home.social

#labormarkets — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #labormarkets, aggregated by home.social.

fetched live
  1. More generous unemployment benefits and labour market support were linked to lower support for populist parties across 134 national elections in 16 countries, while cuts to unemployment protection were associated with higher populist vote shares

    Read Full Article

    #LaborMarkets #Populism #ElectionResearch https://www.kcl.ac.uk/news/could-better-welfare-support-curb-rise-of-populism
    Reenviado desde Science News
    (https://t.me/experienciainterdimensional/11437)

  2. Iowa: The Dead Zone

    By Cliff Potts, CSO, and Editor-in-Chief of WPS News

    Baybay City, Leyte, Philippines — June 19, 2026

    When Nothing Is Actively Wrong—And Nothing Is Right

    I did not understand how damaging Iowa was until after I left it. That is the most honest way to say it.

    While you are inside a stagnant system, stagnation feels like normal life. You work. You pay bills. You wait for things to improve. Because nothing is exploding, you assume progress must be happening somewhere offstage. It is only when you leave that you realize there was no offstage at all.

    Iowa was not hostile to me in the way Illinois had been. It was not quietly closed in the way Minnesota was. Iowa was something else entirely.

    Iowa was still.

    A Place Where Motion Stops

    I lived in Iowa for nine years. That alone should tell you something. People do not remain in places that are actively abusive for nearly a decade unless something subtler is happening.

    Iowa does not push you out. It wears you down.

    Work existed. I was employed. In fact, I worked for one of the largest employers in the region. On paper, that should have meant stability. In reality, it meant a ceiling so low you could touch it with one hand.

    Annual raises capped at four percent—if you were lucky. Promotions rare. Mobility nonexistent. You could do everything right and still be exactly where you started years later.

    That is not a ladder. That is a treadmill.

    Stratification Without Illusion

    Iowa’s class structure is not hidden. It is simply accepted.

    There are people who own land, run businesses, or occupy professional hierarchies. They are stable. They are visible. They are treated as the natural stewards of the community.

    Then there is everyone else.

    Renters. Service workers. Plant employees. People cycling through temporary stability without ever accumulating enough to move into the owning class. The distance between these groups is not enormous in appearance, but it is absolute in practice.

    You can live side by side and still inhabit entirely different economic realities.

    The Brain Drain Tells the Story

    Iowa has good schools. That is not a contradiction. It is the setup.

    Young people get educated—and then they leave.

    This pattern is well documented. Iowa consistently experiences net outmigration of young adults with college degrees, particularly those seeking professional and technical careers (Carr & Kefalas, 2009; U.S. Census Bureau, 2023). The state invests in human capital it cannot retain.

    That alone should raise questions. A system that educates people only to lose them is not broken. It is incomplete.

    What remains behind is a labor market optimized for containment, not growth.

    Liberal Rhetoric, Conservative Reality

    One of the most disorienting aspects of Iowa was its political culture—particularly among Democrats.

    In theory, Democrats represented concern for working people. In practice, they mirrored the conservatism of their Republican counterparts, differing more in tone than in outcome.

    Progressive voices were marginalized to the point that a separate progressive caucus had to be created simply to be heard. That should not be necessary in a functioning party. It was necessary because class discomfort ran deep.

    The moment lived poverty entered the room, enthusiasm evaporated. Solutions became abstract. Conversations ended.

    This is not unique to Iowa, but Iowa made it unmistakable: liberal identity does not guarantee class solidarity.

    Addiction as Infrastructure

    Iowa’s stagnation has consequences. When movement stops, despair fills the space.

    Alcohol abuse and methamphetamine use are not incidental problems there. They are structural symptoms. When people cannot move forward economically or socially, self-destruction becomes one of the few available forms of agency.

    Public health data confirms this pattern. Rural Midwestern states have experienced rising substance abuse rates correlated with economic stagnation and limited opportunity (Case & Deaton, 2020). Iowa is not an exception.

    It is a case study.

    Living Inside the Dead Zone

    While I was there, I knew my life was not improving—but I did not yet understand why. That is the danger of stagnation. It feels personal until you gain distance.

    I rented from a slumlord. I lived in a deteriorating mobile home. Around me were people who owned acreage, property, or family homes passed down through generations. We were told we were equals. We were not.

