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on Human Capital and Human Resource Management |
| By: | Michael Amior; Shmuel San |
| Abstract: | Firms face significant constraints in their ability to differentiate pay by worker productivity. We show how these internal equity constraints generate a quantity-quality trade-off in hiring: firms which offer higher wages attract higher skilled workers, but cannot profitably employ lower skilled workers. In equilibrium, this results in workplace segregation and pay dispersion even among ex-ante identical firms. Our framework provides a novel interpretation of the (empirically successful) log additive AKM wage model, and shows how log additivity can be reconciled with sorting of high-skilled workers to high-paying firms. It can also rationalize a hump-shaped relationship between firm size and firm pay, and provides new insights into aggregate-level, regional and sectoral variation in earnings inequality - which we explore using Israeli administrative data. |
| Keywords: | wages, productivity, labour, labor, skills |
| Date: | 2026–03–16 |
| URL: | https://d.repec.org/n?u=RePEc:cep:cepdps:dp2161 |
| By: | Balázs Reizer (ELTE Centre for Economic and Regional Studies; Corvinus University Budapest) |
| Abstract: | I investigate the relationship between bonus payments and firm performance using Hungarian linked employer-employee data. A raw comparison shows that firms paying bonuses to 10 percentage points more of their employees are 3-5 percent more productive. Then, I construct an instrument to estimate the incentive effect of bonus payments. The IV estimates show that the incentive effect of a 10 percentage point increase in the share of employees with bonus payments increases firm productivity by 7-14 percent. Based on these results, I conclude that the raw comparison of firms with and without bonuses underestimates the incentive effects of bonus payments. Furthermore, some firms may have motivations for paying bonuses other than incentivizing employees. |
| Keywords: | Risk Management, Wage Structure, Personnel Economics |
| JEL: | G32 M5 J31 J23 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:has:discpr:2516 |
| By: | Simon Cordes; Max Müller |
| Abstract: | Labor supply depends on wages and amenities, and standard models implicitly assume that firms hold accurate beliefs about workers’ amenity valuations. In a survey with firms and workers in Germany, we measure workers’ valuations of amenities and firms’ beliefs about workers’ valuations. We find that firms systematically underestimate workers’ valuations of all amenities. These misperceptions are driven by interpersonal projection: managers project their own preferences—they value amenities less—onto workers. Through the lens of a simple model of imperfect competition, we show that firm misperceptions result in (i) labor shortages and (ii) excess labor costs for biased firms, and increase the market power of unbiased firms. Empirical tests confirm these predictions: a simple calibration suggests that non-providing firms could reduce their labor costs by 5% by providing amenities. |
| Keywords: | Amenities, Behavioral Firms, Labor Shortages, Work from Home, Beliefs |
| JEL: | J32 J42 J81 D2 D83 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2025_739 |
| By: | Mallory Avery (Department of Economics, Monash University); Edwin Ip (Department of Economics, University of Exeter); Andreas Leibbrandt (Department of Economics, Monash University); Joseph Vecci (Department of Economics, University of Gothenburg) |
| Abstract: | Recent technological advancements are reshaping pathways to employment by automating the interview process. Asynchronous interviews, in which job applicants submit answers to interview questions via an online platform without interacting with an interviewer, are replacing more traditional face-to-face job interviews. At the same time, AI algorithms are now widely used to assess these interview answers. In this paper, we use a field experiment to comprehensively study how these new technologies affect applicants and employers in the recruitment process. Over 3, 000 job applicants are randomized into asynchronous audio or video interviews, live online interviews, and a control group. Their job interviews are then assessed by both professional recruiters and a commercial AI recruitment tool used by most Fortune 100 companies. We find that asynchronous interviews cause an over 50% decrease in application continuation, including among the most qualified applicants, and that this decline is largest for women. A complementary vignette experiment provides evidence that this deterrence is driven by perceptions about the competitiveness and fairness of the recruitment process. In terms of assessments, we find that the AI evaluation tool scores women and underrepresented racial minorities higher than human evaluators, while the opposite is true for men, Whites and Asians. We track our applicants' subsequent labor market outcomes and find that the AI assessment tool predicts subsequent employment success substantially better than human recruiters, suggesting that AI captures soft skills and potential that humans overlook. In addition, we provide evidence that, unlike AI, human recruiters' assessments suffer from multiple cognitive biases. Our findings provide some of the first key evidence on how recent technological advances are transforming the hiring process. |
| Keywords: | technological change, artificial intelligence, gender, field experiment |
| JEL: | C93 J23 J71 J78 |
| Date: | 2026–03–25 |
| URL: | https://d.repec.org/n?u=RePEc:exe:wpaper:2602 |
| By: | Rocco Macchiavello; Andreas Menzel; Atonu Rabbani; Christopher Woodruff |
