Research for Accounting Policy

Research for Accounting Policy Shyam Sunder, Yale University The 2010 JAAF/KPMG Foundation Conference The Vincent Ross Institute of Accounting Research Stern School of Business, New York University November 19, 2010

An Overview • Social sciences as instruments of social engineering (policy) • Scope and levels of accounting policy • Maintained assumptions of financial reporting policy • Instruments of social sciences: what works, what doesn’t? Why and why not? • Way forward: accounting policy beyond social sciences? Sunder, Research for Accounting Policy

We Could Talk About • Social science and social engineering • Robustness of findings to their discovery • Field data: Causal direction, correlation of hypotheticals • Experiments and bench testing • Scope and levels of accounting and financial reporting policy • Criteria • Assumptions • Problems of efficient standards and their alternatives • Command and control and alternatives • Social science as instrument of policy • Accounting policy beyond social sciences • Challenges for policy research, historical experience • Closed or open systems? Sunder, Research for Accounting Policy

Social sciences as instruments of social engineering • Social science as the dominant model of business research since mid-20th century • Although engineering originated well before the origins of natural sciences, advances in natural sciences have enabled us to engineer great many artifacts we consider indispensable today • Accounting, too, originated well before policy research; but it does not seem unreasonable to think that we can also take advantage of learning from social sciences to make better social policy (maintained assumption of this session) Sunder, Research for Accounting Policy

Limits of Parallels • This parallel can take us only so far • Natural sciences search for, and identify, laws of nature valid across time and space • Validity, replicability, and predictability of these laws confers prestige on sciences • But there is another form of scholarship on our campuses--humanities that regard the behavior of sentient beings as infinitely variable; each of character in Iliad, Macbeth, or Ramayana is unique • They pursue eternal truths, but admit no laws Sunder, Research for Accounting Policy

What are social sciences? • “Social” recognizes that the subject of study are sentient beings (with free will that humanists recognize), not marbles or atoms without will (that scientists study) • “Science” seeks the prestige associated with the search for eternal laws • Neither sciences nor humanities allow much room for laws of human behavior we seek in social sciences • Free will and laws of behavior do not sit well together; we want but can’t have it both ways Sunder, Research for Accounting Policy

Laws of Social Sciences • To serve as a basis for social policy, the “laws” of social sciences must have stability (be robust to their own discovery) • Since humans learn and adapt, social science findings can alter behavior in ways that tend to invalidate the findings • Findings which are robust to such adaptation can be called “laws” of social sciences, and may serve as the basis for social policy Sunder, Research for Accounting Policy

How Robust Are Our Findings? • Independent of the method of research we use, robustness of findings (to their own discovery) is a pre-requisite for their use as basis for policy • Like unclaimed dollar bills on side-walk, many findings (e.g., small firm and Monday effects) disappear upon being reported • There are other findings (e.g., determination of price by intersection of demand and supply) are robust in this sense (not merely statistically) • So the first pre-requisite for usefulness of any research findings for policy is this stability • Most such laws are properties of institutions, not behavior [1] Sunder, Research for Accounting Policy

Causal Link • Policy makers want to know if the manipulation of the policy variable under consideration has a directional (causal) link to the desired objective. Correlation does nothing for them. • Yet, the problem of establishing a causal link between two variables on the basis of field data remains largely unsolved due to endogeneity • Experimental methods have been presented as an alternative to address this problem, but they, too, have limitations of their own • Consider both approaches briefly Sunder, Research for Accounting Policy

Problems of Inference from Field Data: Causal Direction • Labeling of correlation as cause is more of a rule than an exception in accounting research journals • When correctly labeled as correlation, what can the policy maker do with the finding? • To claim that the finding is “consistent” with Hypothesis X fails to point out that • It is also consistent with innumerable other hypotheses not mentioned in the report, and • No hypothesis has been rejected (violating the essence of Fisher-Neyman-Pearson framework) Sunder, Research for Accounting Policy

Accepting or Failing to Reject the Null Hypothesis • It is important to note the philosophical difference between accepting the null hypothesis and simply failing to reject it. The "fail to reject" terminology highlights the fact that the null hypothesis is assumed to be true from the start of the test; if there is a lack of evidence against it, it simply continues to be assumed true. The phrase "accept the null hypothesis" may suggest it has been proved simply because it has not been disproved, a logical fallacy known as the argument from ignorance. Unless a test with particularly high power is used, the idea of "accepting" the null hypothesis may be dangerous.

“Absence of evidence is not evidence of absence” • When a researcher writes the qualified statement "we found no statistically significant difference," which is then misquoted by others as "they found that there was no difference." Actually, statistics cannot be used to prove that there is exactly zero difference between two populations. Failing to find evidence that there is a difference does not constitute evidence that there is no difference. This principle is sometimes described by the maxim "Absence of evidence is not evidence of absence."

