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on Labor Markets - Supply, Demand, and Wages |
| By: | Liepmann, Hannah (ILO International Labour Organization); Hegewisch, Ariane |
| Abstract: | While population ageing increases the demand for care work, new technologies, including AI, reinforce the importance of human interaction, with recent research finding significant wage premiums for social skills. Against this background, we investigate two factors behind the gender wage gap: occupational gender segregation and lower pay in female-dominated occupations, especially care work, where social skills are central. Using 1972-2024 CPS data, we show that occupational gender segregation remains pronounced in the United States, with many care occupations remaining female-dominated. This continues to correlate with lower wages. Conditional on observable characteristics, a 1 percentage point increase in the occupational share of women during 2015-24 was associated with a wage decrease of 0.22 percent for women and 0.20 percent for men. We then analyze whether returns to social skills are distorted in the care sector, where we hypothesize that the wage returns on workers' performance are lower due to the public-goods aspect of care work. Based on combined CPS and O*Net data, we investigate occupation-level skills returns for 2015-24. They are indeed insignificant for care workers but sizeable for business services workers. |
| Keywords: | returns to skills, care work, future of work, undervaluation of women's work, occupational gender segregation, social skills, new technologies and AI, gender wage gap |
| JEL: | H41 J16 J21 J24 J31 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18291 |
| By: | Ma, Shuang (Guangzhou University); Mu, Ren (Texas A&M University); Xiao, Han |
| Abstract: | Minimum wage increases are often accompanied by firms raising qualification requirements in job postings, but whether this skill upgrading reflects changes in who applies (composition effects) or changes in whom firms select from an unchanged applicant pool (selection effects) remains unclear. Using unique data from a large online job platform in China that links job postings, applications, and job offers, we compare firm hiring practices and applicant pools before versus after province-level minimum wage increases, treated versus control provinces, and minimum-wage versus higher-wage occupations. We find that firms raise educational requirements in postings by 3-4 percentage points and increase job offers to college-educated workers by 30\%, while offers to less-educated workers remain unchanged. At the same time, the application volumes and applicant characteristics remain unchanged. This pattern reveals that the shift in job offers occurs entirely through the selection effect, as the short-run labor supply response is limited even when firms actively attempt to reshape their applicant pools. Minimum wage increases thus redistribute employment opportunities among existing job seekers away from less educated workers. |
| Keywords: | job offers, part-time jobs, job postings, minimum wage, China |
| JEL: | J23 J63 O53 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18290 |
| By: | Collis, Manuela R. (University of Toronto); Van Effenterre, Clémentine (University of Toronto) |
| Abstract: | We investigate how much individuals value a workplace that doesn't tolerate hostility, and how these preferences affect sorting in the labor market. We conduct a choice experiment involving 2, 048 participants recruited from recent graduates and alumni from a large public university. Our results show that individuals are willing to forgo a significant portion of their earnings—between 12 and 36 percent of their wage—to avoid hostile work environments, valuations substantially exceeding those for remote work (7 percent). Women exhibit a stronger aversion to exclusionary workplaces and environments with sexual harassment. Combining survey evidence, experimental variations of workplace environments, and individual labor market outcomes, we show that both disutility from workplace hostility and perceptions of risk contribute to gender gaps in early-career choices and in pay. To quantify equilibrium implications, we develop a model of compensating differentials calibrated to our experimental estimates. Using counterfactual exercises, we find that gender differences in risk of workplace hostility drive both the remote pay penalty and office workers' rents. |
| Keywords: | compensating differentials, workplace hostility, gender |
| JEL: | J16 J24 J31 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18302 |
| By: | Sauermann, Jan (Institute for Evaluation of Labour Market and Education Policy (IFAU), Copenhagen Business School; Institute of Labor Economics (IZA); ROA, Maastricht University; UCLS, Uppsala University.); Butschek, Sebastian (Leopold-Franzens Universität) |
