nep-hrm New Economics Papers
on Human Capital and Human Resource Management
Issue of 2024‒03‒04
eight papers chosen by
Patrick Kampkötter, Eberhard Karls Universität Tübingen


  1. Low-Wage Jobs, Foreign-Born Workers, and Firm Performance By Catalina Amuedo-Dorantes; Esther Arenas-Arroyo; Parag Mahajan; Bernhard Schmidpeter
  2. Robot adoption, worker-firm sorting and wage inequality: evidence from administrative panel data By Faia, Ester; Ottaviano, Gianmarco Ireo Paolo; Spinella, Saverio
  3. Incentives, Framing, and Reliance on Algorithmic Advice: An Experimental Study By Greiner, Ben; Grünwald, Philipp; Lindner, Thomas; Lintner, Georg; Wiernsperger, Martin
  4. Decreasing Differences in Expert Advice By Elias Bouacida; Renaud Foucart; Maya Jalloul
  5. Technological change and returns to training By Klauser, Roman; Tamm, Marcus
  6. Household Decisions and the Gender Gap in Job Satisfaction By Bredemeier, Christian; Ndlovu, Patrick; Vujic, Suncica; Winkler, Roland
  7. Deadlines Versus Continuous Incentives: Evidence from the Patent Office By Michael D. Frakes; Melissa F. Wasserman
  8. Do role models matter in large classes? New evidence on gender match effects in higher education By Maurer, Stephan Ernst; Schwerdt, Guido; Wiederhold, Simon

