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on Education |
| By: | Daniel Goller; Samuel Lüthi; Stefan C. Wolter |
| Abstract: | Practical skills are widely believed to be a key determinant of labor market success, yet credible empirical evidence remains scarce, because these skills are occupation-specific, acquired primarily through workplace experience, and notoriously difficult to measure. We address these challenges using an exceptional dataset covering over 170 occupations. Our measure of practical skills is based on high-stakes expert evaluations of apprentices' performance in occupation-specific standardized practical examinations, conducted under authentic workplace conditions and lasting from several hours to several weeks. Combined with rich administrative data, this allows us to separate practical skills from general and vocational knowledge. We show that practical skills form a distinct dimension of human capital, only weakly correlated with traditional achievement measures. Practical skills are the strongest predictor of early labor market success, consistently associated with higher first-year earnings, lower NEET risk, greater retention by the training firm, and a higher likelihood of entering tertiary education. These relationships are robust across occupational task groups and by gender. Out-of-sample analyses show that practical skills substantially improve predictions beyond conventional educational achievement and background characteristics. |
| Keywords: | Return to skills, Practical skills, School-to-work transition, Human capital |
| JEL: | J24 I26 J31 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:crm:wpaper:26206 |
| By: | Joshua S. Goodman; Samuel Nitkin |
| Abstract: | Private tutoring chains like Kumon and Sylvan have expanded rapidly in recent decades. Combining data on business locations, household spending, and district test scores, we study who uses these centers and how they affect academic skills. Nearly half of tutoring users are from the top income decile, with Asian and White households five and two times as likely to purchase tutoring as Black and Hispanic households. A staggered differences-in-differences design shows the opening of a district's first chain center raises district-wide math and reading scores by 0.02-0.03 standard deviations, at a much lower cost than public spending typically producing similar gains. Math effects are largest for White and Asian students, so that center entry widens racial achievement gaps, though less so in more racially integrated districts. These private investments help their users, deepen educational inequality, and shape outcomes by which state accountability systems and families judge schools. |
| Keywords: | tutoring center, test scores, achievement, educational inequality |
| JEL: | I21 I24 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12935 |
| By: | Zachary Bleemer; Jesse Rothstein |
| Abstract: | American colleges and universities are highly stratified by pre-college academic achievement, family background, and institutional resources. We study the meritocratic consensus in American higher education: colleges that high-testing students (who are generally also from high-income families) attend spend dramatically more on instruction than do those that enroll lower-testing students. Stratification by test scores has been largely stable since the 1960s, but the stratification of instructional resources has risen sharply since 1970 at both private and public institutions. Non-academic admissions criteria like athletics, legacy, and affirmative action are second-order in determining the allocation of students to universities. Potential economic justifications for the positive association of instructional expenditures with student prior achievement—q-complementarity between achievement and resources, convex social returns to high human capital, and incentives to invest in learning prior to college—have little empirical support. Resource stratification across universities has not increased in the past decade, largely due to increased public funding of universities that enroll lower-testing students through financial aid programs like California's CalGrant, but stratification within institutions is now rising swiftly. |
| JEL: | I23 I24 N32 Z13 |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35650 |
| By: | Altin, Mehmet Evrim; Jäger, Kirsten; Jütte, Silke; Schneider, Florian |
| Abstract: | The rapid diffusion of artificial intelligence (AI) tools is fundamentally reshaping learning practices in higher education, particularly in mathematics and statistics courses. This study investigates how undergraduate students across multiple programs at IU International University engage with AI-based mathematics tools, which applications they prefer, and how they evaluate their performance. Drawing on survey data from 174 students enrolled in mathematics lectures during the spring term of 2025, we analyze awareness, usage intensity, and perceived usability, understandability, correctness, and value for money of leading AI tools. The results reveal a highly concentrated market structure: ChatGPT, Photomath, and Gemini dominate student awareness and usage. While ChatGPT is perceived as the most user-friendly and offers strong value for money, Photomath receives the highest ratings for correctness of results. Gemini, in contrast, is evaluated more cautiously across dimensions. Differences in awareness between mathintensive and non-math-intensive programs are small and statistically insignificant, suggesting that AI adoption in mathematics is broadly distributed across disciplines. The findings indicate that students integrate AI tools primarily as complementary learning aids rather than replacements for traditional materials. Overall, the study provides an empirical baseline for understanding how AI functions as a study partner in mathematics education and highlights the growing importance of evaluating not only usage frequency but also perceived reliability and pedagogical value. |
