nep-hrm New Economics Papers
on Human Capital and Human Resource Management
Issue of 2026–08–31
five papers chosen by
Patrick Kampkötter, Eberhard Karls Universität Tübingen


  1. Voice AI in Firms: A Natural Field Experiment on Automated Job Interviews By Brian Jabarian; Luca Henkel
  2. Female-Targeted Hiring Subsidies, Firm Learning, and Women’s Employment By Mimosa Distefano; Lorenzo Incoronato; Anna Raute
  3. Price Discovery in Labor Markets: Why Do Firms Say They Cannot Find Workers? By Benjamin Friedrich; Michal Zator; Alison Zhao
  4. Cautious Careers: Job Mobility under Incomplete Markets By Alex Clymo; Piotr Denderski; Yusuf Mercan; Benjamin Schoefer
  5. Idea Rents and Firm Growth By Timo Boppart; Peter J. Klenow; Reiko Laski; Huiyu Li

  1. By: Brian Jabarian; Luca Henkel
    Abstract: This paper studies whether AI automation can improve organizational outcomes by reducing variance when collecting information. We conducted a large-scale natural field experiment in which 70, 000 job applicants were randomly assigned to be interviewed by human recruiters or AI voice agents. In both conditions, human recruiters evaluate the interviews and make hiring decisions. Applicants interviewed by AI agents are 12% more likely to receive job offers, and these gains translate into higher job starts and worker retention, with no decline in the productivity of hired workers. Analyzing interview transcripts reveals that AI voice agents achieve controlled variance: their interviews are more structured and consistent while remaining responsive to individual applicants, which is associated with more hiring-relevant information collected. These results demonstrate that automating information collection with AI can enhance decision quality through standardization.
    Date: 2026–07
    URL: https://d.repec.org/n?u=RePEc:arx:papers:2607.28222
  2. By: Mimosa Distefano; Lorenzo Incoronato; Anna Raute
    Abstract: Women often struggle to re-enter employment after career breaks, possibly because employers are uncertain about their productivity. We study whether hiring subsidies help firms overcome this uncertainty and hire from this group. Exploiting an Italian policy that temporarily cut payroll taxes for women hired from non-employment, we find that firms persistently hire more women with career breaks, including mothers, following subsidy adoption. Consistent with employer learning about target-group productivity, firms with better initial matches later hire more from this group. Subsidized workers also show stronger labor-market attachment. These findings suggest demand-side interventions can complement supply-side policies in addressing gender gaps.
    Keywords: gender employment gap; mothers; hiring subsidies; employer learning; firm hiring behavior
    JEL: J16 J23 H25 D83
    Date: 2026–08
    URL: https://d.repec.org/n?u=RePEc:crm:wpaper:26211
  3. By: Benjamin Friedrich; Michal Zator; Alison Zhao
    Abstract: Why do firms report that they cannot find workers instead of preemptively raising wages? Using German administrative data, we show labor-constrained firms pay lower wages and quasi-exogenous wage increases alleviate constraints, consistent with monopsony. Yet constrained firms' delayed wage increases point beyond this mechanism. We develop a dynamic matching model combining wage-setting power with incomplete information and downward wage rigidity. Consistent with the model, firms raise wages when initial wage plans prove too low, especially for peripheral occupations, and face constraints after wage shocks to adjacent sectors, suggesting that firms' inaccurate beliefs and learning about market wages shape labor constraints.
    Keywords: Hiring difficulties, wage adjustments, outside options, information frictions
    JEL: J23 J31 D83 E24 M51
    Date: 2026–08
    URL: https://d.repec.org/n?u=RePEc:crm:wpaper:26215
  4. By: Alex Clymo; Piotr Denderski; Yusuf Mercan; Benjamin Schoefer
    Abstract: Job mobility is risky, workers are risk averse, and insurance markets are incomplete. This paper studies how these features curb and distort job-to-job transitions by making workers excessively cautious: they place too much weight on job safety over wage and productivity gains. We demonstrate this tradeoff by eliciting employed workers’ wage-safety indifference curves in a custom, representative survey. On average, employed US workers require a 1.63% pay raise to accept each additional percentage point of annual unemployment risk in a new job. We assess the macroeconomic consequences of our mechanism by embedding it into a general equilibrium search model. Jobs differ in both wages (productivity) and unemployment risk, and risk-averse workers self-insure against unemployment risk through a non-state-contingent bond while searching on and off the job. We find that a complete markets counterfactual would boost job mobility by 12% and productivity by 0.19%. We also highlight a new role for unemployment insurance: it encourages employed workers to accept risky but high-productivity offers, thereby increasing productivity (by 1.3%) and job creation—as well as job loss and unemployment.
    JEL: E24 H20 J2 J62 J64
    Date: 2026–08
    URL: https://d.repec.org/n?u=RePEc:nbr:nberwo:35580
  5. By: Timo Boppart; Peter J. Klenow; Reiko Laski; Huiyu Li
    Abstract: Which firms drive aggregate productivity growth? We document that firms with high price-earnings ratios tend to see increases in their subsequent earnings relative to sales, which we interpret as rents from ideas (innovation). We construct an endogenous growth model with shocks to firm innovation step-sizes and R&D efficiency and calibrate it to match patterns in the data. The model implies that growth would be much lower, even with the same innovative effort, if firms had the same step sizes. The model can be used to infer expected growth contributions of individual firms (such as members of the Magnificent Seven). We find that the share of growth coming from smaller listed firms substantially exceeds their sales share, whereas the largest listed firms account for less than their sales share.
    JEL: L11 O31 O41
    Date: 2026–08
    URL: https://d.repec.org/n?u=RePEc:nbr:nberwo:35594

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