Statistical Significance • Attempts to educate researchers on how to avoid pitfalls of using statistical significance have had little success. In the papers "Significance Tests Harm Progress in Forecasting," and "Statistical Significance Tests are Unnecessary Even When Properly Done,“ • Armstrong makes the case that even when done properly, statistical significance tests are of no value. A number of attempts failed to find empirical evidence supporting the use of significance tests. • Tests of statistical significance are harmful to the development of scientific knowledge because they distract researchers from the use of proper methods. • Armstrong suggests authors should avoid tests of statistical significance; instead, they should report on effect sizes, confidence intervals, replications/extensions, and meta-analyses. • J. Scott Armstrong

Choosing the null: Ex ante, or after looking at the data? • Some statisticians have commented that pure "significance testing" has what is actually a rather strange goal of detecting the existence of a "real" difference between two populations. In practice a difference can almost always be found given a large enough sample. The typically more relevant goal of science is a determination of causal effect size. The amount and nature of the difference, in other words, is what should be studied. • Hypothesis testing is controversial when the alternative hypothesis is suspected to be true at the outset of the experiment, making the null hypothesis the reverse of what the experimenter actually believes; it is put forward as a straw man only to allow the data to contradict it. Many statisticians have pointed out that rejecting the null hypothesis says nothing or very little about the likelihood that the null is true.

Problems of Inference from Field Data: Hypotheticals and Efficiency • Our attempt to produce policy-relevant research often take the following form: • Info. Sys. 1  Price system 1 • Info. Sys. 2  Price system 2 • Suppose information system 1 and price function 1 are the status quo and the policy maker wants to know the consequences of changing the information system from 1 to 2 Sunder, Research for Accounting Policy

Problems of Inference from Field Data: Hypotheticals and Efficiency • We can gather data on accounting numbers and prices under status quo and estimate their statistical relationship, R(1) • In many situations, we can also calculate (or reasonably estimate) what the accounting numbers would have been under the policy alternative (the hypothetical) • If we could observe prices that would be generated under the policy alternative, we could also estimate the statistical relationship R(2) • Does a comparison of R(1) and R(2) help the policy makers? • If stronger R(2) implies preference for the policy alternative, it is trivially simple to push R(2) to the upper limit by simply using prices for accounting Sunder, Research for Accounting Policy

Problems of Inference from Field Data: Hypotheticals and Efficiency • Of course, we are rarely so lucky as to be able to observe P(2) • An oft-used practice is to estimate the statistical relationship between the hypothetical I(2) and actually observed P(1), and then compare this R(2)* with R(1) and suggest that a stronger R(2)* implies the alternative to be preferred policy • Info. Sys. 1  Price system 1 • Info. Sys. 2  Price system 1 Sunder, Research for Accounting Policy

Logic of Inference Reporting System 1 Price System 1 Reporting System 2 Price System 2 Sunder, Research for Accounting Policy

Logic of Inference and Policy • This type of inference from field data does not help the policy makers • We like them to give us a nod to acknowledge our work, and perhaps even support it • But the logical foundations of such inference, and its implications for policy remain to be worked out Sunder, Research for Accounting Policy

What about Lab Experiments? • Lab methods allow us to address the causality problem with greater confidence • But they also raise new challenges for use of findings in making of accounting policy • Accounting is highly institutionalized (complex interactions, expectations), like engineering • Experimental methods were developed for social sciences where a single simple example can support a general proposition about existence, or otherwise • Simpler experiments suffice for basic disciplines such as economics, psychology and physics, but not for accounting policy or bridge design • Time scale problem: choosing points vs. functions Sunder, Research for Accounting Policy

Bench Testing of Policy • Bench testing of an accounting policy alternative calls for far greater complexity in design of the lab experiment than in case of testing economic theory • More complex decisions, larger choice space, need more time (order of magnitude) • Compare choice of a point on a function with choice of a function Sunder, Research for Accounting Policy

Scope and levels of accounting policy: alphabet soup • Financial reporting: FASB, IASB, SEC, etc. • Audit: PCAOB, ASB, IAuSB, AICPA • Internal Audit: IIA • Cost accounting: CASB? • Government: GASB, MFOA, OMB, GAO, Congressional committees • Education: AACSB, NASBA, IAESB, AICPA, CFA, IMA Sunder, Research for Accounting Policy

Macro Policy in Accounting • Taxation and collection • National income • Monetary policy • Banking regulation • Securities regulation • Employment, wages, retirement, unions • Wealth generation • Wealth distribution • Government budgets and financial management • Government accounting (control of deficits) • Cost of legislative proposals Sunder, Research for Accounting Policy

