No. 104
Managerial Discretion in Accounting
for Defined Benefit Obligations:
An Empirical Analysis of German
IFRS Statements
Marcus Salewski, Henning Zülch
December 2010
A survey conducted by the Chair of Accounting and Auditing
at HHL – Leipzig Graduate School of Management
supported by „Bertelsmann Business Consulting GmbH“
HHL-Arbeitspapier
HHL Working Paper
No. 104
Managerial Discretion in Accounting
for Defined Benefit Obligations:
An Empirical Analysis of German
IFRS Statements
Marcus Salewski, Henning Zülch
ISSN 1864-4562 (Online version)
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Marcus Salewski/Henning Zülch
Managerial Discretion in Accounting
for Defined Benefit Obligations
An empirical analysis of German IFRS statements
Abstract: This paper aims to make a first contribution to the determination of that proportion of the defined benefit obligation (DBO) to be disclosed in the notes which can be attributed to managerial discretion in IFRS
statements by capital market oriented German companies in the period of
2000-2008. For this, actuarial assumptions – discount interest rates, the compensation growth rate and projected future pension increases – are replaced
by their respective industry medians. In a second step we then assess whether
the thus determined discretion component raises the value relevance of the
reported DBO. As a result, we can state that managerial discretion does at
least not downgrade the value relevance of the DBO. In our view, this can
be explained by the fact that the management possesses private information,
which may become decision useful information when communicated to the
capital market. For the standard setter these results imply that the regulations do not need a further standardization with regard to the actuarial
assumptions.
Keywords: Accounting, Defined Benefit Obligation, Earnings Management,
Earnings Quality, Manipulation of Earnings, Managerial Discretion, Germany, IAS 19, IFRS, Pension Accounting, Value Relevance
JEL Classification M41
1. Introduction
One of the core tasks of the standard setters IASB and FASB is to consider how much
scope for discretion the management should be allowed in the drawing up of a company’s financial statement. On the one hand it is argued that such managerial discretion
could lead to the manipulation of earnings by the management. Thus a significant part
of the literature about international accounting deals with the questions if – and why
– managers manipulate earnings, how they do it and what the consequences of this behavior might be. The results of research in this area are very well summarized in the
survey articles of Schipper (1989), Healy and Wahlen (1999), and Dechow and Skinner
(2000). Other authors believe that managerial discretion serves to communicate the management’s internal information to the statement addressees (Healy and Palepu (1993)).
Thus, the question if the management should be allowed a certain scope of discretion is
mainly a question of whether the advantages of private information being communicated
outweigh the disadvantages created by the management’s opportunistic behavior (Dye
and Verrecchia (1995)).
In the present paper we examine this question by means of a specific accounting parameter - the defined benefit obligation (DBO). On an international level, the accounting
of pensions, which often have a significant influence on the balance sheet structure of
companies, is covered by IAS 19: Employee Benefits. Fundamentally, this regulation differentiates between defined contribution plans and defined benefit plans, a crucial factor
being the economic content of the obligation caused by the company’s pension promises.
Regarding defined contribution plans, the economic obligation resulting from the pension
promise is limited to the payment of a specific sum to an external social security body,
such as a pension fund. These expenses are recorded in the profit and loss statement
with no further balance sheet recognition. In contrast, defined benefit plans, which are
1
the subject of this research, have to be recognized in the balance sheet and also actuarially evaluated. These plans oblige the employer to make payments to the employee after
the occurrence of the insured event. Due to the uncertainty of future events, the sum
of the obligations has to be assessed considering a number of parameters. According to
IAS 19.72, it is imperative to differentiate between demographic and financial assumptions in this context. Amongst the main demographic assumptions relating to defined
benefit plans, IAS 19.72 (a) lists assumptions regarding the employee turnover and the
mortality rate. The financial assumptions essentially comprise, according to IAS 19.72
(b), assumptions regarding the discount rate and the rate of compensation growth and
future pension increases. IAS 19.78 prescribes that the discount rate is to be determined using the return of high-class, fixed interest bearing corporate bonds. If there is
no liquid market for such corporate bonds, the market returns of government bonds
should become the basis for calculation. According to IAS 19.79 , the discount rate only
reflects the time value of money – it does not, per definition, contain any risk component. In general it has to be considered that the different benefit promises have different
durations, which means that different discount rates have to be applied. However, according to IAS 19.80, companies can instead use a single, weighted discount rate reflecting
the settlement dates, the sum and the currency of the benefits to be paid. Regarding
the evaluation of obligations, IAS 19.83 (a) demands that expected future income raises
are to be considered, taking into account inflation, the duration of employment at the
company, promotions, and the structure of supply and demand on the labor market.
Furthermore, adjustments need to be taken into account, which are ascribed to legal or
factual obligations. This is, for example, true if a company has in the past regularly adjusted pension payments by a compensation for inflation. As the determination of both
the discount rate and the rates of compensation growth and future pension increases are
very complex and hardly comprehensible to outsiders, there exists a significant scope of
discretion for the management. This can either be used to communicate decision useful,
2
internal information about the nature of the obligation to the statement addressees, or
to manipulate both the balance sheet structure and the earnings of the company.
Due to extensive criticism of the accounting of pension promises, the IASB incorporated the project post-employment benefits (including pensions)“ into its agenda in July
”
1
2006. However, the managerial discretion examined in this paper has so far not been
discussed by the standard setter. Accordingly, we examine the question whether managerial discretion during the determination of financial assumptions increases or lowers
the value relevance of the disclosed DBO. To this aim, we identify the proportion of the
DBO which is not to be ascribed to managerial discretion by replacing the company
specific assumptions with their respective industry values. The difference between the
disclosed DBO and the identified non-discretionary component constitutes our estimator for that proportion of the DBO which can be ascribed to managerial discretion. By
means of various fixed-effects regressions of our samples, comprising the IFRS statements
of capital market oriented German companies in the period of 2000-2008, we examine the
value relevance of this discretion component. More precisely we examine (1) whether the
discretion component increases the value relevance of the DBO, (2) whether there is a
difference between the periods of the voluntary and the mandatory (from 2005 onwards)
application of IFRS, and (3) whether the funded status of the pension plans influences
the practice of discretion. Accordingly, this paper is structured as follows: chapter ??
provides an overview on the relevant literature, while chapter 3 introduces our research approach. Chapter 4 presents our research results followed by a final conclusion in
chapter 5.
In summary, it appears that the discretion component does at least not downgrade the
value relevance of the DBO. The benefit of communicating private information to the
1
Meanwhile, both a discussion paper and an exposure draft have been published on this topic (see
International Accounting Standards Board (IASB) and International Accounting Standards Board
(IASB))
3
capital market obviously outweighs the possibility of opportunistic behavior on the part
of the management. This result has on the one hand considerable implications for the
process of standard setting in general: Accounting should contain a certain degree of
flexibility, allowing for the management to communicate private information. On the
other hand our result is linked to the IASB’s revision of pension accounting: In the
context of this important project, the standard setters should take care that managerial
discretion is only limited with regard to those aspects in which opportunistic behavior
is proven to predominate.
2. Literature Survey
The literature on international accounting generally subsumes a management’s opportunistic behavior in form of manipulation of the published earnings under the key word
earnings management (a good introduction is provided by the survey articles of Schipper
(1989), Healy and Wahlen (1999), and Dechow and Skinner (2000)). Earnings management is referred to whenever managers apply discretion during financial reporting to
either deceive the statement addressees about the company performance or to influence
specific accounting parameters, which could for example affect performance-based payment components (Healy and Wahlen (1999), p. 368). On the other hand, this discretion
might also serve to communicate company internal, private information to the statement addressees (Schipper (1989), Healy and Palepu (1993), Sankar and Subramanyam
(2001)). This research paper aims to contribute to the debate on how much scope of
discretion should be allowed to the management. This principally means weighing the
benefits of discretion (communication of private information) against their costs (opportunistic behavior by the management) (Dye and Verrecchia (1995)).
