Big data applications in labor economics (Part-A)

Contributor(s):

Material type: Text

TextSeries: Research in Labor EconomicsPublication details: Emerald Publishing Limited Leeds 2025Description: xviii, 260 pISBN:

9781835499757

Subject(s):

DDC classification:

331 ELS

Summary: In the digital age, Big Data offers an unparalleled lens into the intricacies of human behavior. Data sourced from job boards, social media platforms, or news websites allows researchers to answer questions that could not be answered with conventional data sources. Labor markets are no exception here: every day, millions of workers and firms interact, and big data allows us to better understand the complex dynamics arising from worker-firm interactions. This volume showcases new, original research using Big Data to gain fresh insights into how labor markets work. The volume is compiled by Solomon Polachek, a pioneer in gender-related labor market research, and Benjamin Elsner, an expert on causal inference and the economics of migration. Topics include labor force transition dynamics, the labor demand side of involuntary part-time employment, the insights gained from wages in online job postings regarding wage growth, the role of online vacancies in labor market performance, the demand for personality traits, and an analysis of job descriptions from university job boards. All chapters use a combination of innovative data sources and machine learning methods to enhance our understanding of how labor markets work. (https://bookstore.emerald.com/big-data-applications-in-labor-economics-hb-9781835499757.html#firsty.info.description)

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	Public Policy & General Management	331 ELS (Browse shelf(Opens below))	1	Available		008835

Table of Contents:

Chapter 1. Labor Force Transition Dynamics: Unemployment Rate or Job Posting Counts?; Kailing Shen and Yanran Zhu
Chapter 2. The Labor Demand Side of Involuntary Part-time Employment; Hyeri Choi and Ioana Marinescu
Chapter 3. What Do Wages in Online Job Postings Tell Us About Wage Growth?; Pawel Adrjan and Reamonn Lydon
Chapter 4. Online Vacancies and their Role in Labor Market Performance; Leonardo Fabio Morales, Carlos Ospino, and Nicole Amaral
Chapter 5. Demand for Personality Traits, Tasks, and Sorting; Vera Brenčič and Andrew McGee
Chapter 6. Personality Characteristics Demanded by Employers: Analysis of Job Descriptions from University Job Boards; Luiza Antonie, Laura Gatto, Sarah Oloumi, and Miana Plesca

In the digital age, Big Data offers an unparalleled lens into the intricacies of human behavior. Data sourced from job boards, social media platforms, or news websites allows researchers to answer questions that could not be answered with conventional data sources. Labor markets are no exception here: every day, millions of workers and firms interact, and big data allows us to better understand the complex dynamics arising from worker-firm interactions.

This volume showcases new, original research using Big Data to gain fresh insights into how labor markets work. The volume is compiled by Solomon Polachek, a pioneer in gender-related labor market research, and Benjamin Elsner, an expert on causal inference and the economics of migration. Topics include labor force transition dynamics, the labor demand side of involuntary part-time employment, the insights gained from wages in online job postings regarding wage growth, the role of online vacancies in labor market performance, the demand for personality traits, and an analysis of job descriptions from university job boards. All chapters use a combination of innovative data sources and machine learning methods to enhance our understanding of how labor markets work.

(https://bookstore.emerald.com/big-data-applications-in-labor-economics-hb-9781835499757.html#firsty.info.description)

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