How Do Job Vacancy Rates Predict Firm Performance? A Web Crawling Massive Data Perspective

43 Pages Posted: 3 Nov 2020

See all articles by Huai-Chun Lo

Huai-Chun Lo

Yuan Ze University

Kees Koedijk

TIAS School of Business and Society, Tilburg University

Xiang Gao

affiliation not provided to SSRN

Yuan-Teng Hsu

Shanghai Business School

Date Written: May 20, 2020

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.

Keywords: Job vacancy; Web crawler; Big data; Firm performance; Corporate strategy

JEL Classification: G14; G17; G39

Suggested Citation

Lo, Huai-Chun and Koedijk, Kees and Gao, Xiang and Hsu, Yuan-Teng, How Do Job Vacancy Rates Predict Firm Performance? A Web Crawling Massive Data Perspective (May 20, 2020). Pacific-Basin Finance Journal, Forthcoming, Available at SSRN: https://ssrn.com/abstract=3617631 or http://dx.doi.org/10.2139/ssrn.3617631

Huai-Chun Lo

Yuan Ze University ( email )

135, Far-East Rd., Chung-Li
Taoyuan, ROC
Taiwan

Kees Koedijk

TIAS School of Business and Society, Tilburg University ( email )

P.O. Box 90153
Tilburg, DC Noord-Brabant 5000 LE
Netherlands

Xiang Gao

affiliation not provided to SSRN

Yuan-Teng Hsu (Contact Author)

Shanghai Business School ( email )

Shanghai
China

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