  1. By: Catalina Amuedo-Dorantes; Esther Arenas-Arroyo; Parag Mahajan; Bernhard Schmidpeter
    Abstract: We examine how migrant workers impact firm performance using administrative data from the United States. Exploiting an unexpected change in firms’ likelihood of securing low-wage workers through the H-2B visa program, we find limited crowd-out of other forms of employment and no impact on average pay at the firm. Yet, access to H-2B workers raises firms’ annual revenues and survival likelihood. Our results are consistent with the notion that guest worker programs can help address labor shortages without inflicting large losses on incumbent workers.
    Keywords: guest workers, migrants, employment, firm dynamics, H-2B visa
    JEL: J23 F22 J61
    Date: 2024–01
    URL: http://d.repec.org/n?u=RePEc:cen:wpaper:24-05&r=hrm
  2. By: Faia, Ester; Ottaviano, Gianmarco Ireo Paolo; Spinella, Saverio
    Abstract: Leveraging the geographic dimension of a large administrative panel on employer-employee contracts, we study the impact of robot adoption on wage inequality through changes in worker-firm assortativity. Using recently developed methods to correctly and robustly estimate worker and firm unobserved characteristics, we find that robot adoption increases wage inequality by fostering both horizontal and vertical task specialization across firms. In local economies where robot penetration has been more pronounced, workers performing similar tasks have disproportionately clustered in the same firms ('segregation'). Moreover, such clustering has been characterized by the concentration of higher earners performing more complex tasks in firms paying higher wages ('sorting'). These firms are more productive and poach more aggressively. We rationalize these findings through a simple extension of a well-established class of models with two-sided heterogeneity, on-the-job search, rent sharing and employee Bertrand poaching, where we allow robot adoption to strengthen the complementarities between firm and worker characteristics.
    Keywords: robot adoption; worker-firm sorting; wage inequality; technological change; finite mixture models; European Union’s Horizon 2020 research and innovation programme (grant agreement n 789049-MIMAT-ERC2017-ADG)
    JEL: J22 J23 J31 J62 E21 D31
    Date: 2023–02–10
    URL: http://d.repec.org/n?u=RePEc:ehl:lserod:121328&r=hrm
  3. By: Greiner, Ben; Grünwald, Philipp; Lindner, Thomas; Lintner, Georg; Wiernsperger, Martin
    Abstract: Managerial decision-makers are increasingly supported by advanced data analytics and other AI-based technologies, but are often found to be hesitant to follow the algorithmic advice. We examine how compensation contract design and framing of an AI algorithm influence decision-makers’ reliance on algorithmic advice and performance in a price estimation task. Based on a large sample of almost 1, 500 participants, we find that compared to a fixed compensation, both compensation contracts based on individual performance and tournament contracts lead to an increase in effort duration and to more reliance on algorithmic advice. We further find that using an AI algorithm that is framed as incorporating also human expertise has positive effects on advice utilization, especially for decision-makers with fixed pay contracts. By showing how widely used control practices such as incentives and task framing influence the interaction of human decision-makers with AI algorithms, our findings have direct implications for managerial practice.
    Keywords: artificial intelligence; algorithmic advice; human-augmented algorithmic advice; trust; financial incentives; decision-making
    Date: 2024–01–31
    URL: http://d.repec.org/n?u=RePEc:wiw:wus055:60237853&r=hrm
  4. By: Elias Bouacida; Renaud Foucart; Maya Jalloul
    Abstract: We study the impact of external advice on the relative performance of chess players. We asked players in chess tournaments to evaluate positions in past games and allowed them to revise their evaluation following advice from a high or a low ability player. While our data confirms the theoretical prediction that high-quality advice has the potential to act as a “great equalizer, †reducing the difference between high and low ability players, this is not what happens in practice. This is in part because our subjects ignore too much of the advice they receive, but also because low ability players pay – either due to overconfidence or intrinsic preference – a higher premium than high ability ones by following their initial idea instead of high-quality advice.
    Keywords: decreasing differences, expert, advice, chess, control
    JEL: C78 C91 C93 D91 J24 O33
    Date: 2024
    URL: http://d.repec.org/n?u=RePEc:lan:wpaper:408394204&r=hrm
  5. By: Klauser, Roman; Tamm, Marcus
    Abstract: Do returns to training differ if training is accompanied by technological innovations at the workplace? We analyze this potential heterogeneity of returns based on panel data from Germany that provide a unique measure for individuals' adoption of new technology at the workplace. In the preferred analysis we run fixed effects estimations. As a robustness test we also allow for individual time trends. The findings indicate positive wage effects and more job stability for training participants in general but no effects on wages and job mobility for new technology adoption. Furthermore, the combined occurrence of new technology adoption and of training participation does not make individuals better off in terms of wages or job stability compared with individuals experiencing neither training nor new technology adoption.
    Abstract: Unterscheiden sich Weiterbildungserträge, wenn Weiterbildung von technologischen Innovationen am Arbeitsplatz begleitet wird? Wir analysieren die potenzielle Heterogenität der Erträge anhand von Paneldaten aus Deutschland, die ein einzigartiges, individuelles Maß für die Adoption neuer Technologien am Arbeitsplatz bieten. In unserer Hauptanalyse verwenden wir sogenannte Fixed-Effects-Regressionen, die in Robustheitstests durch individuelle "time trends" ergänzt werden. Die Ergebnisse zeigen positive Lohneffekte und eine größere Arbeitsplatzstabilität für Personen, die an Weiterbildungsmaßnahmen teilgenommen haben, aber keine dieser Effekte für Personen, die über eine neue Technologien am Arbeitsplatz berichten. Darüber hinaus führt das gemeinsame Auftreten von neuen Technologien und Weiterbildungsteilnahme nicht dazu, dass Personen in Bezug auf Löhne oder Arbeitsplatzstabilität besser abschneiden als Personen, die weder Weiterbildung noch die Einführung neuer Technologien erfahren.
    Keywords: Returns to education, training, technology
    JEL: I26 J24 J62 M53 O33
    Date: 2023
    URL: http://d.repec.org/n?u=RePEc:zbw:rwirep:282011&r=hrm
  6. By: Bredemeier, Christian (University of Wuppertal); Ndlovu, Patrick (University of Antwerp); Vujic, Suncica (University of Antwerp); Winkler, Roland (University of Jena)
    Abstract: This paper offers a novel theoretical explanation for the gender gap in job satisfaction, where women typically report higher job satisfaction than men. We argue that rational family decisions can result in divergent job choices for women and men, leading to increased job satisfaction but lower earnings for women, even when their preferences and expectations align with those of men. We develop this explanation within a theoretical model of collective household decision-making that considers relative earnings disparities within households. We provide empirical evidence supporting our model's predictions utilizing survey and administrative data from Canada.
    Keywords: job satisfaction, gender gap, households
    JEL: D13 J28 J16
    Date: 2024–01
    URL: http://d.repec.org/n?u=RePEc:iza:izadps:dp16760&r=hrm
  7. By: Michael D. Frakes; Melissa F. Wasserman
    Abstract: A quota system with an associated deadline may retain the possibility of worker procrastination and related deadline behaviors. A performance appraisal system based on continuous temporal incentives, on the other hand, has the potential to alleviate deadline effects but may lose some of the quality-related benefits associated with the flexibility of a quota/deadline system. We explore these tradeoffs by observing patent examiner behavior and examination quality outcomes surrounding a 2011 reform at the U.S. Patent and Trademark Office that built on its bi-weekly quota system by adding a set of bonuses tied to daily examination-pendency measures. We find a substantial reduction in deadline effects and near complete temporal smoothing in examiner behavior in connection with the reform, leading to large reductions in average examination pendency while resulting in no corresponding reductions in the accuracy of examinations.
    JEL: D03 J33 K0 O34
    Date: 2024–01
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:32066&r=hrm
  8. By: Maurer, Stephan Ernst; Schwerdt, Guido; Wiederhold, Simon
    Abstract: We study whether female students benefit from being taught by female professors, and whether such gender match effects differ by class size. We use administrative records of a German public university, covering all programs and courses between 2006 and 2018. We find that gender match effects on student performance are sizable in smaller classes, but do not exist in larger classes. This difference suggests that direct and frequent interactions between students and professors are important for the emergence of gender match effects. Instead, the mere fact that one's professor is female is not sufficient to increase performance of female students.
    Keywords: gender gap; role models; tertiary education; professors
    JEL: I21 I23 I20 J16
    Date: 2023–01–09
    URL: http://d.repec.org/n?u=RePEc:ehl:lserod:121336&r=hrm

This nep-hrm issue is ©2024 by Patrick Kampkötter. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at https://nep.repec.org. For comments please write to the director of NEP, Marco Novarese at <director@nep.repec.org>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.