06 May 2010

All accountants should be trained in econometrics ...

The proposition about accounting and econometrics, a little more formally, is this:
It is necessary for professional accountants to be trained in econometrics.
Most accountants and, I believe, even most accounting professors would strongly disagree with the proposition. ( It is, I can assure you, nonetheless true. :) )  Before presenting the argument supporting the proposition, it's first necessary to have an understanding of what econometrics is.
    What is econometrics?  To paraphrase the econometrician Jeff Wooldridge
Econometrics is the discipline involved in estimation of, and inferences about, causal relationships between economic variables.
For example, suppose economic theory suggests a causal relationship between sunspots and the demand for electronic components; let's say theory suggests sunspots cause an increase in the demand for electronics components.  An inquisitive individual might want to answer at least two questions about the theory:  Is actual data consistent with the prediction that sunspots are, on average, associated with an increase in electronic component demand? And, what is the estimated average effect of (the average) sunspot on electronic component demand?  Both, no doubt, interesting questions ... .  
    Also, attributable to Jeff Wooldridge is the useful idea of a mutually-exclusive-and-exhaustive classification of things we need to know to make decisions: Things we need to know can either be (1) known, (2) estimated, or (3) assumed, where the (rational) decision-making preference ordering is known > estimated > assumed.  Econometric methods are necessary when relationships between economic variables are not known, and when it is a Bad Idea to assume them.  
    In the context of my proposition it is hopefully obvious that simply assuming values in financial statements is a Bad Idea.  It is also hopefully obvious that the values of many things reported in financial statements is not "known".  In any case, with this basic understanding of what econometrics is I'll turn to the main topic.
    Accounting requires econometrics. As background, accounting is basically comprised of the recognition, measurement, and disclosure of economic events and resources in financial statements:
  • recognition refers to when events and resources are presented;
  • measurement refers to how events and resources are valued; and
  • disclosure refers to how such events and resources, recognition, and measurement are described in the statements.
Accounting measurement of many economic events and resources in a way approaching objective measurement requires use of econometric methods (and objectivity is an important characteristic of accounting measurement).  I will explain the idea using FAS 157, Fair Value Measurement and FAS 142, Goodwill and Other Intangible Assets, although I could just as easily use any of a dozen or so other accounting standards, which professional accountants must apply as part of their work.  Roughly speaking,  FAS 142 and 157 in combination require accountants to estimate the fair value of intangible assets, and reduce the financial statement value of the intangibles to the estimated value if less than previously reported.
    So why would estimating the fair value of intangible assets (among other things in financial statements) require use of econometric methods?  To answer, first consider the simplest expression of how fair value of intellectual property ("IP", one broad category of intangibles) is determined, where example numbers for factors influencing value are included for concreteness:
The equation says estimated fair value is a function of (i) expected future marginal profits attributable to the IP, (ii) expected future value of the IP, and (iii) estimated fair market expected risk-adjusted rate of return.  It is relatively easy to show expected future profits and values generally must be estimated using econometric methods, but I will simply focus (very carefully) on the estimated fair market expected risk-adjusted rate of return.  For example, given $1,000 in  expected future profits and value at the end of one year, if the estimated rate of return is .10, then the estimated fair value of the IP is about $909.
    But here's the problem for accountants: They don't know what a fair market's expected risk-adjusted rate of return is for the IP. Why? Because IP is almost by definition unique  and therefore unlike other IP that might have been sold.  Moreover, IP is rarely traded in open, fair markets.  This means that accountants (or someone else) must estimate what a fair market's expected risk-adjusted rate would be; that is, they must predict what the rate would be if the IP was traded in a fair market. 
    So, unless the accountants are willing to abrogate their responsibilities for accounting measurement (which they often do, by the way) or simply make an assumption about the rate (which they also do sometimes), then they must use econometric methods to estimate the rate.
    The argument is essentially complete at this point (QED, quod erat demonstrandum!), but to see this all a little more clearly consider the following graph:

Ignoring the questions posed in the graph momentarily, I will focus on what the graph represents:
  • The graph represents a hypothetical relationship between a certain type of risk (e.g., the risk that a particular class of antibiotics will become obsolete due to development of a newer, better class of antibiotics) and the rate of return implicit in the way a fair market sets the price of the risk.
  • The points shown on the graph represent actual observations ("data") of risk and rate of return set in a fair market (e.g., actual observations of expected market rates of return across different antibiotics each with different levels of risk).
  • The line running through the data represents an estimate of the fair market relationship between the type of risk and the market rate of return on the risk.
Suppose we are accountants for "YX Pharma Corporation" with "Antibiotic X" for which we have a patent expiring in 10 years.  Antibiotic X represents about 1/2 of the revenues and profits for YX Pharma, and has never been offered for sale.  So, the IP represented by the Antibiotic X patent is not traded in any market, let alone traded in a fair market.  So we don't know its fair value. 
    This means we accountants must either estimate or assume the value of the Antibiotic X patent.  Our securities law attorneys have strongly advised us against simply making up an assumption  about the value of the patent without strong supporting data and analysis.  So, we must estimate the value:  Roughly speaking we must first predict expected future marginal profits and value of the patent. Then, because the patent for Antibiotic X doesn't trade in a fair market, we must use publicly-observable data on risk measures and fair market rates of return on other similar antibiotics to estimate the market's risk-return relationship.
    With our estimate of the (equation for) the market's risk-return relationship, we can then use our measure of risk for Antibiotic X and obtain an estimate of a fair market's expected risk-adjusted return on Antibiotic X (even though, as stated, it doesn't actually trade in any market).  The estimated rate would then be used in a valuation model similar to the one shown above (the FV equation) to obtain the FV estimate of the Antibiotic X patent.
    As suggested by the questions on the graph, the scenario poses a lot of important questions we accountants must answer:
  • Where exactly do we get this market rate of return data; which competitors and which antibiotics; how do we separate overall observable market rates of return on competitors' equity from the rates on the antibiotic IP?
  • What is the best way to estimate the risk-return relationship; what method(s); what exactly are we estimating (i.e., the most likely relationship, the most conservative, etc.)?
  • What do we do about observations that don't seem to fit the average risk-return relationship; should they be included in our analysis and estimates?
It turns out that such questions (and their answers) are precisely the domain of econometrics.  Econometricians have largely worked out the general frameworks for thinking about such problems, as well as general solutions to them, over the last 50-60 years.
    So it follows that ...
Unless professional accountants want to abrogate their responsibility for accounting measurement to those trained in econometrics, they must be trained in econometrics themselves.
It would seem strange, almost pathetic really, if accountants were to abrogate the responsibility for accounting measurement--one of the three basic aspects of accounting--to others, don't you think?  :)  QED

São Paulo


  1. This comment has been removed by the author.

  2. I agree with this, I think all accounts should be trained in economics. I think new business techniques used has improved the accounting industry and focusing on economics could be crucial. I think this type of approach would help smaller accounting firms more because they have a more specific set of clients.

  3. I agree, econometrics can add an additional knowledge to accountants, anyway the two discipline are related. Economics deals with general flow of goods and commodities as used by men and accountancy with money.

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  4. I agree with you McElland, accounting should really be related with econometrics! Econometrics is the discipline involved in estimation of, and inferences about, causal relationships between economic variables while accounting is analyzation of finances or numbers. By the way, I am planning to be an accountant in UAE.

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