| Abstract: | To estimate the causal effect of employment protection on firms’ worker selection, we study a policy change that reduced dismissal costs for the employers of over a tenth of Sweden’s workforce. Our difference-in-differences analysis of firms’ hiring uses individual ability measures including estimated worker fixed effects, GPA at age 15, and military test scores. We find that the reform reduced minimum hire quality by around 2%. Our results show that firms both decrease their hiring thresholds and hire more workers. We find that firms increasingly hire young, foreign born and long-term non-employed individuals, suggesting potential welfare gains of the reform. |
| Keywords: | worker selection; screening; hiring standard; employment protection; dismissal costs. |
| JEL: | D22 J24 J38 M51 |
| Date: | 2025–11–27 |
| URL: | https://d.repec.org/n?u=RePEc:hhs:ifauwp:2025_022 |
| By: | Francesca Barigozzi; Natalia Montinari; Giovanni Righetto; Alessandro Tampieri |
| Abstract: | This paper revisits the statistical discrimination model of Phelps (1972) to explain why a gender wage gap emerges immediately at labour-market entry, despite women's superior academic performance. We focus on graduates and extend the framework by adding a productivity-relevant attribute - willingness to work abroad or IT skills - that is correlated with gender and differs across fields of study. Employers observe noisy individual signals and coarse group-level statistics by gender and field, and optimally combine them when setting wages. Within this setting, gender differences in the distribution of these attributes can generate an entry wage premium for men even when women have higher average human capital. We test this mechanism using AlmaLaurea microdata on master's graduates from the University of Bologna (2015-2022). We calibrate the model for the full sample and separately for Economics & Management and Engineering. Human capital alone cannot reproduce the observed wage differences, while augmenting the model with willingness to work abroad or IT skills brings predicted and actual gaps into close alignment. Complementary wage regressions show that mobility intentions explain a substantial share of the raw gender wage gap across fields, whereas IT skills matter primarily in Engineering and only marginally in the aggregate. The combined evidence from the model calibration and the empirical analysis supports an extended statistical discrimination channel operating through gendered distributions of mobility and IT-related attributes. |
| JEL: | J16 J31 J71 J24 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:bol:bodewp:wp1217 |
| By: | Goulas, Sofoklis (Yale University); Megalokonomou, Rigissa (Monash University); Sartori, Tommaso (Monash University) |
| Abstract: | Teachers play a central role in shaping how students benefit from peers, yet little is known about how classroom composition affects their attention-allocation decisions. We conduct a large-scale randomized experiment using realistic class- room vignettes to assess how teachers engage with students under varying scenarios and objectives. The presence of a high achiever reduces the likelihood that teachers engage with a low achiever by about 8%, with substantially larger effects when teachers prioritize task success, consistent with convenience-based decision-making. Using administrative data, we show that low achievers perform worse when quasi-randomly assigned to a classroom with an exceptional student. |
| Keywords: | randomized controlled trial, attention allocation, teacher behavior, educational inequality, peer effects |
| JEL: | I21 I28 C93 D91 J24 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18294 |
| By: | Bietenbeck, Jan (Lund University); Collins, Matthew (Lund University); Lundborg, Petter (Lund University); Majlesi, Kaveh (Monash University) |
| Abstract: | We estimate the effects of exposure to income and wealth inequality during adolescence on long-term educational and labor market outcomes. Using detailed Swedish register data covering all students completing compulsory education between 1989 and 2013, we construct measures of inequality among students’ school-cohort peers and exploit variation between cohorts within schools to identify causal effects of inequality exposure. We find no evidence that exposure to inequality affects GPA, high school graduation, university enrollment, university completion, or income up to age 35. These null results are precisely estimated and robust to alternative measures of inequality, sample definitions, and specifications. Moreover, we find no evidence of systematic heterogeneity by socioeconomic background. Taken together, these findings suggest that school integration policies mixing students from different socioeconomic backgrounds do not necessarily carry hidden long-run costs stemming from exposure to inequality. More broadly, they challenge the view that school-based exposure to peer inequality during adolescence is a causal driver of human capital accumulation or later-life mobility. |
