Earnings management and privatisations: evidence from Pakistan.
Iqbal, Abdullah Muhammad ; Khan, Iram ; Ahmed, Zeeshan 等
This study examines the incidence of earnings management around the
time of the privatisation of State Owned Enterprises in Pakistan during
1991-2005. Using the modified Jones model and a sample of large
privatisations (minimum US$1 million), it shows that the sampled firms
experienced increase in earnings, decrease in cash flows, and increase
in current discretionary accruals in the year prior to and/or in the
year of privatisation. The SOEs used both short term and long term
accruals to inflate reported earnings. These accruals were reversed in
the post-privatisation period. These findings suggest that managers of
the firms slated for privatisation were engaged in earnings management
to inflate their firms' financial worth to maximise the
privatisation proceeds. Hence, we cannot reject the incidence of
earnings management during privatisations in Pakistan. The results imply
that the investors should carefully evaluate the to-be-privatised firms
and keep in view the possibility of earnings management by the SOEs.
JEL Classification: G14, G34, G38, L33, M41
Keywords: Earnings Management, Privatisations, SOEs, Pakistan,
Accruals
1. INTRODUCTION
Earnings management involves manipulation of financial accounts by
management to present a certain image of a firm's
economic/operating performance [see, for example, Healy and Wahlen
(1999); Kothari (2001); and other studies]. Financial accounts generally
require judgment, and thus, provide managers with the scope for
tampering [Schipper (1989)]. Recent evidence supports the incidence of
earnings management around a diverse range of economic events [see, for
example, Teoh, et al. (1998a, 1998b); Iqbal, et al. (2006, 2009)], and
for a broad range of incentives during a firm's life cycle in both
the developed (the US and the UK) and emerging markets (such as China
and Malaysia) [see, for example, Teoh, et al. (1998); Ball and
Shivakumar (2008); Cheng and Warfield (2005); Othman and Zegal (2006);
Yanqiong (2011); Ahmad-Zaluki, et al. (2011)].
In addition, compared with outsiders, managers (insiders) know more
about their business and its relevant risks and opportunities due to the
existence of information asymmetries [Myers and Majluf (1984)].
Therefore, depending on the demands of the situation, their vested
interests as well as the existence and/or the enforcement of relevant
laws, it becomes possible for the insiders to manage earnings upwards or
downwards or even smooth them. (1) The probability of such an occurrence
is greater in Pakistan for several reasons, such as the inefficiency of
judicial system and poor disclosure standards for the State Owned
Enterprises (SOEs) [Guedhami and Pittman (2011)]. Furthermore, a
critical event such as privatisation provides strong incentives to
managers to either show their support (through upwards earnings
management) or opposition (through downward earnings management) to it.
One can, therefore, hypothesise that strong incentives may exist
for managing earnings at the time of privatising SOEs too. (2) Such a
hypothesis derives rationale from the similarities between
privatisations and Initial Public Offerings (IPOs), as one of the means
for divestment of SOEs is through an IPO. Considerable amount of
research, that tests the implications of earnings management hypothesis
around the event of IPOs and seasoned equity offerings (SEOs), has been
done [see for example, Aharony, et al. (1993); Teoh, et al. (1998);
Ahmad-Zaluki, et al. (2011); among others]. However, to the best of
authors' knowledge, this study is one of the few that tests
earnings management hypothesis around the privatisation of SOEs. Thus,
the main purpose of this study is to examine if the managers of SOEs
manage earnings (upward or downward) around the privatisation of SOEs in
Pakistan. The results of the study have important implications for
policy makers and investors in view of the next wave of major
privatisations that are expected during 2015-16 in Pakistan. These
include Pakistan Steel, Pakistan International Airlines (PIA), and Oil
and Gas Development Corporation (OGDC), to name a few.
The rest of the paper is organised as follows. Section 2 reviews
the privatisation policy in Pakistan, while Section 3 explains the
concept of earnings management, draws parallels between IPOs and
privatisations, and develops the testable hypotheses. Section 4 outlines
the criteria for sample selection and discusses the methodology. Section
5 presents empirical results followed by conclusion in the last section.