    Equality of politeness is not equality of position.

    Why It Takes Leaving to See It

    It was only after I left Iowa that the clarity arrived. The fog lifted. The exhaustion made sense.

    I had not failed to advance. There had been nowhere to advance to.

    Sociologists describe this phenomenon as spatial entrapment—regions where economic structures limit upward mobility regardless of individual effort (Chetty et al., 2014). Iowa fits that description with uncomfortable precision.

    Once you understand that, staying becomes irrational.

    A Place People Escape Quietly

    People do not flee Iowa dramatically. They plan their exits carefully. They finish degrees. They accept offers elsewhere. They do not look back.

    That quiet departure is the loudest indictment.

    Places with futures attract return. Places without futures do not.

    Naming It Plainly

    Iowa is not evil. It is not malicious. It is not loud.

    It is a dead zone.

    A place where effort circulates without compounding. Where ambition is treated as restlessness. Where the ladder exists in theory but not in practice.

    Staying there too long costs you time. And time, once spent, does not come back.

    Why This Matters Beyond Iowa

    Iowa is not unique. It represents a category of American places that have slipped into permanent stagnation while maintaining the appearance of normalcy.

    Understanding that category matters—because people are still being told to stay, to wait, to be patient.

    Patience is not rewarded in dead zones.

    Leaving is not failure. It is recognition.

    References

    Carr, P. J., & Kefalas, M. J. (2009). Hollowing out the middle: The rural brain drain and what it means for America. Beacon Press.
    Case, A., & Deaton, A. (2020). Deaths of despair and the future of capitalism. Princeton University Press.
    Chetty, R., Hendren, N., Kline, P., & Saez, E. (2014). Where is the land of opportunity? Quarterly Journal of Economics, 129(4), 1553–1623.
    U.S. Census Bureau. (2023). Net migration by state and age. https://www.census.gov

    #addiction #AmericanClassSystem #BrainDrain #classStagnation #inequality #Iowa #laborMarkets #Midwest #news #ruralEconomy
  3. Remote Work Leaves Younger Workers Sidelined
    libertystreeteconomics.newyork
    "…youth #unemployment has risen dramatically since the pandemic—as has the prevalence of remote work
    … remote work can explain 64% of the recent increase in unemployment among young college graduates."
    This happens because "when people work next to their colleagues, they receive more feedback on their output and more mentorship," making companies "reluctant to hire less-experienced workers in distributed work arrangements.
    …the rise of remote work has meaningfully contributed to the recent challenges facing young college graduates."

    #WfH #LaborMarkets

  4. Google deploys Gemini 3.5 Flash to Search, Spark, and enterprise as Pro delays to June. Meta cuts 8,000 roles while shifting 7,000 to AI work. Anthropic hires Andrej Karpathy for pretraining research. The infrastructure shift is underway—compute becoming the constraint, not capability.

    #AI #LaborMarkets #MLResearch

    implicator.ai/google-ships-age

  5. Help Is Not the Same as a Future

    By Cliff Potts, CSO, and Editor-in-Chief of WPS News

    Baybay City, Leyte, Philippines — May 15, 2026

    The Difference No One Warns You About

    There is a distinction that matters more than most people realize, and it is one America is very careful not to teach explicitly. Help and a future are not the same thing. One can exist without the other, and often does.

    I learned that lesson most clearly in Minnesota.

    After Illinois, help felt like progress. Assistance existed. People noticed. Systems responded. Compared to what I had known before, that alone felt like a step forward. It took time to understand that help, by itself, does not change trajectory. It only stabilizes the present.

    A future requires something else entirely.

    When Assistance Works as Designed

    Minnesota’s support systems did what they were supposed to do. Food pantries were available. Churches stepped in with grocery vouchers. State assistance existed and was accessible. None of it was humiliating or hostile.

    This matters, and it should not be minimized. Compared to many states, Minnesota treats need as a condition rather than a moral failing. That alone reduces suffering.

    But systems designed to alleviate immediate hardship are not the same as systems designed to produce long-term mobility. One keeps you afloat. The other gives you a direction.

    Minnesota offered flotation. It did not offer direction.

    Stabilization Without Movement

    Once basic needs are met, the next question is obvious: what comes next? That is where the silence returned.