4
The majority of works dealing with this subject is based on the model of Jones (1991),
differentiating the accruals by a discretionary and a non-discretionary component.2 Subramanyam (1996), for instance, demonstrates that the practice of discretion on average
increases the value relevance of earnings, whereas Tucker and Zarowin (2006) show that
discretionary income smoothing on the part of the management increases the information efficiency of stock prices. However, Guay, Kothari, and Watts (1996) note that such
a differentiation of accruals tends to be defective, which principally renders the above
statements unreliable.
One possible way of avoiding such defects is to examine specific managerial decision
processes (McNichols (2000)). Some authors, for example, look at the proportion of
loan loss provisions of banking institutions, or alternatively loss provisions of insurance
companies, which can be ascribed to managerial discretion (Wahlen (1994), Beaver and
Engel (1996) und Beaver and Venkatachalam (2003) bzw. Petroni, Ryan, and Wahlen
(2000) und Beaver and McNichols (2001)). The advantage of such an approach is that
the authors can use their expertise in a specific subject area to model the discretionary
component in a more realistic way.
In this present contribution we take a similar step by examining a specific accounting
parameter: the defined pension obligation (DBO). Glaum (2009) offers an overview of
previous research on the subject of pension accounting. The DBO presents itself as
suitable for our analysis due to various factors: On the one hand it has a significant
influence on the companies’ balance sheet structure, on the other hand there exists an
enormous scope for managerial discretion in the determination of its amount. Furthermore, companies have to disclose specifications of the essential parameters determining
the amount of the DBO in the notes of an IFRS statement. Various studies have proven
2
Accruals are defined as the difference between payment surpluses (i.e. incoming payments less outpayments) and profit (i.e. revenues less expenditures). See Jones (1991).
5
that these parameters can vary significantly between companies and that their determination is influenced by the management (Blankley and Swanson (1995), Gopalakrishnan
and Sugrue (1995), Godwin, Goldberg, and Duchac (1996)). Based on Hann, Lu, and
Subramanyam (2007), we thus first determine the non-discretionary proportion of the
DBO by replacing the actuarial assumptions of the management with their respective industry values. The discretionary proportion of the DBO is then deduced by the
subtraction of this sum from the DBO disclosed in the balance sheet notes.
One disadvantage of this approach is inherent in the fact that the amount of the DBO is
only disclosed in the balance sheet notes. Thus our study cannot practically be subsumed
under literature about earnings management, but should rather be seen as a contribution
to accounting management in general. In this context, we must ask ourselves whether
statement addressees appreciate the notes at all, or whether the capital market appraises
them equally to the specifications made in the earnings statement or the balance sheet.
Barth (1991), however, demonstrates that specifications regarding pension obligations
are perceived by the market in a similar way to specifications about other obligations
reported in the balance sheet. We thus believe that our approach is a valuable method
to exploring the question whether the benefit of managerial discretion in accounting
pension obligations outweighs the inherent costs.
3. Research Approach
3.1. Determining the discretion component of DBO
The determination of that proportion of the DBO which can be ascribed to managerial
discretion (henceforth DBOD ) is based on Hann, Lu, and Subramanyam (2007), who
derive the discretionary component DBOD from the difference between the DBO disclo-
6
sed in the notes and that proportion of the DBO which is explicitly not to be ascribed
to discretion (DBOX ). DBOX is determined by replacing company specific actuarial
assumptions with their respective industry medians, as in the following equation 1.3
We thus suggest that the DBO can be defined as4
DBO =
ˆ (1 + g)N )
Pi,r,L (KW
.
(1 + i)N
(1)
In this context, Pi,r,L describes the present value factor of a pension which geometrically
progresses over a period L with an annuity factor r and a discount rate of i, formally
expressed by Pi,r,L =
(1+i)L −(1+r)L
(i−r)(1+i)L
(in contrast to our approach, Hann, Lu, and Sub-
ramanyam (2007) do not take into account the projected future pension increases in
their segmentation of the DBO, which must be considered a weakness of their model).
L defines the average life expectancy of an employee after retirement, K indicates the
proportion of the current wage level W , which is to be paid as a pension in N years.
The factor (1 + g)N is used to anticipate future salary increases. It should be noted that
N has to be equally applicable both to employees and to pensioners - it thus represents
the average, weighted years to retirement of the complete labor pool. In other words,
ˆ (1 + g)N , which has to be
the DBO is the present value of the predicted pension KW
paid over a period of L years after retirement.
Determining the evaluation parameters i, g and r is uncomplicated, as these can be
extracted directly from the notes. This is not possible for L and N , meaning that various
assumptions have to be made:
3
4
We base our classification of industry on the industry sector specifications of the German stock
exchange, see German Stock Exchange (2010).
For reasons of clarity, we suppress both the time index and the company index.
7
Assumption regarding L: In the mid-2000s, the average life expectancy of 65-year-old
men was ca. 16.5 years, that of 65-year-old women about 20 years.5 Thus we assume
an average remaining life time of L = 18 years.
Assumption regarding N: The average age in Germany in the mid-2000s was about
42 years6 , while the average age of retirement was at ca. 62 years7 . This would
mean 20 years to retirement N . Since N refers to both employees and pensioners,
however, we first determine an estimator to identify which proportion of each DBO
is allotted to pensioners. For this purpose, the benefit payments V Z, which were
due in a specific period and disclosed in the balance sheet notes, are multiplied
by annuity present value factors RBF gained from the Professional Association
”
of Mathematics Experts“ of the Commission for Company Pension Schemes Inc.
”
(Arbeitsgemeinschaft für betriebliche Altersversorgung e.v.)“. The proportion of
the DBO allotted to pensioners can thus be defined as
λ=
V Z · RBF
.
DBO
(2)
The proportion allotted to the employees thus amounts to ϕ = 1 − λ. This is
multiplied by the original 20 years to retirement, providing a company- and period
specific estimator for N in dependance to ϕ.
ˆ , all elements of equation 1 are thus either known (i, r and g) or
Apart from KW
ˆ can be determined as follows:
assumed (L and N ). Accordingly, KW
5
6
7
See specifications of the Federal Statistical Office, to be viewed at: http://www.destatis.de/
jetspeed/portal/cms/Sites/destatis/Internet/DE/Content/Statistiken/Bevoelkerung/
GeburtenSterbefaelle/Tabellen/Content50/LebenserwartungDeutschland,templateId=
renderPrint.psml.
See German Federal Statistical Office (2007), S. 44.
See Deutsche Rentenversicherung Bund (German pension fund Bund), S. 68.
8
N
ˆ = DBO(1 + i) .
KW
Pi,r,L (1 + g)N
(3)
If we now replace the actuarial assumptions of the management (i, r and g) in equation
1 by their respective industry medians (i∗ , r∗ and g ∗ ), the result is DBOX , the nondiscretionary proportion of the DBO.
DBOX =
ˆ (1 + g ∗ )N )
Pi∗ ,r∗ ,L (KW
.
(1 + i∗ )N
(4)
By subtracting
DBOD = DBO − DBOX
(5)
we determine the discretionary proportion of pension obligations DBOD .