2. THE NATURE OF PRIVATISATION AND ITS OBJECTIVES IN PAKISTAN
This paper attempts to explore earnings management around the SOEs
privatisation, a term defined in Megginson and Netter (2001) as the
'deliberate sale by a government of state-owned enterprises (SOE)
or assets to private economic agents'. Privatisation programmes
emerged in the 1960s, with the Adenauer government in Germany divesting
a major stake in Volkswagen, followed by the massive privatisation
invoked by the Thatcher government in the UK in 1980s. This policy then
began to spread worldwide, adopted by the Latin American and European
countries (especially Eastern Europe). The popularity of privatisation
establishes its credibility as an event of sufficient significance to be
studied independently. This unique policy is not specific to a region
but is present and practised around the world.
Cameroon (1997) and Kemal (1996) point out that the privatisation
policy was adopted in Pakistan as an essential component of the
structural adjustment programme, when the Privatisation Commission (PC)
was established as part of the 1988 IMF/World Bank structural adjustment
package [Cameroon (1997); Paddon (1997)]. Though Kemal (1996) claims
that there was not much conviction behind its initiation on the part of
the government, privatisation has continued to persist as a preferred
economic policy option despite governments having different ideological
hues and political dispensations [Kemal (2000); PC (1996a, 1997, 2000);
Qureshi (1992)]. The fact is that in Pakistan, international financial
aid was conditioned on the privatisation and restructuring of SOEs.
Mirza (1995) gives a number of examples that highlight the role of
international donors in privatisation in Pakistan.
According to Khan (2003), since privatisation was an imported
phenomenon in Pakistan, it had no clearly spelled out objectives
initially. The government reports on privatisation do not list even a
single objective until 1992 [Qureshi (1992)]. It was as late as 1996,
that the broad contours of privatisation policy and its objectives
emerged [PC (1996b)].
According to the ex-Chairman, Privatisation Commission, the
government programme for privatisation is based on "the principle
of reducing its direct participation in commercial activities" and
ensuring "equity and economic justice" [Asif (1998)]. PC
(2000), states: "distorted prices, lack of competition, and poor
government management of business have hindered economic development,
introduced inefficiencies, generated unproductive and unsustainable
employment, slowed down investment, reduced access to services by the
poor, resulted in substandard goods and services, and contributed to
fiscal bleeding". By privatising, the government intends to remove
these impediments.
By the end of May 2011, the GOP had completed or approved 167
transactions. (3) This number also included some multiple transactions
for the same unit. The gross privatisation proceeds stood at Rs 476.421
billion. Telecom and power sectors alone account for around 50 percent
of all the proceeds.
3. EARNINGS MANAGEMENT OPPORTUNITIES
According to Healy and Wahlen (1999), earnings management occurs
when managers use judgment and discretion in financial reporting and
choose accounting methods to structure transactions to alter financial
reports. This enables them to mislead stakeholders about the underlying
economic performance of a company or to "influence contractual
outcomes that depend on reported accounting numbers" (p. 8).
Managers can exercise their discretion in case of discretionary part of
the accruals, which involve estimation by the management and thus serve
as a proxy for determining the level of earnings management [Healy and
Wahlen (1999)].
3.1. Incentives for Upward Earnings Management
Recent research has identified a number of situations in which
firms may engage in upward earnings management. These include period(s)
leading to equity offerings (IPOs and SEOs--Seasoned Equity Offerings),
increasing manager's compensations when they are linked to year-end
earnings (e.g. bonus plans), and avoiding violating clauses within
lending contracts, etc.
Ahmad-Zaluki, et al. (2011) and Smith, et al. (2001) argue that in
times of an economic downturn, there is external pressure on firms to
choose income increasing accounting methods. During the East Asian
crisis in 1997-98, IPOs recorded a higher amount of discretionary
accruals than they would have done otherwise. The managers were under
pressure to maintain investors' confidence in IPOs, which affected
the choice of accounting methods that showed upwards earnings. Thus,
their studies establish a positive relationship between upward earnings
management in IPOs and the periods of economic stress.
Earnings management is common during privatisation introduced at
times of economic stress. Karatas (1995) finds instances of data
manipulation in Turkey in the pre-privatisation period. Such data
falsification is more likely to be present in situations where
government is facing opposition to its privatisation policy and wants it
to look good.
Putting these studies in the context of Pakistan and the period
(1991-2005) under review, we find that Pakistan's economy was not
faring very well. Arby (2001) noted that the recession in Pakistan
started in the early 1990s and was expected to continue till 2004-05.
