Accounting and Information Systems (ACCT)

ACCT 530-0 Special Topics in Empirical Accounting Research (1 Unit)  

Part I: Students will be introduced to research studies that examine unstructured data (e.g., textual) and/or use non-traditional research methods (e.g., machine learning). We will focus primarily on popular textual measures (e.g., sentiment, readability, and similarity) and machine learning methods (e.g., Naïve Bayes and Support Vector Machines). The focus will be both on learning the underlying techniques, as well as developing an understanding of the relevant economic contexts in which to apply them to accounting questions. Part II: This part of the course will focus on current empirical techniques used in archival accounting research. The focus will be on research design and identification issues in the context of recent and evolving research on disclosure, information processing costs and real effects of reporting and disclosure.

ACCT 540-1 Empirical Research in Accounting I (1 Unit)  

Students will become acquainted with research questions, methodologies, and findings of empirical research on the implications of accounting information for capital markets through journal readings, replications of existing research, and a final exam. The goal is for students to develop skills in issue identification and research design that can be used to do research and to evaluate research of others.

ACCT 540-2 Empirical Research in Accounting II (1 Unit)  

This course focuses on examining and evaluating the economic arguments underpinning capital-markets based, empirical accounting research. The course includes discussion and critical assessment of research designs and statistical methods used by accounting researchers with a focus on the appropriateness of the research question. Students are responsible for presenting research papers and preparing a final research proposal.

ACCT 540-3 Empirical Research in Accounting III (1 Unit)  

Students will be introduced to research studies that examine unstructured data (e.g., textual) and/or use non-traditional research methods (e.g., machine learning). This will include research in economics, finance, and marketing as well as accounting. We will focus primarily on popular textual measures (e.g., sentiment, readability, and similarity) and machine learning methods (e.g., Naïve Bayes and Support Vector Machines). The focus will be both on learning the underlying techniques, as well as developing an understanding of the relevant economic contexts in which to apply them to accounting questions.

ACCT 550-1 Research in Accounting Theory I (1 Unit)  

This course provides an introduction to contemporary research in financial accounting theory and is designed for PhD students in Accounting, Economics, and related disciplines. The course analyzes models of voluntary and mandatory disclosures, the design of accounting standards, income measurement, earnings management, and auditing.

ACCT 550-2 Research in Accounting Theory II (1 Unit)  

Students study economic models of financial reporting and disclosure together with the economics of accounting standards. The course includes study of the linkages among financial accounting, managerial accounting and auditing. Students learn to evaluate the existing models in the literature and to construct basic models of their own.

ACCT 590-0 Research (3 Units)  

Independent investigation of selected problems pertaining to thesis or dissertation. May be repeated for credit.