| Keywords: | education, causal, school, inequality, labor outcomes |
| JEL: | D31 J24 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18289 |
| By: | Emiliano Tealde (Universidad Católica del Uruguay) |
| Abstract: | This work studies how drug trade-related violence affects individuals’ employment prospects. Using an experimental design, I find that candidates residing in areas associated with drug trade-related violence face significant labor market discrimination. Willingness to hire decreases a 16 % in candidates from a ”narco” neighborhood. Education acts as a mitigating factor, and candidates from a narco neighborhood who finish secondary school do not face discrimination. The results are not driven by employers’ perceptions of the candidates’ quality. I find that discrimination is higher among more experienced employers and that employers who are more concerned about public safety are not more likely to discriminate, which does not support statistical discrimination as the mechanism driving the effect. |
| Keywords: | Discrimination, Drug Trafficking, Violence |
| JEL: | D74 J23 J71 K42 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:col:000089:021811 |
| By: | Hansen, Kristian S. (National Research Centre for the Working Environment (NFA), Copenhagen, Denmark); Moreno-Ternero, Juan D. (Department of Economics, Universidad Pablo de Olavide); Østerdal, Lars Peter (Department of Economics, Copenhagen Business School) |
| Abstract: | This paper develops a unified framework for evaluating health outcomes that jointly incorporates equity and productivity. Extending beyond traditional QALYs, PALYs, and the more recent PQALYs, we introduce a class of evaluation functions that integrate fairness- and productivity-sensitive principles. By imposing normative principles, includ-ing independence from measurement scales and Pigou-Dalton transfer properties, we ob-tain tractable power-form representations. In balancing distributive justice and efficiency, the framework provides a coherent foundation for assessing health interventions in con-texts where both equity and productive capacity are at stake. |
| Keywords: | Health; Productivity; Equity; Distribution; QALYs; PALYs; PQALYs |
| JEL: | D63 I10 J24 |
| Date: | 2025–10–07 |
| URL: | https://d.repec.org/n?u=RePEc:hhs:cbsnow:2025_009 |
| By: | Burga, Carlos; Cespedes, Jacelly; Parra, Carlos R; Ricca, Bernardo |
| Abstract: | A long-standing debate concerns whether technological change widens wage gaps by benefiting skilled labor. We show that financial technologiesspecifically, instant payment systemscan instead reduce wage inequality. Using an administrative dataset covering all registered employees in Brazil, we study the nationwide rollout of Pix, an instant payment platform introduced in late 2020. Our empirical strategy is a triple difference-in-differences design that exploits variation in preexisting mobile penetration across municipalities, the differential benefits of Pix for cash-intensive versus non-cash-intensive sectors, and the timing of Pixs rollout. A one standard deviation increase in mobile penetration leads to a 1.2 percent wage increase in cash-intensive sectors relative to non-cash-intensive sectors following Pixs introduction. These wage gains are concentrated among workers with less education, reducing the college wage premium by 1 percentage point. Further evidence suggests that increased small-business labor demand, amplified by local labor market frictions, drives these effects. Overall, instant payment systems disproportionately benefit small, cash-intensive businesses, enhancing labor demand in sectors reliant on low-skill workers and highlighting how financial technologies can shape distributional outcomes differently from skill-biased technologies. |
| JEL: | J31 O33 G23 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:idb:brikps:14416 |
| By: | Matias Ciaschi (CEDLAS-IIE-FCE-UNLP and CONICET); Guillermo Falcone (CEDLAS-IIE-FCE-UNLP and CONICET); Santiago Garganta (CEDLAS-IIE-FCE-UNLP); Leonardo Gasparini (CEDLAS-IIE-FCE-UNLP and CONICET); Octavio Bertín (CEDLAS-IIE-FCE-UNLP); Lucía Ramirez-Leira (CEDLAS-IIE-FCE-UNLP) |
| Abstract: | This paper investigates the potential distributional consequences of artificial intelligence (AI) adoption in Latin American labor markets. Using harmonized household survey data from 14 countries, we combine four recently developed AI occupational exposure indices—the AI Occupational Exposure Index (AIOE), the ComplementarityAdjusted AIOE (C-AIOE), the Generative AI Exposure Index (GBB), and the AIGenerated Occupational Exposure Index (GENOE)—to analyze patterns across countries and worker groups. We validate these measures by comparing task profiles between Latin America and high-income economies using PIAAC data, and develop a contextual adjustment that incorporates informality, wage structures, and union coverage. Finally, we simulate first-order impacts of AI-induced displacement on earnings, poverty, and inequality. The results show substantial heterogeneity, with higher levels of AI-related risk among women, younger, more educated, and formal workers. Indices that account for task complementarities show flatter gradients across the income and education distribution. Simulations suggest that displacement effects may lead to only moderate increases in inequality and poverty in the absence of mitigating policies. |