Burki (2000) also argues that "the economy and state of Pakistan
are in crisis... Pakistan has not faced a crisis of this magnitude in
its entire 60-year history" (p. 152). Thus, the economic rationale
would dictate that due to the economic downturn and a chronic fiscal
budget deficit, the government should quickly privatise as many SOEs as
possible. To achieve this, the government had the incentives to use
income increasing accounting policies and positive discretionary
accruals to achieve higher value for the firms, just as IPO firms would
manage earnings upward in order to retain investors' confidence and
avoid reduced stock trading. In such a situation, managers are expected
to get along with the government rather than resist and face the
consequences of refusing orders. The economic incentives apart, the
political will behind a privatisation programme is also likely to affect
the earnings management perspective.
Yarrow (1999) argues that the most common trigger for privatisation
and SOE reform is fiscal pressure. This statement clearly applies to
Pakistan where the government had a clear incentive to use privatisation
proceeds as a substitute for taxes and to compensate for the pervasive
tax evasion. This makes intuitive sense as we already know that one of
the reasons for the privatisation of SOEs is the revenue that such a
divesture would generate. (4) Weak democratic regimes followed by
military rule made it even more difficult for the successive governments
to introduce a stringent tax system.
Public debt also provides an incentive for upward earnings
management; the goal would be to maximise the revenue to be generated
from the privatised unit, which can then be used to finance public
expenditure. In case of debt financing for SOEs, government could show
through upward earnings manipulation the efficiency of its management.
Khan (2003) has also concluded that managers had incentives for
upwards earnings management to increase the probability of
privatisation. This is because after the initial shock of privatisation
was over, they benefitted both in terms of better wages and increased
employment opportunities. This is also evident from the study by De Luca
(1997) and Martin and Parker (1997) which shows that managers mostly
benefit from it, enjoying better pay and perks in the post privatisation
period. According to Harris (1995), they either advocate it or at least
show less stress and low uncertainty level [Nelson, et al. (1995); Cam
(1999)].
The reasons outlined above provide sufficient incentives for upward
earnings management in the years before privatisation. This leads to our
first hypothesis,
H1: the management of state-owned enterprises (SOEs) is likely to
engage in upward earnings management.
3.2. Incentives for Downward Earnings Management
A number of studies on IPOs and SEOs have found a negative
relationship between pre-offer accruals and post-offer operating and
stock returns performance[for example, Teoh, et al. (1998a) and (1998b);
Iqbal, et al. (2006, 2009)]. This negative relationship (or conservative
earnings management) can be important when privatised firms plan an
IPO/SEO in the long run. For example, Ball and Shivakumar (2008) argue
that the IPO firms which need subsequent rounds of financing tend to be
conservative in their earnings management practices.
Another possible reason for conservative earnings management can be
political dimension normally associated with privatisation. For example,
politicians might want units under privatisation to be underpriced to
gain political favours from investors. Thus conservative earnings
management (i.e. underpricing) may be used to overcome political
obstacles standing in the way of a successful privatisation [Megginson
and Netter (2001); Laurin, et al. (2004); and Farinos, et al. (2007)].
Similarly, the state would like to avoid the risk of failure of
privatising its SOEs. Its primary motive could be to sell rather than to
maximise the sale proceeds. Thus, firms may resort to downward earnings
management, which would enable the government to dispose-off SOEs as
quickly as possible to show the success of its economic policy [Jones,
et al. (1999); Chen, et al. (2011)].Conservative earnings management may
also be used as a means to convince unions and labor that privatisation
is the only viable option [Boubakri and Cosset (1998)]. The political
dimension has been a broad consideration in Pakistan through different
regimes. The sale/divestment of public assets has generally been
construed as an indicator for the success of a privatisation effort. It
is the output, not the outcome, which has mattered the most.
The privatisation process in Pakistan entails hiring a Financial
Advisor or a valuator. (5) If the privatisation process is scrutinised
by a third party, the incentive could be to follow conservative
accounting practices to avoid any bad publicity. Financial advisers and
chartered accountants themselves would be concerned with the loss of
their reputation or risk facing civil law suits [Guedhami and Pittman
(2011)] if they allow aggressive management of earnings. Zhou and Elder
(2003) find that big auditing firms and industry specialist auditors
have a high correlation with conservative earnings management.