| Keywords: | Artificial Intelligence, Mathematics Education, Student Perceptions, Learning Tools |
| JEL: | I21 I23 O33 A22 C83 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:iubhbm:342564 |
| By: | A. Patrick Behrer; Joshua S. Goodman; J. Parker Goyer; R. Jisung Park |
| Abstract: | Nearly the entire world’s population breathes air exceeding WHO pollution guidelines, but the extent to which that exposure impairs the accumulation of human capital is not well understood. We study this using longitudinal PSAT data on nearly 10 million U.S. high school students, comparing the same student’s scores across attempts preceded by differing air quality and instrumenting for local PM2.5 with smoke from distant wildfires. A year of observed pollution exposure reduces learning by 0.04-0.06 standard deviations, or 14-19% of typical annual score growth. The damage comes almost entirely from moderate pollution days (8–12 μg/m3), below the EPA’s historical standard, and from exposure during the school year rather than summer, pointing to instructional disruption as a mechanism. Effects are three times larger in disadvantaged schools and among Black and Hispanic students, who are harmed more by the same exposure. Exposure to air pollution widens achievement gaps. |
| Keywords: | air pollution, test scores, achievement gaps, PM2.5, wildfire smoke |
| JEL: | I2 I24 Q5 Q53 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12936 |
| By: | Matthew Collins; Patrick Wing McHale; Devon Spika |
| Abstract: | Education is widely seen as a key driver of economic growth, yet social institutions may mediate efforts to improve outcomes. We study how age-set organisation---where societies are structured into age-based social groups---shapes parental human capital investments and children’s educational attainment. Children in age-set societies receive greater investments, improving health and schooling at younger ages. Yet effects on education dissipate between the ages of 13-16, coinciding with the timing of age-set initiation. We also find that universal secondary education raised schooling only in non-age-set societies. These findings highlight how the impacts of social institutions can vary across the life-cycle. |
| Keywords: | social organisation, parental investment, human capital, child development |
| JEL: | I25 J24 O15 Z13 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12940 |
| By: | Stanislav Avdeev |
| Abstract: | This paper provides the first evidence on the impact of exposure to international students on the long-term outcomes of native students. I combine unique survey and administrative data from the Netherlands covering one million students across three decades and employ an across-cohort design. I find that exposure to international students leads natives to (i) form social ties with non-natives, (ii) hold more positive attitudes towards migration and learning about other cultures, and (iii) seek opportunities abroad. Notably, I find precisely estimated zero effects on employment, income, entrepreneurship, and the share of international co-workers up to 25 years after university entry. |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2607.28842 |
| By: | Adam A. Dzulkipli; Nicole Black; David W. Johnston; Leonie Segal |
| Abstract: | Debate over the optimal school starting age has focused largely on children’s educa- tional and developmental outcomes, with little attention given to whether starting school earlier may protect vulnerable children from maltreatment. This paper examines that pos- sibility by exploiting a date-of-birth cut-off for school entry in Australia. We find that earlier school entry reduces the probability of a maltreatment notification from a non- education reporter by 4.3 percentage points or 50% relative to the mean. The reduction is driven largely by fewer police notifications and notifications involving emotional abuse. In contrast, notifications from education-sector reporters are unaffected overall, reflect- ing offsetting changes in notifications from preschool and school-based educators. The protective effects are concentrated among children without younger siblings and extend to older siblings, with the pattern of results suggesting that relaxed childcare constraints and increased maternal employment may be important mechanisms. |
| Keywords: | school entry, child maltreatment, child protection, regression discontinuity |
| JEL: | I21 I28 J13 |
| Date: | 2026–09–02 |
| URL: | https://d.repec.org/n?u=RePEc:mhe:chemon:paper_1788311805474_394 |
| By: | Hoffmann, Linda; Wicht, Alexandra |
