Electronic copy available at: http://ssrn.com/abstract=1952739

1    

The Recognition and Measurement of Liabilities in IFRS

Working Paper – October 2011

Richard Barker r.barker@jbs.cam.ac.uk Judge Business School Cambridge University Anne McGeachin anne.mcgeachin@abdn.ac.uk University of Aberdeen Business School

The authors are grateful for comments from seminar participants at Aberdeen, Cambridge, Edinburgh, ICAS, Oxford and the ASB’s Academic Panel.

Electronic copy available at: http://ssrn.com/abstract=1952739

2    

The Recognition and Measurement of Liabilities in IFRS

Abstract

An important application for financial accounting theory is in accounting standards, for

which clarity of conceptual foundation can be viewed as essential in addressing the practical

complexities of determining financial position and financial performance. Viewed from this

perspective, the recognition and measurement of liabilities in IFRS is inadequately theorised:

there is an absence of coherent and consistently-applied theory in both the conceptual

framework for financial reporting and in accounting standards themselves. Moreover, this

absence does not result simply from a failure to apply theory that is well-established in the

literature. Instead, potentially relevant contributions from the literature are few in number,

largely disconnected from one another, and at best only indirectly focused on the challenge

at hand. In this paper, we focus on measurement theory, which has come to play an

increasingly important role in IFRS, but to an extent that we argue takes it beyond the

boundaries of practical applicability. In contrast, yet for related reasons, a theory of

conservatism has been downplayed in IFRS, in spite of its relevance as a complement to

measurement theory under conditions of uncertainty. Our analysis has implications both for

accounting theory with respect to recognition and measurement and for the application of

that theory in accounting standards.

Keywords

Liabilities; Recognition; Measurement; Conservatism; Conceptual Framework; IFRS.

3    

The Recognition and Measurement of Liabilities in IFRS

1. Introduction

The purpose of this paper is to contribute to accounting theory and financial reporting

practice with respect to the recognition and measurement of liabilities. Our research is

motivated by the observation that IFRS is inadequately theoretically grounded in this area.

Without formal explanation or justification, IFRS standards and proposals contain multiple

different methods of recognising and measuring liabilities, with inconsistencies among these

methods and with no two standards or proposals adopting the same method.

We question why such diversity exists. Does it imply inappropriate application by the IASB

of established theory, or inadequately developed theory? We do not find answers to either of

these questions in the literature. Indeed, potentially relevant contributions from the literature

are few in number, largely disconnected from one another, and at best only indirectly focused

on the challenge at hand.

The paper is structured as follows. In the next section, we set out our research motivation,

data and method. Our paper is both theoretical and (qualitatively) empirical. The paper is

empirical in so far as we treat the text of IFRS as qualitative data, against which we test the

IASB’s application of measurement theory. The paper is theoretical in so far as we seek to

analyse and develop recognition and measurement theory and to identify normative

implications.

Drawing upon the literature, we set out in Section 3 an analysis of theory concerning the

recognition and measurement of liabilities. We focus on a specific interpretation of

4    

‘measurement theory’, the primary insights of which, for the purposes of our paper, can be

summarised as follows.

The process of measurement requires the existence of a currently observable measurement

attribute. The future cannot be observed directly, and therefore it is not possible to measure

directly attributes that are expected to exist in the future. In particular, future cash flows are

not currently measurable. What can be measured is a currently-held expectation of a future

cash flow, as for example captured in a market price. In this case, while a currently

observable measurement attribute does exist, the measurement is of current expectations, not

future cash flows. Viewing measurement in this way, and noting that expectations are

inherently subjective, an important question is whether (and if so in what way) it is

appropriate to base the balance sheet valuation of liabilities upon expectations.

In Sections 4 and 5, we apply our analysis to, respectively, the theoretical position that is

stated in the IASB’s conceptual framework (IASB, 2010; hereafter ‘Framework’)1 and to

IFRS standards and proposals. The IASB’s approach can be characterised as one of

presuming measurability for all liabilities. We argue that the distinction between the

‘measurable’ and the ‘immeasurable’ noted above provides insight into the limitations of this

approach.2 In particular, there exist categories of liabilities which, for good informational

reasons, are recognised in IFRS, yet for which measurement theory provides no support.

Accordingly, we set out in Section 6 implications for extending accounting theory with

respect to the recognition and measurement of liabilities. In particular, we identify that a

theory of conservatism has been downplayed in IFRS, in spite of its relevance as a

complement to measurement theory under conditions of uncertainty. We conclude the paper

in Section 7, identifying potential avenues for revisions to IFRS and for further research.

5    

2. Research Method

Our motivation for this paper arises from the IASB’s inconsistent approach to liability

recognition and measurement. The evidence for this inconsistency is found in our source

data, which comprise all accounting standards, exposure drafts and discussion papers issued

(or revised) by the IASB concerning the recognition and measurement of liabilities, coupled

with all public-record comment letters sent to the IASB in response to these pronouncements.

These data are summarised in Table 1.3 Taken together, these documents comprise a rich

source of information. They contain not only the formal requirements of IFRS, but also the

IASB’s formal explanations for these requirements. Through the issues raised by each

document, the changes made from previous documents, and the responses of stakeholders,

these documents also help to reveal areas of tension and challenge, together with the reasons

why these challenging situations are perceived to exist, and the extent to which they are either

similar or different in nature across accounting standards.

** Insert Table 1 here **

At first sight, it is surprising that the IASB, with the benefit of extensive stakeholder

engagement, is knowingly inconsistent4 in the development of IFRS. To understand how this

has happened on such a widespread basis, we sought to analyse the theoretical foundations of

recognition and measurement in IFRS. This process initially involved considerable iteration

between our source data and the literature, as we sought to develop a theoretical framework

with which to address the inconsistency that we observed in practice (Van de Ven, 2007). As

will be explored in Sections 3, 4 and 5, we found that we were able to achieve traction on our

research question by focusing on measurement theory. Specifically, we first test

measurement theory against IFRS data, which leads us to conclude, as will be argued in

Sections 4 and 5, that the application of this theory in IFRS is flawed.5 We then argue that a

6    

direct implication of this conclusion is a need for new theory to complement that which is

already evident in IFRS. In seeking to contribute to theory development in this way, our

analysis of measurement theory suggested a natural path to follow. We argue that the limited

applicability of measurement theory is manifest for liabilities to a greater degree than for

assets, and that conservatism in accounting is the underlying reason for this. Yet the IASB’s

application of measurement theory has led it to reject conservatism as being nothing more

than biased measurement, instead of adopting theory to rationalise the presence of

conservatism. We will argue in Section 6 that, under conditions of measurement uncertainty,

a theory of conservatism is required. We also argue that this position finds support in the

literature.

Our paper therefore focuses on two theories in accounting: measurement and conservatism.

We argue that the former is used incorrectly in IFRS and is not applicable to all liabilities,

while the need for the latter is unacknowledged in IFRS. While these conclusions help to

explain the extant inconsistencies in IFRS, they do not in themselves lead to comprehensive,

normative prescriptions for liability recognition and measurement in IFRS.

Acknowledgement of the limitations of measurement theory implies a need for an alternative

theory, which is provided only partially by extant theory concerning conservatism.

The paper now proceeds as follows. Drawing upon the academic literature, Section 3

provides a summary of relevant aspects of recognition and measurement theory, with a

particular focus on contrasting a measurement perspective with an informational perspective.

Sections 4 and 5 then apply this analysis of theory to, respectively, an evaluation of the

Framework, and to the requirements or proposals issued by the IASB. We argue that our

analysis contributes considerably to understanding extant inconsistencies in IFRS. In Section

6, we then discuss the implications of our analysis for conservatism in accounting. Section 7

concludes the paper.

7    

3. Extant Recognition and Measurement Theory

The literature contains many theoretical papers and other contributions, published over

several decades, relating primarily to the recognition and measurement of assets (for

example, Edwards and Bell, 1961; Sterling, 1970). Relatively little has been published

specifically addressing liabilities.6 There are perhaps two reasons for this. First, when

addressing value attributes, it is natural and intuitive to think first of assets. Second, if a

liability is conceptualised as the opposite of an asset, then an analysis of assets can simply be

viewed in the mirror for the purpose of analysing liabilities. We will argue later in the paper

that this reasoning is insufficient for the theoretical analysis of liabilities. In this section,

however, we are concerned with summarising the extant literature, and so our analysis views

liabilities as the mirror-image of assets.

