Jenny Li Zhang
Relevant Thesis-Based Degree Programs
Affiliations to Research Centres, Institutes & Clusters
Financial reporting, corporate disclosure, restatements, disclosure of foreign firms listed in the U.S.
Complete these steps before you reach out to a faculty member!
- Familiarize yourself with program requirements. You want to learn as much as possible from the information available to you before you reach out to a faculty member. Be sure to visit the graduate degree program listing and program-specific websites.
- Check whether the program requires you to seek commitment from a supervisor prior to submitting an application. For some programs this is an essential step while others match successful applicants with faculty members within the first year of study. This is either indicated in the program profile under "Admission Information & Requirements" - "Prepare Application" - "Supervision" or on the program website.
- Identify specific faculty members who are conducting research in your specific area of interest.
- Establish that your research interests align with the faculty member’s research interests.
- Read up on the faculty members in the program and the research being conducted in the department.
- Familiarize yourself with their work, read their recent publications and past theses/dissertations that they supervised. Be certain that their research is indeed what you are hoping to study.
- Compose an error-free and grammatically correct email addressed to your specifically targeted faculty member, and remember to use their correct titles.
- Do not send non-specific, mass emails to everyone in the department hoping for a match.
- Address the faculty members by name. Your contact should be genuine rather than generic.
- Include a brief outline of your academic background, why you are interested in working with the faculty member, and what experience you could bring to the department. The supervision enquiry form guides you with targeted questions. Ensure to craft compelling answers to these questions.
- Highlight your achievements and why you are a top student. Faculty members receive dozens of requests from prospective students and you may have less than 30 seconds to pique someone’s interest.
- Demonstrate that you are familiar with their research:
- Convey the specific ways you are a good fit for the program.
- Convey the specific ways the program/lab/faculty member is a good fit for the research you are interested in/already conducting.
- Be enthusiastic, but don’t overdo it.
G+PS regularly provides virtual sessions that focus on admission requirements and procedures and tips how to improve your application.
ADVICE AND INSIGHTS FROM UBC FACULTY ON REACHING OUT TO SUPERVISORS
These videos contain some general advice from faculty across UBC on finding and reaching out to a potential thesis supervisor.
Graduate Student Supervision
Doctoral Student Supervision
Dissertations completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest dissertations.
This dissertation comprises two studies on the voluntary disclosures of intangible assets. The past decades have witnessed the increasing economic importance of corporate innovation. Yet, innovation-related information is relatively limited in accounting reports for the capital market. This dissertation investigates firms’ voluntary disclosure of their R&D outputs through channels outside the financial reporting system: patent documents and corporate scientific publications. Chapter 2 examines the informativeness of patent documents in assessing firm value. As milestones of firms’ innovation process, patents periodically summarize the outputs of firms’ innovation activities. I leverage two text-based characteristics of a patent document to measure its information content—linguistic tone and the number of independent claims. Using large-sample patent documents granted by the U.S. Patent and Trademark Office, I find that these two characteristics can predict up to 7 years' future earnings. This predictive power is incremental to R&D expenses information from the accounting reports. Furthermore, the stock market reacts positively, but under-reacts, to information in patent documents at the release. This chapter demonstrates that the patent disclosure system is an alternative information source of firms’ internally developed intangibles outside the financial reporting system.Chapter 3, co-authored with Professor Jenny Li Zhang, studies corporate voluntary R&D disclosure through scientific publications around the enactment of the Leahy-Smith America Invents Act of 2011 (AIA). The AIA switches the patent system from “first-to-invent” to “first-inventor-to-file” system. This change invalidates private records as evidence for patent grants and induces a patent “race”: post-AIA patent grants largely depend on the speed of “filing” applications with the patent office, rather than on whether a firm is the original inventor. Firms with resource constraints could be slow in filing a patent and are disadvantaged in this race. Using a difference-in-differences design, we show that highly leveraged firms increase scientific publications to extend the patent race and/or block competitors from obtaining a patent after the enactment of AIA. The findings suggest that patent legislation is a crucial determinant of firms’ scientific publications. The positive effect of the AIA on corporate scientific publications is consistent with the policy makers’ goal to promote knowledge spillover in society.
This thesis explores the impacts of blockchain technology on accounting practice in two separate chapters. Blockchain is a system of distributed ledgers that can record information in a verifiable and permanent way. As the underlying technology of Bitcoin, Blockchain has received increased attention since 2008.Chapter 2 takes an empirical approach to examine how startup firms use blockchain to finance their projects in the market for Initial Coin Offerings (ICOs). The blockchain technology allows entrepreneurs to commit to disclosing their transactions with investors before the transactions take place. Such decisions are coded into computer programs, known as ‘smart contracts,’ which become immutable once deployed on blockchains. I manually collected and analyzed the ‘smart contract’ code of 2085 ICO projects. I find that ICOs that make more disclosure commitments with blockchains are more likely to succeed, as measured by the likelihood of reaching fundraising goals and delivering preliminary products. I also find that transaction volumes disclosed on blockchains predict ICO outcomes and that investors punish ICOs with suspicious volumes, e.g., volumes that show signs of automated trading. These findings indicate that blockchains can function as a self-commitment device, and firms in the ICO market use blockchain to signal project quality.Chapter 3 takes an analytical approach to study how blockchain differs from traditional commitment mechanisms, e.g., regulations, and how firms can benefit from the additional features. When firms make commitments through disclosure regulations, they are choosing a regulation ‘combo,’ a set of predetermined disclosure requirements that apply to many firms. However, when firms make commitments on blockchains, they can customize a set of disclosure requirements that best suit them. I develop a model to study firms’ endogenous commitment decisions. A manager can commit to disclosing a value relevant signal before it is realized, or he can defer the disclosure decision until after he observes the signal. My analyses demonstrate that the commitment decision can credibly convey information that otherwise could not be disclosed, suggesting that blockchain enhances firms’ ability to communicate private information to the market.