| Abstract: | Vocational education and training (VET) dropout disrupts school-to-work transitions. While spatial mobility is an important strategy for accessing VET, little is known about how it relates to subsequent dropout. Drawing on a cost-benefit perspective, this study examines whether first-year VET dropout differs by spatial mobility and whether these differences vary with resources available to bear mobility-related costs and returns that may offset them. We use representative longitudinal data from the German National Educational Panel Study linked to administrative geospatial data. Logistic regression models distinguish non-mobile students from those mobile within and between regional labor markets (RLMs) and assess heterogeneity by parental socioeconomic status (SES), VET wages, realized occupational aspirations, regional attractiveness, and regional person-environment match. Predicted dropout probabilities are approximately three percentage points higher for mobility within RLMs and four points higher for mobility between RLMs than for no mobility. These mobility-related differences decrease with increasing parental SES for both mobility types. Higher VET wages correspond to smaller dropout differences for mobility within RLMs, whereas greater realization of occupational aspirations corresponds to smaller differences for mobility between RLMs. Higher regional attractiveness shows a similar pattern only for mobility within RLMs, while higher regional person-environment match coincides with smaller dropout differences for both mobility types. Overall, mobility-related dropout differences vary with available resources and realized returns. The social patterning of mobility-related dropout differences may contribute to inequalities in school-to-work transitions, underscoring the importance of considering spatial mobility and regional contexts in research on youths’ educational decision-making. |
| Date: | 2026–08–14 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:kbcq6_v1 |
| By: | Bobba, Matteo |
| Abstract: | This paper explores an information intervention designed and implemented within a school assignment mechanism in Mexico City. Through a randomized experiment, we show that providing a subset of applicants with feedback about their academic performance can enhance sorting by skill across high school tracks. This reallocation effect results in higher completion rates three years post-assignment. We further integrate the experimental evaluation into an empirical model of school choice and educational outcomes to assess the impact of the intervention for the overall population of applicants. Information provision is shown to increase the ex-ante efficiency of the student-school allocation, while congestion externalities are detrimental for the equity of education outcomes. |
| Keywords: | Subjective expectations; Information provision; School choice |
| JEL: | D83 I21 I24 J24 |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19238 |
| By: | Anna Hasselqvist |
| Abstract: | Academic inequality between migrants and natives is often attributed to family dynamics that are difficult to observe. Siblings provide a way to study them: I estimate the effect of having a high-achieving sibling on the educational outcomes of children in migrant and native families. Using exogenous variation in sibling achievement from Sweden’s school-entry cutoff in a Regression Discontinuity Design, I show that second-generation migrant girls face a unique disadvantage. A high-achieving brother lowers their grades, while a high-achieving sister has a small positive influence. Spillover effects are negligible for boys and native children regardless of sibling gender. Heterogeneity analysis suggests that traditional cultural norms contribute to this disadvantage, and parental labor market integration substantially attenuates it. |
| Keywords: | Sibling spillovers, second-generation migrants, gender norms, school starting age |
| JEL: | I24 J13 J15 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:diw:diwwpp:dp2178 |
| By: | Guillermo Cruces (University of Nottingham); Diego Fernandez Meijide (Universidad de San Andres); Sebastian Galiani (Tulane University); Ramiro Galvez (UTDT); Maria Lombardi (UTDT) |
| Abstract: | Does generative artificial intelligence (AI) widen or narrow productivity gaps across workers? We study this in a randomized online experiment with 1, 174 adults aged 25-45 who completed a workplace-style problem-solving task with or without a generative AI assistant, followed by an unassisted module. AI improves performance for all participants, but gains are larger among those with less education. Without AI, higher-education participants outperform lower-education participants by 0.548 standard deviations; with AI, the gap falls to 0.139, closing about three-quarters of the initial difference. Chat logs show that lower-education participants obtain substantial assistance, while higher-education participants use AI more effectively. Gains are not purely due to delegation: treated participants do not perform worse once AI is removed, and lower-education participants retain part of their improvement, although a sizable gap re-emerges. Intensive AI use raises assisted performance regardless of participants' own effort, but follow-up performance improves only when intensive use is combined with sustained effort. Generative AI narrows effective productivity differences in task execution, while human-capital differences continue to shape unassisted performance and tool use. |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2608.04198 |
| By: | Hülya Eraslan; Jeremy T. Fox; YingHua He |