Ahmad-Zaluki, et al. (2008) hypothesise that older companies do not
engage in upward earnings management as they follow sound business
practices and have a reputation for following prudent accounting
practices. Since SOEs usually have a long history of existence, and are
subject to public scrutiny by analysts and media, which reduces their
scope for upwards or downwards earnings management.
Nagata and Hachiya (2006) argue that retained ownership by
management in IPO firms creates competing motives between control and
wealth creation. On the one hand, aggressive earnings management would
lead to an overpriced IPO and wealth creation for shareholders. Whilst
on the other hand, conservative earnings management would lead to
underpricing of the IPO, oversubscription and a broader allocation of
shares to the public, which would enable the management to retain
control. This argument can be applied to units being privatised in
stages as retained ownership in such firms would remain with the state
and its agents, the managers.
Megginson, et al. (2004) study share issue privatisations (SIPs)
and find that governments aim to establish and strengthen their equity
markets through public market privatisations. While our study does not
differentiate between asset sale and IPO privatisations, it can be
hypothesised that in the light of the efficiency gains made by
privatised firms, there may be an incentive to underprice units being
privatised through lower discretionary accruals. A lower priced firm
would seem a good investment by investors and would maintain capital
investments within the country (like Pakistan) and discourage the flight
of capital abroad.
Finally, in case of Pakistan where managers were not provided job
security in the post-privatisation period, they may not want their
companies privatised so as not to risk losing their jobs [Fluck, et al.
(2007)].
Thus we argue that there may be incentives for firms to be more
prudent and conservative in their use of accounting policies in the
pre-privatisation period. Hence, our second hypothesis is,
H2: the management of state-owned companies manages earnings
downwards before privatisation as a result of conservative accounting
practices.
Our study combines HI and H2 to formulate a single Hypothesis,
[H.sup.*], i.e. 'earnings management exists around privatisations
in Pakistan'. In addition, Privatisation Commission of Pakistan
considered privatising both profit making (supposedly with inflated
earnings) and loss making (supposedly with deflated earnings) SOEs
[Naqvi and Kemal (1991)]. Therefore, we conduct an un-directional test
for this hypothesis and evaluate the significance of (both
upward/downward) earnings management.
4. METHODOLOGY AND DATA SELECTION
Prior to testing earnings management hypothesis ([H.sup.*]), we
examine abnormal changes in earnings at or around privatisation of SOEs.
For this purpose, we use return on assets (ROA), return on sales (ROS),
and asset-scaled cash flow from operations (ACFO) of SOEs and of their
matched firms [Barber and Lyon (1996)] from two years before to two
years after the privatisation. The matched firm is chosen from the same
industry with the closest ROA from year -1 (the year preceding
privatisation). While choosing a matched firm, we exclude firms that
have been privatised in the previous two years to avoid any
contamination effects.
Following the estimation of abnormal earnings (if any) in the years
around the privatisation year, we estimate total accruals by subtracting
CFOs from net earnings for each year. We use modified Jones model to
estimate discretionary accruals that are an important tool for
manipulating earnings and hence, to detect earning management.
Due to differences in the nature and operations of industries, a
variation may exist in the 'normal' levels of discretionary
accruals. Given the particular cycle an industry may be passing through,
the industry wide 'normal' levels may also change and the
absolute level of discretionary accruals may not tell us much about the
existence of earnings management. We, therefore, use the accruals of the
matched firm to ascertain whether the discretionary accruals of SOEs are
significantly different from those of the matched firms.
The accrual-based model developed by Jones (1991) and modified by
Dechow, et al. (1995) aims to measure earnings management by segregating
total accruals (both short and long-term) into the discretionary and
non-discretionary components. In this model, first coefficients for the
components that are susceptible to managerial discretion (such as
'change in sales revenue' for current accruals and
'property, plant, and equipment' and 'change in sales
revenue' for total accruals) are estimated for each industry using
ordinary least square regressions. These coefficients are then used to
calculate non-discretionary current and long-term accruals. Finally, the
difference between the total current (long-term) accruals and the
non-discretionary current (long-term) accruals provides discretionary
current (long-term) accruals. This is explained in more detail in
Appendix I. The 'discretionary component' is expected to be
affected by the management's choice of accounting practices, and
changes in this component are used as the basis for estimating earnings
management around privatisations.