3.2. Value relevance tests
3.2.1. Preliminary remark
For the purpose of determining the value relevance of managerial discretion in the identification of the DBO, we execute a variety of regressions in which the market capitalization as of December 31st serves as the dependent variable. The use of this variable
9
(in contrast to using returns) is suitable for our study, since we examine the value relevance of a balance sheet item. Furthermore, such a model is in accordance with other
contributions dealing with pension accounting (Hann, Lu, and Subramanyam (2007),
Landsman (1986), Barth (1991), Barth, Beaver, and Landsman (1992)). Such a specification, however, suffers from a number of econometric difficulties, mainly those created
by heteroscedasticity and economies of scale. To account for these problems, all variables are standardized by the revenues. In addition, we apply time fixed effects panel
regressions with White (1980) adjustment.
3.2.2. Influence of discretionary component
First we examine the relative value relevance of the pension obligation with and without
discretion. For this we compare the corrected coefficient of determination R2 as well as
the coefficients of the following models I. and II.
M ARCAPit =
2008
X
αt It + β1 DBOit + β2 P Ait + β3 N Iit + β4 EM Pit
t=2000
+β5 RDit + β6 T Ait + ut
M ARCAPit =
2008
X
(I.)
αt It + β1 DBOX,it + β2 P Ait + β3 N Iit + β4 EM Pit
t=2000
+β5 RDit + β6 T Ait + ut
10
(II.)
M ARCAPit defines the market capitalization as of December 31st, DBOit the defined
benefit obligation, DBOX,it the non-discretionary proportion of the DBO and P Ait
the present value of plan assets to be enclosed. It indicates the time fixed effects. In
addition, we incorporate the following control variables into our model: N Iit defines
the income before extraordinary items, RDit the research and development expenses,
EM Pit identifies the average number of full-time employees during a fiscal year, and
T Ait the total assets. We have incorporated N Iit because Ohlson (1995) has shown that
a correct specification of such a price equation must also consider the profit for the
period. EM Pit and RDit are used to account for the service cost anomaly 8 , while T Ait
serves to accommodate the aforementioned economies of scale.
In a second step we examine the additional explanatory power of the discretionary
component by estimating model III.:
M ARCAPit =
2008
X
αt It + β1 DBOX,it + β2 DBOD,it + β3 P Ait + β4 N Iit
t=2000
+β5 EM Pit + β6 RDit + β7 T Ait + ut
(III.)
In this case, DBOD,it indicates the proportion of the DBO which can be ascribed to
managerial discretion. All other variables are as defined above.
8
The service cost anomaly refers to the unexpectedly positive relation between service costs and stock
price (Barth, Beaver, and Landsman (1992)). Subramanyam and Zhang (2001) demonstrate that the
inclusion of EM Pit and RDit into the regression equation disposes of this anomaly.
11
3.2.3. Transition to mandatory application of IFRS
The number of companies included in our sample increases dramatically with the transition from a voluntary application of IFRS until 2004 to the mandatory IFRS application
for capital market oriented companies from the year 2005 onwards. As it seems likely
that companies make a significantly higher use of discretion in their first application of
IFRS to allow for a good start“ into the accounting by IFRS standards, we estimate
”
the following model IV. and examine whether a difference between these two periods can
be observed:
M ARCAPit =
2008
X
αt It + β1 DBOX,it + β2 DBOD,it + β3 DBOD,it · P ost2004 + β4 P Ait
t=2000
+β5 N Iit + β6 EM Pit + β7 RDit + β8 T Ait + ut
(IV.)
P ost2004 in this case indicates a dummy variable with the value of 1 for all years from
2005 onwards, and 0 for all others. All other variables are as defined above.
3.2.4. Influence of funded status
Companies whose plans are strongly underfunded have, under otherwise equal conditions, stronger incentives to reduce the DBO by a careful choice of actuarial assumptions.
This is why, in a final step, we examine in accordance with Hann, Lu, and Subramanyam
(2007) whether there is a difference with regard to the funded status of the obligations.
We define the extent of underfunding as the non-discretionary proportion of the obligations DBOX less the present values of plan assets to be enclosed (P A), divided by the
12
disclosed DBO. In the following estimation equation V., U F U N D indicates a dummy
variable by the value of 1 if the extent of underfunding is above its median, and 0 if
otherwise:
M ARCAPit =
2008
X
αt It + β1 DBOX,it + β2 DBOD,it + β3 DBOD,it · U F U N D + β4 P Ait
t=2000
+β5 N Iit + β6 EM Pit + β7 RDit + β8 T Ait + β9 U F U N D + ut
(V.)
3.3. Data description
The empirical analysis is based on a sample which consists of the 160 companies from the
main indexes DAX, MDAX, TecDAX and SDAX of the German capital market. These
indexes comprise the largest and most traded German capital market oriented companies
(by market capitalization), which often serve as benchmarks for smaller entities regarding
the application of IFRS regulations. These companies also offer themselves for an analysis
as they are both in the public focus and under observation of analysts.
The limitation to the German capital market offers the advantage that all companies
under consideration come from the same institutional and regulatory environment and
are governed by the same enforcement mechanisms (Ernstberger (2008), p. 14). Furthermore, latest since the late 1990s, sufficient companies have been accounting according
to IFRS, so that there are ample observations to be gathered for the sample. Glaum
(2009) additionally notes that studies about pension accounting have up to this point
almost exclusively been based on US-American data and regulations. We aim to close
this research gap with the present contribution.
13
First of all, in accordance with other studies (see for example Leuz, Nanda, and Wysocki
(2003), Francis and Smith (2005) or Pronobis, Schwetzler, Sperling, and Zülch (2008)),
we eliminate all banking institutions and insurance companies from the sample, as their
balance sheet structure differs fundamentally from the balance sheet structure of other
companies, which would seriously affect the comparability of the various entities. The
basic data of balance sheets and profit and loss statements of the remaining 123 companies were extracted from the Hoppenstedt balance sheet data base, while data about
market capitalization was taken from Thomson Reuters Datastream. However, the relevant specifications made in the balance sheet notes concerning the DBO, the discount
rates, the rates of compensation growth and future pension increases, etc., had to be
handpicked.
Our sample is restricted to the period of 2000-2008. Since not all of the observed companies were accounting by IFRS during all these years, we first gain a basis of 973 firm-years
for our analysis. In a next step, all those observations are eliminated, in which either
the respective company was not capital market oriented or no (alternatively insufficient)
specifications were made regarding the pension obligations. We then determined the industry medians i∗ , g ∗ and r∗ for the years 2000-2008, keeping to the sector classification
provided by the German stock exchange.9 We decided to exclude all those sectors to
which less than five companies could be counted10 , since such a small number of companies cannot provide for the determination of reliable medians. In all other branches, i∗ , g ∗
and r∗ are determined for those years in which observations could be gathered for at least
five companies. All observations to which this does not apply were also eliminated.
9
10
The German stock exchange classifies each of the listed companies as belonging to one of the following
sectors: Automotive, basic resources, banking institutions, chemicals, construction, consumer, financial services, food & beverages, industrial, insurance, media, pharma & healthcare, retail, software,
technology, telecommunication, transportation & logistics, utilities. For further information see ?.
These are, apart from the already excluded sectors banking institutions and insurances: Basic resources, food & beverages, software, technology, telecommunication and utilities.
14
Our sample was thus reduced to 100 companies and 482 firm-years. To account for the
effects of outliers, both the 0.5-percentile and the 99.5-percentile were winsorized (Tukey
(1962), p. 18.).
4. Results
4.1. Descriptive analysis
Companies can influence the total sum of the DBO by choosing actuarial assumptions, with higher (lower) interest or a lower (higher) rate of compensation growth and
future pension increases respectively, resulting in a lower (higher) DBO. According to
IAS 19.120A (n), each company is obliged to specify the evaluation parameters they applied. Table 1 provides an overview on the development of the discount rate, the rate of
compensation growth and of future pension increases on the whole. As the development
pictured in table 1 is aggregated for all industry sectors, observations are also considered here which were later excluded from the study due to the marginal representation of
individual sectors in the sample. It becomes apparent that the development of actuarial
assumptions is certainly taking place in dependance of economic conditions. However,
both the standard deviation and the spread indicate that there are significant differences
between individual companies.