The mirror-like relationship between assets and liabilities is perhaps most straightforward in

the case of a simple, fixed-rate bank loan, which, as an asset (liability) in a bank’s

(borrower’s) accounts, is a right to receive (obligation to transfer) economic benefits: the

liability mirrors the asset, and the accounting for each counterparty can be expected to be

identical. 7 Moreover, and as set out in Table 2, for any measurement attribute of an asset,

there is an analogue for a liability (see also Baxter, 1975; Nobes, 2001; Lennard, 2002;

Horton et al., 2011). Taking, for example, the first two cases in Table 2, the exit value for an

asset is likely to differ depending upon whether it derives value from being held (value-in-

use) rather than through exchange with a market participant (fair value). Analogously, the

exit value for a loan held as a liability is either, respectively, the present value of contractual

payments (cost of performance) or the amount for which the loan could be exchanged in the

capital market (fair value). The third case in Table 2 (cost of release) is also an exit value

attribute, being the amount that the counterparty is contractually obliged to accept, at the

balance sheet date, in full settlement of the outstanding balance.8 The fourth case, in contrast

8    

to the first three, is an entry cost. For a bank loan held as an asset, the analogue here is the

amount that the entity would expect to receive if it chose to replace an existing loan. This

amount can be termed current equivalent proceeds. Cases five and six in Table 2 are hybrids

of the above (Macve, 2010).

** Insert Table 2 here **

This theoretical consistency holds in spite of data limitations that may exist in practice. For

many liabilities, for example, a cost of transfer may not exist. Such a case might arise in

practice for liabilities where inflows occur in advance of performance, for example

performance obligations arising from revenue contracts with customers (Samuelson, 1993).

The difference here from the earlier case of the bank loan is that, while there is an inflow of

economic benefits, the liability is in the form of a performance obligation (an expected

outflow of goods or services), rather than a contractual future cash outflow.9 Such

obligations typically have unique, entity-specific attributes, and there may be no readily

available way of transferring the liability, and hence no cost of transfer. For other liabilities,

there is no cost of release. This is often the case of with provisions,10 which typically have

either no underlying contract (e.g. lawsuits) or else a contract with effectively no current exit

option (e.g. pension obligations in most jurisdictions). Moreover, provisions can in general

be viewed as liabilities for which the debit entry on initial recognition is not an asset with an

observable value, such as cash.11 Hence there is no observable entry value. Indeed, in a case

such as a lawsuit, there is arguably no entry value at all, because there is no inflow of

resource; so the only applicable measurement attribute is exit value.

In principle, these observations concerning the data limitations for liabilities could also be

said to hold for some assets. This is illustrated in Table 3, which summarises the four

possible cases concerning the availability of entry and/or exit prices. The case of the bank

9    

loan is the simplest, where both entry and exit values are observable. For many fixed assets,

there is likely to be an observable entry value without an observable exit value, where value

is derived in use. In contrast, the example of an asset generated by (some) share-based

compensation illustrates the case of an exit value that is observable with an entry value is not

observable. Finally, the case where neither value is observable is possible for certain

intangible assets, such as internally-generated brands. Overall, therefore, there is not an in-

principle difference in the four categories in Table 3 between assets and liabilities.

** Insert Table 3 here **

Further, in practice, for both assets and liabilities, and where only the entry value is

observable, a typical, implicit assumption is that of an exchange of equal value. This means

that the (unknown) value of the asset or liability can be set equal to the (known) value of the

corresponding side of the double entry: assets are valued at the cost of resources sacrificed

and liabilities are valued at the value of resources received. This approach of indirect, proxy

measurement can be argued to provide the prevailing logic of historical cost accounting

(Paton, 1922; Sterling, 1970). Equally, if an observable exit value exists but there is no

observable entry value, the exit value can act as a proxy for the entry value. The assumption

of an exchange of equal value does not, however, provide an answer for the final case in

Table 3, which is when neither the entry value nor the exit value is currently observable. In

principle, recognition in this case would require that the value of the asset or the liability

must, in some way, be estimated. This creates a problem. As will now be discussed, on the

interpretation of measurement theory presented in this paper, such values are not actually

measurable but are instead estimates based only on forecasts. This is a point of considerable

importance for this paper, and so the remainder of this section is devoted to exploring it

further.12

10    

There is no universally accepted definition of measurement. A standard reference is Stevens

(1946), who defines measurement as any process of ‘the assignment of numerals to objects or

events according to rules.’ This definition has been criticised for being too loose, because it

allows more or less any assignment of numbers to categories to be defined as measurement,

even if the underlying method of assignment is inherently arbitrary (Lord, 1953). On this

basis, any number reported in a financial statement is by definition a measure, based as it is

upon the application of a rule, in the form of an accounting standard. If the concept of

measurement is to have any analytical traction, something more is required.

Deeper insight comes from considering the process of measurement, which can be broken

down into three stages: definition of the attribute to be measured, determination of the

quantum (or measurement scale) and application of a measurement instrument to the item in

question (Vehmanen, 2007). It is only the third of these stages that is empirical. While the

measurement attribute and the measurement scale can be determined in principle, the

application of a measurement instrument can only be done in practice, and it requires the

existence of a currently observable measurement attribute. This is an essential point.

Measurement is straightforward in certain cases, such as cash, or assets and liabilities with

observable market values in active markets, or where there exist certain contractual

commitments at the balance sheet date.13 Yet if, for example, the attribute to be measured is

the cost of performance, and the quantum is money, then a fundamental problem arises,

which is that a measurement instrument cannot be applied. This is because future cash flows

are not currently observable. The cost of performance therefore cannot, in the sense

described here, be measured: the future does not currently exist, and so future cash flows are

immeasurable (Chambers, 1998; Rosenfield, 2003).

The concept of measurement error is likewise inapplicable to the (non-existent) future. While

there is likely to be estimation error in practice for the measurement of any currently

11    

observable item, the item is nevertheless in principle measurable (Morgenstern, 1950). This

measurement is also in principle verifiable and it can therefore be considered to be objective

(McKernan, 2007). In contrast, forecast error is not measurement error; it is instead the

difference between a current forecast and a future realisation that does not yet exist. And to

the extent that any given forecast is a matter of individual opinion about something that is

unobservable, it is subjective and cannot be verified.14 Moreover, while measurement can be

viewed, in the simplest case, as relating to a single, measurable amount, forecasts can be

conceptualised as a probability distribution, making the perceived economic value of the

asset or liability equal to expected value. The values determined by measurement and by

forecasting are therefore different in nature.

It is essential here not to confuse the data in a forecasting model, with which a cost of

performance can be determined, and future data themselves, which do not currently exist

(Winston, 1988). It is possible to use a model to determine the expected value of future cash

flows, and while the future cash flows themselves do not exist, the currently-held

expectations do, and so they are in principle measurable. Sterling (1970) cautions that these

expected values, based upon forecasts, are ‘not a measurement of wealth unless one defines

wealth as a state of mind,’ and an important question is therefore whether (and if so in what

way) it is appropriate to base the balance sheet valuation of liabilities upon measures of

expectations.15

It is in this context that the market mechanism comes into play as a measurement instrument,

because market prices provide observable and verifiable evidence of currently-held

expectations. In effect, the market transforms subjective expectations about the future into

currently observable amounts. In contrast, certain other types of expectation, such as those

underpinning management’s forecast of the cost of performance, are not directly observable

12    

in practice, meaning that they cannot be measured, and that they are subjective and non-

verifiable (Nagel, 1986).16

A further consideration is that measurement can be of different types. Stevens (1946) noted

the existence of ‘different kinds of scales and different kinds of measurement, not all of equal

power and usefulness.’ He proposed a classification of these scales into four types: nominal,

ordinal, interval and ratio. Chambers (1964, 1965) noted that the secondary metrics common

in accounting, such as net assets, leverage and return on equity, are conceptually valid only if

there is ratio measurement, which is the most demanding category in Stevens’ typology.

Moreover, for this purpose, there must be only a single measurement attribute used for all

assets and liabilities, because core properties of additivity and ratio measurement would

otherwise not hold (Chambers, 1998; Barth, 2006).