    Work was available, but it clustered in roles that did not lead anywhere else. Security work. Overnight shifts. Positions that absorbed time and energy without building leverage. These jobs kept people alive, but they did not help them move.

    Labor economists have noted that many regional economies rely on what are effectively “containment jobs”—roles that stabilize labor markets without creating upward mobility (Autor, 2019). They are not meant to be ladders. They are meant to be endpoints.

    If you enter one of those jobs from the outside, you tend to stay there.

    The Ceiling You Don’t Hit—You Just Reach

    In more openly stratified states, ceilings announce themselves. Wages stall. Housing becomes impossible. You are pushed out.

    In Minnesota, the ceiling is quieter. You simply stop rising.

    You receive help. You survive. You do not advance.

    There is no dramatic rejection. No explicit denial. Just a gradual realization that nothing is opening further, no matter how steady your effort remains.

    This is a subtler form of closure, and in some ways, it is more dangerous. It encourages patience where action might otherwise occur. It teaches people to wait.

    Temporary Lives Become Permanent

    When help replaces opportunity, lives become provisional. You do not plan long-term. You do not invest. You do not imagine permanence.

    You tell yourself you are “getting through this period,” even when the period stretches into years.

    Sociological research on precarity shows that long-term instability, even when buffered by assistance, erodes planning capacity and future orientation (Standing, 2011). People adapt to the absence of forward motion by shrinking their expectations.

    That adaptation is rational. It is also corrosive.

    Why Decency Is Not Enough

    Minnesota is often held up as evidence that decency solves inequality. The logic is appealing: if systems are kind, outcomes will improve.

    But kindness does not rewire labor markets. It does not dismantle closed networks. It does not create pathways where none exist.

    Decency reduces harm. It does not redistribute access.

    That is not a moral critique. It is a structural one.

    The Emotional Cost of Waiting

    There is a particular exhaustion that comes from being told, implicitly, that things are fine because you are being helped. Gratitude becomes an obligation. Frustration becomes inappropriate.

    After all, the system is doing its part.

    This dynamic silences critique. It frames dissatisfaction as ingratitude. It keeps people from naming the absence of a future because the present is tolerable.

    I felt that pressure in Minnesota. I felt the need to justify leaving a place that had treated me decently—despite knowing I could not build a life there.

    When Leaving Is the Only Honest Choice

    Eventually, circumstances made the decision easier. My daughter returned to Texas. The reason I had come to Minnesota dissolved. What remained was a choice between staying static or moving on.

    Leaving did not feel dramatic. It felt necessary.

    That is often how exits happen in systems that offer help without futures. People do not flee. They drift away when they realize waiting will not change anything.

    A National Pattern, Not a Local Failure

    This essay is not an indictment of Minnesota alone. It describes a pattern visible across many “well-run” states and cities.

    Assistance expands. Opportunity contracts. People survive longer without advancing further.

    This is how inequality becomes normalized. Not through cruelty, but through containment.

    Naming the Distinction Clearly

    Help matters. It saves lives. It reduces suffering. It should exist everywhere.

    But help is not a future.

    A future requires access to networks, mobility, housing stability, and work that compounds rather than consumes time. Without those, assistance becomes a holding pattern.

    Minnesota taught me that lesson clearly.

    It showed me that survival and progress are not the same thing—and that confusing the two can cost you years.

    References

    Autor, D. (2019). Work of the past, work of the future. AEA Papers and Proceedings, 109, 1–32.
    Standing, G. (2011). The precariat: The new dangerous class. Bloomsbury Academic.

    #AmericanClassSystem #classMobility #inequality #laborMarkets #Minnesota #precarity #socialAssistance #socialSafetyNet
  6. Firm Pay, Amenities, and Inequality d.repec.org/n?u=RePEc:nbr:nber
    "Non-wage attributes are an important driver of job choice: workers frequently choose lowerpaying offers. Amenity valuations are highly dispersed across firms and approximately orthogonal to wages, so amenities do not offset between-firm pay differences. In money-metric units, the signal variance of amenities is about one-third that of wage premia. Conditional on the wage, high-amenity firms tend to be larger, have lower quit rates, and are more favorably reviewed by employees. Amenity preferences vary across demographic groups. Men and women do not value the same firms equally: the correlation between their firm-specific valuations is 0.239. Women work at firms that pay less. They also work at firms that offer them higher amenity value. Using gender-specific valuations, women do not work at firms that offer them lower overall value. In some specifications, they work at firms that offer more."
    #LaborMarkets #wages #ExperimentalEcon #gpg

