to me that the unemployment rate has no longer served as a sufficient statistic for whether the labor market is loose or tight. We need to look, and look hard, at those who do not have jobs and do not say that they are looking for jobs but who would take jobs if they existed. And we need to look very hard at hours. Read David Bell and David Blanchflower, “Underemployment in the US and Europe,” in which they write: “The most widely available measure of underemployment is the share of involuntary part-time workers in total employment. This column argues that this does not fully capture the extent of worker dissatisfaction with currently contracted hours. An underemployment index measuring how many extra or fewer hours individuals would like to work suggests that the U.S. and the U.K. are a long way from full employment, and that policymakers should not be focused on the unemployment rate in the years after a recession, but rather on the underemployment rate.”
  3. Dan Davies on financial fraud is certainly the most entertaining book on economics I have read this year. I highly recommend it. Read Chris Dillow’s “Review of Dan Davies: Lying for Money,” in which Dillow writes: “Squalid crude affairs committed mostly by inadequates. This is a message of Dan Davies’ history of fraud, Lying For Money … Most frauds fall into a few simple types … Setting up a fake company … pyramid schemes … control frauds, whereby someone abuses a position of trust … plain counterfeiters. My favourite was Alves dos Reis, who persuaded the printers of legitimate Portuguese banknotes to print even more of them … All this is done with the wit and clarity of exposition for which we have long admired Dan. His footnotes are an especial delight, reminding me of William Donaldson. Dan has also a theory of fraud. ‘The optimal level of fraud is unlikely to be zero’ he says. If we were to take so many precautions to stop it, we would also strangle legitimate economic activity.”
  4. Read the 2001 paper by Thomas Laubach and John C. Williams, “Measuring the Natural Rate of Interest,” in which they write: “A key variable for the conduct of monetary policy is the natural rate of interest—the real interest rate consistent with output equaling potential and stable inflation. Economic theory implies that the natural rate of interest varies over time.” The assumption driving the argument here is that the natural rate of interest varies one for one with productivity growth. That is probably right, but not certainly right. If it is right, the Federal Reserve’s 2 percent inflation rate target is a huge mistake generating huge risks.
  5. It is such a bad idea for a central bank to invert the yield curve. If central bankers can do only one thing, that is probably the thing they should know. Read Glenn D. Rudebusch and John C. Williams, “Forecasting Recessions: The Puzzle of the Enduring Power of the Yield Curve,” in which they write: “For over two decades, researchers have provided evidence that the yield curve … contains useful information for signaling future recessions. … Professional forecasters appear worse at predicting recessions a few quarters ahead than a simple real-time forecasting model that is based on the yield spread.”
  6. It is a surprise to most economists to learn that the outbreak of inflation in the 1970s was not due to central bankers and governments trying to exploit the Phillips curve to run a high-pressure economy. The most important shocks were the oil shocks. The second most important shocks were those that caused the productivity growth slowdown. The third most important shocks were Presidents Lyndon Johnson’s and Richard Nixon’s unwillingness to listen to their economic advisers, and Federal Reserve Board Chairmen William McChesney Martin’s and Arthur Burns’ unwillingness to pull a Volcker. Perhaps it is because it is such a surprise that so few have learned it and how many forget it immediately after it is pointed out. And since the 1970s, the strong belief that another 1970s is always and everywhere lurking around the corner has been very damaging. Read Paul Krugman, “The Demand-Side Temptation,” in which he writes: “[Nick] Rowe goes on to suggest that demand-side logic is dangerous … could lead to irresponsible policies. Well, there have been times and places … But what I think Nick misses is the power of the contrary narrative, of the notion of the government as being like a family that must tighten its belt when the rest of us do, of the evils of printing money (hey, I can’t do that, why can Bernanke?).”

 

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Competitive Edge: Antitrust enforcers need reinforcements to keep pace with algorithms, machine learning, and artificial intelligence

Posted on by Maria Monroe

Antitrust and competition issues are receiving renewed interest, and for good reason. So far, the discussion has occurred at a high level of generality. To address important specific antitrust enforcement and competition issues, the Washington Center for Equitable Growth has launched this blog, which we call “Competitive Edge.” This series features leading experts in antitrust enforcement on a broad range of topics: potential areas for antitrust enforcement, concerns about existing doctrine, practical realities enforcers face, proposals for reform, and broader policies to promote competition. Terrell McSweeny has authored this month’s contribution.