This strict measurement perspective can be contrasted with an informational perspective

(Christensen, 2010a). While not tightly defined, an informational perspective views

accounting information as part of a broader information set, providing one source of input to

users’ economic decision-making. Proponents of this perspective would argue that, given the

inherent practical difficulties of a strict measurement perspective under conditions of

imperfect and incomplete markets, it is inappropriate to rule out of consideration value

attributes that are not strictly measurable (Beaver and Demski, 1974; Beaver, 1989), nor to

automatically disallow mixed measurement. In particular, an informational perspective

would suggest reporting information relevant to the sustainable economic performance of the

entity, as opposed to a stricter statement of financial position at the balance sheet date,

especially where that statement does not capture the economic choice that is likely to be

undertaken by the entity (Macve, 2010; Whittington, 2010). An informational perspective

would in principle allow the recognition of assets and liabilities that are not strictly

measurable, for example because recognition of such items is necessary for the timely

13    

recognition of unrealised gains and losses, an important part of accruals accounting (Ball and

Shivakumar 2005).17

In summary, it has been argued here that liabilities are in principle direct analogues for assets,

even though the practical context for recognition and measurement may differ. (We discuss

the implications of that practical context in Section 6.) We argue that an important

conceptual distinction can be made between a measurement perspective and an informational

perspective. It is only in the former domain that the language and method of measurement

can be used without reservation or contention. The implication is that measurability cannot

be universally presumed to exist. Assets or liabilities may nevertheless be deemed to exist

even if their values cannot be measured, and information pertaining to them may be useful

even though it is inevitably subjective.

The next sections of this paper apply the analysis from this section to the current

requirements or proposals concerning the recognition and measurement of liabilities in IFRS.

Our aim is to test whether there is valid application of measurement theory in IFRS. We

present our analysis in two parts, which are the theoretical foundations of liability

measurement in the Framework (Section 4) and theory and practice in accounting standards

themselves (Section 5).

4. Recognition and Measurement Theory in the Conceptual Framework

It is striking, and perhaps revealing with respect to theoretical foundations, that the IASB’s

Framework provides remarkably little guidance on recognition and measurement, even

though it is clear on the importance of both factors for effective financial reporting. To the

14    

extent that the Framework does reveal the IASB’s position, the communication is often

implicit.

A liability is defined in the IASB’s Framework as ‘a present obligation of the entity arising

from past events, the settlement of which is expected to result in an outflow from the entity of

resources embodying economic benefits.’ The Framework also states that ‘a liability is

recognised in the balance sheet when it is probable that an outflow of resources embodying

economic benefits will result from the settlement of a present obligation and the amount at

which settlement will take place can be measured reliably’ (italics added). There are

therefore two recognition thresholds in the Framework: first, that an outflow of resources is

probable and, second, that measurement of the settlement amount is reliable.  

While a liability is defined in the Framework as an expected outflow of resources, the

probable outflow recognition threshold constrains the practical applicability of this definition.

It does so by excluding outflows that are unlikely to happen. This exclusion is not precise, in

that ‘probable’ is not defined, although an interpretation such as ‘more likely than not’ is

consistent with both the Framework (Botosan et al, 2005) and with the binary nature of

recognition (an item is either recognised or it is not).

Viewed in terms of the analysis in Section 3, the concept of ‘probable’ is explicitly concerned

with unobservable future cash flows, and therefore with the absence of strict measurability at

the balance sheet date, and yet the definition also calls for reliable measurement. There is a

prima facie conflict here. It is possible, for example in the case of a liability that is a

derivative financial instrument, to have a currently observable market price, and so objective

measurement, yet for it to be probable that there will not be an outflow of resources. It is also

possible, for example in the case of a provision, for the liability to not be reliably measurable

and yet for it to be (subjectively) determined that there is a probable cash outflow. The point

15    

is that the probability threshold is relevant when there is not reliable measurement, and vice

versa.

To illustrate, consider Table 4. In the case of the simple bank loan, both recognition

thresholds are crossed and recognition is unambiguous. Likewise, for a contingent liability,

neither is crossed, and non-recognition is unambiguous.18 The interesting cases are when one

threshold is crossed and the other is not, which ought to lead to non-recognition under the

Framework, but where the opposite conclusion seems to be the more tenable (indeed, and as

will be discussed in Section 4, it is the opposite conclusion that is reached in practice in

IFRS; Murray, 2010). These cases are the derivative with an improbable outflow and the

provision with no observable measure. In the former case, if a currently observable, reliably

measurable liability exists at the balance sheet date, it is difficult to argue that it should not be

recognised. In the latter case, if the definition of a liability is met, and there is the

expectation of an outflow of resource, then it is difficult to argue that the aims of financial

reporting are best met by non-recognition.

** Insert Table 4 here **

The problem is that probable outflow and reliable measurability are both treated by the

Framework as necessary conditions for recognition, when either could be sufficient in itself.

This is made clear in Figure 1, which is proposed as an alternative to the current recognition

thresholds in the Framework. Consistent with the Framework, a prerequisite for recognition

is meeting the definition of a liability. The first filter thereafter is whether there is a probable

outflow, and if there is then the liability is recognised. Critically, this filter is only necessary

when the recognised liability is a subjective forecast of future cash flows, as in the case of a

provision. If, in contrast, the market mechanism has transformed uncertain future cash flows

into quantified risk and thereby created an observable measure, then the probable outflow

16    

threshold is not needed. The second filter is reliable measurability, with the effect that all

reliably measurable liabilities are recognised. If Figure 1 is applied, three of the four

categories in Table 4 now lead to recognition, as opposed to only one under the Framework.

All probable outflows are recognised (not just those that are reliably measurable) and all

reliably measurable liabilities are recognised (not just those with a probable outflow).

Contingent liabilities that cannot be measured reliably and do not have a probable outflow

continue to remain unrecognised, and the imprecise nature of ‘probable’ outflows remains as

a pragmatic recognition threshold for immeasurable liabilities. The imprecision is an

unavoidable corollary of immeasurability: while recognition is desirable, precision is in

principle unobtainable.

** Insert Figure 1 here **

A possible difficulty with this approach is the inclusion of probable outflows that are not

observable and therefore not reliably measurable, which conflicts with the traditional

emphasis on reliability in financial accounting. The analysis of measurement theory in

Section 3 suggests that this difficulty is unavoidable if forecasts are to be recognised in

financial statements. In its revision to the Framework, however, the IASB has adopted an

approach of attempting to avoid the unavoidable, by effectively broadening its definition of

reliable measurement to encompass subjective forecasts. Specifically, the 2010 Framework

revision replaces ‘reliability’ with ‘faithful representation’, the components of which are

completeness (representation is not partial), neutrality (there is no intended bias) and freedom

from error (the item portrayed is the economic phenomenon in question). As the following

extract makes clear, faithful representation is considered to be applicable even when

observable measurement is not possible.

17    

Faithful representation does not mean accurate in all respects ... For example, an

estimate of an unobservable price or value cannot be determined to be accurate or

inaccurate. However, a representation of that estimate can be faithful if the amount is

described clearly and accurately as being an estimate, the nature and limitations of

the estimating process are explained, and no errors have been made in selecting and

applying an appropriate process for developing the estimate.

There is confusion here between faithful representation of the process of determining an

estimate, and faithful representation of the balance sheet item itself. The absence of an

unobservable price or value means that the amount in question cannot in principle be

verifiably complete, neutral or free from error, no matter what process is applied in its

determination. Curiously, the IASB even appears to have acknowledged this point in the

above quotation but nevertheless to have persisted in disconnecting faithful representation

from observability. The Discussion Paper that preceded the revised Framework had included

the notion of verifiability, but then dropped it, as explained in BC3.36: “some respondents (to

the DP) pointed out that including verifiability as an aspect of faithful representation could

result in excluding information that is not readily verifiable ... (which) would make the

financial reports much less useful. The Board agreed and repositioned verifiability as an

enhancing qualitative characteristic, very desirable but not necessarily required.”

