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  3. 2022
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  5. LERA Best Papers V: Referrals and Hiring Policy
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LERA Best Papers V: Referrals and Hiring Policy

Paper Session

Saturday, Jan. 8, 2022 12:15 PM - 2:15 PM (EST)

Hosted By: Labor and Employment Relations Association
  • Chair: Erica Groshen, Cornell University

Overeducation as Hiring Policy

Guillaume Vermeylen
,
University of Mons
Alexandre Waroquier
,
University of Mons

Abstract

Purpose: We provide first evidence regarding the direct effect of a hiring policy oriented through higher (over) education on firm productivity. Moreover, we put light on the moderating role of the working environment of the firm, qualified as high-tech/knowledge intensive.

Approach: Using a detailed Belgian firm panel data, and computing a measure of overeducation hiring policy robust to sectorial bias,

Findings: We show that firms that decide to implement a hiring policy of overeducation are found to be more productive than others which follow the hiring standards in terms of educational levels. Concerning the role of the technological environment, we show that high-tech firms may take advantage of additional skills provided by highly educated workers to a bigger extent, the overeducation hiring policy leading to even higher productivity improvements.

Originality: Unlike much of the earlier literature (still essentially focused on workers' wages, job satisfaction and related attitudes and behaviours), our econometric estimates are based on direct measures of productivity. They are also robust to a range of measurement issues, such as time-invariant labour heterogeneity and firm characteristics.

Connections, Referrals, and Hiring Outcomes: Evidence from an Egyptian Establishment Survey

Adam Osman
,
University of Illinois-Urbana-Champaign
Jamin D. Speer
,
University of Memphis
Andrew Weaver
,
University of Illinois-Urbana-Champaign

Abstract

Network-based hiring is a double-edged sword. On the one hand, the literature shows that use of employee referrals can improve job matching and productivity. On the other hand, many analysts worry that nepotism and corrupt use of connections exclude disadvantaged workers from promising job opportunities. Researchers have generally not been able to disentangle these phenomena as most datasets do not contain establishment-level information on both owner- and employee-network hiring. Using a unique survey, we document important differences in retail establishments’ use of ties to the owner (“connections") and to employees (“referrals") and their relationships with hiring outcomes. While all types of establishments use referrals at similar rates, use of owner connections varies widely and is most common among small informal establishments. We develop a model of hiring which predicts that connections and referrals have heterogeneous effects on hiring outcomes depending on establishment type. Our empirical results are consistent with the model's predictions. When high-productivity establishments use connections, the practice is associated with lower-productivity hires (nepotism), yet when low-productivity establishments use connections, they find more productive workers. By contrast, referrals benefit high-productivity establishments more. These findings indicate that policies designed to either limit or expand network-based hiring could benefit one type of organization while having negative effects on others.

The Role of Referrals in Admissions: A Signaling Perspective

Colleen Flaherty Manchester
,
University of Minnesota
Brandy Edmondson
,
University of Minnesota
Anders Frederiksen
,
Aarhus University

Abstract

Prior research shows that referred candidates are more likely to be hired as compared to those who lack a referral; this advantage also holds in an admissions context. The literature on referrals includes several proposed reasons for these higher hiring and admission rates, including information-based explanations (e.g., superior qualifications or fit) and social influence (e.g., the influence of referring to individuals, social exchange). Using data from an MBA program admissions context where the role of social influence is mitigated, we evaluate referrals from an information-based perspective drawing on signaling theory. First, given applications contain multiple signals of candidate quality and fit (e.g., GMAT score, work experience, GPA), we deploy a signaling model to identify conditions under which a separating versus a pooling equilibrium emerges. We find support for the model’s predictions: having a referral increases admission rates for those with moderate GMAT scores (separating equilibrium); in contrast, those with low and high GMAT scores tend to lack referrals (pooling equilibrium). Second, we consider the diversity implications of referrals. While there is concern that referrals may reduce diversity through homophily, we find evidence that referrals may play a vouching role, reinforcing the view that a referral conveys information about the candidate. We find that referrals are more beneficial to candidates whose background does not as closely align with stereotypes of traditional managers (in our context) in terms of race. Stated differently, we find that having a referral is associated with a greater increase in admissions rate for non-white domestic candidates as compared to white domestic candidates. In contrast, we find no evidence of gender differences in the relationship between having a referral and admission rates.

Discussant(s)
Lucombo J. Luveia
,
Howard University
Olaniyi Olabiyi
,
University of the Western Cape
Christine Wen
,
Good Jobs First
JEL Classifications
  • D2 - Production and Organizations