[Table 1 about here]
Table 2 presents the mean value of evaluation parameters differentiated by industry
sectors. It must be noted that for the majority of sectors, the number of companies
sufficient for the determination of the median could only be obtained after the transition
to mandatory IFRS accounting in 2005.
15
[Table 2 about here]
Table 3 provides an overview on the main characteristics of our sample. The variables are
defined as follows: M ARCAP indicates the market capitalization as of December 31st,
T A the total assets, DBO the defined pension obligation, DBOX the non-discretionary
proportion of the DBO, and DBOD that proportion of the DBO which can be ascribed
to discretion. N I identifies the income before extraordinary items, RD indicates the
research and development expense, EM P the average number of full-time employees
during a fiscal year and N the weighted, average years to retirement of the complete
labor pool. All variables apart from EM P and N are divided by the revenues to obtain
standardization.
[Table 3 about here]
4.2. Influence of the discretionary component
Table 4 summarizes the results of the estimations of models I. and II.. The only difference between these two estimations is that the DBO functions as an exogenous variable
in the first estimation, being replaced by the non-discretionary proportion of the DBO
(DBOX ) in the second estimation. All variables in model I. point in the expected direction and are significant on the level p = 0.02%. This is similarly true for model II.,
except that P A is only significant on the level p = 0.1%. The coefficient of DBO (-2.149)
is slightly lower than that of DBOX (-1.964).
[Table 4 about here]
16
Comparing the two models, the R2 offers itself for consideration. At 54.59%, it is marginally higher for model I. than it is for model II. at 54.47%. The three outlined information
criteria also tend to support the strength of model I., which may be seen to indicate that
the capital market actually rewards managerial discretion. However, there are various
econometric difficulties inherent in the simple comparison of the R2 of two models (Greene (2003), p. 152-159 and Kennedy (2008), pp. 87-88). We thus controlled whether the
difference between the R2 is significant on a common level by applying the Vuong (1989)
test, the results of which are summarized in table 5. Clearly positive values in Vuong’s
Z-statistics indicate the superiority of model I., while clearly negative values point to
a superiority of model II.. Accordingly, on a common level of significance we cannot
assume that model I. is superior to model II. (p = 0.203).
[Table 5 about here]
In summary, the results show that managerial discretion does at least not downgrade
the value relevance of the DBO. A superiority in a statistical sense is, however, not
observable.
In a next step, we examined the additional explanatory power of discretion by model
III. The results of this estimation are shown in table 6. Again, all coefficients point
in the expected direction and are significant on the level p = 0.01%. At -5.789, the
coefficient in front of DBOD is about three times larger than the coefficient in front of
DBOX . This result is not unexpected, however, if we look at the dimensions of these
two variables (see table 3). Corresponding to the results of the comparison of model
I. and II., this estimation also demonstrates that the capital market does not punish
managerial discretion in the determination of pension obligations, but on the contrary
rather tends to reward it. In this context it should be noted that the capital market
17
evaluates the component of pension obligations ascribed to discretion similarly to the
non-discretionary component.
[Table 6 about here]
4.3. Transition to mandatory application of IFRS
With the transition from a voluntary to the mandatory accounting by IFRS in the
year 2005, our sample increases significantly. To examine whether the management of
companies accounting by IFRS for the first time made more use of discretion in the
determination of pension obligations, we estimated model IV.. Table 7 summarizes the
results of this estimation. Neither the coefficient for DBOD ( -3.665) nor the coefficient
for DBOD · P ost2004 (-2.521) are significant on a common level. The sum of these coefficients (-6.186), which indicates the coefficient for the whole period of 2005-2008, is
slightly higher than the DBOD coefficient of model III.. However, due to the lack of
significance, these results do not allow the deduction that the coefficient had changed
after the introduction of mandatory IFRS accounting. Overall, we cannot observe that
companies accounting by IFRS for the first time are making a stronger use of discretion.
[Table 7 about here]
4.4. Influence of funded status
The incentives to (downwardly) manipulate the total sum of pension obligations by
a careful choice of actuarial assumptions increase directly in correspondence with the
underfunding of plans. We used model V. to verify this hypothesis, the results being
18
shown in table 8. The coefficient for DBOD is the one indicating the companies with
the least underfunded plans. It is significant at -12.528. The joint coefficient for DBOD
and DBOD · U F U N D is also highly relevant (23.678). This represents the effect on
those companies whose plans are the most underfunded. The capital market takes a
perceivably stronger notice of the managerial discretion wielded by these companies. In
this case, the prefix points to the opposite direction, which suggests a positive relation
between the scope of discretion and market capitalization.
[Table 8 about here]
4.5. The functional determination of DBOD : Opportunities and limitations
It needs to be stressed that the validity of our results is strongly dependent on the
functional determination of the discretionary component of the DBO, which is certainly
not altogether free of mistakes. We are forced to make assumptions that influence the
amount of DBOD , particularly the fundamental assumption that the scope of discretion
might be determined by a deviation from the industry median, as well as the assumptions
regarding life expectancy (L) and the average years to retirement (N ). Thus, estimating
the life expectancy after retirement to a general 18 years is an extreme simplification.
Insofar as there are differences between the various companies under observation (and
undoubtedly there are), DBOD must be flawed. Also, the estimator of the years to
retirement N is based on assumptions, again distorting the determination of the true“
”
discretionary component.
For this reason we estimate another regression equation, identifying the proportion of
DBOD which can be deduced from the basic deviation between the disclosed actuarial
assumptions and the respective industry medians:
19
DBOD,it
∗
∗
= α + β1 (iit − i∗it ) + β2 (git − git
) + β3 (rit − rit
) + ut
DBOit
(VI.)
Table 9 below summarizes the results of this estimation. The coefficients are significant
and point in the expected direction. Furthermore, the R2 value of 97.9% is meaningful.
It indicates that the significantly largest part can be ascribed to deviations between the
disclosed i, g and r and the industry medians of i∗ , g ∗ and r∗ . The results demonstrate
that in this context flawed assumptions about L and N have less influence on the determination of DBOD . DBOD is mainly driven by the deviations between the companies’
actuarial assumptions and the respective branch values.
[Table 9 about here]
To further verify the fault tolerance of our models, we estimated all models for a sample
limited to the years 2005-2008, and also conducted the estimations with and without
winsorizing the upper and lower percentile. For all the tested specifications we received
results of equal quality.
However, we do not want to conceal two further simplifications, which may lead to
erroneous measurements and flawed specifications: In the case of companies providing
both domestic and foreign pension plans, we assumed that the foreign pension plans
may be neglected. Thus the determination of the scope of discretion in the DBO is only
based on domestic actuarial assumptions, regardless of the fact that foreign assumptions
might also play a certain role. We justify this means however by the observation that
only a very small proportion of companies has foreign pension obligations, and that these
are significantly lower than the domestic ones. Regarding the specifications disclosed in
20
the balance sheet notes, it should be stressed that interest rates as well as the rates
of compensation growth and future pension increases are, contrary to the regulations of
IAS 19.120A (n), not always provided in absolute percentages. We are confronted in a few
cases with specifications of a certain (if little) spread. In these cases we simply assume
that the mean of this spread represents the true value of the respective assumptions. This
then is incorporated in the determination both of the industry values and of DBOD .
5. Conclusion
There is a lot of disagreement as to the scope of flexibility a management should be
allowed in their drawing up of IFRS statements. On the one hand it is argued that discretion might be used to manipulate the balance sheet structure and the earnings. Others
believe that discretion may serve to better communicate company internal information
to the statement addressees.