Yet verifiability is the essence of objectivity, because it is the basis on which independent

observers can reach the same measurement (Sterling, 1970; Nagel, 1986). In relegating the

requirement for verifiability, the applicability of the IASB’s concept of faithful representation

is broadened, while its meaning is weakened. Viewed in terms of Table 4, the approach fails

to make the distinction between items that are reliably measurable and those that are not, but

instead creates a concept that embraces both categories.19 If the concept of faithful

representation is, in this way, allowed to embrace both objective, verifiable measurement and

18    

subjective forecasts, then it cannot in principle be tightly defined. This is, in effect, an

informational perspective, not a measurement perspective.20

The IASB’s approach to faithful representation is not inconsistent with its own definition of

measurement, but this is only because that definition is similarly loose. The Framework states

that “Measurement is the process of determining the monetary amounts at which the elements

of the financial statements are to be recognized and carried in the balance sheet and income

statement.” (para. 99) Under this definition, anything that ends up being recognised in the

financial statements has been though some (undefined) process of measurement. Equally, a

‘numerical depiction’ can be deemed to be faithfully representational even if it cannot in

principle be verifiably complete, neutral or free from error. In short, these definitions

broaden, and so weaken, the definition of measurement to the extent that it loses any effective

meaning.

Elsewhere in the Framework also, the distinction made in Section 3 between the measurable

and the immeasurable is conspicuous by its absence. The Framework’s definitions of

measurement and measurement attributes suggest that little consideration was given (in the

1989 text, still extant) to the concept of measurement, and that the ‘measurement as

numerical depiction’ approach was pervasive.

The Framework (implicitly) defines the measurement attribute as the settlement amount. Yet

the notion of settlement is ambiguous because it could be interpreted either as settlement at

the balance sheet date or settlement in due course of business. This is a distinction analogous

to that between value-in-exchange and value-in-use, as applied to assets. The Framework

appears to endorse both interpretations, because it describes measurement bases applicable to

each. Specifically, settlement at the balance sheet date is implied by ‘current cost’, which is

described as follows: ‘Liabilities are carried at the undiscounted amount of cash or cash

19    

equivalents that would be required to settle the obligation currently.’ For settlement in due

course, there are two measurement bases, one undiscounted and the other discounted. The

former, somewhat confusingly, is ‘settlement value’ and is described as follows: ‘the

undiscounted amounts of cash or cash equivalents expected to be paid to satisfy the liabilities

in the normal course of business.’ The latter, ‘present value’, is the ‘present discounted value

of the future net cash outflows that are expected to be required to settle the liabilities in the

normal course of business.’ Finally, the Framework includes a further measurement attribute,

which fits the criteria of strict measurability, yet is not current. This is historical cost, which

is described as follows: ‘liabilities are recorded at the amounts of proceeds received in

exchange for the obligation, or in some circumstances (for example income taxes), at the

amounts of cash or cash equivalents expected to be paid to satisfy the liability in the normal

course of business.’

A single measurement attribute could in practice be measured directly or indirectly, making

the application of more than one method of measurement conceptually acceptable, as is

explicit in IFRS 13 (Fair Value Measurement).21 There is no evidence, however, that such a

perspective is intended in the Framework. A more plausible interpretation is that the

Framework offers neither a single, unambiguous measurement attribute, nor a relationship

between such an attribute and applicable methods of measurement. Moreover, the Framework

contains only a limited discussion of measurement methods. It is silent on: first, whether a

liability is initially recognised at an amount identified in an exchange transaction or else as a

forecast of future cash flows; second, whether the carrying amount is revised as expected

cash flows change; third, whether a liability is valued at the most likely settlement amount or

instead the expected value of future cash flows; fourth, whether there is discounting at any

specific rate; fifth, whether there is an adjustment for risk.

20    

In conclusion, we cannot reconcile the IASB’s approach in the Framework with the analysis

of measurement theory outlined in Section 3. If liabilities are to be recognised in cases where

the desired measurement attribute is not observable, which suggests a latent informational

perspective, then one of two approaches is possible. The first is that adopted by the IASB,

which is to adopt a notion of faithful representation that is broad enough to encompass both

amounts that are measurable and amounts that are not. Such an approach has been argued

here to be inadequate, because it does not allow analytically coherent distinctions to be made.

The second approach is to apply the notion of faithful representation only when it is

theoretically valid to do so, meaning that immeasurable items are excluded. This leaves open

the question of how to account for these items, for which the theory of measurement cannot

be a sufficient foundation. We will return to this theme in Section 6. We first address, in the

next section, the application of measurement theory in accounting standards themselves.

5. Consistency of IFRS Requirements with Underlying Theory

While the Framework can be viewed as an expression of the theoretical foundations of IFRS,

it has three limitations in this respect. First, while partially revised in 2010, much of the

extant text is over twenty years old, dating from 1989. Second, the Framework exists only to

provide general guidance, and it does not have the authoritative status for financial reporting

practice of accounting standards themselves. Third, the Framework is a fairly short

document, without the richness and depth of accounting standards. In this section, we

therefore extend our testing of measurement theory to the IASB’s requirements in standards

for liability recognition and measurement, including proposals for new standards. The

recognition and measurement requirements of all of these IASB pronouncements is

summarised in Table 5. In line with the structure of that table, the subsections below discuss

21    

recognition first, followed by measurement. The analysis of measurement considers first the

objective of measurement, followed by the existence of observable measures and then the

approach taken by the IASB when the measurement attribute is unobservable.

** Insert Table 5 here **

Probability recognition threshold

The first issue we consider is that of a probability recognition threshold. As discussed above,

such a threshold is included in the Framework. Yet it is present in only one IASB

pronouncement other than the Framework (column 1 in Table 5), in IAS 37. Moreover, the

EDs of amendments to IAS 37 (2005 and 2010) propose removing the threshold, which, if

enacted, would result in the Framework being the sole outlier.22   In this context, the IASB has

stated ‘The IASB regards aligning IAS 37 with other IFRSs - so that all liabilities are

recognised - as more important than preserving consistency with all aspects of the existing

20-year-old Framework’ (IASB, 2010).

The IASB’s stance is rooted in the belief that all liabilities can be measured, and hence

should be recognised. Under this view, a probability recognition threshold is just an

arbitrary barrier. This is illustrated in the explanation in that applying such a threshold would

result in ‘the flawed conclusion that a performance obligation arising from a guarantee, a

warranty or an insurance contract should not be recognised until it is probable that a claim

will arise’ (IASB, 2006). Here the IASB is rightly saying that a probability threshold is not

needed when there is an observable measurement (an entry value in these cases). However,

the IASB also claims that a probability threshold would be inconsistent with a measurement

based on the probability-weighted average of expected cash flows (IASB, 2006), a claim that

fails to recognise that, in the sense described in Section 3, there can be no strict measurement

22    

based on estimates of expected future cash flows and that it is precisely in such cases that a

probability threshold has a role to play.

The difficulty here seems to have been recognised instinctively by respondents to the 2005

ED, albeit without clearly articulating the source of the problem. In contrast to the IASB’s

clear wish to remove the threshold (except for leases), many respondents to the IAS 37 EDs

opposed its removal, particularly in the context of single liabilities not held in a portfolio of

similar liabilities. Their consensus view was that the probability recognition criterion is a

useful screen to exclude items from the balance sheet when it is uncertain whether a present

obligation exists, or for liabilities for which there is only a low or remote likelihood of a

future cash outflow from the statement of financial position.

The analysis here suggests an absence of theory concerning liabilities that are not strictly

measurable. The IASB’s response has been to assert, incorrectly, the applicability of

measurement theory in this context. The IASB’s stakeholders have instinctively opposed this

approach. While not explicitly theoretically grounded, the stakeholders’ viewpoint is

consistent with the implications for financial reporting of the analysis of measurement theory

in this paper.

Reliable measurement threshold

As with the probability threshold, despite the fact that a reliable measurement threshold exists

in the Framework, it is rare in standards on liabilities (column 2 in Table 5). The criterion

that the liability is capable of reliable measurement is explicit only in IAS 37 and in specific

parts of IAS 19.23   Elsewhere, it is assumed to be met. IAS 37 mirrors the Framework, both in

requiring a liability to be recognised only if the obligation can be estimated reliably, and also

in noting that the use of estimates is an essential part of the preparation of financial

statements and does not undermine their reliability. It goes on to state that this is especially

23    

true of provisions, even though by nature they are more uncertain than most other items in the

statement of financial position. It concludes that, except in extremely rare cases, an entity

will be able to determine a range of possible outcomes and can therefore make an estimate of

the obligation that is sufficiently reliable to use in recognising a provision. In short,

measurability is typically presumed.