Scope and levels of financial reporting policy • Financial reporting policy is made at many levels, with higher levels having broader scope • Most common level is the choice of specific accounting methods and disclosures • At the other end of the spectrum are institutional and structural decisions usually made by Congress • Most research is concentrated at the micro end of the policy spectrum, probably because the high frequency of such decisions, and ex ante availability of data sets from comparable contexts • At higher institutional levels of policy making, ex ante data becomes more scarce, leaving us with ex post analyses that come too late to serve as inputs to decisions on policy alternatives Sunder, Research for Accounting Policy

Policy Criteria • Research input for policy calls for identifying the policy criteria and including them in research design • While accounting policy makers proclaim allegiance to qualitative criteria such as representativeness, timeliness, neutrality, decision usefulness, etc., few of them find their way into our research designs • Research on representativeness and neutrality, for example, would require comparison of accounting data with their corresponding principals which are difficult to observe • Research on decision usefulness is subsumed into correlation with stock prices, setting aside questions about market efficiency and the interests of non-equity stakeholders Sunder, Research for Accounting Policy

Assumptions of financial reporting policy • Subjecting them to investigation, instead of assuming that they hold Sunder, Research for Accounting Policy

1. Universal Standards • Universal standards of financial reporting applied across time, economies, industries and corporate size and organizational forms best serve the constituent interests • Standardization does save costs and effort, (coordination vs. efficiency benefits; electrical plugs, clothing, cars, street grids, commercial codes, cell phones, software) • When does standardization become counterproductive • How do we know where to stop? • Rhetoric of universal accounting standards using analogy of weights and measures and universal language Sunder, Research for Accounting Policy

2. The Static Ideal • There exists a set of financial reporting standards that, once discovered and implemented, will induce corporations and their auditors to prepare the best attainable financial reports • Dynamics of the game between financial reporting and financial engineering makes any such a static ideal all but impossible • Consider leases, derivatives, design of transactions Sunder, Research for Accounting Policy

3. People or Structure • If we select knowledgeable, experienced, self-less, public-spirited, and wise individuals to constitute bodies that devise accounting standards through deliberation and due process, we can improve financial reporting • Individuals stand where they sit • Much emphasis on the quality of individuals, too little attention to the structure of game they are asked to play Sunder, Research for Accounting Policy

4. Design, not Evolution • It is possible to construct or discover better financial reporting standards through deliberation in properly organized corporate entities (such as the IASB, the FASB, etc.). • Assumes that such bodies can know the consequences of their actions • History does not support the proposition • Balancing Cartesian design vs. Darwinian evolution • Hayek’s spontaneous emergence Sunder, Research for Accounting Policy

5. Specialization in Setting Standards • Specialist standard setting bodies, standing ready to address new problems, inquiries and requests for clarifications help improve financial reporting • Their existence encourages a new “clarification” game targeted at them • They must keep a full agenda (performance) • Revenue and budget pressures • Over time, their output must accumulate to a thick rule book Sunder, Research for Accounting Policy

6. What is Good and Bad? • Standard setters can tell which standards are better and why. • Little evidence that they know, or can know • Cost-of-capital is the result of complex interactions among many factors (including accounting) • To what extent can we sort these influences by ex ante analysis and research? Sunder, Research for Accounting Policy

7. Standards Monopolies • Granting monopoly power in a given jurisdiction to standards written by a given body can help improve corporate financial reporting • Informational disadvantage of a monopoly • No opportunity for experimentation • No opportunity to learn from the experience of alternatives • No pressure to do better, or to correct errors Sunder, Research for Accounting Policy

8. Competition and Race to the Bottom • A regime that encourages reporting entities to choose among the standards written by competing organizations (and paying them a royalty for the privilege) induces a “race to the bottom” to devise less demanding standards • Counter examples (Stock exchanges, bond rating services, appliance standards, college accreditation, bank regulation, corporate charters across U.S. states, etc.) • Research on tendency of race to the bottom (or top)? Sunder, Research for Accounting Policy

9. Force and Effectiveness • Increase in the power of enforcement behind authoritative standards improves compliance and quality of financial reporting • Increased enforcement also increases resources devoted to evasion • Do draconian punishments induce better behavior • Comparison of evidence from domains of crime, alcohol and drug abuse Sunder, Research for Accounting Policy

10. Effectiveness of Statutory vs. Common Law Approaches • The quasi-statutory approach to setting accounting standards dominates a common law approach to financial reporting • Evidence? • Constitution (U.K., U.S., Europe) Sunder, Research for Accounting Policy