Based on the levels of actual total accruals, we deduct the
non-discretionary portion to calculate the discretionary portion of the
accruals. This is done separately for both the current and long term
components to derive the level of discretionary current and long-term
accruals for each event-year for the sample and the matched firms. The
difference between the levels of accruals of two types of firms is the
observations that we use to conduct the analysis and perform various
tests.
Test observations = Level of discretionary accruals in sample firm
less Level of discretionary accruals in matched firm
Using this method, we obtain 'positive' or
'negative' values for each year. A positive value indicates a
higher level of accruals for the event firm compared to the matched
firm. This implies that the firm has recognised lower levels of expenses
this year and/or has engaged in accelerating revenue recognition
policies. The firm has, therefore, managed its earnings in an
'upward' direction. Similarly a 'negative'
observation indicates that the firm has lower levels of discretionary
accruals as compared to its matched firm. This would result in higher
levels of expenses being recognised by the event firm and/or delayed
revenue recognition policies. This indicates 'downward'
earnings management.
We use January 1991 to June 2005 as our sample period.
Privatisation Commission privatised 158 state owned units during this
period. (6) We also use the following additional criteria for sample
selection,
(1) The privatised unit is a non-financial company;
(2) The minimum sale price of the unit is Rs 60 million
(approximately US$1 million);
(3) The minimum ownership stake sold is 5 percent;
(4) Accounting data is available to apply the modified Jones model
for the years 1 and 0.
The first criterion is imposed due to the distinct financial
reporting requirements of financial companies that lead to the exclusion
of 17 firms. In order to draw meaningful conclusions from the event of
privatisation, it is vital to keep two main characteristics of the
sample in mind i.e. materiality and controlling ownership as noted in
criterion 2 and 3 above. The larger the amount of the transaction, the
greater is the incentive for manipulation. Similarly, the larger the
stake being sold, the greater is the incentive for earnings manipulation
as the management would have lesser control over future decisions of the
firm. The application of these two criteria further reduces our sample
to 67 event firms. No information was available on the privatisation of
two companies that left us with 65 event firms.
Prior studies [such as Teoh, et al. (1998)] use a limit of 10 firms
to form the relevant industry sample to estimate the regression
coefficients from the modified Jones model. Given the low levels of
public listing in Pakistan, this is a difficult condition to satisfy for
each and every sample firm. To address this, we form broader industry
groups similar to Level-3 SIC codes used in the U.S. This classification
allows us to increase the size of the relative industry and helps in
easing the data restrictions we face. We impose the restriction of
minimum six firms [Iqbal, et al. (2006, 2009)] in each industry to apply
the modified Jones model. This restriction further reduces our sample
size to 40 firms. Table 1 and Table 2, respectively, report the
distribution of sample firms by industry and year, and the industrial
and yearly distribution of the amount raised from privatising SOEs.
We examine earnings and accruals over a five year period around the
event year, that is, two years before to two years after privatisation.
Hence, we test the hypotheses by analysing the time-series of earnings
and discretionary accruals from event years -2 to +2 for all the firms.
It is for this reason that we examine the operating and accruals
performance from 1989 till 2007.
5. RESULTS AND DISCUSSION
We report operating performance (median and mean) results in Table
3 for 33 SOEs, as we could not find suitable matched firms for the
remaining seven. The results show that the SOEs start to experience an
improvement in their matched-firm adjusted operating performance from
year -1, with a peak in year 0 and then deterioration in year + 1. This
pattern is observed for the matched firm adjusted ROA and ROS (mean and
median) measures of operating performance. At the same time, matched
firm adjusted asset-scaled cash flow from operations (ACFO) do not show
any such pattern. This suggests that SOEs may be using income increasing
accounting accruals to inflate reported earnings at the time of
privatisations, as the increase in earnings measures is not supported by
ACFO. These results are consistent with Teoh, et al. (1998a, 1998b) for
U.S equities and Iqbal, et al. (2006, 2009) for U.K. equity issues. This
warrants further analyses of accruals and its components.
Panel A of Table 4 reports average matched firm adjusted
discretionary current and long term accruals during two years after and
before the privatisation year (year 0). It shows that discretionary
current accruals are positive and statistically significant in the year
prior to privatisation (at 1 percent level) and in the year of
privatisation (at 5 percent level). However, this trend is reversed in
the two years after privatisation, which is consistent with the reversal
of these accruals. Long term accruals are negative and marginally
significant in years -1, 0 and +1 and show a trend opposite to that of
current accruals.
