Business

An algorithm for predicting job vacancies using online job postings in Australia

D. Evans, C. Mason, et al.

This research, conducted by David Evans, Claire Mason, Haohui Chen, and Andrew Reeson, introduces an innovative signal averaging algorithm that leverages online job postings to assess job vacancies in Australia. This method significantly outperforms traditional raw posting counts, offering a timely and reliable means of tracking changes in job vacancies over a 4.5-year timeline.

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Abstract

This study develops a robust signal averaging algorithm to measure job vacancies using online job postings data. Applying the algorithm to Australian job postings data, the study shows it accurately predicts changes in job vacancies over a 4.5-year period and is significantly more accurate than using raw counts of job postings. The algorithm offers a promising approach for timely and reliable measurement of vacancy changes.

Publisher

Humanities & Social Sciences Communications

Published On

Mar 13, 2023

Authors

David Evans, Claire Mason, Haohui Chen, Andrew Reeson

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