  7. Human–AI Evaluation and Gender Transparency: Application Decisions in Competitive Hiring
    docs.iza.org/dp18517.pdf
    #AI involvement deters applicants, particularly women, across both pure algorithmic and hybrid human-in-the-loop regimes. This effect is driven by non-competitive candidates; non-competitive women apply least despite receiving the strongest objective evaluations under AI assessment. Competitive men exhibit #overconfidence -driven selection, while competitive women remain resilient and well-calibrated under AI assessment. Notably, randomizing candidate #gender disclosure does not significantly impact application behavior in any evaluation category.
    #hiring #llms #algorithmaversion #LaborMarkets #jobtech #ExperimentalEcon

  8. The hidden power keeping wages low
    npr.org/sections/planet-money/
    #Monopsony theory explains how employer dominance suppresses wages by distorting competitive market dynamics. Modern research reveals that market concentration and search frictions grant firms widespread control over pay; most employers have power to keep #wages low because worker options are actually limited. This explains why minimum wage hikes often raise incomes without reducing employment as once predicted. While new rules could raise pay, these fixes are limited by the choices of politicians and companies.
    #laborMarkets

  9. A Job I Like or a Job I Can Get: Designing Job #RecommenderSystems Using Field Experiments d.repec.org/n?u=RePEc:arx:pape
    "… welfare-optimal RSs rank vacancies by an expected-surplus index, and shows why rankings based solely on utility, #hiring probabilities, or observed application behavior are generically suboptimal
    … Algorithms informed by the model-implied optimal ranking substantially outperform existing approaches and perform close to the welfare-optimal benchmark.

    While the joint application-and-hiring probability is not welfare-optimal in theory, it emerges as a strong empirical benchmark in our setting. This result is structural rather than algorithmic: application probabilities are empirically small and remain so even under recommendation rules designed to stimulate applications
    … rankings based solely on application behavior are theoretically fragile
    … Machine-learning tools can substantially improve matching outcomes, but only when embedded in a framework that defines the economic objective and disciplines behavioral assumptions with experimental evidence. Without such a framework, RSs optimized for observable behaviors may perform well on predictive metrics yet remain misaligned with welfare-relevant outcomes."
    #LaborMarkets #jobtech #socialWelfare #ExperimentalEcon

  10. What Makes New Work Different from More Work? d.repec.org/n?u=RePEc:nbr:nber
    “… new work is central to maintaining and augmenting the value of human expertise in the face of automation because, unlike simply more (preexisting) work, new work demands novel expertise that commands a scarcity premium
    … new work is disproportionately performed by younger, more educated workers, both across and within occupations, consistent with new work requiring investments in new #skills
    … new work commands a wage premium even within detailed occupations and industries, controlling for demographics and human capital. These premiums reflect quasi-rents from skill acquisition that persist beyond initial entry into new work
    … the wage premiums in new work decline as new work ages, consistent with the transitory nature of expertise scarcity
    … new work serves as a countervailing force to #automation not only because it expands the set of tasks performed by labor, but also because it generates new demand for scarce human expertise."
    #wages #LaborMarkets

  11. Yann LeCun pushes back on Anthropic CEO Dario Amodei's prediction that AI could eliminate 50% of entry-level white-collar jobs within five years. LeCun argues AI executives shouldn't forecast labor shocks - that's for economists. Current BLS data shows 4.3% unemployment, not the 10-20% spike Amodei warns about, though young workers in AI-exposed roles face early pressure.

