Personnel Economics: Hiring and Incentives

Oyer, Paul; Schaefer, Scott

doi:10.1016/s0169-7218(11)02418-x

Cited by 76 publications

(9 citation statements)

References 179 publications

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“…reinforcing, and legitimating social structures of power and status along gender, race, and class lines (Acker 1990(Acker , 2006Ray 2019;Stephens et al 2014;Turco 2010). These "inequality regimes" (Acker 2006) shape members via implicit organizational logics (e.g., McPherson and Sauder 2013;Ray 2019), organizational policies (e.g., Noonan, Estes, and Glass 2007;Oyer and Schaefer 2011), as well as local culture: the day-to-day practices and norms of operation enacted routinely by organizational members (Bowles et al 1999;Ray 2019;Turco 2010).…”

Section: Organizations As Socializing Agentsmentioning

confidence: 99%

Classed Beginnings: Status Socialization in Two Preschool Classrooms

Espy,

Lynn

2023

Socius: Sociological Research for a Dynamic World

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Research on class inequality in education shows how the hidden curriculum—the tacit yet systematic lessons taught alongside the official curriculum—tends to favor the cultural capital that class-advantaged students bring from home over that of their less advantaged peers. This ethnography instead explores variation in what schools implicitly teach and how organizations potentially class their members. Comparing one Head Start with one tuition-charging preschool, the authors document how Head Start implicitly treats preschoolers, who are from predominantly disadvantaged backgrounds, as students who lack decision-making power and occupy the lowest position in a rigid status hierarchy. In contrast, the advantaged preschoolers were implicitly encouraged to take ownership of their actions, make the curriculum work for them, and activate support from teachers and administrators. Insofar as this “internal control” mindset of the tuition-charging preschool is favored in later academic and professional arenas, the authors argue that organizations can be agents of class socialization.

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Section: Organizations As Socializing Agentsmentioning

confidence: 99%

Classed Beginnings: Status Socialization in Two Preschool Classrooms

Espy,

Lynn

2023

Socius: Sociological Research for a Dynamic World

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“…In the economics literature the process of recruitment and hiring is largely viewed from an employee's perspective (Oyer & Schaefer, 2011). Information from the national employment agency or job ads placed by employers was used as an empirical database of the number and quality of vacancies.…”

Section: Literature Reviewmentioning

confidence: 99%

Better understanding of the labour market using Big Data

Vankevich

Kalinouskaya

2021

EiP

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Motivation: As the result of digitalisation of the economy, the number of Internet users is increasing, which leads to an increase in the number of vacancies posted on online platforms and services. The description of vacancies includes information about skills and competencies, which is the source of additional data for the labour market analysis. This information cannot be received through the analysis of statistical and administrative data. Therefore, it is important: — to learn how to evaluate new information sources, and use the data they generate; — to develop tools that people and organizations will use for finding an employee or a vacant post. The study focuses on the analysis and forecast of labour demand in the context of skills and competencies, which significantly enriches and adds to the information about the labour market and facilitates effective decision-making. Aim: The main goals of this article are the following: (1) identification of the methodological approaches in the labour market analyses using Big Data; (2) assessment of the labour demand and labour supply in the context of skills and competencies listed in the vacancy description posted on job portals; and (3) determination of the matches (mismatches) between skills and competencies in order to help the companies and individuals get better employment and education. Empirical data used in the research were collected from the description of job vacancies (16 401 vacancies) and CVs (227 215 CVs) from the most popular open job portals in Belarus through the scraping approach and classified according to the ESCO and ISCO codes. Quantitative analysis by the means of artificial intelligence was used in the research. Results: The study results revealed that the information about the volume and structure of skills and competencies obtained by scraping data from vacancy descriptions and Cvs, which are posted on online portals, allows for more precise diagnostics of labour demand and supply and overcoming of bilateral information asymmetry in the labour market. Based on the analysis, the parameters of scarcity and excess in competencies for individual occupations in the labour market are determined (the level of the correlation ratio between applicants’ competencies and those requested by employers in the context of occupations (four digits according to the ISCO classification) is less 0.8; the deviation of the ranks of competencies listed in CVs and vacancy descriptions according to the ESCO groups of skills/competencies and a sign of revealed deviations). The methodology is developed to set areas for necessary knowledge acquisition (by the analysis of competencies listed in CVs and vacancy descriptions at the 3rd and 4th digit level of ISCED classification) and skills (by the analysis of competencies at the 2nd digit level in ESCO groups). The paper illustrates limitations in using Big Data as an empirical database and explains the measures to eliminate those limitations.

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“…Second, this paper relates to the personnel economics literature on recruitment and selection. While a large body of literature has documented moral hazard and policies to motivate workers on the job, relatively little is known about how to attract the "right" workers in the first place (Lazear and Oyer, 2007;Paul and Scott, 2011). In contrast to the literature that examines selection by varying financial incentives (Bo et al, 2013;Deserranno, 2014;Ashraf et al, 2014), we focus on the impact of reputational externalities in attracting or deterring applicants.…”

Section: Related Literature and Implicationsmentioning

confidence: 99%

How Does Collective Reputation Affect Hiring? Selection and Sorting in an Online Labour Market

2015

SSRN Journal

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How does collective reputation affect hiring and selection into jobs? Using detailed hiring data from a global online labour market, where the country of residence is the salient group characteristic, we document a mechanism through which collective reputation can perpetuate initial group inequality. Using an instrumental variable strategy, we first identify reputational externalities between an employer's very first hire and the propensity to contract more workers from the same country. Employers, contingent on their first worker's performance (as measured by a public rating), go on to almost exclusively hire from the same country. This coincides with a strong and positive supply-side sorting response: Observing their predecessor's success, workers from the same country are more likely to apply and tend to be of higher quality. Employers, facing better applicants, are in turn more likely to continue providing top ratings for later hires from the first hire country. Collective reputation hence appears to serve as a coordination device that enables workers to positively sort with employers: Good workers then attract more good workers from the same country and vice versa. JEL codes: J7, J16, L14 * I am indebted to Oriana Bandiera and Robin Burgess for their supervision and continued guidance. I

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Personnel Economics: Hiring and Incentives

Cited by 76 publications

References 179 publications

Classed Beginnings: Status Socialization in Two Preschool Classrooms

Classed Beginnings: Status Socialization in Two Preschool Classrooms

Better understanding of the labour market using Big Data

How Does Collective Reputation Affect Hiring? Selection and Sorting in an Online Labour Market

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