EcoSta 2018: Registration
View Submission - EcoSta2018
A0464
Title: JobEnomics: Firm growth prediction by online job posting data Authors:  Jing Wu - City University of Hong Kong (Hong Kong) [presenting]
Abstract: What would you do if you had access to over 44m unique job postings representing approximately 28,000 distinct private and public companies with over 32,000 new jobs posted daily as well as 16bn words captured in job posting descriptions? In this novel research, we explain firm growth and human capital investment using a giant web-crawled textual dataset on job posting. Our results show that job posting information has strong predictive power on firm future performance and stands out differently from investment patterns such as CMA in Fama French five-factor asset pricing model.