In this present study we take a specific balance sheet item – i.e. the defined pension
obligation (DBO) – to identify that proportion which can be ascribed to managerial
discretion. In doing so, we replace the essential actuarial assumptions – discount rate,
rate of compensation growth and projected future pension increases – by their respective industry medians. We examine whether the thus determined discretion component
increases or decreases the value relevance of the DBO disclosed in the balance sheet
notes.
As a result we can state that the application of managerial discretion at least does not
lower the value relevance. In fact, the capital market seems to even reward the use of
discretion. The option to adapt actuarial assumptions to company specific conditions
is generally welcomed by the capital market. This can partly be explained by the fact
21
that the management has access to private knowledge about the respective obligations
and that the communication of this knowledge to the statement addressees may relay
decision useful information. In addition, our research results demonstrate that there is no
difference in the application of managerial discretion before and after the introduction of
mandatory IFRS accounting for capital market oriented companies from 2005 onwards,
and that, furthermore, companies with distinctly underfunded pension plans tend to
influence their actuarial assumptions to lower the amount of pension obligations more
than others.
These results carry significant implications for the process of standard setting by the
IASB: Accounting should allow for a certain degree of flexibility, granting the management the opportunity to communicate private information to the statement addressees.
Additional implications arise for the revision of pension accounting carried out by the
IASB project post-employment benefits“: In the course of this project, the standard
”
setter should take care to limit managerial discretion only with regard to those aspects
in which opportunistic behavior is proven to predominate (such as in the treatment of
actuarial profits or losses in the balance sheets).
22
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27
A. Appendix
i
2000
2001
2002
2003
2004
2005
2006
2007
2008
Mean
6.10
5.84
5.74
5.46
5.01
4.27
4.44
5.38
5.88
Median
6.00
6.00
5.75
5.50
5.00
4.25
4.50
5.50
5.90
Standard deviation
0.32
0.38
0.32
0.30
0.41
0.29
0.28
0.39
0.48
Minimum
5.00
4.75
4.75
4.50
3.98
3.59
3.10
4.15
4.27
Maximum
6.50
6.50
6.02
6.00
6.00
5.75
5.52
6.60
8.00
Mean
2.85
2.65
2.67
2.51
2.39
2.21
2.25
2.50
2.55
Median
3.00
2.75
2.75
2.50
2.50
2.50
2.50
2.50
2.61
Standard deviation
0.49
0.71
0.75
0.76
0.82
0.90
0.92
0.99
0.97
Minimum
2.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Maximum
3.69
3.66
4.50
4.50
4.00
4.75
7.75
5.00
4.90
Mean
1.90
1.85
1.81
3.28
1.59
1.58
1.62
1.76
1.91
Median
2.00
2.00
2.00
1.75
1.50
1.50
1.60
1.75
2.00
Standard deviation
0.47
0.46
0.47
1.13
0.45
0.39
0.35
0.39
0.36
Minimum
1.25
1.20
0.30
0.00
0.00
0.90
0.88
1.00
1.00
Maximum
3.00
3.00
2.57
8.40
3.00
2.50
2.50
2.85
8.87
g
r
Table 1: Development of i, g and r
28
i∗
2000
2001
2002
2003
2004
2005
2006
2007
2008
Automobile
Chemicals
Construction
Consumer
Financial Services
Industrial
Media
Pharma & Healthcare
Retail
Transp. & Logistics
5.94
-
5.49
5.86
-
5.44
5.78
-
5.48
5.39
5.39
5.31
5.42
-
5.01
5.06
5.01
4.99
4.75
5.08
5.08
-
4.29
4.37
4.17
4.40
4.27
4.27
4.20
4.48
4.12
4.17
4.49
4.55
4.53
4.13
4.36
4.43
4.50
4.55
4.51
4.44
5.58
5.40
5.59
5.40
5.24
5.31
5.36
5.35
5.55
5.41
5.76
6.06
5.93
5.78
5.92
5.87
5.54
6.01
6.05
5.93
3.00
-
2.59
2.33
-
2.59
2.56
-
2.61
2.41
2.56
2.82
2.55
-
2.59
2.50
2.45
2.30
2.26
2.49
2.56
-
2.51
2.47
2.30
2.60
1.98
2.14
2.10
2.45
2.66
2.35
2.41
2.38
2.52
2.80
2.36
2.18
1.45
2.83
2.56
2.60
2.64
2.61
2.71
3.53
2.39
2.42
1.70
3.16
2.66
2.63
2.81
2.78
2.78
3.56
2.54
2.34
1.75
3.08
2.50
2.67
1.69
-
1.81
1.60
-
1.81
1.59
-
1.40
2.44
1.73
1.68
1.62
-
1.89
1.47
1.48
1.66
1.56
1.59
1.54
-
1.81
1.44
1.36
1.71
1.59
1.52
1.63
1.52
1.75
1.65
1.78
1.55
1.55
1.55
1.67
1.57
1.63
1.57
1.68
1.84
1.95
1.87
1.55
1.99
1.79
1.68
1.62
1.66
1.99
1.70
1.86
1.88
1.63
2.16
1.94
1.89
1.74
1.97
2.10
2.07
g∗
Automobile
Chemicals
Construction
Consumer
Financial Services
Industrial
Media
Pharma & Healthcare
Retail
Transp. & Logistics
r∗
Automobile
Chemicals
Construction
Consumer
Financial Services
Industrial
Media
Pharma & Healthcare
Retail
Transp. & Logistics
Table 2: Development of i∗ , g ∗ and r∗ differentiated by industry sectors
29
M ARCAP
TA
PA
DBO
DBOX
DBOD
NI
RD
EM P (in thousands)
N (in years)
Mean
Median
Sd.
Minimum
Maximum
1.028
1.678
0.045
0.106
0.107
-0.001
0.075
0.016
34.620
7.526
0.625
0.899
0.011
0.071
0.070
0.000
0.066
0.000
7.867
1.753
1.417
4.030
0.076
0.104
0.106
0.011
0.131
0.025
74.874
5.443
0.019
0.292
0.000
0.000
0.000
-0.063
-0.990
0.000
0.000
0.000
15.297
59.419
0.391
0.542
0.565
0.054
0.676
0.163
524.803
20.000
Table 3: Sample characteristics
30
Dependent Variable: MARCAP
Method: Panel Least Squares
Sample: 2000 2008
Periods included: 9, Cross-sections included: 99
Total panel (unbalanced) observations: 449
White cross-section standard errors & covariance (d.f. corrected)
P
Model I.: M ARCAPit = 2008
t=2000 αt It + β1 DBOit + β2 P Ait + β3 N Iit
+β4 EM Pit + β5 RDit + β6 T Ait + ut
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
DBO
PA
NI
EMP
RD
TA
0.532825
−2.148596
1.204533
4.125958
−1.69 · e−6
6.662352
0.172323
0.110038
0.344770
0.488380
1.376958
8.11 · e−8
1.026844
0.009080
4.842188
−6.231978
2.466387
2.996429
−20.81202
6.488180
18.97800
0.0000
0.0000
0.0140
0.0029
0.0000
0.0000
0.0000
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
0.992357
1.298948
2.604484
2.741690
2.658567
Period fixed (dummy variables)
R-squared
Adj. R-squared
S.E. of regression
F-statistic
Prob(F-statistic)
0.560048
0.545856
0.875364
39.46217
0.000000
Model II.: M ARCAPit =
P2008
t=2000 αt It
+ β1 DBOX,it + β2 P Ait + β3 N Iit
+β4 EM Pit + β5 RDit + β6 T Ait + ut
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
DBOX
PA
NI
EMP
RD
TA
0.525322
−1.963728
1.056695
4.124981
−1.70 · e−6
6.566739
0.171923
0.110188
0.351286
0.558614
1.382543
8.69 · e−8
1.004610
0.008863
4.767511
−5.590112
1.891636
2.983618
−19.55998
6.536602
19.39738
0.0000
0.0000
0.0592
0.0030
0.0000
0.0000
0.0000
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
0.992357
1.298948
2.607129
2.744335
2.661212
Period fixed (dummy variables)
R-squared
Adj. R-squared
S.E. of regression
F-statistic
Prob(F-statistic)
0.558882
0.544653
0.876523
39.27603
0.000000
Table 4: Relative value relevance of discretion
31
Model I.