Panel B of Table 4 shows that out of the 153 sample observations
that are available over the testing period, we find that, for
discretionary current accruals, 87 values are positive and 66 are
negative. Further examination for each event years shows a tendency
towards upward earnings management. For example, in year -1 (year prior
to privatisation), we find that 73 percent (24 out of 33 points) show
'upward' earnings management (positive level of difference
between the sample and its matched firm). This pattern is reversed in
year +1 (year following privatisation) where only 33 percent of firms
show upward and 67 percent show downward earnings management. This ties
in with the general observation that earnings management that takes
place before an event is reversed in the future years, which is
reflected in the downward earnings management in the post-event years
[Teoh, et al. (1998a, 1998b)].
Similarly, if we analyse the long term discretionary accruals
(those accruing after one year) comprising of provisions for
depreciation and bad debts, the pattern is pointed more towards downward
earnings management through the long-term component of discretionary
accruals. Out of total 153 sample observations, 56 percent (85) show
negative earnings management. In year -1, we find that 20 (61 percent)
out of the 33 sample points are negative. This could be explained as an
attempt to overstate the book value of assets in the years preceding
privatisation. However in year +1, we see that 20 out of 30 sample
points show downward earnings management. Downward management of these
components will have a positive effect on the value of assets in the
balance sheet. Generally, firms try to avoid using long term accruals to
manipulate earnings as they are relatively easier to identify.
Given a relatively smaller sample size, we do not draw our results
only using mean values and conventional tests (for example t-test). As
an alternative, we use median values of matched-firm adjusted
(discretionary current and long term) accruals and Wilcoxon's
sign-rank test. The results of this test are reported in Panel A, Table
5. It shows that discretionary current accruals are positive and
significant in year -1 and year 0, and negative and significant in year
+1, which is an indication of the reversal of pre-privatisation
discretionary current accruals. The significance in year -1 of
discretionary current accruals is directly in line with our earlier
discussion that the incentives for earnings management are most intense
in the year before privatisation. Even with a one-tail test for upward
earnings management, the above value is significant. This shows that
there is strong evidence of earnings management via current
discretionary accruals in the year prior to privatisation. These
findings are consistent both with the information asymmetry model of
Mayers and Majluf (1984) and the implications of studies by Healey and
Wahlen (1999) and Kothari (2001).
In addition, discretionary long term accruals are significantly
negative in year -1 and year 0, and positive and significant in year +2
but without showing any specific pattern of earnings management. This
positive significance of the long term accruals in year +2 is, however,
harder to understand. This could primarily be attributed to the reversal
of previous long term accruals or to the discretion available to the
post-privatisation management while restructuring long term provisions.
In privatisations, the state shortlists firms for divesture a few years
in advance. Given a longer time frame and the demand made on the
short-listed firms to prepare for privatisation, a substantial amount of
restructuring can be undertaken. These factors naturally affect the long
term portion of accruals instead of just current accruals. The
management makes sufficient provisions for restructuring and exercises
its discretion in estimating these amounts. Thus, it is not only the
current accruals, which may be tampered with, but also the long term
accruals which provide an opportunity for earnings management.
Finally, we perform Spearman rank correlation test between
discretionary current and long term accruals from year -1 and the change
in performance matched ROA from years 0, +1, and +2. The results
reported in Panel B of Table 5 show that the pre-privatisation
discretionary current accruals are significantly negatively related to
change in performance adjusted ROA from years 0, +1, and +2. This
further strengthens our results that SOEs use discretionary current
accruals in year -1 to inflate reported earnings.
It is important to note that Pakistan's economy did not
undergo any structural change during the period 2005-2013 [Pakistan
(2014)]. The share of agriculture and manufacturing in the GDP was 23
percent and 20.6 percent during 2005-06, which slightly changed to 21
percent and 20.8 percent during 2013-14 respectively. Following a
similar pattern, the share of service sector increased from 56 percent
to 58.1 percent during the same period. This shows that the results
presented and discussed above are current and relevant even today.
6. CONCLUSION
This study tests earnings management hypothesis around
privatisations in Pakistan. Our results support the hypothesis that SOEs
use upward earnings management around the privatisation event. Due to a
smaller sample size, we have not been able to perform a regression
analysis of pre-privatisation accruals and post-privatisation earnings.
