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on Human Capital and Human Resource Management |
| By: | Alam, Afroza; Diegmann, André |
| Abstract: | This paper provides new causal evidence on how patent allowances affect firms and their employees based on quasi-random assignment of patent applications to examiners. Exploiting employer-employee records with newly linked German firm data and web-scraped patent documents, we show that patent-induced shocks reduce firm exit, improve productivity, and increase wages, with rent-sharing elasticities between 0.10 and 0.21. Wage gains are broadly observed across occupational tasks, with high heterogeneity: managers benefit disproportionately in publicly traded firms, whereas broader wage increases accrue to workers in non-traded firms. Our findings highlight the role of institutional features and firm organization in shaping how rents are shared. |
| Keywords: | firm performance, innovation, rent sharing, worker compensation |
| JEL: | D22 J31 O31 O34 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:iwhdps:341391 |
| By: | Abel, Martin (Bowdoin College); Dawi, Raghad (Bowdoin College); Lenk, Tyler (Bowdoin College); Singer, Aidan (Bowdoin College) |
| Abstract: | How do workers respond when artificial intelligence replaces human judgment in evaluating prosocial work? Partnering with a non-profit addressing food insecurity, we recruit 1, 491 U.S. volunteers to write fundraising messages and cross-randomize evaluation by humans versus AI and the presence of performance pay. AI evaluation reduces effort by 11–14 percent among volunteers with low commitment to the cause, while having no effect on those strongly aligned with the mission. Performance pay fails to mitigate these adverse effects. Workers perceive AI as less effective at identifying quality, which appears to be the primary mechanism, and as less fair and transparent than human evaluation. Introducing an AI algorithm that explicitly applies human evaluation criteria does not mitigate these negative effects, suggesting that resistance to AI evaluation reflects deeper skepticism about machines' capacity for subjective judgment. |
| Keywords: | algorithm aversion, algorithmic management, artificial intelligence, intrinsic motivation, worker effort |
| JEL: | J24 M54 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18678 |
| By: | Samantha Horn; Peter Schwardmann; Egon Tripodi |
| Abstract: | Evaluative social interactions are pervasive in labor markets. Inequality in these settings can arise not only from how individuals are treated or perform when evaluated, but from whether they enter evaluation at all. We study these margins in the context of social anxiety. In a controlled online experiment (N = 922), applicants decide whether to complete a live video interview that determines a monetary hiring bonus. We find that inequities associated with social anxiety are concentrated in participation rather than in performance or treatment. Socially anxious applicants are substantially less willing to interview, hold more pessimistic beliefs about being hired, and correctly anticipate a worse experience. Yet they perform no worse and are evaluated no differently. Interview experience does not attenuate the relative pessimism of socially anxious individuals, a pattern that is inconsistent with Bayesian updating under comparable signals. We use our rich audio-visual data and open-ended reflection texts to show that, instead, socially anxious applicants interpret similar interactions more negatively. We then provide evidence on organizational interventions aimed at closing social anxiety gaps. Finally, we show that social anxiety explains a meaningful share of inequalities commonly attributed to gender and social skill differences and is associated with significant earnings gaps in national data. |
| Keywords: | social anxiety, job interviews, beliefs, mental health, discrimination, learning |
| JEL: | D83 J71 I10 C90 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12722 |
| By: | Yoko Okuyama; Takeshi Murooka; Shintaro Yamaguchi |
| Abstract: | We estimate the child penalty using detailed personnel records that allow decomposition into distinct pay components. The penalty initially arises from reductions in time-based pay after childbirth. Over time, job-rank-based pay becomes increasingly significant. These effects are interconnected: reduced working hours lead to lower performance evaluations, which subsequently limit promotion opportunities. Our model demonstrates that current promotion practices, which reward extended hours at entry-level positions, can generate production inefficiency. This finding suggests that addressing promotion practices could simultaneously reduce gender inequality and improve talent allocation, making a business case for organizational reform. |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:dpr:wpaper:1314 |
| By: | Hattori, Keisuke |
| Abstract: | Does diversity in ability and in mutual concern help or hurt team performance? We study a team in which efforts may be complements or substitutes. Holding mean ability and mean relational orientation fixed, we vary the dispersion of each. In horizontal teams, where no one leads, ability diversity raises performance through specialization regardless of the task, whereas diversity in relational orientation lowers it under complementarity and raises it under substitutability—so complementary tasks call for diverse hands but aligned hearts. Holding both attribute gaps fixed, performance is strictly higher when the abler member has the higher relational orientation, and the fully homogeneous team is a saddle point. In vertical teams, where one leads and the other follows, under weak interaction ability diversity remains beneficial regardless of who leads, while the optimal placement of the more prosocial member flips with the task—she should follow when efforts are complements and lead when they are substitutes. Taken together, the results show that the two dimensions of diversity interact and must be designed jointly rather than separately. Measuring relational orientation therefore pays off in both team composition and role assignment. |
| Keywords: | team production, ability diversity, social preferences, complementarity, assortative matching, leadership |
| JEL: | D23 J24 M54 D91 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:esprep:341465 |
| By: | Lindenlaub, Ilse; Oh, Ryungha; Rodriguez, Maria Alejandra; Veldkamp, Laura |
| Abstract: | We document and explain the gap between measures of AI exposure and measures of AI adoption in the workplace. This leads us to propose a new AI adoption index based on comparative advantage. Using the representative German DiWaBe employee survey linked to worker and establishment information, we compare worker-reported AI use to prominent exposure measures and find that the relationship is weak. Motivated by this gap, we develop a framework in which adoption depends not only on technical feasibility—AI’s absolute advantage measured by exposure—but also on profitability—AI’s comparative (dis)advantage relative to a specific worker—balancing AI productivity against AI user costs and worker productivity against wages. We operationalize this framework at the task level by (i) estimating worker productivity relative to pay, (ii) mapping exposure indices into AI productivity, and (iii) inferring task-specific AI user costs from revealed-preference adoption. The resulting occupation-level index accounts for 60% of the cross-occupation variation in observed AI adoption, compared with 14% for an exposure-only model. The two approaches diverge substantially for approximately 30% of workers, highlighting that comparative advantage—not exposure alone—is crucial for assessing AI’s labor-market impact. |
| Keywords: | Artificial intelligence; Comparative advantage; Technology diffusion; Worker productivity |
| JEL: | E24 D24 J24 O33 |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:21589 |
| By: | Aksoy, Cevat Giray; Bloom, Nicholas; Davis, Steven; Marino, Victoria; Özgüzel, Cem |
| Abstract: | Remote work has expanded rapidly, but the value of regular in-person contact remains unclear. We report a randomized controlled trial with a large business-process-outsourcing provider serving a multinational telecommunications client, in which 248 customer-service employees were assigned either to remain fully remote or to work from the office together one day per month. Monthly office days gradually increased productivity, with treated employees handling 7.8% more calls per hour in the post-intervention period. Office days also strengthened workplace communication: treated employees spent 36 additional minutes communicating with colleagues in the week after an office visit, were more likely to report receiving manager feedback, and employee pairs randomly assigned as desk neighbors were 11 percentage points more likely to communicate afterward. In addition, monthly office days reduced attrition by a third. The resulting gains in productivity and retention generated a benefit–cost ratio of about 5:1. These findings show that even limited but coordinated in-person contact can improve communication, performance, and retention in remote teams. |
| Keywords: | Remote work; Productivity; Workplace interactions |
| JEL: | M54 D23 |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:21597 |