Model II.
0.5459
1.2731
0.2030
0.5447
Adj. R-Squared
Vuong Z-Statistic
p-value
Table 5: Vuong (1989)-Test for model-comparison I. and II..
Dependent Variable: MARCAP
Method: Panel Least Squares
Sample: 2000 2008
Periods included: 9, Cross-sections included: 99
Total panel (unbalanced) observations: 449
White cross-section standard errors & covariance (d.f. corrected)
Model III.: M ARCAPit =
P2008
t=2000 αt It
+ β1 DBOX,it + β2 DBOD,it + β3 P Ait
+β4 N Iit + β5 EM Pit + β6 RDit + β7 T Ait + ut
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
DBOX
DBOD
PA
NI
EMP
RD
TA
0.527882
−2.139723
−5.789322
1.134035
4.133503
−1.70 · e−6
6.725172
0.173029
0.110226
0.337293
2.065376
0.437295
1.375105
7.56 · e−8
1.068802
0.009580
4.789108
−6.343803
−2.803035
2.593295
3.005955
−22.45484
6.292254
18.06148
0.0000
0.0000
0.0053
0.0098
0.0028
0.0000
0.0000
0.0000
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
0.992357
1.298948
2.607185
2.753538
2.664874
Period fixed (dummy variables)
R-squared
Adj. R-squared
S.E. of regression
F-statistic
Prob(F-statistic)
0.560818
0.545604
0.875607
36.86161
0.000000
Table 6: Additional value relevance of discretion
32
Dependent Variable: MARCAP
Method: Panel Least Squares
Sample: 2000 2008
Periods included: 9, Cross-sections included: 99
Total panel (unbalanced) observations: 449
White cross-section standard errors & covariance (d.f. corrected)
P
Model IV.: M ARCAPit = 2008
t=2000 αt It + β1 DBOX,it + β2 DBOD,it
+β3 DBOD,it · P ost2004 + β4 P Ait + β5 N Iit
+β6 EM Pit + β7 RDit + β8 T Ait + ut
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
DBOX
DBOD
DBOD · P OST 2004
PA
NI
EMP
RD
TA
0.528457
−2.137548
−3.664535
−2.521463
1.120966
4.129601
−1.70 · e−6
6.707689
0.173158
0.110808
0.335223
2.920430
4.216216
0.424616
1.377596
7.50 · e−8
1.064739
0.009584
4.769101
−6.376500
−1.254793
−0.598039
2.639952
2.997686
−22.64788
6.299845
18.06766
0.0000
0.0000
0.2102
0.5501
0.0086
0.0029
0.0000
0.0000
0.0000
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
0.992357
1.298948
2.611527
2.767027
2.672821
Period fixed (dummy variables)
R-squared
Adj. R-squared
S.E. of regression
F-statistic
Prob(F-statistic)
0.560868
0.544604
0.876570
34.48489
0.000000
Table 7: Transition to mandatory application of IFRS
33
Dependent Variable: MARCAP
Method: Panel Least Squares
Sample: 2000 2008
Periods included: 9, Cross-sections included: 99
Total panel (unbalanced) observations: 449
White cross-section standard errors & covariance (d.f. corrected)
P
Model IV.: M ARCAPit = 2008
t=2000 αt It + β1 DBOX,it + β2 DBOD,it
+β3 DBOD,it · U F U N D + β4 P Ait + β5 N Iit
+β6 EM Pit + β7 RDit + β8 T Ait + β9 U F U N D + ut
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
DBOX
DBOD
DBOD · U F U N D
PA
NI
EMP
RD
TA
UFUND
0.365130
−1.932723
−12.52822
36.20626
1.243569
4.113293
−1.18 · e−6
7.525593
0.176734
0.299807
0.133268
0.389621
2.953558
8.482752
0.587619
1.311814
1.51 · e−7
1.344575
0.009827
0.090552
2.739816
−4.960524
−4.241736
4.268221
2.116283
3.135577
−7.803780
5.597003
17.98413
3.310886
0.0064
0.0000
0.0000
0.0000
0.0349
0.0018
0.0000
0.0000
0.0000
0.0010
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
0.992357
1.298948
2.570634
2.735280
2.635533
Period fixed (dummy variables)
R-squared
Adj. R-squared
S.E. of regression
F-statistic
Prob(F-statistic)
0.580337
0.563784
0.857912
35.05961
0.000000
Table 8: Influence of funded status
34
Dependent Variable: DBOD /DBO
Method: Panel EGLS (Cross-section weights)
Sample: 2000 2008
Periods included: 9, Cross-sections included: 91
Total panel (unbalanced) observations: 408
Linear estimation after one-step weighting matrix
Model VI.:
DBOD,it
DBOit
∗ ) + β (r − r ∗ ) + u
= α + β1 (iit − i∗it ) + β2 (git − git
3 it
t
it
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
i − i∗
g − g∗
r − r∗
0.000262
−14.25134
6.357272
8.303532
0.000318
0.108714
0.108036
0.167396
0.825143
−131.0902
58.84399
49.60399
0.4098
0.0000
0.0000
0.0000
Mean dependent var
S.D. dependent var
Sum squared resid
Durbin-Watson stat
0.005315
0.408574
1.373289
1.184848
R-squared
Adjusted R-squared
S.E. of regression
F-statistic
Prob(F-statistic)
0.979541
0.979389
0.058303
6447.482
0.000000
Table 9: Examination of fault tolerance
35
HHL-Arbeitspapiere / HHL Working Papers
106
Reinhardt, Markus (2010)
An Incentive Compatible Double Auction for Multi-Unit Markets with
Heterogenous Goods
105
Zülch, Henning; Detzen, Dominic (2010)
Enforcing Financial Reporting Standards: The Case of White Pharmaceuticals AG
104
Salewski, Marcus; Zülch Henning (2010)
Managerial Discretion in Accounting for Defined Benefit Obligations: An Empirical
Analysis of German IFRS Statements
103
Zülch, Henning; Salewski, Marcus (2010)
Ermessensspielräume bei der Bilanzierung von Pensionsverpflichtungen: eine
empirische Analyse deutscher IFRS-Bilanzierer
102
Scherzer, Falk (2010)
On the Value of Individual Athletes in Team Sports
101
Wulf, Torsten; Brands, Christian; Meißner, Philip (2010)
A Scenario-based Approach to Strategic Planning: Tool Description –
360° Stakeholder Feedback
100
Viellechner, Oliver; Wulf, Torsten (2010)
Incumbent Inertia upon Disruptive Change in the Airline Industry: Causal Factors
for Routine Rigidity and Top Management Moderators
99
Wulf, Torsten; Meißner, Philip; Bernewitz, Friedrich Frhr. von (2010)
Future Scenarios for German Photovoltaic Industry
98
Wulf, Torsten; Meißner, Philip; Stubner, Stephan (2010)
A Scenario-based Approach to Strategic Planning – Integrating Planning and
Process Perspective of Strategy
97
Wulf, Torsten; Stubner, Stephan; Blarr, W. Henning; Lindow, Corinna (2010)
Erfolgreich bleiben in der Krise
96
Wulf, Torsten; Stubner, Stephan (2010)
Unternehmernachfolge in Familienunternehmen – Ein Untersuchungsmodell zur
Analyse von Problemfeldern bei der Übergabe der Führungsrolle
95
Zülch, Henning; Pronobis, Paul (2010)
The Predictive Power of Comprehensive Income and Its Individual Components
under IFRS
94
Zülch, Henning; Hoffmann, Sebastian (2010)
Lobbying on Accounting Standard Setting in a Parliamentary Environment –
A Qualitative Approach
93
Hausladen, Iris; Porzig, Nicole; Reichert, Melanie (2010)
Nachhaltige Handels- und Logistikstrukturen für die Bereitstellung regionaler
Produkte: Situation und Perspektiven
92
La Mura, Pierfrancesco; Rapp, Marc Steffen; Schwetzler, Bernard; Wilms,
Andreas (2009)
The Certification Hypothesis of Fairness Opinions
91
La Mura, Pierfrancesco (2009)
Expected Utility of Final Wealth and the Rabin Anomaly
90
Thürbach, Kai (2009)
Fallstudie sekretaria - Vom New Economy-Internet-Startup zum
Old Economy-Verlagsunternehmen
89
Wulf, Torsten; Stubner, Stephan; Blarr, W. Henning (2010)
Ambidexterity and the Concept of Fit in Strategic Management – Which Better
Predicts Success?