This contrasts with the requirements for assets in IAS 38, where it is acknowledged that for

internally-generated goodwill and some internally-generated intangible assets, it is not

possible to determine reliably either an entry value (cost) or an exit value. Such assets are

thereby not recognised. The IASB does not explain why it believes that liabilities such as

provisions can be measured more reliably than assets such as internally-generated goodwill.

Moreover, the IASB does not make a distinction between estimates and forecasts, where the

former are in principle measurable while the latter are not.

Again, the evidence here is that of inadequate theoretical foundations: measurability is

assumed inappropriately for certain liabilities, and also, without explanation, measurability is

assumed to differ between assets and liabilities.

Specified measurement objective

As noted in Section 3, the Framework is ambiguous with respect to whether the objective of

measurement concerns settlement currently or in due course, and four measurement bases for

liabilities - historical cost, current cost, settlement value and present value - are duly offered

that support either interpretation.

In the accounting standards themselves, there is not always a specified measurement

objective. Indeed, it is remarkable that, whenever an objective is stated, it is in each case

different from any objective stated elsewhere (column 3 of Table 5). Further, none of these

24    

objectives is described in the same terms as any of the measurement bases described in the

Framework. This appears to suggest an extraordinary lack of conceptual clarity.

Although the stated objectives in the standards, exposure drafts and discussion papers are all

different in some way, they fall into three groups: fair value, cost (subsequently amortised

cost), and the amount the entity would rationally pay at the end of the reporting period to be

relieved of the present obligation (or similar wording). The first, fair value, is an observable

measure if there are active markets. However, the IASB also requires fair value in situations

where there are no active markets, at which point it ceases to be observable. The second,

cost, is an observable measure on initial recognition, but amortised cost in subsequent periods

need not be. The third group, the amount the entity would rationally pay at the end of the

reporting period to be relieved of the present obligation, is the definition that the IASB has

developed for liabilities for which it wishes to recognise a cost of performance. Establishing

such a definition goes some way towards the appearance of an observable measure, because it

transforms expectations about future cash flows into a current attribute. However, as with

fair value, only the existence of an active market can transform those subjective expectations

into an observable measure.

The third group of objectives, based as they are on attributes that are not observable, have in

general not been supported by IASB constituents, who have been on the whole unconvinced

by the IASB’s definition of cost of performance. For example, IAS 37 (1998) gives a

measurement objective of the best estimate of expenditure required to settle the present

obligation at the end of the reporting period. It states that this is the amount that an entity

would rationally pay to settle the obligation at the end of the reporting period or to transfer it

to a third party at that time. In the 2005 ED of amendments to IAS 37, the objective was

clarified as being the amount the entity would rationally pay at the end of the reporting period

to be relieved of the present obligation (Rees, 2006). Although the IASB regarded this as a

25    

clarification of the original measurement objective, many respondents disagreed. They argued

that existing IAS 37 does not require the use of a transfer amount and that an amount that the

entity would pay to transfer or settle the liability at the reporting date is not a relevant

measure for a liability that is almost certainly going to be discharged when it falls due. In

other words, they instinctively opposed the attempt to transform cost of performance from an

estimate of future cash flows into a current attribute. Nonetheless, in the 2010 ED of

amendments to IAS 37, the IASB continued to aim for a strict measurement perspective,

proposing that an entity should measure a liability at the amount that it would rationally pay

at the end of the reporting period to be relieved of the present obligation. Again, the strict

adherence here to the language of measurement, and the presumed generalisability of

measurement, contrasts sharply with stakeholders’ practical instincts and concerns, with the

latter being explicable in terms of the theoretical analysis in Section 3.

Link to transaction amount

One aspect of liability measurement that is not discussed in the Framework, but that has a

strong influence in the IASB’s standards and proposals, is whether the amount initially

recognised should be linked to an amount observed in a transaction. There is an obvious

difference between those liabilities where initial recognition is at an amount identified in an

exchange transaction, as opposed to cases where determination of an amount to be recognised

relies on estimates of future cash flows (column 4 in Table 5).

Liabilities for which an initial measure can be identified in an exchange transaction are

covered by IFRS 9, the insurance contracts ED and the revenue recognition ED. In all these

cases, the initial measurement of the liability is linked to the amount identified in the

exchange transaction (albeit only after substantial debate in the insurance project). In terms

of measurement theory, these proposals could be characterised as a preference for an

observable measure over a forecast of future cash flows.

26    

Using an observable transaction price, when one exists, does not solve the problem of what to

do when one does not exist, or if it is thought desirable to remeasure the liability subsequent

to initial recognition. In these cases, and in the absence of active markets, there is no

observable measure. Nonetheless, the IASB has shown little inclination to take a pure

measurement approach by thereby not recognising a liability. Rather, as discussed above, it

has tried to extend a measurement approach to the cost of performance by defining it as a

current attribute. In the absence of active markets or specific transactions, however, the cost

of performance is not an observable measure. This lack of observability leads to problems

for the IASB in specifying how the amount it wishes to be recognised should be determined.

We discuss these problems next.

Cash flows

If cost of performance could be observed, there would be no need to consider what cash

flows should be included in its measurement. Because it cannot be observed, the IASB has

specified that the probability-weighted average of all possible cash flows (expected value)

should be used (column 5 of Table 5), arguing that this is necessary to meet the measurement

objective of an amount that the entity would pay to transfer or settle the liability at the

reporting date (for example, 2005 and 2010 EDs of amendments to IAS 37). This approach

has been generally accepted when there is a portfolio of similar liabilities to be measured.

However, in relation to single liabilities, respondents to the IAS 37 EDs disagreed with use of

expected value and the proposed measurement objective, arguing that that the most relevant

information is given by the best estimate of what the cash flows ultimately will be.

The debate over expected value illustrates clearly the IASB’s confusion over measurement.

The IASB has repeatedly argued that expected value is necessary to arrive at a meaningful

measure, whereas under a strict measurement perspective the question would never arise. In

turn, the IASB’s constituents are not persuaded by the IASB’s desire to follow its perceived

27    

principle of measurement. Ironically, many of them regard this approach as too driven by

theoretical but impractical concepts.

Discount rate

As with cash flows, if cost of performance could be observed, there would be no need to

consider what discount rate to use. However, because it cannot, this has become a major

issue in the measurement of liabilities. IFRSs, EDs and DPs are uniform in their

requirements and proposals that all measures that are based on estimates of future cash flows

should be discounted, whenever the impact of discounting is material (except for IAS 12).24

There are differences, however, on which discount rate to use to reflect the time value of

money (column 6 of Table 5).

There is one (almost) universal feature, which is that all the discount rates being considered

by the IASB are current rates. The only exception to this is the rate proposed in the leases

ED.25 However, even having established an almost common approach to including the time

value of money, further questions arise as to how this should be done. For example the

insurance contracts DP and ED raise the issue of the liquidity characteristics of the liability

and propose that the discount rate should reflect the liquidity characteristics of the item being

measured. All other IFRS, EDs and DPs are silent on this issue.

So the question of the discount rate illustrates another aspect of the problems facing the IASB

when there is no observable measure. Even if there is consensus on the principle, how much

guidance is needed on how the amount to be recognised should be determined?

Risk adjustment

The final set of problems relate to adjustments for risk. There are differences in IFRS on

whether to include a risk-adjustment for the uncertainties surrounding the cash flows and, if a

28    

risk-adjustment is included, what the objective of the risk-adjustment is, how to treat

diversifiable risk, and how to treat credit risk (column 7 of Table 5).

As with the cash flows and discount rate, the question of the effect of risk would not need to

be considered if cost of performance were an observable measure. But as with the previous

issues the IASB has had to consider the effect of risk in trying to extend measurement theory

to the cost of performance. It has been a particular issue in the IAS 37 and insurance

contracts projects, both of which require/propose an adjustment for risk, but only after

significant debate and disagreement over its objective and the impact of diversifiable risk

(IAS 37 2010 ED, Insurance Contracts ED). The IASB’s arguments are all expressed in

terms of achieving the stated measurement objective (IAS 37 2010 ED). In contrast,

respondents to the proposals both in the IAS 37 project and the insurance project are

generally much more concerned with the practical aspects of how such an adjustment should

be made, and whether it can be determined in a reliable and comparable way. In doing so,

they are implicitly acknowledging the difficulties that arise because the measurement

objective is not an observable measure.