The octopus image, above, updates an iconic editorial cartoon first published in 1904 in the magazine Puck to portray the Standard Oil monopoly. Please note the harpoon. Our goal for Competitive Edge is to promote the development of sharp and effective tools to increase competition in the United States economy.

Terrell McSweeny

Algorithmic price fixing isn’t science fiction. The U.S. Department of Justice’s Antitrust Division and the United Kingdom’s Competition and Markets Authority have already brought their first case in which competitors agreed to use specific pricing algorithms for the sale of posters online. This particular case did not stretch the traditional antitrust framework for price fixing because humans were involved. But as technology becomes more powerful and autonomous, some competition experts are raising concerns about whether analog antitrust doctrines can keep pace. The debate is far from settled, but it is increasingly clear that 21st century regulators are going to need technological expertise to aid them in making enforcement decisions.

Competition regulators in major markets around the world are actively assessing whether technology requires changes to their antitrust enforcement frameworks. Here in the United States, the Federal Trade Commission is wrapping up a series of public hearings on “Competition and Consumer Protection in the 21st Century” by focusing on algorithms, artificial intelligence, and predictive analytics. It plans to examine ethical and consumer protection issues associated with the use of these technologies and how competitive dynamics are affected by them.

In their most basic form, algorithms are instructions that computers follow to process data and solve problems. They are essential building blocks of our digital lives. Frequently they are used to set prices. Increasingly sophisticated pricing algorithms can offer more personalized prices or different prices for people based on information about them. Algorithms can help consumers quickly and easily locate and compare prices of products. Personalized pricing based on a customer’s ability to pay, expected individual demand, and other data points can improve efficiency and benefit consumers, though it doesn’t always work that way. For instance, studies find that people are shown higher prices on mobile devices than on desktop computers or higher prices depending on how far they are from a store location. Some antitrust experts worry that the pricing algorithms that are increasingly common in both digital and analog markets might facilitate coordination—either expressly or tacitly—thereby minimizing competition on price to the detriment of consumers while remaining undetected by antitrust enforcers.

It is important for competition enforcers to study changes in technology that affect competition, but it doesn’t necessarily follow that pricing algorithms will collude or that they will be used in collusive schemes. If pricing algorithms are truly personalized—that is, quoting different prices for different people based on a number of different data points—then collusion is unlikely since it will be nearly impossible for would-be conspirators to discipline “cheaters,” or those competitors who are deviating from the agreement.

There are two key concerns that antitrust regulators must grapple with regarding pricing algorithms, particularly in highly concentrated industries. The first has to do with technical capabilities. As the use of algorithms becomes more common, will regulators be able to understand and detect when algorithms are being used to collude? The second concern has to do with pricing algorithms automatically and independently gravitating to higher prices without human intervention or agreement. Such conduct might be hard to detect and address under existing law.

Much of the current antitrust debate also is focused on whether regulators properly understand and address the role of data in digital markets. Data’s significance as a competitive asset depends on the facts. Some data, for example, are public or can be obtained from data brokers for a fairly nominal cost. And some data can be nonrivalrous, meaning it can be used by many companies at the same time. But other data are proprietary and can operate as a barrier to entry. Antitrust agencies have proven relatively capable of addressing competition issues around data, but the demands on agencies to engage in highly technical, fact-based examinations are only likely to increase as data becomes more important in the world of predictive analytics and artificial intelligence.

Against this backdrop, it is essential for antitrust agencies to rely not only on legal and economic expertise but also technological expertise. While antitrust frameworks have proven relatively adaptable, a key question is whether the agencies themselves have the capabilities required for the digital age. Some regulators are already incorporating technologists into their work. Brazil, for example, has a technology lab. Similarly, the European Union’s Commissioner for Competition Margrethe Vestager has suggested that the Directorate General for Competition create its own algorithms in order to figure out if collusion is taking place.

