Show simple item record

FieldValueLanguage
dc.contributor.authorHe, Qiyang
dc.date.accessioned2025-07-31T04:23:25Z
dc.date.available2025-07-31T04:23:25Z
dc.date.issued2025en
dc.identifier.urihttps://hdl.handle.net/2123/34173
dc.description.abstractThis thesis consists of three empirical corporate finance studies. The first examines the impact of U.S. EPA enforcement on corporate green innovation. We find that EPA-enforced firms significantly increase green innovation output due to higher efficiency and greater hiring of green inventors. This effect is stronger in states for firms headquartered in states with stronger environmental enforcement intensity, firms with higher institutional ownership, and those with fewer financial constraints. Green innovations further help firms avoid future EPA actions and reduce toxic emissions. The second study employs FinBERT to develop a labor-shortage exposure measure. We validate this measure by showing that states with higher labor-shortage exposure experience lower future unemployment but higher wage growth and labor market tightness. while firms with higher exposure have greater growth in future per-employee staff expenses. Firms with labor-shortage exposure experience lower earnings call CARs, lower stock returns, and reduced operating performance. Firms mitigate these effects by substituting labor with capital and R&D investments, and by producing more process patents, which help offset negative performance impacts. The third study constructs a novel patent utilization measure using FastText, capturing the extent to which a firm’s patent portfolio contributes to new product development. We find that new products backed by more patents yield higher announcement returns, while firms with higher patent utilization rates experience future better new product development, market share growth, profitability, and valuation. These effects are primarily driven by high-value patents and are stronger in competitive markets. We address endogeneity concerns using R&D tax credits as instruments and demonstrate robust findings across various tests.en
dc.language.isoenen
dc.subjectCorporate Financeen
dc.subjectMachine Learningen
dc.subjectTextual Analysisen
dc.subjectInnovationen
dc.subjectLaboren
dc.titleThree Essays on Empirical Corporate Financeen
dc.typeThesis
dc.type.thesisDoctor of Philosophyen
dc.rights.otherThe author retains copyright of this thesis. It may only be used for the purposes of research and study. It must not be used for any other purposes and may not be transmitted or shared with others without prior permission.en
usyd.facultySeS faculties schools::The University of Sydney Business School::Discipline of Financeen
usyd.departmentFinanceen
usyd.degreeDoctor of Philosophy Ph.D.en
usyd.awardinginstThe University of Sydneyen
usyd.advisorQiu, Buhui


Show simple item record

Associated file/s

Associated collections

Show simple item record

There are no previous versions of the item available.