| Abstract: | Women remain disadvantaged in promotion to managerial positions. We conduct a field experiment with 24 large garment factories in Bangladesh to test for inefficient representation of women among line supervisors. We identify the marginal female and male candidates for supervisory positions and randomly assign them to manage production lines. We document four findings: (1) In contrast to widespread negative beliefs about women’s ability as supervisors at baseline, female candidates selected by the factories had similar skills to males; (2) during the trial, females performed worse than males, which we show is related to negative bias against them; (3) after the trial, however, many female candidates were retained as supervisors and, conditional on that, performed similarly to males; and (4) after the end of our intervention, factories permanently increased the share of women among newly appointed supervisors. A conceptual framework of experimentation over discrimination rationalizes all these facts and cautions against the standard logic to test for discrimination: when there is uncertainty about the performance of the discriminated group, equal – or even worse – performance of the marginal candidates of that group is no longer sufficient to rule out inefficient discrimination. |
| Keywords: | Gender Discrimination, Productivity, Export Manufacturing |
| JEL: | J16 J71 M51 M54 O14 O15 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:csa:wpaper:2026-04 |
| By: | Chirowodza, Joe |
| Abstract: | This paper examines gendered mobility patterns for early career workers, focusing on family motivated job changes. Using the Swiss Household Panel data (1999-2023) we use multinomial logit, fixed effects, and event study models to understand the impact of family related job mobility on early career workers. The paper shows that compared to men; women are more likely to cite family reasons for job change. Women who change jobs for family reasons face wage stagnation although they earn improvements in specific satisfaction dimensions whilst overall job satisfaction is lower as compared to career motivated job mobility. We also find that job mobility rates for mothers remain constant around childbirth and among mothers who change jobs, family considerations emerge reactively post birth. The results have policy implications for early career job mobility which include subsiding childcare, standardizing flexibility at work and increasing paternity leave periods. |
| Keywords: | Job mobility, Early career, family motivated mobility, gendered mobility patterns, job satisfaction |
| JEL: | J13 J24 J62 |
| Date: | 2026–01–21 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:127809 |
| By: | Salomé Baslandze; Zachary Edwards; John Graham; Ty McClure; Brent H. Meyer; Michael Sparks; Sonya R. Waddell; Daniel Weitz |
| Abstract: | We use novel data from a survey of nearly 750 corporate executives to study the effects of artificial intelligence (AI) on productivity and the workforce. We document substantial heterogeneity in AI adoption across firms, with more than half having already invested, though many smaller firms are only beginning to do so. Labor productivity gains are positive, vary across sectors, and are expected to strengthen in 2026, with the largest effects concentrated in high-skill services and finance. These gains are not primarily driven by firms' capital deepening but instead reflect increases in revenue-based total factor productivity, closely associated with innovation-and demand-oriented channels. We document a productivity paradox, in which perceived productivity gains are larger than measured productivity gains, likely reflecting a delay in revenue realizations. In labor markets, we find little evidence of near-term aggregate employment declines due to AI, though larger companies anticipate AI-driven workforce reductions, while smaller firms expect modest gains. We also find evidence of compositional reallocation of labor both within and across firms, with routine clerical roles declining and a relative demand for skilled technical roles increasing. We develop an index that ranks job functions most negatively affected by AI. |
| JEL: | D22 D24 G0 J01 J24 M15 O33 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34984 |
| By: | Davide Antonioli; Elisa Chioatto; Giovanni Guidetti; Riccardo Leoncini; Mariele Macaluso |
| Abstract: | This paper analyses how firms' skill development strategies affect their propensity to introduce innovation. We develop an adjustment-cost framework that links human capital theory and institutionalist and evolutionary approaches, considering innovation as an activity that entails costs in labour adjustment arising either from the training activities of workers or the recruitment of skilled employees. Using a two-wave panel of Italian manufacturing firms observed in 2017-2018 and 2019-2020, we analyse firms' adoption of total, product, process, and circular innovation as a function of internal training practices and of external skills acquisition. Overall, the empirical analysis confirms the expected positive relationship between training and innovation, while also revealing important nuances in the workforce upskilling strategies required for different types of innovation. Moreover, while training activities and skills development are essential across all forms of innovation, our findings indicate that internal training is particularly effective in supporting the implementation of circular innovations. By contrast, external recruitment appears to be consistently necessary whenever innovations are introduced, regardless of their type. |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2603.05153 |