In addition, though our study covers a period from 1991-2005, there have
been only five further non-financial-sector related privatisations. We
feel that the results of our study, though limited to a certain time
period, are still pertinent to the future cases of privatisations. The
paper highlights an entirely different dimension in the context of
privatisation and should help the Government of Pakistan in better
valuation of its public sector units offered for privatisation. None the
less, this paper makes a significant contribution to a field that has
not been explored as yet, especially in the context of Pakistan. Future
studies can draw upon the rationale that we have provided, as the
incentives are in place for accounting manipulations by the management
of SOEs. The limitations faced in our study can be attributed to the
availability of relevant data, the size of each privatised unit, and the
number of firms in the industry being studied. Future research could be
carried out to empirically test the hypothesis in other countries where
such limitations can be addressed.
Our results show that earnings management occurs around
privatisations, but it is somewhat different from the usual pattern of
earnings management reported in prior literature. Numerous studies have
established the current component of discretionary accruals as being the
relevant indicator of earnings management, and time and again it has
been the current accruals component that has been tampered with by the
management. While this is the case for privatised firms as well, we also
find the long term accrual component to be understated in our sample.
This is due to the long term restructuring provisions that are created
before privatisation. Most firms have the leeway to adjust the current
portion of accruals, but in the case of privatisations, the intention to
privatise is made clear in advance, so that such provisions provide
ample time and scope for earnings management. Thus, our paper
establishes earnings management in the case of Pakistani privatisations
via manipulation of both the short term and the long term accruals.
The ability to manage earnings depends strongly on the regulatory
structure and the degree of information asymmetry. Stricter scrutiny of
firms identified for privatisation (such as OGDC, Pakistan Steel, and
PIA to name a few) by autonomous regulatory bodies can ensure that it is
more difficult for firms to manage their earnings and hence, window
dress their financial statements. Decision makers (bidders) need to be
aware of the potential for firms to misrepresent their financial
situation and engage in closer assessment at the time of sale
(purchase). Establishing an independent review committee and subjecting
public sector firms to greater accountability could also reduce the
degree of earnings management thereby, reinforcing public investor
confidence in SOEs and in the privatisation policy.
APPENDIX I
THE MODIFIED JONES MODEL
The modified Jones model segregates the accruals into its current
and long term components. Each of these components is then tested via a
two-step process to determine the level of discretionary current and
long term accruals for each year. The first step involves estimating the
coefficients through regressions (1) and (2) on the data for each
industry and the results for the current and long term portions are
presented in Table 4:
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (1)
where:
[CAC.sub.j,i] = Current accruals, scaled by beginning total assets
for firm j in year t,
[TA.sub.j,i-1] - firm/s book value of total assets at the beginning
of year t,
[DELTA]REVj,t = firm/s change in revenues from year f-1 to year t.
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (2)
[TAC.sub.j,i] = Total accruals, scaled by beginning total assets
for firm j in year t,
[PPE.sub.j,i] = firm j's gross value of property, plant and
equipment at the end of year t
The second step involves using the same variables for our event
firms and matched firms to estimate their levels of non-discretionary
accruals based on the industry coefficients determined in the first
step. The modified Jones model adjusts for changes in the levels of
accounts receivables. The equation used to find the firm's
non-discretionary accruals is shown below for the current and long-term
portions:
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (3)
where:
[NDCAC.sub.j,i] = Non-discretionary current accruals, scaled by
beginning total assets for firm j in year t,
[DELTA]RECj,t = Net receivables in year t minus net receivables in
year t-1, and
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] = Estimates of
a, [[beta].sub.i] obtained from Equation (1).
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (4)
[NDTAC.sub.j,i] - Non-discretionary total accruals, scaled by
beginning total assets for firm j in year t, and
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] = Estimates of
a, [b.sub.1], and [b.sub.2] obtained from Equation (2).
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(1) Managers may use 'big bath accounting' [Jiang (2007)]
or 'cookie jar reserves' [Badertscher, et al. (2009)] as
possible tools to manage earnings. They may also defer current earnings
to future years or recognise revenues earlier [Lin and Shih (2002)].
Barth, et al. (1999) argue that managers may have incentives to smooth
income over different time periods.