| Abstract: | Ordinal mechanisms use rankings but not preference intensities. Cardinal mechanisms also elicit school utilities, allowing them to use students’ preferences over assignment lotteries. We compare probabilistic serial with four cardinal mechanisms that maximize the same welfare objective under successively stronger restrictions: capacity-only, ε-envy-free, envy-free, and a welfare-maximizing cardinal-preference pseudomarket. Because the feasible sets are nested, maximum welfare weakly falls as the restrictions tighten from capacity alone to approximate no-envy, exact no-envy, and equal budgets with common prices. We establish positive and negative results on large-market truthtelling. All 44 theorem parts in the paper are machine-checked in the Lean 4 proof assistant. We develop methods for computing cardinal-preference pseudomarket equilibria for Seattle’s 898 students and 11 schools. Using set-identified cardinal preferences from Seattle high-school choice data, we estimate that, under exact capacity, capacity-only raises mean welfare over probabilistic serial by 0.053, equivalent to shifting 5.3 percentage points of assignment probability from the average student’s worst school to the top school. Exact envy-freeness retains 79% of this gain; best-found pseudomarket equilibria yield a mean gain of 0.002. The estimates show both the value of cardinal information and the welfare cost of pseudomarket fairness restrictions. |
| JEL: | C78 I20 |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35658 |
| By: | Ran Abramitzky; Santiago Pérez; Joseph Price |
| Abstract: | We use newly digitized records for 1.2 million students at 60 co-educational U.S. colleges, 1915–1943, linked to enrollment records for their children through 1963, to study how colleges shape marital matching and the intergenerational transmission of educational advantage. About 6% of men and 9% of women marry someone from their own college. This homogamy is largely causal: within colleges, more different-sex classmates and longer campus overlap both raise same-college marriage. Same-college spouses are more educated, and this advantage persists across generations. Children of same-college couples more often attend selective colleges, with spousal education explaining a third of the gap. |
| JEL: | J0 N32 |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35602 |
| By: | Emily Cuddy; Janet Currie; Elisa Jácome; Lucy Manly |
| Abstract: | By age 17, a quarter of U.S. students have experienced a peer suicide. Using linked administrative data from South Carolina and a matched difference-in-differences design, we find that exposure to a peer's self-harm death increases the probability of a self-harm diagnosis by nearly 50% and both the incidence and frequency of mental health visits. Effects on care use and criminal behavior are concentrated among white boys, and responses diverge by prior mental health history: students without a prior diagnosis increase felony offending rather than care-seeking. Deaths from assault and transportation accidents produce no comparable rise in self-harm, consistent with contagion. |
| JEL: | I12 J13 K42 |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35603 |
| By: | Imad Aarab (FSJES - Faculty of Legal, Economic, and Social Sciences of Fes); Issam Debbagh (FSJES - Faculty of Legal, Economic, and Social Sciences of Fes) |
| Abstract: | Against a backdrop of increased competition, higher education institutions, whether private or public, are compelled to implement new strategies aimed at improving the quality of the services they offer whilst meeting market demands; hence the need to carry out a diagnostic assessment of their services. This study aims to assess the quality of service as perceived by students at the Faculty of Legal, Economics and Social Sciences at Sidi Mohamed Ben Abdellah University in Fez (FSJES-FEZ), using a rigorous quantitative cross-sectional approach based on the SERVQUAL instrument, applied to a sample of 306 students enrolled in Master's programmes for the 2025-2026 academic year. The results revealed negative gaps across the five dimensions of service quality, with Tangibility recording the most critical deficit (-3.12) and Assurance the lowest score (-1.88), for an overall average gap of (-2.53). Whilst a notable paradox emerges, the Assurance dimension, deemed the most important by 29.2% of the students surveyed, paradoxically shows the smallest deficit, whereas Tangibility show the most critical deficit, this study proposes the use of Mitchell et al.'s stakeholder framework (1997) to interpret the hierarchy of the deficits observed, as well as to draw on the theory of the adaptation of aspirations, which opens up new perspectives on how students adjust their expectations in a context of structural massification. Furthermore, the results call for targeted institutional responses concerning physical infrastructure, the digitisation of administrative procedures, and the strengthening of the human dimension of the teaching relationship. |
| Keywords: | SERVQUAL model, Quality of service, Higher education, Massification, FSJES Fez, Expectations, Perceptions, Stakeholders, Empirical Research |
| Date: | 2026–07–08 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05685655 |
| By: | Sarah Turner |