    #AI #LaborMarkets #FutureOfWork

    implicator.ai/yann-lecun-chall

  12. While there is some "boardroom disillusionment" with #AI
    Companies have seen "micro-efficiencies" (faster emails, quicker coding), but these haven't scaled to "macro-gains," and the Cost of Implementation (energy, licensing, and talent) is currently outstripping the Value of Output.
    archive.md/vs2B4

    …Brynjolfsson is more optimistic.
    The #productivity boost is coming, but it is currently masked by the massive intangible investments companies must make to reorganize their workflows. Companies are keeping expensive human staff while they figure out how to use AI, which artificially suppresses productivity per worker.
    archive.md/CABjm
    #gdp #LaborMarkets

  13. The Work-from-home Wage Premium frbsf.org/wp-content/uploads/w
    "… find that workers who work from home earn higher hourly wages than those who do not.
    … premium is driven by selection on unobservable worker characteristics (which could include ability, negotiation skills or bargaining power). Indeed, WFH was more prevalent for workers who already had high hourly wages before the pandemic, and was not associated with higher post-pandemic wage growth.
    … in a world with more widespread #WFH, differences in hourly #wages may significantly understate #inequality, as the best-paid workers are also more likely to receive the WFH amenity.
    … changes in WFH policies (e.g., through widely debated RTO mandates) could have important implications for the allocation of talent and for aggregate productivity: firms offering WFH disproportionately attract more educated and experienced workers
    … stringent #RTO mandates may induce the most productive employees to leave firms that do not offer WFH."
    #LaborMarkets

  14. We’re Planning for the Wrong AI Job Disruption archive.ph/2026.02.04-151036/h
    "Many politicians and commentators assume that if #AI can perform some of a job’s tasks, the role will disappear.
    But the distinction between task repricing—when technology can take over all or part of a task—and job destruction isn’t semantic, it is economic. When technology lowers the cost of performing specific tasks by lifting some of the load, firms reorganize production. Workers specialize differently.
    … software has automated large portions of bookkeeping and tax preparation without eliminating accountants, who have moved up the value chain toward advisory, forensic and judgment-intensive work.
    … A job that scores as 40% “exposed” to AI in these rankings doesn’t have a 40% chance of vanishing. It is more likely to be reorganized.
    … Technology automates, accelerates or reduces the cost of specific tasks within a job, allowing employees to spend more time on higher-value activities. As a result, output expands and #wages often rise."
    #LaborMarkets

  15. Wage Expectations and Job Search d.repec.org/n?u=RePEc:ajk:ajkd
    "While average misperceptions are relatively small, substantial shares of job seekers display pronounced optimism or pessimism.
    … Treated job seekers who were initially strongly optimistic increase their search effort and find jobs more quickly. Conversely, initial pessimists narrow the geographic scope of their search in response to the treatment, which accelerates re-employment—consistent with mitigated spatial search frictions.
    … accounting for job seekers’ subjective beliefs is essential when studying search behavior
    … suggest that job seekers seem to jointly determine multiple dimensions of their search strategy—including their wage demands, search intensity, and geographic scope. Exogenous changes in one domain can spill over into others
    … Both initially optimistic and initially pessimistic job seekers find employment more quickly when holding more accurate beliefs."
    #LaborMarkets #jobtech #wageTransparency

  16. Measuring Labor Market Tightness: Data Update and New Web Feature libertystreeteconomics.newyork
    "… Traditional tightness measures such as vacancies over unemployment (V/U) also do a relatively good job in predicting wage growth until about 2015, when V/U begins to falter. The steady deterioration in the forecasting performance of vacancy-based measures such as V/U and V/ES on its own aligns with earlier work finding that the relationship between vacancies and other labor market variables has shifted over time.

    Our findings suggest that the HPW Index and the quits rate are the best predictors of wage growth in the next quarter. Going forward, the web feature newyorkfed.org/research/labor- launched today will update both a quarterly and a monthly series of HPW in conjunction with the ECI, to track wage pressures in real time"
    #LaborMarkets #wages

  17. The Trust Equation: It’s Not Just Who You Hire, It’s How You Hire behavioralscientist.org/the-tr
    "Talent represents the most valuable asset of any firm, and candidates evaluate employers as rigorously as vice versa. #AI threatens to further depersonalize human interactions. To thrive in an era that threatens to erode human interactions, organizations must create consistently valuable experiences.

    The competitive advantage isn’t in fighting harder in the “war for talent” but in building systems that cultivate #trust, performance, and, with it, an employer brand at scale. Every organization claims to put people first. The ones that succeed are those whose processes prove it."
    #LaborMarkets #jobtech #hiring

  18. Who Works from Home After the Pandemic? d.repec.org/n?u=RePEc:iae:iaew
    "… while worker preferences are relevant, the results suggest that it is the nature of jobs that is the main factor determining who has the option to work from home.
    … strong associations between #WFH full days and both occupation and industry
    … findings suggest that the growth in WFH may be driving further increases in labour market inequality. WFH comes with obvious benefits for workers such as reduced commuting costs and improved work-family fit, and these benefits are mostly being captured by workers in higher paying jobs and occupations, employed on permanent contracts, and working full-time hours.