| JEL: | O33 J21 D31 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:dls:wpaper:0361 |
| By: | Lukas B. Freund |
| Abstract: | Production increasingly requires specialized expertise. To study the macroeconomic implications, I develop a tractable theory in which firms assemble teams of workers with heterogeneous task-specific skills. Deriving the firm’s production function from optimal task assignment shows that output is maximized when coworkers excel at different tasks yet possess similar overall talent. Crucially, greater skill specificity, while raising potential productivity, endogenously amplifies talent complementarities, i.e., the productivity loss from talent mismatch. This promotes talent concentration into select firms with “superstar teams, ” though search frictions prevent perfect sorting. Using German panel micro data, I document industry patterns consistent with this mechanism and calibrate the model. The quantified model shows that, first, growing skill specificity since the mid-1980s has amplified sorting, explaining a significant share of the widely documented “firming up of inequality”. Second, “Smithian” productivity gains from specialization are muted when labor market frictions impede the matching of coworkers with complementary expertise. |
| Keywords: | firms, inequality, productivity, specialization, teams |
| JEL: | D21 D24 E24 J31 J64 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12303 |
| By: | Giovanni Marin (Dipartimento di Economia, Società, Politica, Università di Urbino Carlo Bo, SEEDS, and Fondazione Eni Enrico Mattei) |
| Abstract: | This study examines how extreme heat affects workplace accidents in Italy’s various economic sectors. Using granular data by sector, day, and province (NUTS-3) for 2018–2024, we evaluate the contribution of occupational exposure as a source of diverse effects at the sector level. Our findings imply that while the average effects of extreme heat on workplace accidents are, at best, negligible, high temperatures significantly raise the frequency of medium-to-low severity accidents for sectors with high levels of exposure, while exposure and extreme heat alone do not account for fatalities. |
| Keywords: | workplace accidents, heterogeneous effect, fixed-effect regression, vulnerability, extreme temperature |
| JEL: | Q54 I18 J28 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:fem:femwpa:2025.28 |
| By: | Sidharth Rony; Jack Patman |
| Abstract: | Standard Occupational Classifiers (SOC) are systems used to categorize and classify different types of jobs and occupations based on their similarities in terms of job duties, skills, and qualifications. Integrating these facets with Big Data from job advertisement offers the prospect to investigate labour demand that is specific to various occupations. This project investigates the use of recent developments in natural language processing to construct a classifier capable of assigning an occupation code to a given job advertisement. We develop various classifiers for both UK ONS SOC and US O*NET SOC, using different Language Models. We find that an ensemble model, which combines Google BERT and a Neural Network classifier while considering job title, description, and skills, achieved the highest prediction accuracy. Specifically, the ensemble model exhibited a classification accuracy of up to 61% for the lower (or fourth) tier of SOC, and 72% for the third tier of SOC. This model could provide up to date, accurate information on the evolution of the labour market using job advertisements. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2511.23057 |
| By: | Jaime Alonso-Carrera (Universidade de Vigo); María Jesús Freire-Serén (Universidade de Vigo); Xavier Raurich (Universitat de Barcelona) |
| Abstract: | We measure sectoral price markups, elasticities of substitution between capital and labor, and rates of factor-augmenting technical change in the United States from 1947 to 2010. Our approach utilizes the user cost of capital to decompose firms' operating surplus into capital payments and profits, enabling a direct computation of sectoral price markups. The results reveal that these markups are time-varying and exhibit a positive trend since 1980 in both manufacturing and services, mirroring the observed behavior of markups in the aggregate economy. Additionally, we estimate the elasticities of substitution and the rates of technical progress for each sector. We find that the estimated values of these technological parameters vary significantly depending on the assumption regarding the market structure of sectoral goods: perfect or imperfect competition. |