In the United States, the Federal Trade Commission created a position for a chief technologist in the FTC chair’s office in 2011 and expanded its research and technology capabilities with the creation of the Office of Technology Research and Investigation, or O-Tech, in 2015. But that office is currently housed in the agency’s Bureau of Consumer Protection, suggesting its work and resources are mostly directed toward the consumer protection mission of the agency. The Federal Trade Commission should consider creating an independent and fully staffed office for the chief technologist or even a Bureau of Technology to enhance its required technological expertise and support its competition mission.

—Terrell McSweeny is a former commissioner of the Federal Trade Commission and previously held senior positions in the White House, the U.S. Department of Justice, and the U.S. Senate. She currently is a partner at the law firm Covington and Burling LLP.

Weekend reading: “Workers deserve higher wages” edition

Posted on by Maria Monroe

This is a weekly post we publish on Fridays with links to articles that touch on economic inequality and growth. The first section is a round-up of what Equitable Growth published this week and the second is the work we’re highlighting from elsewhere. We won’t be the first to share these articles, but we hope by taking a look back at the whole week, we can put them in context.

Equitable Growth round-up

This week, Equitable Growth economist Kate Bahn and computational social scientist Austin Clemens published their monthly analysis of the Job Openings and Labor Turnover Survey data released by the U.S. Bureau of Labor Statistics. The JOLTS data reflects a strengthened labor market characterized by elevated quit rates, fewer unemployed workers per job vacancy, and fewer hires per job opening.

University of California, Berkeley economist and Equitable Growth guest blogger Brad Delong highlighted recent research and writing on labor markets and other topics in macroeconomics in his weekly reads column. In addition to elevating Equitable Growth’s upcoming event next week on “Building a New Consensus on Antitrust Reform,” he points readers to Sarah Jane Glynn’s report on gender wage inequality for Equitable Growth and empirical evidence from Harald Dale-Olsen on the positive impact of unions on regional productivity.

Yesterday, Korin Davis, our Academic Programs Director, discussed the launch of our sixth Request for Proposals for Equitable Growth’s grantmaking program. On top of explaining how Equitable Growth develops the RFP with the advice of our staff, Steering Committee, and Research Advisory Board, she highlights some of the topics of research funded by Equitable Growth over our past five years of grantmaking.

Links from around the web

Whitney Filloon at Eater digs into a recent quote from the CEO of fast-food giant The Wendy’s Company, confirming the negative effects of low wages on aggregate demand and thus overall economic growth. On the company’s quarterly earnings call, the CEO argued that low wage growth for working and middle-class Americans has hurt sales for the company. In addition to reviewing some statistics on the relatively low wages of workers in the fast food industry, Filloon points out recent efforts of groups such as Fight for $15 to raise wages for this group of workers—including at Wendy’s.

At Bloomberg, Michelle Jamrisko and Dan Murtaugh unpack a speech by former Federal Reserve Chair and current Equitable Growth Steering Committee member Janet Yellen at the New Economy Forum in Singapore. In her speech, Yellen argued that while the monetary policy role of central banks may be more limited than fiscal policy in fighting inequality, central banks can nevertheless help alleviate inequality by securing full employment for low-income workers across racial groups and maintaining post-crisis financial regulations, which reduce the likelihood of another economic downturn with disproportionate impacts on low-income workers.

David Leonhardt of The New York Times looks into the research on another negative effect of inequality: ethnic division. In particular, Leonhardt summarizes some of the key findings of a new book by Steven Pearlstein of The Washington Post. Among other topics, Pearlstein’s book, Can American Capitalism Survive?, explains how wage stagnation in recent decades for working class Americans across ethnic groups has led to scapegoating, which turns these groups of workers against each other while economic and political forces continue to drive rising inequality.