    That said, those taking advantage of the option to work from home might face long-term career penalties, with evidence from choice experiments suggesting that fully remote workers are at a disadvantage in terms of future promotion and salary increase prospects"
    #LaborMarkets #wages

  19. Labor market size and occupational skill match d.repec.org/n?u=RePEc:hhs:ifau
    The urban wage premium may be related to a city-size match quality gap:
    "… occupational skill-match quality is higher for individuals living in large local labor markets. Conditional on skills, differences in match quality explain around 30 percent of the city-size wage gap."
    #LaborMarkets #wages

  20. Bargaining power and #wages: Collective wage agreements and union membership in Germany d.repec.org/n?u=RePEc:zbw:ifso
    "Even in an era of declining membership of #unions, their roles remain vital in addressing contemporary labor market inequalities.
    #bargainingPower exerts a significant influence on both individual wage levels and wage inequality in Germany
    … both collective wage agreements and union membership… raise wage levels at the national level.… this effect is regionally heterogeneous: Collective wage agreements continue to be linked to higher wages at the regional level, whereas the relationship is weakened or disappears altogether for union membership.
    … collective wage agreements go along with lower overall wage #inequality, while union membership compresses wage inequality mainly at the lower end of the distribution."
    #LaborMarkets

  21. There's Nothing in the Air arxiv.org/abs/2510.22294
    "the urban wage growth premium: substantially faster wage growth in larger cities
    … part of this premium is driven by the firms that choose to sort themselves into bigger cities
    … eliminating the job ladder mechanism, the urban wage growth premium falls by 94.1% after accounting for firms and coworkers.
    … results challenge the view that cities generate human capital spillovers “in the air,” suggesting instead that urban wage dynamics reflect the #sorting of firms and workers and the pace of job #mobility."
    #wages #matching #LaborMarkets

  22. #Signaling in the Age of AI: Evidence from Cover Letters d.repec.org/n?u=RePEc:arx:pape
    "While #AI tools allow freelancers to produce more polished and tailored applications with less effort, our findings suggest that they fundamentally reshape how employers interpret cover letters. The widespread adoption of AI-assisted writing diminishes the informational value of cover letters, weakening their role as a hiring signal.

    Workers with weaker pre-AI writing skills saw larger improvements in cover letters, indicating that AI substitutes for workers’ own skills. Although only a minority of applications used the tool, the overall correlation between cover letter tailoring and callbacks fell by 51%, implying that cover letters became less informative signals of worker ability in the age of AI."
    #LaborMarkets #jobtech

  23. The Role of Firms and Occupations in Wage Inequality d.repec.org/n?u=RePEc:zbw:vfsc
    "… find that between-occupation job variance is roughly as important as within-occupation between-firm variation, and that between-occupation sorting is significantly more important than within-occupation between-firm sorting in our context.
    … 21% of total log-wage variance can be attributed to between-occupation pay variance and sorting of workers between occupations, while 9% can be attributed to variance within occupations between firms and sorting between workers and firms within occupations.
    … suggests that occupation-based factors, such as #heterogeneity in skill prices, are quantitatively more important than firm pay dispersion.
    … in higher-wage occupations and larger labor markets firm-level heterogeneity is relatively more important, although the importance of firm-worker sorting does not vary.
    … individual-level differences are significantly more important in both higher-wage occupations and larger labor markets."
    #LaborMarkets #wages #occupationalClassification #skills

  24. Are decredentialed jobs a route to upward mobility? d.repec.org/n?u=RePEc:osf:soca
    "… for some jobs, a degree requirement may be a rough and ready #screening tool, filtering out many qualified candidates, or even a result of occupational closure.
    When workers move into jobs that have recently dropped degree requirements they receive an earnings premium of around $6000 per year relative to similar workers moving into never-credentialled jobs. This is despite the fact that when employers decredential they deskill the job and reduce pay by around 20%.
    Non-college workers hired into these roles are more socio-economically disadvantaged than the college-educated workers they replace
    … results show that the movement toward decredentialing holds promise for boosting earnings mobility for workers.
    Despite these benefits, most employers that drop explicit college requirements continue to hire college graduate applicants into those positions.
    … suggestive evidence that employers struggle to integrate new non-college hires and that they face backlash from existing employees."
    #LaborMarkets #wages #vocationalTraining #credentials