Finally, the inclusion of own credit risk in the measurement of a liability is a controversial

subject. IAS 37 is silent on the matter. The insurance DP (2007) argued that credit

characteristics should be included in the measurement of an insurance contract liability. In

2009, IASB issued a staff-developed DP on the subject that set out some common views on

credit risk. The responses to the DP demonstrated clearly that most respondents took an

informational approach to the issue. The responses indicated that, broadly, constituents

wanted to include credit risk when a liability was assumed in an exchange transaction with an

observed price, yet did not want to include it in the measurement of a liability if its effects

had to be estimated rather than included in an observed price. Consistency of measurement

29    

across different liabilities was not an overriding concern; indeed, it was down the list of

priorities.

As a result of these responses, the IASB decided not to continue with a standalone project on

own credit risk. Instead it decided to consider credit risk in the conceptual framework

measurement project and on a standard-by-standard basis. In 2010, it issued the ED of

amendments to IAS 37 that remained silent on credit risk, and the insurance contracts ED that

includes it only in the residual margin that calibrates the liability measurement to the

transaction price.26

A general conclusion here is that while the IASB’s thinking can be characterised by

adherence to a presumed generalisability of measurement, the concerns of stakeholders arise

when the boundaries of the applicability of measurement theory are reached. While certain

aspects of financial reporting practice are adequately theorised from a measurement

perspective, others require adoption of an informational perspective, from which theorising is

notable for its absence. In the next section, we therefore turn to the need for new theory to

complement that which is already evident in IFRS. We note that this need for new theory is

greater for liabilities than for assets, primarily because the practice of conservatism has

greater consequence for liabilities in terms of the applicability of measurement theory.

6. The Need for Additional Theory

The analysis in Sections 4 and 5 has applied measurement theory to identify areas of tension

and inconsistency in IFRS. It was argued in Section 4 that a probable outflow recognition

threshold is not needed when recognition is restricted to items that are reliably measurable,

but that it has a role to play when strict measurement is not possible. The IASB has in effect

avoided this issue by means of a broad definition and interpretation of measurement, and

30    

thereby a presumption of measurability for all recognised items. The consequences of this

position, as discussed in Section 5, have included disagreement with stakeholders over both

the probable outflow recognition threshold and the boundaries of measurement. The IASB’s

position has also generated confusion through the conflation of measurement objectives that

are in practice measurable (fair value when active markets exist or cost) with those that are

not (the amount that an entity would rationally pay to be relieved of the liability). While the

IASB describes all three of these objectives as measurable, the third is an amount based on

forecasts rather than on observable measurement, and it therefore introduces the subjective

complexities of probability distributions of expected cash flows, discount rates and risk

adjustments.

If recognition was in practice restricted to items that are observable, and so in principle

reliably measurable, these tensions and inconsistencies would not arise. In other words, the

central problem is that IFRS requires items to be recognised even though they cannot be

reliably measured. A central question, therefore, which we address in this section of the

paper, is why such recognition is required in the first place.

This question is particularly important for liabilities. This is in part for practical reasons. An

important difference between assets and liabilities is that entry values are more likely to be

observable for assets, because their acquisition is usually associated with the sacrifice of

monetary resource.27 This makes both entry valuation and indirect exit valuation relatively

difficult to attain for liabilities than for assets. The recognition of a provision, for example, is

not triggered by a transaction stated in monetary terms. In other words, while (as argued in

Section 3) measurability may be no different in principle between assets and liabilities, it is

likely to be more problematic in practice for liabilities.28

31    

There is also an important theoretical reason for the required recognition of immeasurable

liabilities, but not of immeasurable assets. We have so far argued, in Section 3, that

measurement attributes for assets are in principle the mirror-image of those for liabilities, and

that while the theoretical literature has focused mainly on assets, this is understandable in the

absence of anything conceptually distinctive about liabilities. Sections 4 and 5 have shown,

however, that recognition is in practice required for liabilities that cannot strictly be

measured, and for which theoretical support therefore needs to come elsewhere than from

measurement theory. We will now argue that this theoretical foundation concerns

conservatism, the implications of which are different for liabilities than for assets.

Conservatism is the differential verifiability required for the recognition of gains and losses,

whereby expected losses are recognised with less verification than expected gains (Basu,

1997; Watts, 2003a). Hence, while conservatism makes it possible to argue against

recognising asset values that are based upon forecasts, the same need not apply to liabilities.

Rather, conservatism would encourage their recognition. Referring back to Table 3, if, in

practice, entry values and exit values are unavailable, the principle of conservatism is

conventionally applied. In the case of a lawsuit, for example, a liability of uncertain amount

is typically recognised in the accounts of the defendant, while, even with no difference at all

in either the amount under consideration or the associated uncertainty, an asset is typically

not recognised in the accounts of the plaintiff. Consistent with this reasoning, it was argued

in Section 4, using Table 4, that the Framework’s recognition criteria for liabilities would be

conceptually more coherent if there was recognition when an outflow of resources is probable

(as well as for all measurable liabilities, see Figure 1). In contrast, the practice of

conservatism for assets means that a ‘probable inflow’ recognition threshold would not be

needed, thereby simplifying the algorithm in Figure 1 to the questions of definition (does an

asset exist?) and measurement (can the asset be measured reliably?). In summary,

32    

conservatism creates a challenge that is specific to liabilities, because, in contrast with assets,

it leads to their recognition even when they cannot strictly be measured. This distinction

between assets and liabilities is based upon verifiability, which makes the application of

conservatism inseparable from issues of measurability.

To some extent, conservatism has been viewed in the academic literature as evidence of

tradition and convention, rather than as a practice that can be justified conceptually (Sterling,

1970). In contrast, a more recent strand in the literature has provided theoretical support for

conservatism. In particular, a contracting explanation (Watts, 2003a) identifies a need for

conservatism as a means of addressing the moral hazard that arises when management and

investors have asymmetric information and asymmetric payoffs. Central to this explanation is

the role of verifiability, because it is optimal for contractual metrics to have a higher standard

of verifiability for assets than for liabilities. Empirical evidence supports both the existence

of conservatism and the contracting explanation (Basu, 1997; Watts, 2003b; Ryan, 2006;

LaFond and Watts, 2008; LaFond and Roychowdhury, 2008; Giner et al, 2011).

The IASB has explicitly rejected conservatism, however, through its use in the Framework of

the language of measurement, by which anything that is deemed to be representationally

faithful is treated conceptually as a measure. In evaluating conservatism as a candidate for

‘an aspect of faithful representation,’ the Framework (BC3.27) argues that its inclusion in this

regard would be ‘inconsistent with neutrality.’ Yet the Framework defines neutral

information as ‘without bias,’ which has little practical meaning when applied to unverifiable

subjective estimates. In explicitly ruling out conservatism in this way, the Framework argues

from a position that is tenable only when there is reliable measurement, and yet the theory of

conservatism outlined above applies only when there is not reliable measurement.29 The

Framework therefore dismisses conservatism on inappropriate grounds, misinterpreting it as a

deliberate process of biased measurement, rather than (in the context of liabilities) as a

33    

justification, based upon asymmetry of information and payoffs, for recognising probable

outflows in the absence of observable measurement.30

Conservatism is also not used to support IASB proposals for requirements in standards, even

when it would be a natural argument to use. For example, in terms of conservatism, not

having a probability recognition threshold for liabilities is more conservative than having

one. But the IASB does not use conservatism as a justification for the proposed removal of

the threshold from IAS 37. All its arguments are based on the view that liabilities can be

measured, and therefore should be recognised. Conservatism also could be used as an

argument in discussions of credit risk. The IASB is aiming for a measurement attribute of the

amount that an entity would pay to transfer or settle the liability at the reporting date. This

would include the effect of its creditworthiness. However, conservatism would argue against

recognition of a liability at the smaller amount caused by including the effect of credit risk

and recognition of a gain when an entity’s creditworthiness decreases. Although the IASB

seems willing to accept its constituents’ dislike of the inclusion of credit risk (which is surely

in part derived from a desire for conservatism), it does not use conservatism to justify this

departure from its stated measurement objective.

