This course, AI2: Artificial Intelligence and Accounting Information, focuses on understanding the applications of Artificial Intelligence (AI) in the realm of financial information, emphasizing recent AI innovations such as Large Language Models (LLMs) and Agentic AI Systems. The financial information environment surrounding corporations involves processing vast amounts of data both to generate and review documents like 10-K reports, earnings calls, analyst reports, and press releases. Key topics include techniques for effectively using and communicating with LLMs (e.g., Prompting & Context Engineering), methods for building and using with vectorized data representations (Embedding), strategies for contextualizing AI-generated answers (Retrieval-Augmented Generation), and understanding the promises and limitations of Agentic AI. The course covers the economic framework, real-world examples, hands-on exercises, and AI safety considerations. Multiple guest speakers will share their expertise, and lectures will be integrated with lab exercises to provide a comprehensive learning experience.
Empirical Research on Corporate Reporting: This doctoral-level course covers research on the role of financial and non-financial information in capital and labor markets. The focus is on introducing students to key themes in empirical accounting and capital markets research, and to key research designs applied to examine information-related questions. Course topics include the informational role of financial reports, accounting measurement attributes, earnings management, earnings quality, environmental, social, and governance-related disclosures and the role of key actors in the reporting environment, including management, investors, auditors, analysts, employees, and regulators. The course is interdisciplinary in nature. The readings focus on research design, and key theories, themes and approaches from the accounting, finance, economics, and psychology literature. Our overall goal is develop your understanding of existing research and its strengths and limitations, and to identify new research opportunities.
This course studies basic concepts of financial and managerial reporting. The viewpoint is that of readers of financial and managerial reports rather than the accountants who prepare them.
Empirical research at the intersection of accounting and labor economics has evolved substantially in recent years. This rise is largely a result of radical institutional changes that have created opportunities for researchers to explore new topics and settings. Moreover, the advent of technologies such as block chain and generative AI promise to permanently alter how labor as an input is used and managed in the corporation’s information supply chain. Meanwhile, the corporate information environment has also become increasingly complex with the proliferation and maturation of internet-enabled communication. Social media platforms like Twitter and LinkedIn have revolutionized the way employees interact with their current or prospective employers and fellow labor market participants. These outlets have also led to new data repositories (e.g., Burning Glass and Revelio) that have allowed researchers to tackle previously unexplored or newly relevant questions with fresh empirical methods and insights.
Financial accounting is the measurement of economic activity for decision-making. Financial statements are a key product of this measurement process and an important component of firms' financial reporting activities. The objective of this course is not to train you to become an accountant but rather to help you develop into an informed user of financial statement information. While financial statement users face a wide variety of decisions, they are often interested in understanding the implications of financial statement information for the future cash flows and earnings potential of a firm. We will focus on understanding the mapping between underlying economic events and financial statements, and on understanding how this mapping affects inferences about future profitability and liquidity. The following learning objectives will be emphasized: (1) familiarity with the transactions businesses engage in, (2) fluency in accounting terminology, (3) understanding the structure that maps transactions into accounting numbers, (4) understanding the rationale for various accounting methods, and (5) awareness of the judgment involved and the discretion allowed in choosing accounting methods, making estimates, and disclosing information in financial statements.