Gareth Hutchens of The Guardian published a recent interview with Columbia University economist and Nobel laureate Joseph Stiglitz. Hutchens discusses some of the findings of Stiglitz’s 2012 book, The Price of Inequality, notably including the disproportionate income gains of the top 1 percent and the top 0.1 percent of income earners compared to the bottom 90 percent over the past 40 years. Hutchens also includes quotes from Stiglitz detailing the negative effects of inequality on economic growth, environmental protection, and democratic institutions.

Friday Figure

Figure is from Equitable Growth’s, “JOLTS Day Graphs: September 2018 Report Edition.”

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Veterans in the U.S. labor market face barriers to success that can and should be addressed

Posted on by Maria Monroe

The transition of U.S. military veterans back into the civilian labor market is an issue steeped in complexities. Veterans face unique hurdles that can impede them from finding work in the civilian job market, including lower rates of higher education and a lack of understanding how to translate military experience into civilian job terms, to say nothing of the health challenges veterans face, such as Post Traumatic Stress Disorder.

Anna Zogas of the University of Washington observes in her 2017 research that the U.S. military does an extremely effective job of training veterans to operate within the military and an extremely poor job of preparing them, especially young servicemembers, for post-military jobs. In 2008, the year in which the highest number of U.S. troops were deployed overseas, 52 percent of servicemen and servicewomen were under 25 years old, and only 4.5 percent held a bachelor’s degree or higher. Zogas’ research finds that among the post-9/11 veterans surveyed in Los Angeles, 61 percent reported the need for additional education assistance and 65 percent said that they needed assistance finding civilian employment. These numbers actually exceeded the veterans who reported needing assistance with physical and mental health care, which clocked in at 56 percent and 47 percent, respectively.

A 2015 study from the University of Southern California School of Social Work, in partnership with Veterans of America, reported similar issues for veterans trying to enter the civilian labor market after their military service. The study found that the unemployment rate of veterans ages 18 to 65 is higher than the unemployment rate of nonveterans. This research focused on interviews with individuals in jobs that had the responsibility of assisting veterans with finding employment. From these interviews, the researchers gleaned that there was often a lack of understanding among both employers and veterans regarding suitable positions based on military-specific skills, responsibilities, and experiences that could translate into civilian workplace environments.

Additionally, that study found that many veterans held unrealistic employment expectations. Almost all of the service providers interviewed reported that their veteran clients lacked knowledge about the types of jobs that would be available to them after their military service, about the level at which they would enter the workforce, and about the kind of compensation they could expect to receive. This gap in expectations leaves veterans feeling as if they are completely starting over in their careers, as they find themselves in entry-level positions that often pay lower wages than they earned as service members.

Reports of earnings from the U.S. Census Bureau and a report from Colleen Chrisinger at the University of Oregon found mixed results for veterans’ unemployment and net worth, depending on their ages. In Chrisinger’s report, she found that there were some positive signs such as evidence suggesting no relationship between being a veteran and wages among white veterans (though this was not the case for nonwhite veterans) and actually found a wage premium for recent veterans regardless of race with a high school education or less compared to nonveterans.

But using data from the Bureau of Labor Statistics, her research found that post-9/11 veterans faced higher unemployment rates compared to nonveterans, with a rate of 12.1 percent compared to 8.7 percent in 2011 and 9.9 percent compared to 7.9 percent in 2012. In addition, Chrisinger found that these veterans were associated with higher risks of homelessness compared to nonveterans. Similarly, the U.S. Census data found that among all men who own or rent a house ages 55 to 64 years old, veterans had lower median net worth than nonveterans ($160,809 compared to $232,669—approximately 31 percent lower).

For veterans, one of the toughest barriers for entering the labor market can be physical or psychological ailments. Zogas’s research delved into this issue, too, finding that in a survey of 1,845 post-9/11 veterans, 65 percent reported a physical or psychological complaint. Individuals who reported these complaints also reported having greater difficulty transitioning into civilian life, including barriers to employment, with 23 percent being unemployed.