It is only in the insurance and revenue recognition projects that conservatism is

acknowledged as a desirable attribute, albeit not by name. The basis for conclusions to the

insurance contract DP argued that the observed price for the transaction with the

policyholder, although useful as a reasonableness check on the initial measurement of the

insurance liability, should not override an unbiased estimate of the amount another party

would require to take over the insurer’s contractual rights and obligations. The justification

for the IASB’s change from this approach in the insurance ED was the desire to avoid day

one gains, consistent with the revenue recognition project.

34    

While conservatism does not find theoretical endorsement in IFRS, it is nevertheless

prevalent in accounting standards themselves, and it is therefore in practice consistent with

the theory outlined above from the literature. A simple need, therefore, is to embed a theory

of conservatism from the literature into IFRS. Where the literature falls short in this regard,

however, is that it is insufficiently normative. Empirical evidence points to the existence of

conservatism in practice, and underlying theory explains this practice in terms of economic

benefits. This is a positive approach, describing and attempting to explain behaviours that

have evolved in practice. Yet standard setting is a normative activity. It exists as a market

intervention, as a mechanism of policy with the explicit aim of creating outcomes that the

market itself would not be expected to generate. Viewed in this light, the literature leaves

several questions unanswered. There are therefore implications for future research, as will be

discussed in the final section of the paper.

In conclusion, the argument here is that there is a role for conservatism, both in the theory of

recognition and measurement, and also in practice in IFRS, yet this role is denied by the

Framework and elsewhere in IFRS. While the literature provides some insight into a theory

of conservatism, there is a need for further normative contributions to inform the

implementation of conservatism in accounting standards.

7. Conclusions

We set out to understand why IFRS contains multiple and inconsistent recognition and

measurement requirements for liabilities. We apply measurement theory to extant and

proposed IFRS, identifying where the theory can be said to hold and where it cannot. We

argue that, while measurement attributes for liabilities are conceptually analogous to those for

assets, measurement is relatively problematic for liabilities in practice, primarily because

35    

conservatism encourages the recognition of liabilities that have no observable measure.

However, the IASB does not acknowledge either the limitations of measurability or the

existence of conservatism. This leads the IASB to seek all its answers within the context of

measurement, thereby missing the opportunity to adopt insights resulting from a theory of

conservatism. In contrast, conservatism has become increasingly important in the literature,

in particular in positive empirical studies. The literature does not, however, offer a

sufficiently normative theory of conservatism, and it therefore falls short from the perspective

of adoption by the IASB in the Framework and in accounting standards. Our paper therefore

has implications for both revisions to IFRS and for further research.

The implications for revising IFRS are as follows. First, measurement should be defined

more tightly in the Framework, in line with the analysis in Sections 3 and 4. This tightening

would make verifiability a necessary requirement for reliable measurement, in contrast with

the present state where verifiability is ‘desirable but not necessarily required.’ The tightening

would also clarify that the notion of faithful representation relates uniquely to observable

amounts, and cannot in principle relate, as in the present Framework, to the faithful

description of the process of forecasting an unobservable amount. Second, the recognition

thresholds in the Framework should be re-defined in line with Figure 1 and the associated

analysis in Section 4. Accordingly, all measurable amounts would be recognised, with the

probable outflow recognition threshold being reserved for immeasurable amounts. Third, the

probable outflow recognition threshold should be justified conceptually in the Framework.

Such justification cannot in principle be based upon measurement theory, for the reasons

argued in Section 4. Instead, and as argued in Section 6, a theory of conservatism is required

in IFRS, for which the literature provides a foundation. Fourth, and in line with the analysis

in Section 5, individual accounting standards should make a clear distinction between

amounts that are measures and those that are forecasts.

36    

Beyond these proposed changes to IFRS, there is also scope for further improvement, yet for

this to be possible there is a need for a normative theory of conservatism. Meeting this need

is an implication of the paper for further research. The potential for research in this area can

be illustrated with two examples.

The first example concerns the degree of differential verifiability that IFRS should require for

the recognition of gains and losses, and the extent to which this should vary in different

applications. For practical purposes, accounting standards need to specify not just whether

conservatism should be applied, but also to what degree. This requires understanding the

informational value of conservatism in different settings, for example where asymmetries of

incentives and information are likely to arise and why. One possible line of enquiry, which

addresses the underlying behavioural aspects of conservatism, is suggested by decision

theory. The concept of Choquet expected utility concerns decisions that are made in the

absence of a known distribution, where a decision-maker’s utility is a function of his or her

degree of ambiguity aversion, which in turn determines the desired level of conservatism

(Gilboa and Schmeidler, 1989). In this setting, which can be modelled analytically and/or

tested experimentally, the level of ambiguity can be determined endogenously by the game-

theoretic actions of other players, and so it enables analysis not just of information

asymmetry but also of incentive asymmetry.

The second example concerns financial statement presentation, in particular whether amounts

recognised conservatively should be presented differently from amounts that can be

interpreted as unbiased measures. On this question, a normative approach would seek to

develop financial statement presentation in a way that is currently not required. In this

context, an implication of the IASB’s presumption of measurability is the effective denial of

the role of forecast error in balance sheet valuation, because errors are presumed to arise from

measurement alone (Christensen, 2010b). Viewed from this perspective, the probable

37    

outflow recognition criterion appears unacceptably imprecise and arbitrary. Indeed, it is not

needed if all liabilities are viewed as measurable. Yet if the concept of forecast error is

acknowledged, amounts recognised on the basis of an estimated probable outflow provide

useful information, albeit of a different nature than measurable amounts. Management’s

willingness and ability to forecast future outcomes provide information both ex ante, at the

time of the forecast, and ex post, in comparing the outcome that was forecasted with that

which ultimately arose. Acknowledgement of the role of forecasting error, and of a

distinction in financial statement presentation between measures and forecasts, and between

ex ante forecasts and ex post forecast revisions, would enhance the informational usefulness

of the financial statements (Barker, 2004; Glover et al, 2005).

In conclusion, our paper is motivated by extant and important conceptual inconsistencies in

IFRS, for which the literature offers limited directly relevant analysis. We seek to apply

measurement theory in order to explain these conceptual inconsistencies, which leads to three

conclusions: first is the need to revise the treatment of recognition and measurement in IFRS,

in order to make it consistent with measurement theory; second is the need to introduce a

theory of conservatism in IFRS, in order to justify financial reporting practice than cannot be

explained by measurement theory; and third is the need to develop a normative theory of

conservatism in the literature, in order to enable and justify a greater impact on policy and

practice.

38    

References

Ball, R., and L. Shivakumar (2005). The role of accruals in asymmetrically timely gain and loss recognition. Journal of Accounting Research 44, pp. 207-242.

Barker, R. (2004). Reporting Financial Performance. Accounting Horizons, 18(2), pp. 157-172.

Barth, M. (2006). Including Estimates of the Future in Today’s Financial Statements, Accounting Horizons, 20(3), pp.271-285.

Basu, S. (1997). The conservatism principle and the asymmetric timeliness of earnings. Journal of Accounting and Economics, 24, pp. 3-37.

Baxter, W.T. (1975). Accounting Values and Inflation. London: McGraw-Hill.

Beaver, W. H. and J. S. Demski. (1974). The nature of financial accounting objectives: A summary and synthesis. Journal of Accounting Research, pp. 170-187.

Beaver, W. (1989). Financial Reporting: An Accounting Revolution. Englewood Cliffs, NJ: Prentice-Hall.

Beaver, W. (1991). Problems and Paradoxes in the Financial Reporting of Future Events. Accounting Horizons, 5 (4), pp.122-134.

Botosan, C., L. Koonce, S. Ryan, M. Stone and J. Wahlen (2005). Accounting for Liabilities: Conceptual Issues, Standard Setting, and Evidence from Academic Research. Accounting Horizons, 19(3), pp. 159-186.

Chambers, R. (1965). Measurement in accounting. Journal of Accounting Research (Spring), pp. 32-62.

