"Libby Boxes"

"Libby Boxes"

Revenue recognition is one of FASRI’s key target areas for research over the coming year.   We are going to take a big step forward on Tuesday, October 6th, 4pm by laying out some possible approaches to research studies on RevRec.  We will be structuring our discussion around the key independent variables that researchers might have at their disposal, and that seem likely to mesh with FASB deliberations.  Jeff Wilks, Jeffrey Hales and I talked yesterday and identified four classes of such variables:

  • The timing and certainty of the cash flow stream from the customer.  Does cash come immediately or with a long delay and probability of nonpayment.
  • The timing and certainty of the costs associated with production.  Are there ongoing costs after cash is received?
  • The precision with which associated assets and liabilities can be measured.  Is there a readily-measurable market price for receivables and performance obligations?
  • The timing and completeness of the transfer of control to customers.

These four classes of variables tie reasonably closely to the four RevRec ‘conventions’ in a memo from 2003, identified as driving over 180 separate instances of revenue recognition guidance:  the collection convention, the proportionate performance convention, the mark-to-market convention and the sales convention. Our goal will be to brainstorm about experiments, surveys and archival/econometric studies that could examine how these variables alter the usefulness of various revenue recognition standards.

We will also discuss a key difference between the academic approach and the standard-setting approach, which I think is conveyed well by the ‘Libby Box’ framework (see image*).   Theories describe conceptual links between conceptual variables, but as researchers our job is to identify statistical associations between observable proxies for those variables, controlling for other factors that might interfere with our inferences.

In much the same way, standard setters focus on conceptual models of revenue recognition.  But ultimately, as researchers, we assess the usefulness of those models by examining specific measurable circumstances.  In an experiment, for example, we might manipulate both the timing of cash flows from customers and the revenue recognition standard, and look at dependent variables like user investment decisions or forecasts.  Archival studies can’t easily assess variation across standards, but can still look at differences in cash flow streams.

My impression is that the most politically-charged battles in standard settings are at the conceptual level, rather than at the operational level.  In particular, a goal of the RevRec project has been to create a broad unitary model that can cover every case. Questions then arise on whether the model is the right one, whether certain industries should be ‘scoped out’, and whether a unitary model is even the right goal.   But as academics, we can simply show whether particular standards improve decision making in particular circumstances.  Such a demonstration can be helpful in debates about conceptual issues, without getting academics directly involved in the political complexities.

Remember that you can join the discussion in Second Life or just watch on the web (and still participate in text chat).

*Image from Josep Bisbe, Joan-Manuel Batista-Foguet, Robert Chenhall, Defining management accounting constructs: A methodological note on the risks of conceptual misspecification, Accounting, Organizations and Society, Volume 32, Issues 7-8, October-November 2007, Pages 789-820, ISSN 0361-3682, DOI: 10.1016/j.aos.2006.09.010.