How do job vacancy rates predict firm performance? A web crawling massive data perspective

Huai Chun Lo, Kees G. Koedijk, Xiang Gao, Yuan Teng Hsu*

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Traditionally, the relationship between a firm's performance and its business strategy is studied using structured data taken from proxy statements and financial reports. However, there have been increasing efforts to explore the linkages between corporate outcomes and unstructured information, such as text or image/audio/video files. Until recently, semi-structured data had been largely overlooked. Given that a substantial amount of such data can be extracted using web crawler techniques and then processed using big data solutions, the current study employed this procedure to investigate whether dynamic job vacancy postings by Taiwanese publicly listed companies are associated with subsequent stock returns and operating ratios. We report that new job openings foreshadow a firm's operating performance, both indirectly, by boosting stock prices, and directly, by signaling positive developments. This finding remains robust to tests addressing endogeneity concerns and the adoption of alternative specifications. We thus shed light on the role of metadata in financial analysis.

Original languageEnglish
Article number101371
JournalPacific Basin Finance Journal
Volume62
DOIs
Publication statusPublished - Sep 2020

Keywords

  • Big data
  • Corporate strategy
  • Firm performance
  • Job vacancy
  • Web crawler

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