11. Written Standards Dominate Social Norms • Written standards backed by power of enforcement work better than unwritten social norms backed only by internal and external informal sanctions • Social norms govern great parts of our lives including many aspects of law • Insider trading • Guilty beyond reasonable doubt • Private commercial codes (cotton, diamond trades) Sunder, Research for Accounting Policy

12. Who defends the middle ground? • The ideal accounting regime would consist of all written standards or all social norms • Easier to make the extreme cases for standards or norms alone • Difficulty of defending the middle ground where both may co-exist, as they do in many other aspects of life • Most of our models tend to be linear and monotonic in decision variables Sunder, Research for Accounting Policy

13. What is New?: Historical Analysis • Did financial reporting and governance problems originate in the 20th century • History tells us otherwise • E.g., governance problems of the East India Company • Clive, Hastings, and the Company’s Court of Directors • Evolution of internal directives, financial reporting and auditing Sunder, Research for Accounting Policy

14. Financial Reporting is Getting Better • Has eighty years of standardization of financial reports (in U.S.) helped improve the quality of financial reporting? • Evidence? • Is a thicker (or thinner) rule book indication of better financial reporting? • Perfect correlation between accounting and stock returns? • How do we judge if our financial reports are getting better? Sunder, Research for Accounting Policy

15. Fewer Alternatives, Better Reports • Fewer the alternative treatments the reporting entities are allowed to choose from, the better the quality of financial reporting • Fewer alternatives also tie the hands of the management of well-run companies who may wish to signal their confidence, competence and prospects by choosing reporting practices others find difficult to emulate • Spence on signaling Sunder, Research for Accounting Policy

16. Auditor’s Bargaining Power • Do well-specified standards enhance the bargaining power of the auditor vis-à-vis the client? Reduce their legal liability? • Standards also encourage clients to demand: show me the rule • Reduced reliance on judgment • More detailed the standards, greater the part of accountant’s work that can be replaced by a computer, and lower the value of the service Sunder, Research for Accounting Policy

17. Accounting & Auditing Games • Written standards constrain the tendency of managers, auditors and investment bankers to play accounting and auditing games • On the contrary, they encourage and facilitate game-playing by reducing uncertainty about what is, and is not, acceptable • 3 percent SPEs => Enron • Does codification of GAAP serve as a roadmap for evasion to guide the financial engineers? Sunder, Research for Accounting Policy

18. Individual responsibility • Written financial reporting standards strengthen the individual responsibility of managers, auditors, and investment bankers for fair representation • On the contrary, they may undermine individual responsibility for fair representation and the big picture by shifting attention to meeting the letter, not spirit, of the specific provisions and their wording • John C. Burton (1975) on “true and fair” override Sunder, Research for Accounting Policy

19. Education • Written standards make it easier to educate better accountants and attract talent to the profession • Written standards may also degrade the class room from reasoning and intellectual debate to rote memorization, reinforce street image of accounting as boring and mechanical • They make it less attractive to young talent Sunder, Research for Accounting Policy

The Problem of Setting Efficient Standards Calling for Research • Criteria • Generation of alternatives • Evaluation of alternatives • Complex interactions among accounting, capital and labor markets financial engineering • Facilitation of evolution of accounting norms • Balancing statutory and common law • Balancing adjustment speed and errors of policy • Extent of standards, and consequences for personal responsibility • Command-and-control (nanny knows all) or bottom up (laissez faire) or some combination of the two? What combination? Sunder, Research for Accounting Policy

Command & Control Perspective • To develop accounting standards: • A single set (monopoly?) • Of high quality (what does that mean?) • Understandable (to who?) • Enforceable (stick, not social norms) • Global (no clientele or diversity) • Are we willing to explore alternative mind sets about financial reporting through research? Sunder, Research for Accounting Policy

Instruments of social sciences • Analysis of data gathered from the field • Analysis of controlled experiments in the lab or the field • Abstract mathematical analysis • Historical analysis • Introspection • If accounting research is to contribute to policy, we shall have to use all the tools at our disposal as and when necessary • Prior commitment to one or the other tool set is likely to be self-defeating Sunder, Research for Accounting Policy

Way forward: accounting policy beyond social sciences? • Accounting policy includes considerations that go beyond the scope of social sciences • I do not believe that a stable financial system is feasible without broadly accepted social norms of personal responsibility business and accounting community • Our own (academic) community could not function without such norms • We should not expect that written codification of accounting standards to be sufficient to create order in the world of financial reporting, no matter how much resources and power is given to the Boards • They can only do so much. The rest is up to the community of accountants Sunder, Research for Accounting Policy

Research for Accounting Policy