Fall 2018

Art by Amanda Sage https://www.amandasage.com/

Bushman’s PhD Seminar Fall 2018

Mixed data sampling; the role of accounting information in debt contracting

The course begins with a guest lecture on mixed data sampling, and then turns to a deep dive into debt contracting. We will consider the economics of debt including issues of information asymmetry; incentive conflicts between borrowers and lenders, and between lenders in loan syndicates; loan syndicate structure; and loan contract terms, covenant package design and renegotiation. The main emphasis will be on the role of accounting information in debt contracting.

I expect you to come to class having read the assigned papers. Some of the papers are quite difficult (e.g., theory papers), and so I recommend reading them to the point of diminishing returns. For some papers, it may require coming back to it again (and perhaps again and again) to fully internalize the idea. No one said it was easy!

Session Details

Session 1 Wednesday October 24th: 2:00pm to 5:00pm, Room 3575

Ryan Ball from Michigan will develop in some depth the Mixed Data Sampling (MIDAS) approach to empirical research designs.

Information loss from aggregation pervades most areas of accounting research and includes both temporal and cross-sectional aggregation. For example, stock returns observed on a daily basis are temporally aggregated to construct an annual return in order to measure and test for an association with annual earnings. Aggregation neglects potentially important variation in how the daily returns are temporally distributed throughout the fiscal year, such as the beginning vs. the end of fiscal year, or disclosure dates vs. non-disclosure dates. In a second example, earnings forecast errors of individual analysts in the cross-section are averaged to form a consensus earnings surprise and then measure its association with the market reaction at earnings announcement. Such aggregation neglects potentially important variation in observable characteristics of the individual forecasts, such as how recently each forecast was issued and the prior accuracy of each analyst. MIDAS regression models parsimoniously incorporate variation embedded in existing economic data that are observed at much higher frequencies than accounting data.

Papers for Class Discussion

We will discuss papers 2, 4 and 5 in some detail, while papers 1 and 3 will be briefly referred to.

There is a Risk-Return Trade-Off After All, Ghysels, Santa-Clara, and Valkanov (JFE, 2005). Only “gloss” over this paper. Ryan will use it as a way of illustrating the state of the MIDAS literature when he picked it up back in 2007.
A Mixed Data Sampling Approach to Accounting Research. Ball, Ryan T. and Gallo, Lindsey A., (September 16, 2018).
Dissecting Earning Recognition Timeliness, Ball and Easton (2013). Just “Gloss” over this paper.
Does It Pay to 'Be Like Mike'? Aspirational Peer Firms and Relative Performance Evaluation, Ball, Bonham, and Hemmer (2018)
Tilting the Evidence: The Role of Firm-Level Earnings Attributes in the Relation between Aggregated Earnings and Gross Domestic Product, Ball, Gallo, and Ghysels (2018)

Session 2 Wednesday October 31st: 2:00pm to 5:00pm, Room 3575

The economics of debt contracting: An Overview beginning with Modigliani and Miller 1958

Papers for Class Discussion

The Leverage Ratchet Effect. Admati, Anat R. and DeMarzo, Peter M. and Hellwig, Martin F. and Pfleiderer, Paul C., Journal of Finance, Volume 73, Issue 1, February 2018. We will primarily focus on Part I Debt Overhang and Leverage Distortions.
Accounting Information in Financial Contracting: The Incomplete Contract Theory Perspective. Journal of Accounting Research, 54, 2016. Christensen, Hans Bonde and Nikolaev, Valeri V. and Wittenberg Moerman, Regina.

Valuable Reviews of Debt Contracting Literature