| Abstract: | The One Big Beautiful Bill Act (OBBBA, P.L. 119-21) eliminates the federal GradPLUS loan program for new borrowers effective July 1, 2026, replacing nearly two decades of uncapped federal graduate lending with annual limits of $20, 500 ($50, 000 for eleven professional fields) and new aggregate caps. The resulting financing gap — approximately $8 billion annually across roughly 370, 000 affected borrowers — raises the question of whether and how private capital will substitute for displaced federal lending. This paper analyzes the economics of that transition. Before GradPLUS, private lenders filled the gap between federal Stafford limits and graduate program costs, with nonfederal graduate originations reaching $5.3 billion (constant 2024 dollars) by 2005–06. After GradPLUS extended federal borrowing to the full cost of attendance in 2006, private lending collapsed — falling more than 70 percent within a few years and never recovering. The federal program provided not only credit but, through income-driven repayment and Public Service Loan Forgiveness, insurance against earnings risk that no private product could replicate. The same features that crowded out private lending generated compounding distortions: borrowing untethered to repayment capacity, upward pressure on tuition, and a reversal from projected federal surpluses to losses exceeding thirty cents per GradPLUS dollar lent. Linking institution-by-field federal borrowing data to institution-by-field earnings outcomes, I examine the relationship between historical borrowing above the new OBBBA caps and post-completion earnings across programs. I find substantial variation in the extent to which different degree programs would likely support above-cap borrowing from private lenders or other sources. In fields such as law and MBA, earnings rise steeply with borrowing exposure, providing a basis for program-level risk pricing; in fields such as social work, counseling psychology, and physical therapy, the earnings-to-borrowing gradient is essentially flat. I also examine features of the private capital market and institutional responses shaping the transition — including capital constraints on scaling private lending, legal barriers to using program-level outcomes data in underwriting, and the emerging role of institutions as intermediaries between lenders and students. |
| JEL: | I22 I23 |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35683 |
| By: | Paul Gompers; George Hu; Will Levinson; Sachin Srivastava |
| Abstract: | This paper examines how networks formed through college athletics influence the early-career trajectories of Ivy League graduates. Tracking professional histories of 120, 306 Ivy League graduates, we compare each graduate's actual first job against other potential jobs that the graduate could reasonably have taken. Athletics-based networks, especially team-based connections, materially influence initial job choice. Employing one additional alum from a specific Ivy League collegiate sports team increases the probability that a same-team athlete joins the firm by 193.70% relative to the baseline match probability. Likewise, employing one more Ivy League alum who played a specific Varsity sport increases the probability that any Ivy League athlete who plays the same sport joins the firm by 16.40%, while employing one more alum who played any sport at a specific Ivy League university raises the probability that any Ivy League athlete from the same university joins the firm by 4.60%. For team-based connections, these effects persist whether the alum and the college athlete were direct peers whose college years overlapped or older “network” affiliates whose college years were completely disjoint. Our results demonstrate that college athletics-based social networks materially influence initial job placement and early-career trajectories for top college graduates. More generally, they clarify how non-academic social capital shapes the job searching and matching process within labor markets. |
| JEL: | I23 J24 J38 J4 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35527 |
| By: | David Neumark; Emma Wohl |
| Abstract: | We provide the first direct estimates of the effects of minimum wages on low-wage workers in families at different points of the distribution of income-to-needs, using data from the Survey of Income and Program Participation, which oversamples low-income families. We find adverse – rather than beneficial – effects of minimum wages on the employment, hours, and earnings of initially-employed low-wage workers in poor and low-income families. Although we do not find a gradient indicating more adverse effects on the poorest low-wage workers, the adverse effects for poor and low-income low-wage workers help explain why minimum wages do not reduce poverty. |
| JEL: | J23 J38 |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35628 |
| By: | Gradstein, Mark; Ishak, Phoebe W. |
| Abstract: | We explore the effects of early life income shocks on human capital using oil price fluctuations in a large sample of relevant African countries and employing micro data from multiple waves of the Demographic and Health Survey (DHS). Such shocks enable human capital investment via the standard income effect; but also crowd it out because of substitutability between natural resource and human capital income sources. The relative strength of the two effects depends on the age at which the shock is experienced. Consistent with these insights, we find that income shocks in early life are associated with enhanced educational attainment and wealth but are sometimes linked to reduced levels of such outcomes if experienced in adolescence. These results survive multiple robustness checks, and their broader implications are discussed. |