88
Wulf, Torsten; Stubner, Stephan; Miksche, Jutta; Roleder, Kati (2010)
Performance over the CEO Lifecycle – A Differentiated Analysis of Short and
Long Tenured CEOs
87
Wulf, Torsten; Stubner, Stephan; Landau, Christian; Gietl, Robert (2010)
Private Equity and Family Business – Can Private Equity Investors Add to the
Success of Formerly Owned Family Firms?
86
Wulf, Torsten; Stubner, Stephan (2008)
Executive Succession and Firm Performance – the Role of Position-specific Skills
85
Wulf, Torsten; Stubner, Stephan (2008)
Unternehmernachfolge in Familienunternehmen – Untersuchungsmodell zur
Analyse von Problemfeldern bei der Übergabe der Führungsrolle
84
Wulf, Torsten; Stubner, Stephan (2008)
Executive Departure Following Acquisitions in Germany – an Empirical Analysis
of Its Antecedents and Consequences
83
Zülch, Henning; Gebhardt, Ronny (2008)
Politische Ökonomie der Rechnungslegung - Empirische Ergebnisse und kritische
Würdigung des Forschungsansatzes
82
Zülch, Henning; Löw, Edgar; Burghardt, Stephan (2008)
Zur Bedeutung von IFRS-Abschlüssen bei der Kreditvergabe von Banken an
mittelständische Unternehmen
81
Suchanek, Andreas (2007)
Die Relevanz der Unternehmensethik im Rahmen der Betriebswirtschaftslehre
80
Kirchgeorg, Manfred; Jung, Kathrin (2007)
User Behavior in Second Life: An Empirical Study Analysis and Its Implications for
Marketing Practice
79
Freundt, Tjark (2007)
Neurobiologische Erklärungsbeiträge zur Struktur und Dynamik des
Markenwissens
78
Wuttke, Martina (2007)
Analyse der Markteintrittsstrategien chinesischer Unternehmen in Mitteldeutschland am Beispiel von chinesischen Unternehmen im MaxicoM in Leipzig
77
La Mura, Pierfrancesco; Swiatczak, Lukasz (2007)
Markovian Entanglement Networks
76
Suchanek, Andreas (2007)
Corporate Responsibility in der pharmazeutischen Industrie
75
Möslein, Kathrin; Huff, Anne Sigismund (2006)
Management Education and Research in Germany
74
Kirchgeorg, Manfred; Günther, Elmar (2006)
Employer Brands zur Unternehmensprofilierung im Personalmarkt :
eine Analyse der Wahrnehmung von Unternehmensmarken auf der Grundlage
einer deutschlandweiten Befragung von High Potentials
73
Vilks, Arnis (2006)
Logic, Game Theory, and the Real World
72
La Mura, Pierfrancesco; Olschewski, Guido (2006)
Non-Dictatorial Social Choice through Delegation
71
Kirchgeorg, Manfred; Springer, Christiane (2006)
UNIPLAN Live Trends 2006 : Steuerung des Kommunikationsmix im
Kundenbeziehungszyklus ; eine branchenübergreifende Befragung von
Marketingentscheidern unter besonderer Berücksichtigung der Live
Communication. – 2., erw. Aufl.
70
Reichwald, Ralf; Möslein, Kathrin (2005)
Führung und Führungssysteme
69
Suchanek, Andreas (2005)
Is Profit Maximization the Social Responsibility of Business? Milton Friedman and
Business Ethics
68
La Mura, Pierfrancesco (2005)
Decision Theory in the Presence of Uncertainty and Risk
67
Kirchgeorg, Manfred; Springer, Christiane (2005),
UNIPLAN LiveTrends 2004/2005 : Effizienz und Effektivität in der Live
Communication ; eine Analyse auf Grundlage einer branchen-übergreifenden
Befragung von Marketingentscheidern in Deutschland
66
Kirchgeorg, Manfred; Fiedler, Lars (2004)
Clustermonitoring als Kontroll- und Steuerungsinstrument für
Clusterentwicklungsprozesse - empirische Analysen von Industrieclustern in
Ostdeutschland
65
Schwetzler, Bernhard (2004)
Mittelverwendungsannahme, Bewertungsmodell und Unternehmensbewertung
bei Rückstellungen
64
La Mura, Pierfrancesco; Herfert, Matthias (2004)
Estimation of Consumer Preferences via Ordinal Decision-Theoretic Entropy
63
Wriggers, Stefan (2004)
Kritische Würdigung der Means-End-Theorie im Rahmen einer Anwendung auf
M-Commerce-Dienste
62
Kirchgeorg, Manfred (2003)
Markenpolitik für Natur- und Umweltschutzorganisationen
61
La Mura, Pierfrancesco (2003)
Correlated Equilibria of Classical Strategic Games with Quantum Signals
60
Schwetzler, Bernhard; Reimund, Carsten (2003)
Conglomerate Discount and Cash Distortion: New Evidence from Germany
59
Winkler, Karsten (2003)
Wettbewerbsinformationssysteme: Begriff, Anforderungen, Herausforderungen
58
Winkler, Karsten (2003)
Getting Started with DIAsDEM Workbench 2.0: A Case-Based Tutorial
57
Lindstädt, Hagen (2002)
Das modifizierte Hurwicz-Kriterium für untere und obere Wahrscheinlichkeiten ein Spezialfall des Choquet-Erwartungsnutzens
56
Schwetzler, Bernhard; Piehler, Maik (2002)
Unternehmensbewertung bei Wachstum, Risiko und Besteuerung –
Anmerkungen zum „Steuerparadoxon“
55
Althammer, Wilhelm; Dröge, Susanne (2002)
International Trade and the Environment: The Real Conflicts
54
Kesting, Peter (2002)
Ansätze zur Erklärung des Prozesses der Formulierung von
Entscheidungsproblemen
53
Reimund, Carsten (2002)
Internal Capital Markets, Bank Borrowing and Investment: Evidence from German
Corporate Groups
52
Fischer, Thomas M.; Vielmeyer, Uwe (2002)
Vom Shareholder Value zum Stakeholder Value? Möglichkeiten und Grenzen der
Messung von stakeholderbezogenen Wertbeiträgen
51
Fischer, Thomas M.; Schmöller, Petra; Vielmeyer, Uwe (2002)
Customer Options – Möglichkeiten und Grenzen der Bewertung von
kundenbezogenen Erfolgspotenzialen mit Realoptionen
50
Grobe, Eva (2003)
Corporate Attractiveness : eine Analyse der Wahrnehmung von
Unternehmensmarken aus der Sicht von High Potentials
49
Kirchgeorg, Manfred; Lorbeer, Alexander (2002)
Anforderungen von High Potentials an Unternehmen – eine Analyse
auf der Grundlage einer bundesweiten Befragung von High Potentials und
Personalentscheidern
48
Kirchgeorg, Manfred; Grobe, Eva; Lorbeer, Alexander (2003)
Einstellung von Talenten gegenüber Arbeitgebern und regionalen Standorten :