Chambers, R. (1998), Wanted: Foundations of Accounting Measurement, Abacus 34(1), pp. 36-47.

Christensen, J. (2010a). Conceptual Frameworks of accounting from an information perspective, Accounting and Business Research, 40(3), pp. 287-299.

Christensen, J. (2010b). Accounting Errors and Errors of Accounting, Accounting Review, 85(6), pp. 1827-1838.

Colson, R. et al. (2010). Response to the FASB’s and the IASB's joint discussion paper entitled preliminary views on revenue recognition in contracts with customers: American Accounting Association's Financial Accounting Standards Committee (AAA FASC). Accounting Horizons (December), pp. 689-702.

Edwards, E.O. and P.W. Bell (1961). The Theory and Measurement of Business Income, University of California Press.

Gilboa, I. and D.Schmeidler (1989). Maxmin Expected Utility with a Non-Unique Prior. Journal of Mathematical Economics, 18, pp. 141-153,

39    

Giner,B., A. Tahoun and M. Walker (2011). Do cross-country differences in accounting conservatism explain variation in the degree of investor international diversification; working paper.

Glover, J., Y.Ijiri, C. Levine and P. Liang (2005). Separating Facts from Forecasts in Financial Statements. Accounting Horizons, 19(4), pp. 267-282.

Gray, R. (2003). Revisiting Fair Value Accounting––Measuring Commercial Banks’ Liabilities Abacus 39(2), pp. 250-61.

Horton, J., R. Macve and G. Serafeim (2011). Deprival Value vs Fair Value Measurement for Contract Liabilities in Resolving the Revenue Recognition Conundrum: Towards a General Solution; working paper.

IASB (2010). The Conceptual Framework for Financial Reporting. London: IASB.LaFond, R., and Watts, R. (2008). The information role of conservatism. Accounting Review, 83(2), pp. 447-478.

LaFond, R., and Roychowdhury, S. (2008). Managerial ownership and accounting conservatism. Journal of Accounting Research, 46(1), pp. 101-135.

Lennard.A. (2002). Liabilities and how to account for them: an exploratory essay. London: ASB.

Lipe, R. C. (2002). Fair valuing debt turns deteriorating credit quality into positive signals for Boston Chicken. Accounting Horizons (June), pp. 169-181.

Lord, F. (1953). On the Statistical Treatment of Football Numbers. American Psychologist, 8 (12), pp. 750–751

Macve, R. (2010). The Case for Deprival Value. Abacus, 46(1), pp. 111-119.

McKernan, J. (2007). Objectivity in Accounting. Accounting, Organizations and Society, 32, pp.155-180.

Miller, P. (1998). The Margins of Accounting. European Accounting Review, pp. 605-621.

Morgenstern, O. (1950). On the Accuracy of Economic Observations. Princeton, NJ: Princeton University Press.

Murray, D. (2010). What are the Essential Features of a Liability? Accounting Horizons, 24(4), pp. 623-33.

Nagel, T. (1986). The view from nowhere. New York: Oxford University Press.Nobes, C. (2003). Liabilities and their measurement in UK and international standards. London: ACCA.

Paton, W. (1922). Accounting theory, with special reference to the corporate enterprise. NY: Ronald Press.Rees, H. (2006). The IASB’s Proposed Amendments to IAS 37. Accounting in Europe, 3, pp. 27-34.

Power, M. (2004). Counting, control and calculation: reflections on measuring and measurement. Human Relations, 57(6), pp. 765-782.

40    

Rosenfield, P. (2003). Presenting discounted future cash receipts and payments in financial statements. Abacus 39(2), pp. 233-249.

Ryan, S. (2006). Identifying Conditional Conservatism. European Accounting Review, 15(4), pp. 511-525.

Samuelson, R. (1993). Accounting for Liabilities to Perform Services. Accounting Horizons, 7(3), pp. 32-45.

Sterling, R. (1970). Theory of the Measurement of Enterprise Income. Lawrence, KA: University of Kansas Press.

Stevens, S. (1946). On the Theory of Scales of Measurement. Science, 103, pp. 677–680.

Van de Ven, A. (2007). Engaged scholarship. Oxford: Oxford University Press.

Vehmanen, P. (2007). Measurement in Accounting and Fair Value. In P. Walton (Ed.), The Routledge Companion to Fair Value and Financial Reporting (pp. 152–172). Routledge.

Watts, R. (2003a), Conservatism in accounting Part I: Explanations and implications, Accounting Horizons, 17, pp. 207-221.

Watts, R. (2003b), Conservatism in accounting Part II: Evidence and research opportunities, Accounting Horizons, 17, pp. 287-301.

Whittington, G. (2010). Measurement in Financial Reporting. Abacus, 46(1), pp. 104-110.

Winston, G. (1988). The Treatment of Time in Economics. In Winston, G. And R. Teichgraeber (Ed.), The Boundaries of Economics (30-52). Cambridge: Cambridge University Press.

41    

Figure 1: Recognition Algorithm (Liabilities)

Does the item meet the definition of a

liability?

No

Do not recognise

Yes

Is an outflow probable?

Yes

No

Recognise Is the item reliably measurable?

No Do not recognise

Yes

Recognise

42    

Table 1: IFRS Sources on Liability Recognition and Measurement

Date Comment letters End of comment period

Framework 198931 N/A N/A

IAS 12 Income Taxes 199632 N/A N/A

IAS 17 Leases 1997 N/A N/A

IAS 19 Employee Benefits 1998 N/A N/A

IAS 37 Provisions, contingent liabilities and contingent assets

1998 N/A N/A

IFRS 2 Share-based payments 2004 N/A N/A

IFRS 4 Insurance contracts 2004 N/A N/A

IAS 37 ED June 2005 123 Oct 2005

Insurance contract DP May 2007 162 Nov 2007

Revenue recognition DP December 2008 211 [July 2009 Board paper]

June 2009

Pensions DP (for contribution-based promises)

March 2009 150 Sept 2009

Leases DP March 2009 302 July 2009

Credit risk DP June 2009 123 Sept 2009

IAS 37 ED/Working draft of revised standard

January 2010 211 May 2010

Revenue recognition ED June 2010 973 Oct 2010

Insurance contracts ED July 2010 248 Nov 2010

Leases ED August 2010 760 Dec 2010

IFRS 9 Financial Instruments October 2010 (liabilities)

N/A N/A

 

43    

Table 2: Assets vs Liabilities - Measurement Attribute Analogues

Measurement Attribute Assets Liabilities

1. Current holding value

Value-in-use

(Entity-specific present value of expected economic benefits)

Cost of performance

(Entity-specific present value of economic benefits expected to be consumed in settlement of the liability)

2. Current market exit value

Fair value

(The price that would be received to sell an asset in an orderly transaction between market participants at the measurement date.)

Cost of transfer (fair value)

(The price that would be paid to transfer a liability in an orderly transaction between market participants at the measurement date.)

3. Current contractual exit value

Cost of liquidation

(The amount that the entity is currently, contractually obliged to accept to liquidate the asset.)

Cost of release

(The amount that the entity is currently, contractually entitled to pay in full settlement of the liability.)

4. Current entry value Replacement cost

(The outflow of economic benefits that would be required to replace the service potential of the existing asset).

Current equivalent proceeds

(The inflow of economic benefits corresponding to the current replacement of the liability).

5. Mixed measurement: exit value

Recoverable amount

(Higher of value-in-use and value-in-exchange)

Settlement amount

(Higher of cost of performance or cost of release)

6. Mixed measurement: entry and exit value

Deprival value

(Lower of replacement cost or recoverable amount)

Relief value

(Lower of current equivalent proceeds of settlement amount)

44    

Table 3: Measurement Attributes on Initial Recognition33

Is an exit value observable?

Yes

No

Is an entry value observable?

Yes

Asset: Bank loan Liability: Bank loan

Asset: Some intangible assets and specialised PPE Liability: Performance Obligation

No

Asset: Donated assets Liability: Some shared-based payments

Asset: Some intangible assets Liability: Provisions

45    

Table 4: Recognition Thresholds

Is the liability reliably measurable?

Yes

No

Is an outflow of resource probable?

Yes

Bank loan

Provision

No

Derivative financial liability with market price but improbable

outflow34

Contingent

Liability