| Keywords: | Human capital |
| JEL: | O12 I2 |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19305 |
| By: | Tarun Sabarwal (Department of Economics, University of Kansas, Lawrence, KS 66045, USA) |
| Abstract: | We propose pathways toward academic excellence in graduate education in rural settings by focusing on community-based scholarship, an anchor institution framework, and a locally based sustainable research culture as comparative advantages of rural higher education institutions. Instead of viewing rural institutions through a deficit framework, we leverage their comparative advantages into sources of academic strength. The vision here goes beyond improving educational access in underserved regions, positioning rural institutions as central actors in intellectual, social, and regional transformation. |
| Keywords: | complementarities, equilibrium, fixed point, poset, monotone comparative statics |
| JEL: | I2 I22 I23 |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:kan:wpaper:202616 |
| By: | Pierri, Gastón; Fontenele, Marcelo; Nunes, Jose Luiz |
| Abstract: | This paper presents preliminary results from a pilot study conducted in the courts of Ceará, Brazil. The study evaluates the impact of introducing a tool that uses natural language processing and machine learning techniques to cluster judicial acts by textual similarity on clerk productivity, measured as the number of case files a clerk can produce in a day. Estimates indicate that treatment-group clerks produced approximately 10 more case files per day than control-group clerks, a statistically significant difference equivalent to a 37% increase relative to the control group mean. The results are robust to the exclusion of outlier observations and exceptionally productive clerks. |
| Keywords: | artificial intelligence;Judicial Productivity;Natural Language Processing;Court Administration;Public Sector Automation;machine learning;Field experiment;access to justice |
| JEL: | O33 H83 K40 C93 J24 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:idb:brikps:14700 |
| By: | Jonathan Hall; Jason Hicks; Morris M. Kleiner; Yun taek Oh |
| Abstract: | We examine whether occupational licensing improves service quality and safety using trip-level Uber data that include driver ratings and telematics-based measures of driving behavior. Exploiting quasi-random assignment from proximity-based dispatch, we compare trips served by licensed and unlicensed drivers in two settings: a cross-border comparison between New York City and New Jersey, and a deregulation event in Houston. Across settings and specifications, including instrumental variable estimates, we find no consistent evidence that licensing improves consumer outcomes. In Houston, post-deregulation entrants are indistinguishable from previously licensed drivers on ratings and driving behavior, despite differing markedly in experience and age. |
| JEL: | J0 J44 J48 J89 K29 L10 L8 |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35635 |
| By: | Fatima, Freeha; Ozen, Efsan Nas; Raju, Dhushyanth |
| Abstract: | This paper examines how artificial intelligence (AI) is reshaping Türkiye’s labor market by documenting patterns in skill supply, employer demand, and labor market adjustment using high-frequency digital labor market indicators from LinkedIn. The analysis focuses on the mechanisms through which AI-related change is associated with shifts in skills, hiring, occupational mobility, exposure to generative AI, and international migration. The evidence shows a relatively broad presence of foundational digital and AI literacy skills across sectors and demographic groups, alongside a persistent and increasing concentration of advanced AI engineering talent within a narrow set of occupations and industries. Measured skill penetration follows non-monotonic patterns over time, while frontier AI talent accumulates steadily, indicating a divergence between the breadth and depth of AI capability. Entry into AI roles often follows strongly path-dependent pathways, and employer demand signals for technical and AI-adjacent capabilities are only partially reflected in realized hiring, with no sustained positive divergence in AI-related hiring relative to overall labor demand. Potential exposure to generative AI varies systematically across sectors and demographic groups, with the balance between task augmentation and disruption differing across sectors rather than uniformly favoring one over the other. International migration emerges as a salient adjustment margin for highly specialized AI talent, operating alongside domestic reallocation mechanisms and influencing the availability of frontier skills within the domestic labor market. These patterns indicate that the central challenge associated with AI in Türkiye’s labor market lies not in whether AI-related capabilities will spread, but in how reallocation unfolds across skills, occupations, and workers over time. The findings highlight the role of skill formation systems, hiring and credentialing practices, occupational structures, and cross-border mobility in shaping the trajectory of labor market adju stment. The analysis also illustrates how digital labor market data can complement traditional sources by providing timely evidence on emerging skills, evolving demand, and early adjustment dynamics in middle-income economies navigating the AI transition. |
| Date: | 2026–04–01 |
| URL: | https://d.repec.org/n?u=RePEc:wbk:hdnspu:209921 |