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postgraduate thesis: Essays on information economics and finance

TitleEssays on information economics and finance
Authors
Advisors
Advisor(s):Kwan, APLin, C
Issue Date2024
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
Citation
Liu, P. [劉博瑀]. (2024). Essays on information economics and finance. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR.
AbstractThis thesis consists of two essays on information economics and finance. Chapter 1 empirically quantifies the value of data to U.S. public firms by using the General Data Protection Regulation (GDPR), an EU privacy law, as a natural experiment that exogenously shocks data processing activities. Analyzing a sample of 2,371 firms over seven years, I find that treated firms - those with larger legal departments - reduce data processing activities by 11% relative to control firms post-GDPR, and experience a 1.2% drop in sales. If the exogenous reduction in data processing contributes fully to the sales decline, it implies a 1% increase in data processing can raise sales by 0.11%, quantifying the value of data. Additional evidence such as treated firms' non-increasing SG&A and IV regressions supports the same interpretation that data processing is the most likely channel between GDPR and sales. Heterogeneity analysis reveals that among treated firms, GDPR's impacts on data and sales coincide in firms with lower share of software engineers or workers located in EU. The coinciding impacts of GDPR on data and sales further support the positive value of personal data. Chapter 2, co-authored with Alan Kwan and Tse-Chun Lin, tests the managerial learning hypothesis using a novel dataset on corporate reading. A long literature argues corporate managers learn from stock prices, but organizations’ learning process and the types of learning they perform are challenging to observe. We present a novel test using firm-level readership of financial media articles as a manifestation of managerial learning behavior. We hypothesize that reading financial media, perhaps in conjunction with other unobserved learning activities, helps managers interpret noisy signals in stock prices. We show that the classic Q-sensitivity of R&D expenditure increases by 26% when firms’ reading of financial articles increases by one standard deviation. This relationship is driven by reading from near the headquarters and by articles likely more informative to managers.
DegreeDoctor of Philosophy
SubjectKnowledge economy
Information theory in economics
Dept/ProgramBusiness
Persistent Identifierhttp://hdl.handle.net/10722/343772

 

DC FieldValueLanguage
dc.contributor.advisorKwan, AP-
dc.contributor.advisorLin, C-
dc.contributor.authorLiu, Po-yu-
dc.contributor.author劉博瑀-
dc.date.accessioned2024-06-06T01:04:52Z-
dc.date.available2024-06-06T01:04:52Z-
dc.date.issued2024-
dc.identifier.citationLiu, P. [劉博瑀]. (2024). Essays on information economics and finance. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR.-
dc.identifier.urihttp://hdl.handle.net/10722/343772-
dc.description.abstractThis thesis consists of two essays on information economics and finance. Chapter 1 empirically quantifies the value of data to U.S. public firms by using the General Data Protection Regulation (GDPR), an EU privacy law, as a natural experiment that exogenously shocks data processing activities. Analyzing a sample of 2,371 firms over seven years, I find that treated firms - those with larger legal departments - reduce data processing activities by 11% relative to control firms post-GDPR, and experience a 1.2% drop in sales. If the exogenous reduction in data processing contributes fully to the sales decline, it implies a 1% increase in data processing can raise sales by 0.11%, quantifying the value of data. Additional evidence such as treated firms' non-increasing SG&A and IV regressions supports the same interpretation that data processing is the most likely channel between GDPR and sales. Heterogeneity analysis reveals that among treated firms, GDPR's impacts on data and sales coincide in firms with lower share of software engineers or workers located in EU. The coinciding impacts of GDPR on data and sales further support the positive value of personal data. Chapter 2, co-authored with Alan Kwan and Tse-Chun Lin, tests the managerial learning hypothesis using a novel dataset on corporate reading. A long literature argues corporate managers learn from stock prices, but organizations’ learning process and the types of learning they perform are challenging to observe. We present a novel test using firm-level readership of financial media articles as a manifestation of managerial learning behavior. We hypothesize that reading financial media, perhaps in conjunction with other unobserved learning activities, helps managers interpret noisy signals in stock prices. We show that the classic Q-sensitivity of R&D expenditure increases by 26% when firms’ reading of financial articles increases by one standard deviation. This relationship is driven by reading from near the headquarters and by articles likely more informative to managers.-
dc.languageeng-
dc.publisherThe University of Hong Kong (Pokfulam, Hong Kong)-
dc.relation.ispartofHKU Theses Online (HKUTO)-
dc.rightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works.-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subject.lcshKnowledge economy-
dc.subject.lcshInformation theory in economics-
dc.titleEssays on information economics and finance-
dc.typePG_Thesis-
dc.description.thesisnameDoctor of Philosophy-
dc.description.thesislevelDoctoral-
dc.description.thesisdisciplineBusiness-
dc.description.naturepublished_or_final_version-
dc.date.hkucongregation2024-
dc.identifier.mmsid991044808103003414-

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