In a similar study among Vietnam-era veterans, those diagnosed with PTSD were 8.6 percentage points less likely to be currently working than a veteran without a PTSD diagnosis. Additionally, veterans with PTSD who were employed were more likely to have lower hourly wages compared to those without a PTSD diagnosis. This concern also was highlighted in the 2015 study by USC’s School of Social Work, which detailed service-provider interviews regarding unemployment among their veteran clients, in addition to those with criminal backgrounds and/or dishonorable discharge. Along with the unique challenges that these service providers faced in helping find employment for their veteran clients, those veterans reporting physical/psychological complains and those who had criminal backgrounds or were dishonorably discharged faced additional barriers, with many employers displaying an unwillingness to hire them.

Zogas finds that the Department of Veterans Affairs’ spending on programs related to improving veterans’ education and post-military employment has been growing substantially. Vocational rehabilitation training that includes support for apprenticeships, on-the-job training, postsecondary training at colleges, technical, and business schools, as well as supportive case management all have been expanding post-9/11, with spending on these programs totaling $92.7 billion from 2002 through 2015. Between these years, the agency’s total investment in education for veterans and preparing them for re-entry into the civilian labor market has more than doubled. In 2002, the VA spent $1.9 billion on employment and education, constituting 3.6 percent of its total expenses for the year. By 2015, that amount had more than doubled to more than 8 percent of the agency’s annual expenditures.

These expenditures also included counseling veterans about employment and relocation assistance, access to health and life insurance, financial planning, resume writing, and job search skills. Chrisinger’s report also outlined individuals who took advantage of the VA’s Disabled Veterans’ Outreach Program, which provides eligible veterans with case-managed intensive employment and training services, connections with potential employers, and referrals to other programs—including medical services from the VA. The report found that those veterans, both women and men, who used this program experienced higher earnings than nonveterans at both six months and one year after exiting the program.

Veterans face unique challenges entering the civilian job market related to education and differences between employer and employee expectations, to say nothing of the unique physical and psychological burdens that come with veteran status. It is why academics and policymakers alike must continue to do research to better understand the burdens of servicemen and servicewomen entering into the civilian labor market to ensure economic prosperity for our 20.4 million veterans.

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Equitable Growth releases 2019 Request for Proposals

Posted on by Maria Monroe

The Washington Center for Equitable Growth is mission-driven to advance evidence-based ideas and policies that promote strong, stable, and broad-based economic growth. One of the core ways we further that mission is through our academic grants program, which supports cutting-edge scholarly research investigating the various channels through which economic inequality may or may not impact economic growth and stability. On Monday, November 5, 2018, Equitable Growth issued its 2019 Request for Proposals and is inviting researchers at U.S. universities—both faculty members and Ph.D. candidates—to explore the questions we are hoping to answer and consider applying for a research grant.

Founded in 2013, Equitable Growth has awarded roughly $4 million to more than 150 researchers over 5 years of grantmaking. Findings from funded research, as well as that of our in-house experts, Steering Committee members, and Research Advisory Board, have informed policy debates on a wide range of topics at all levels of government, from legislative proposals for fair work scheduling to the importance of the minimum wage for broad-based economic growth.

Our grantmaking is organized around key drivers of economic growth, allowing us to ask questions to better understand the mechanisms through which inequality may be affecting growth. After 5 years of funding research, we have, for the first time, altered how we organize our grantmaking. While the underlying questions have not changed, the reorganization captures what we’ve learned about what makes the U.S. economy grow. The updated funding channels are: macroeconomic policy, market structure, the labor market, and human capital.

While not drastically different from our previous funding channels, this new organization reflects important findings from recent research. One case in point: A growing body of research into the relationship between inequality and economic mobility highlights the notable variations in economic outcomes across place and by race. These findings, among others, led us to refine our focus on human capital to better understand how economic inequality might be impeding the acquisition and cultivation of human capital. This and similar research also leads us in our new round of grantgiving to ask about the effectiveness of people-based versus place-based policies to counteract the dynamics of inequality.

Other research funded by Equitable Growth focused on a similarly disturbing trend—despite dropping interest rates, the return to capital has remained steady, and firms are reaping record profits, yet they are not investing in their operations or workforces. Instead, the share of income going to labor has declined while the share going to capital has increased. The authors conclude that these trends can be explained by a sizable increase in monopoly power. This and other studies lead Equitable Growth to focus on market structure as a key mechanism through which inequality may be affecting economic growth.

