Job postings

  • 详情 Better Late than Never: Environmental Punishments and Corporate Green Hiring
    Do firms adjust their hiring decisions after receiving environmental punishments? Using data on over 4.3 million job postings for Chinese listed firms from 2015 to 2021, we find that firms subjected to environmental punishments will subsequently increase their corporate green hiring (i.e., employees with green skills). Pressure from local environmental concerns and regulatory efforts incentivizes firms to increase their demand for employees with green skills. Environmental punishments have a more pronounced effect on corporate green hiring for non-state-owned enterprises and firms with lower financial constraints. Moreover, green hiring can have a remediation effect on firms' environmental performance and stimulate their green innovation activities and spillover effects on other firms within the industry. Overall, our findings shed light on corporate hiring decisions under environmental regulations.
  • 详情 Investments and Innovation with Non-Rival Inputs: Evidence from Chinese Artificial Intelligence Startups
    Large technology firms have substantial advantages in data, a key non-rival input for developing AI technology. We argue that investments by large technology firms stimulate innovation by AI startups through the sharing of data, bringing more than money to the startups. We assemble a unique dataset containing (nearly) the universe of AI-inventing firms in China to examine the innovation effects of these investments. Our difference-in-differences estimation shows that, after receiving investments from large technology firms, AI startups increase the number of AI patent applications by 62% and the number of software products by 56%, relative to their mean values prior to the investments. Using a triple-differences strategy, we further find that the innovation impact of investments by large technology firms is stronger than that of investments by other firms without data advantages. We confirm these findings using an instrumental variables approach based on recent investments by large technology firms in peer startups. Finally, we provide novel evidence that the innovation effect works mainly through sharing non-rival data by leveraging our rich information on non-AI data-related patent applications and data-related online job postings.