eine Analyse auf der Grundlage einer Befragung von
Talenten aus der Region Mitteldeutschland
(not published)
47
Fischer, Thomas M.; Schmöller, Petra (2001)
Kunden-Controlling – Management Summary einer empirischen Untersuchung in
der Elektroindustrie
46
Althammer, Wilhelm; Rafflenbeul, Christian (2001)
Kommunale Beschäftigungspolitik: das Beispiel des Leipziger Betriebs für
Beschäftigungsförderung
45
Hutzschenreuter, Thomas (2001)
Managementkapazitäten und Unternehmensentwicklung
44
Lindstädt, Hagen (2001)
On the Shape of Information Processing Functions
43
Hutzschenreuter, Thomas; Wulf,Torsten (2001)
Ansatzpunkte einer situativen Theorie der Unternehmensentwicklung
42
Lindstädt, Hagen (2001)
Die Versteigerung der deutschen UMTS-Lizenzen – eine ökonomische Analyse
des Bietverhaltens
41
Lindstädt, Hagen (2001)
Decisions of the Board
40
Kesting, Peter (2001)
Entscheidung und Handlung
39
Kesting, Peter (2001)
Was sind Handlungsmöglichkeiten? – Fundierung eines ökonomischen
Grundbegriffs
38
Kirchgeorg, Manfred; Kreller, Peggy (2000)
Etablierung von Marken im Regionenmarketing – eine vergleichende Analyse der
Regionennamen "Mitteldeutschland" und "Ruhrgebiet" auf der Grundlage einer
repräsentativen Studie
37
Kesting, Peter (2000)
Lehren aus dem deutschen Konvergenzprozess – eine Kritik des „Eisernen
Gesetzes der Konvergenz“ und seines theoretischen Fundaments
36
Hutzschenreuter, Thomas; Enders, Albrecht (2000)
Möglichkeiten zur Gestaltung internet-basierter Studienangebote im Markt
für Managementbildung
35
Schwetzler, Bernhard (2000)
Der Einfluss von Wachstum, Risiko und Risikoauflösung auf den
Unternehmenswert
34
No longer available. There will be no reissue.
33
Löhnig, Claudia (1999)
Wirtschaftliche Integration im Ostseeraum vor dem Hintergrund der
Osterweiterung der Europäischen Union: eine Potentialanalyse
32
Fischer, Thomas M. (1999)
Die Anwendung von Balanced Scorecards in Handelsunternehmen
31
Schwetzler, Bernhard; Darijtschuk, Niklas (1999)
Unternehmensbewertung, Finanzierungspolitiken und optimale Kapitalstruktur
30
Meffert, Heribert (1999)
Marketingwissenschaft im Wandel – Anmerkungen zur Paradigmendiskussion
29
Schwetzler, Bernhard (1999)
Stochastische Verknüpfung und implizite bzw. maximal zulässige
Risikozuschläge bei der Unternehmensbewertung
28
Fischer, Thomas M.; Decken, Tim von der (1999)
Kundenprofitabilitätsrechnung in Dienstleistungsgeschäften –
Konzeption und Umsetzung am Beispiel des Car Rental Business
27
Fischer, Thomas M. (2000)
Economic Value Added (EVA) - Informationen aus der externen
Rechnungslegung zur internen Unternehmenssteuerung?
(rev. edition, July 2000)
26
Hungenberg, Harald; Wulf, Torsten (1999)
The Transition Process in East Germany
25
Vilks, Arnis (1999)
Knowledge of the Game, Relative Rationality, and Backwards Induction
without Counterfactuals
24
Darijtschuk, Niklas (1998)
Dividendenpolitik
23
Kreller, Peggy (1998)
Empirische Untersuchung zur Einkaufsstättenwahl von Konsumenten
am Beispiel der Stadt Leipzig
22
Löhnig, Claudia (1998)
Industrial Production Structures and Convergence: Some Findings
from European Integration
21
Schwetzler, Bernhard (1998)
Unternehmensbewertung unter Unsicherheit – Sicherheitsäquivalentoder Risikozuschlagsmethode
20
Fischer, Thomas M.; Schmitz, Jochen A. (1998)
Kapitalmarktorientierte Steuerung von Projekten im Zielkostenmanagement
19
Fischer, Thomas M.; Schmitz, Jochen A. (1998)
Control Measures for Kaizen Costing - Formulation and Practical Use
of the Half-Life Model
18
Schwetzler, Bernhard; Ragotzky, Serge (1998)
Preisfindung und Vertragsbindungen bei MBO-Privatisierungen in Sachsen
17
Schwetzler, Bernhard (1998)
Shareholder-Value-Konzept, Managementanreize und Stock Option Plans
16
Fischer, Thomas M. (1998)
Prozeßkostencontrolling – Gestaltungsoptionen in der öffentlichen
Verwaltung
15
Hungenberg, Harald (1998)
Kooperation und Konflikt aus Sicht der Unternehmensverfassung
14
Schwetzler, Bernhard; Darijtschuk, Niklas (1998)
Unternehmensbewertung mit Hilfe der DCF-Methode – eine Anmerkung
zum „Zirkularitätsproblem“
13
Hutzschenreuter, Thomas; Sonntag, Alexander (1998)
Erklärungsansätze der Diversifikation von Unternehmen
12
Fischer, Thomas M. (1997)
Koordination im Qualitätsmanagement – Analyse und Evaluation im Kontext der
Transaktionskostentheorie
11
Schwetzler, Bernhard; Mahn, Stephan (1997)
IPO´s: Optimale Preisstrategien für Emissionsbanken mit Hilfe von
Anbot-Modellen
10
Hungenberg, Harald; Hutzschenreuter, Thomas; Wulf, Torsten (1997)
Ressourcenorientierung und Organisation
9
Vilks, Arnis (1997)
Knowledge of the Game, Rationality and Backwards Induction
(Revised edition HHL Working Paper No. 25)
8
Kesting, Peter (1997)
Visionen, Revolutionen und klassische Situationen – Schumpeters
Theorie der wissenschaftlichen Entwicklung
7
Hungenberg, Harald; Hutzschenreuter, Thomas; Wulf, Torsten (1997)
Investitionsmanagement in internationalen Konzernen
- Lösungsansätze vor dem Hintergrund der Agency-Theorie
6
Hungenberg, Harald; Hutzschenreuter, Thomas (1997)
Postreform - Umgestaltung des Post- und Telekommunikationssektors in
Deutschland
5
Schwetzler, Bernhard (1996)
Die Kapitalkosten von Rückstellungen zur Anwendung des ShareholderValue-Konzeptes in Deutschland
4
Hungenberg, Harald (1996)
Strategische Allianzen im Telekommunikationsmarkt
3
Vilks, Arnis (1996)
Rationality of Choice and Rationality of Reasoning (rev. Edition, September 1996)
2
Schwetzler, Bernhard (1996)
Verluste trotz steigender Kurse? - Probleme der Performancemessung
bei Zinsänderungen
1
Meffert, Heribert (1996)
Stand und Perspektiven des Umweltmanagement in der betriebswirtschaftlichen
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