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5. MONOGRAPHISCHE LITERATUR
6. BEITRÄGE ZU SAMMELWERKEN


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4. ARBEITSPAPIERE/DISCUSSION PAPER
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@Book{Borm:2019:WDJ,
   Institution={Forschungsinstitut zur Zukunft der Arbeit (Hrsg.)},
   Author=     {Hannah van Borm and Ian Burn and Stijn Baert},
   Title=      {What Does a Job Candidate's Age Signal to Employers?},
   Year=       {2019},
   Pages=      {44},
   Address=    {Bonn},
   Series=     {IZA discussion paper},
   Number=     {12849},
   Annote=     {URL: http://hdl.handle.net/10419/215245},
   Annote=     {URL: http://hdl.handle.net/10419/215245},
   Abstract=   {"Research has shown that hiring discrimination is a barrier for older job candidates in many OECD countries. However, little research has delved into why older job candidates are discriminated against. Therefore, we have conducted an online scenario experiment involving recruiters to empirically investigate 15 potential stigma related to older age drawn from a systematic review of the literature. We found that older age particularly signals to recruiters that the applicant has lower technological skill, flexibility, and trainability levels. Together, these perceptions explain about 41% of the effect of age on the probability of being invited to a job interview. In addition, we found that the negative association between age and invitation probability is smaller when recruiters work for firms with a higher percentage of older employees." (Author's abstract, IAB-Doku) ((en))},
   Annote=     {Schlagwörter: Diskriminierung; Personalauswahl; altersspezifische Faktoren; Stereotyp; ältere Arbeitnehmer; Vorurteil; Plattformökonomie; Auftragsvergabe; OECD; },
   Annote=     {JEL-Klassifikation: J71 ; J23 ; J24 ; J14},
   Annote=     {Sprache: en},
   Annote=     {Quelle: IAB, SB Dokumentation und Bibliothek, LitDokAB, K200304AXC},
}


@Book{Burn:2019:OWN,
   Institution={National Bureau of Economic Research, Cambridge (Hrsg.)},
   Author=     {Ian Burn and Patrick Button and Luis Felipe Munguia Corella and David Neumark},
   Title=      {Older Workers Need Not Apply? Ageist Language in Job Ads and Age Discrimination in Hiring},
   Year=       {2019},
   Pages=      {70},
   Address=    {Cambridge, Mass.},
   Series=     {NBER working paper},
   Number=     {26552},
   Annote=     {URL: https://doi.org/10.3386/w26552},
   Abstract=   {"We study the relationships between ageist stereotypes - as reflected in the language used in job ads - and age discrimination in hiring, exploiting the text of job ads and differences in callbacks to older and younger job applicants from a previous resume (correspondence study) field experiment (Neumark, Burn, and Button, 2019). Our analysis uses methods from computational linguistics and machine learning to directly identify, in a field-experiment setting, ageist stereotypes that underlie age discrimination in hiring. We find evidence that language related to stereotypes of older workers sometimes predicts discrimination against older workers. For men, our evidence points most strongly to age stereotypes about physical ability, communication skills, and technology predicting age discrimination, and for women, age stereotypes about communication skills and technology. The method we develop provides a framework for applied researchers analyzing textual data, highlighting the usefulness of various computer science techniques for empirical economics research." (Author's abstract, IAB-Doku) ((en))},
   Annote=     {Schlagwörter: Stellenanzeige; Diskriminierung; ältere Arbeitnehmer; Personalauswahl; Personaleinstellung; Stellenbesetzung; altersspezifische Faktoren; Sprache; Stereotyp; USA; },
   Annote=     {JEL-Klassifikation: J23 ; J14 ; J78 ; J7},
   Annote=     {Sprache: en},
   Annote=     {Quelle: IAB, SB Dokumentation und Bibliothek, LitDokAB, K200221AS5},
}



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