Bushman’s PhD Seminar Fall 2026

Real Effects: Information, Incentives and Investment

This seminar will discuss both theory and economics-based empirical analysis. This will include foundational theories of optimal investment, information, liquidity and the cost of capital, and incentive design. We will also examine specific investment settings including the AI infrastructure build-out, intangibles and innovation, as well as relations between internal information & investment efficiency. Key objectives are to

Build foundational knowledge and guage the current trajectory of the literature (a number of the papers will have 2026 dates);
Deepen economic sophistication and sharpen economic intuition;
Appreciate that powerful economic storytelling can frame convincing explanations of important phenomenon. Following David Deutsch, I believe that the creation of new knowledge is driven by the pursuit of good explanations, rather than mere predictions or passive data collection

Couse Structure: This seminar is an opportunity to gain fundamental knowledge, explore new ideas, and build your intellectual foundation. You will likely never again have an opportunity to consume knowledge at this scale. Post-PhD, reality will shift from consumption to production as myriad demands stake claims on your time. The intellectual foundation you leave with will play a crucial role in navigating the ruthless tyranny of the tenure clock. While I certainly benefit from these seminars, how much you learn is up to you. It is your life. Learning and idea discovery are hard work, fueled by the energy of curiosity and drive to learn. I cannot create curiosity or drive for you, and will not force you to learn. The ultimate final exam is your thesis, long-run research success and career trajectory.

I encourage you to read and deeply consider the papers, including the ones that you are not presenting. Simply asking AI to produce paper summaries is not learning. AI can be an intellectual jackhammer to breakthrough to deeper levels, but it can't learn for you. You have to confront the papers. All registered students will be expected to present two papers. Others are also free to present if there is availability. I will send out a signup sheet for papers. Papers marked in green are available for student presentations. In these presentations I expect to see critical thinking. Demonstrate that you understand the paper and have critical thoughts on it: Is it interesting or not? Are there problems or weaknesses in the design or econometrics? Does it inspire new ideas for future research? Suggested questions to consider:

What is the research question and why is it important? What is the theoretical framework or economic narrative used to motivate the research question and hypotheses? What are the main concerns, limitations, and weaknesses? How accurately do the empirical proxies capture the underlying economic constructs of interest? To what extent is the research design capable of distinguishing between alternative hypotheses? What are the main results? How do the authors interpret them? How do you interpret them?

A challenge for PhD students is getting enough opportunities to present in front of a group. Powerful presentation skills are crucial for success and are developed by actually presenting. The more time on stage the better. But opportunities are scarce. I highly recommend that you use these presentations to develop your presentation skills with the objective of finding your unique, natural style.

Session Details

Session 1 Wednesday 10/28/26 1pm to 4pm

AI, reality & change

While I will present some aspects of the listed papers, the papers themselves are just reflections of smart people trying to figure out how to proceed and are only suggestive of the trajectory the singularity is imposing on the future of accounting research. I view the session in the spirit of a brainstorming platform to strategize about adjustments in skill sets and perspectives necessary to enhance survival probability in a world with vast, accessible intelligence beyond our little individual brains. The old gray mare, ain't what she used to be! Nothing can stop this train!

Harvey, Campbell R., 2026. AI and Scholarship in Financial Economics.
Schwartz, Andrews & Shapiro, 2026. An LLM Workflow That Reproduces, Improves, and Extends Published Economics Research
John Barrios, 2026 Keynote Talk. Trust, but Verify: Accounting and Finance Research in the Age of AI (especially parts 3,4 & 5)
Aggarwal, Rishabh and Balakrishnan, Karthik, 2026. Do Large Language Models Discriminate Among Research Ideas? Evidence from Reasoning Traces.
Novy-Marx, Robert and Velikov, Mihail, AI-Powered (Finance) Scholarship, 2026. Journal of Economic Literature vol. 64, no. 1. Available at SSRN.
Ciconte, Will and Rozario, Andrea and Urcan, Oktay, 2026. Using AI to Identify Exogenous Shocks and Conduct Archival Accounting Research. Review of Accounting Studies, Volume 31, pages 1638–1676. Published version.