Similarly, the labor market is one of the most important institutions determining economic growth, particularly its distribution, as labor income is more than two-thirds of national income. Skill levels and the efficient matching of skills to jobs are key for economic growth. Yet the labor market is not a perfectly competitive market, but rather one that is regulated by a wide array of institutions that affect labor income and its distribution. A wealth of research on stagnating wages, pay inequality, and other issues facing workers led Equitable Growth to place a heavier emphasis on the two-way link between equitable growth and the labor market.

Finally, there is increasing political unrest in the United States. Democratic institutions are fundamental to the stability and smooth functioning of the U.S. economy. To help us understand what role inequality may play in levels of trust in government, its institutions, and the ability of elected officials to make policies to ensure strong, stable, and broadly shared growth, Equitable Growth has included questions related to political economy within its macroeconomic policy funding channel.

After 5 years of grantmaking, we have learned a lot, but we still have a lot to learn. We encourage you to read our 2019 Request for Proposals—an open solicitation to researchers at U.S. universities to apply for funding for new, cutting—edge research on inequality and growth—and to explore our funded research.

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Brad DeLong: Worthy reads on equitable growth, November 2-8, 2018

Posted on by Maria Monroe

Worthy reads from Equitable Growth:

  1. If I did not have to teach next Wednesday, I would be at this event: “Building a New Consensus on Antitrust Reform” Wednesday, November 14, 2018 at noon. Here’s the invite pitch: “Please join the Washington Center for Equitable Growth … for a conversation on reforming federal antitrust law [with] Sen. Amy Klobuchar (D-MN), Ranking Member of the Senate Subcommittee on Antitrust, Competition Policy and Consumer Rights, [who] will deliver keynote remarks. … RSVP is required by Friday, November 9.”
  2. This is a remarkably nihilistic column from Bob Solow, a member of Equitable Growth’s Steering Committee. Read his “A Theory Is a Sometime Thing,” in which he writes: “One can speculate. Maybe a patchwork of ideas like eclectic American Keynesianism, held together partly by duct tape, is always at a disadvantage compared with a monolithic doctrine that has an answer for everything, and the same answer for everything. Maybe that same monolithic doctrine reinforced and was reinforced by the general shift of political and social preferences to the right that was taking place at about the same time. Maybe this bit of intellectual history was mainly an accidental concatenation of events, personalities, and dispositions. And maybe this is the sort of question that is better discussed while toasting marshmallows around a dying campfire.”
  3. The U.S. unemployment rate continues to be a relatively bad indicator of how many workers are available for employers to hire at the currently prevailing wage. The flows of workers from out of the labor force directly into employment without their ever being a week in which they say they are unemployed and looking for a job continue to be large and continue to astound me in magnitude. This metric continues to be a relatively better indicator of how many workers are available for employers to hire at the currently prevailing wage. Check out Equitable Growth’s Jobs Day Graphs for this tidbit: “Workers previously out of the labor force are re-entering at higher rates, continuing the long-term upward trend.”
  4. Definitely read (or re-read) Sarah Jane Glynn from this past April, “Gender wage inequality: What we know and how we can fix it,” in which she writes: “Policies … could help reduce … pay inequality between men and women … The future economic competitiveness of the nation is under threat due to the lack of policies that would boost the labor force attachment, productivity, and wages of workers now and their children tomorrow.”

 

Worthy reads not from Equitable Growth:
 