  25. Labour market power, firm productivity, and the immigrant-native pay gap d.repec.org/n?u=RePEc:zbw:clef
    "Immigrants earn 16% less than native-born workers in Canada, and this pay gap is similar in many other high-income countries.
    … immigrants earn 77% of their MRPL on average, compared to 84% for natives

    First, differences in labor supply curves between immigrants and natives contribute significantly to the pay gap. Second, immigrants tend to work at more productive firms, driven by their tendency to work in cities where firms are more productive on average. Finally, interactions between firm productivity and labor supply are important, implying methodologies that rely on additive separability assumptions will likely produce biased decompositions of the immigrant-native pay gap."
    #LaborMarkets #wages #discrimination

  26. Do Employers Comply with Pay Transparency Requirements in Job Postings? libertystreeteconomics.newyork
    "… employers ignore #payTransparency requirements; roughly a quarter of job listings covered by these laws fail to include salary information."
    #wages #LaborMarkets #oja

  27. Developing a New European Indicator of Potential Skill Shortages d.repec.org/n?u=RePEc:iza:izad
    "… estimate that approximately 2% of job vacancies in the European Union are likely to experience skill shortages.
    … there is substantial variation across occupations, ranging from 5.1% for ICT professionals to approximately zero in more elementary occupations. There is also substantial variation in the estimated incidences of potential skill shortages at member state level, ranging from over 10% in Luxembourg to under 1% in Estonia and Poland.
    … analysis shows that occupations that are most likely to experience #skillShortages also tend to experience relatively high rates of changes in skill requirements over time"
    #LaborMarkets #skills

  28. Explaining the Dynamics of the Gender Gap in Lifetime Earnings d.repec.org/n?u=RePEc:bfr:banf
    "Comparing our results with the US, we find that the gender gap in lifetime earnings has remained significantly smaller in France
    .… while the US has seen a striking narrowing of the gap between cohorts across the whole distribution (except at the very top), in France, we observe a sharp narrowing only at the top and bottom of the distribution for the youngest cohorts.
    .… In France, lifetime earnings have increased across the entire distribution for both men and women. In contrast, in the US, men below the median have experienced losses.
    … the contribution of unobserved factors decreases across cohorts but increases across the distribution
    … this sharp decline in the unexplained part has been accompanied by a growing role of observable factors. The most important effect comes from… the decline in the years worked full time, which has slowed down the convergence across genders.
    … At the bottom of the distribution, the minimum wage helps reduce earnings disparities, while #workingTime remains the primary driver of the gender gap in lifetime earnings. At the top, our results are consistent with a glass-ceiling effect, which has weakened over time.
    … the increase in educational attainment and the narrowing of the gender gap in returns to #education have also contributed to the reduction in the gender pay gap"
    #LaborMarkets #wages #gpg

  29. Decomposing Trends in the Gender Gap for Highly Educated Workers d.repec.org/n?u=RePEc:cwl:cwld
    "… much of the large gap in earnings between the 1931 and 1950 cohorts is due to a cohort specific “residual component” that shifts the gender gap in earnings by the same amount for all college graduates. Most of the decline is within occupation, especially for the early cohorts. The residual gap varies little for the 1951 to late 1970s birth cohorts, after which it resumes its decline.
    … the extensive literature on the long term trend in the gender gap suggests changes in total labor experience at a given age, hours per week, lower fertility, shifting gender norms and preferences affecting occupation choice, and reduced #discrimination against women have all played a role.
    … gender differences in the relative return to undergraduate and graduate degree combinations contribute to the gender gap, but very little to the decline in the gender gap over the full time period
    … the education gap is large for the early cohorts but declines substantially and is an important part of the narrowing of the gender gap. However, to our surprise, this decline is mostly offset by cohort trends in the relative returns to specific fields that favored men"
    #LaborMarkets #wages #gpg