| Keywords: | Price markups, sectoral productivity, elasticity of substitution, factor-augmenting technical change |
| JEL: | O11 O41 O47 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ewp:wpaper:483web |
| By: | McGuinness, Seamus; Staffa, Elisa; Flynn, Eimear; Redmond, Paul |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:esr:wpaper:wp809 |
| By: | Luca J. Uberti; Drini Imami; Mariapia Mendola |
| Abstract: | We examine the impact of an election campaign on the labor market outcomes of incumbent party supporters. Using unique data on voters' political preferences during a critical pre-election period in Albania, our difference-in-differences estimates show that supporting the ruling party prior to elections significantly improves individuals' employment and earnings. This labor market premium is particularly pronounced among individuals with low costs of campaign participation, whereas patronage jobs are concentrated in lower-tier public sector positions. Administrative data further show that job distribution to party supporters strongly correlates with increased vote shares for the incumbent. Our findings suggest that parties strategically allocate public employment to mobilize grassroots supporters and secure votes—a practice that fosters corruption and weakens democratic institutions. |
| Keywords: | Job patronage; political corruption; vote-buying; Albania; post-communist transition. |
| JEL: | D72 D73 H83 J45 M59 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:mib:wpaper:561 |
| By: | Federico Zilia (Department of Environmental Science and Policies, University of Milan); Paolo Nota (Department of Environmental Science and Policies, University of Milan); Alessandro Olper (Department of Environmental Science and Policies, University of Milan) |
| Abstract: | This paper examines how weather variability influences inter-sectoral labour reallocation and sectoral value-added (GVA) growth across 238 European regional units (NUTS2 level) from 1980 to 2022. Leveraging this large and granular dataset, we employ flexible functional forms within a fixed-effects panel framework, where the impact of weather shocks is conditional on long-term climate. Unlike previous empirical research in climate economics, which primarily focused on inter-annual variations in average temperature, this study emphasizes the significant role of daily temperature variability. Temperature variability is particularly critical in warmer regions with low seasonal variability, which are more vulnerable to sudden temperature shifts or rainfall shocks. In hot and low seasonal variability regions – i.e. Mediterranean ones – we find a robust adaptive response of the labour market where workers move from climate-sensitive agriculture to less affected service sector. The heterogeneous effects of weather shocks on sectoral value-added growth appear to be a possible mechanism driving this labour reallocation, although more complex factors may also be at play. |
| Keywords: | climate change, labour reallocation, day-to-day temperature variability, panel econometrics, European NUTS2 |
| JEL: | O13 Q51 Q54 J43 J31 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:fem:femwpa:2025.30 |
| By: | Jeannie Annan (International Rescue Committee); Estelle Koussoubé (World Bank); Joséphine Tassy (World Bank); Léa Rouanet (World Bank); Clara Delavallade (World Bank); David K. Evans (Center for Global Development) |
| Abstract: | Despite evidence of positive returns, many youth training programs in Sub-Saharan Africa have low take-up. Behavioral interventions, or nudges, have been proposed as low-cost tools to influence such decisions. This study reports on a randomized experiment in Côte d’Ivoire testing a behavioral nudge—varying the content and recipient of text message reminders—to increase enrollment in a youth employment program. We compare two framings—highlighting the free cost of the program versus the long-term career benefits—sent either to youth alone or to both youth and their nominated social contacts. Messages sent to youth alone have no impact. In contrast, targeting both youth and contacts significantly affects enrollment, with gendered effects: among young men, both messages reduce enrollment, while among young women, enrollment decreases when the message highlights free cost. These impacts are driven by youth with male contacts. Qualitative data suggest that trust and perceived program quality shape responsiveness, particularly among those unfamiliar with the program. The findings underscore how message framing and social context influence program take-up, and how misaligned messaging can discourage participation. |
| Keywords: | O15, J16, J24, D83 |
| Date: | 2025–12–05 |
| URL: | https://d.repec.org/n?u=RePEc:cgd:wpaper:737 |