  1. More evidence that unions are not at all anti-productivity. I first saw this point made a generation ago in Freeman and Medoff’s book What Do Unions Do?. Now, very much worth reading is Harald Dale-Olsen, “Wages, Creative Destruction, and Union Networks,” in which he writes: “Do unions promote creative destruction? … Increased unionization yields a positive impact on regional productivity, exceeding the wage growth, partly due to the closure of less productive firms, but also enhanced productivity of the survivors and new entrants.”
  2. The massive technological improvements in information technology that have made it much easier to write articles and publish journals have had surprising and counterintuitive effects on health academic economists, at least, seeking to gain reputation. Here we have some not so modest proposals for reform from James Heckman and Sidharth Moktan, “The Tyranny of the Top Five,” in which they write: “The appropriate solution requires a significant shift from the current publications-based system of deciding tenure to a system that emphasizes departmental peer review of a candidate’s work. Such a system would give serious consideration to unpublished working papers and to the quality and integrity of a scholar’s work.”
  3. I still find it surprising that this argument is not conventional wisdom inside the Federal Reserve among its governors, bank presidents, and staff. I do not understand what they are seeing in the data flow that I am not seeing. Read Neel Kashkari, “Pause Interest-Rate Hikes to Help the Labor Force Grow,” in which he writes: “The Fed has raised the federal-funds rate eight times in the past three years, and inflation now stands right at the 2 percent goal. A hard inflation ceiling would justify pre-emptive rate increases to ensure inflation doesn’t climb any higher. But the symmetric objective gives the Federal Open Market Committee the flexibility to see how the economy evolves before determining if further rate increases are necessary. The FOMC should seize this opportunity for a pause.”
  4. This is absolutely brilliant, both on the difficulties in forecasting technology and also on the difficulties of forecasting uses to which we will put technology. Read Rodney Brooks, “The Seven Deadly Sins of AI Predictions,” in which he writes: “Imagine we had a time machine and we could transport Isaac Newton from the late 17th century to today, setting him down in a place that would be familiar to him: Trinity College Chapel at the University of Cambridge. Now show Newton an Apple. Pull out an iPhone from your pocket, and turn it on so that the screen is glowing and full of icons, and hand it to him.”
  5. Up until 2000, it looked like we had an unemployment-rate (or vacancy-rate) adaptive-expectations price Phillips curve. Since the mid-1990s, we had a nonemployment-rate static-expectations wage Phillips curve. How long before another structural shift? We do not know. But right now Team Slack has the empirical evidence. And Team Slack says: The economy still has plenty of room to grow. Check out Jay C. Shambaugh’s tweet, “Score One for Team Slack,” in which he notes: “As @ModeledBehavior notes, it is not clear how long this relationship will hold, but it looks really good in 2018 (even better than in 2017). Almost impossible to argue slack is not part of wage growth story even if you don’t think it is whole story.”
  6. While Paul Krugman believes that “old-fashioned macroeconomics” did very well from 2005 to 2015, I have significant doubts. The gap between the short-term safe interest-rate that the Federal Reserve controls and the long-term risky real interest rate, which is what matters for the economy, was never and is not now well-understood. But here we do have substantial progress being made. Read Ricardo J. Caballero, “Risk-Centric Macroeconomics and Safe Asset Shortages in the Global Economy: An Illustration of Mechanisms and Policies,” in which he writes: “In these notes I summarize my research on the topic of risk-centric global macroeconomics. Collectively, this research makes the case that a risk-markets dislocations perspective of macroeconomics provides a unified framework to think about the mechanisms behind several of the main economic imbalances, crises, and structural fragilities observed in recent decades in the global economy. This perspective sheds light on the kind of policies, especially unconventional ones, that are likely to help the world economy navigate this tumultuous environment.”

 

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JOLTS Day Graphs: September 2018 Report Edition

Posted on by Austin Clemens

Every month the U.S. Bureau of Labor Statistics releases data on hiring, firing, and other labor market flows from the Job Openings and Labor Turnover Survey, better known as JOLTS. Today, the BLS released the latest data for September 2018. This report doesn’t get as much attention as the monthly Employment Situation Report, but it contains useful information about the state of the U.S. labor market. Below are a few key graphs using data from the report.

1.

The quits rate held steady at 2.4 in September, with workers leaving jobs at a higher rate than they did in the last economic expansion.

2.

The hire-per-job-opening rate was little changed over the month, increasing slightly from .81 to .82, and still at historically low levels.

3.

The vacancy yield was little changed and is still less than one unemployed worker per job opening.

4.

The job openings rate decreased from 4.7 to 4.5, but with continued low unemployment, the relationship between the two still reflects a tight labor market.

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