(2) We provide details of earnings management incentives and the
types of firms involved in managing earnings upwards or downwards in
Section 3.
(3) http://www.privatisation.gov.pk/about/Completed%20Transactions%20(new).htm. Accessed on September 10, 2013.
(4) Pinheiro and Schneider (1994, 1995), however, show that
ownership transfers are neutral from fiscal perspective and the
privatisation proceeds are often too little and arrive too late to help
in times of economic crisis. Hemming and Mansoor (1987) and Mansoor
(1988b, 1988a) also argue that ideally, the change of ownership should
have no effect on fiscal deficit due to the fair market price of SOEs.
(5) The valuator is a qualified Chartered Accountant in case of
large transactions.
(6) List of Privatisations from 1991 to 2005, available at
http://www.privatisation.gov.pkA_ln addition, according to the
Privatisation Commission of Pakistan website (checked on 18 March 2015),
there are only five further privatisation transactions over the period
2006-2014 in the non-financial sectors. This further suggests that our
study did not leave out significant amount of data. We would not have
gained significant information even if we had extended our sample period
to 2012, as we needed two further years of accounting data after the
privatisation to examine their performance.
Abdullah Muhammad Iqbal <
[email protected]> is Assistant
Professor, Kent School, University of Kent, Medway, Chatham Maritime, UK
and National University of Sciences and Technology, Islamabad, Pakistan.
Iram Khan <
[email protected] is Joint Secretary, Cabinet
Division, Cabinet Secretariat, Islamabad. Zeeshan Ahmed
<
[email protected]> is Assistant Professor, Lahore University
of Management Sciences (LUMS), Lahore.
Table 1
Distribution (Industrial and Yearly) of Sample Firms,
1991-2005
Chemical/F
Year/Industry Auto Cement ertiliser
1991 1
1992 4 8 4
1993 1
1994
1995 1 1
1996 1
1997
1998
1999
2000
2001
2002 2
2003 1
2004 1
2005 1
%age of the sample 15% 32.5% 17.5%
Total 6 13 7
Fuel/ %age of
Year/Industry Energy Edible Oil Sample Total
1991 2.5% 1
1992 2 45% 18
1993 2.5% 1
1994 1 2.5% 1
1995 5% 2
1996 2 7.5% 3
1997
1998
1999
2000 1 2.5% 1
2001 1 2.5% 1
2002 5 1 20% 8
2003 2.5% 1
2004 1 5% 2
2005 2.5% 1
%age of the sample 25% 10% 100%
Total 10 4 100% 40
The table provides yearly and industrial distribution of the
40 selected sample firms that were privatised during the
period January 1991 to December 2005. It also reports the
percentage of the privatised firms in each year and
industry.
Table 2
Distribution (Industrial and Yearly) of Proceeds (Millions
of Pakistan Rupees) Raised from Privatisations during 1991-2005
Chemical/F
Year/Industry Auto Cement ertiliser
1991 105.60
1992 904.80 5013.70 1407.90
1993 69.20
1994
1995 110.00 399.50
1996 2415.80
1997
1998
1999
2000
2001
2002
2150.90
2003 255.00
2004 793.00
2005 3204.90
%age of total
sample 3.57% 39% 13.08%
Total 1079.60 11792.40 3958.30
Fuel/ %age of
Year/Industry Energy Edible Oil Sample Total
1991 0.35% 105.60
1992 216.30 25% 7542.70
1993 0.22% 69.20
1994 102.40 0.34% 102.40
1995 1.68% 509.50
1996 10151.00 41.55% 12566.80
1997 0.00
1998 0.00
1999 0.00
2000 369.00 1.22% 369.00
2001 142.00 0.47% 142.00
2002 14.90%
2259.40 94.00 4504.30
2003 0.8% 255.00
2004 80.70 2.89% 873.70
2005 10.60% 3204.90
%age of total
sample 43.06% 1.29% 100%
Total 13023.80 391.00 100% 30245.10
The table provides yearly and industrial distribution of the
proceeds raised from the 40 sample firms that were privatised
during the period January 1991 to December 2005. The proceeds
are reported in millions of Pakistani Rupees. It also reports
the percentage of the amount raised from the sample firms in
each year and industry.
Table 3
Operating Performance of SOEs Around Privatisations
Year -2 -1 0
Performance Matched Non-issuer's Adjusted ROA
Median -0.43 0.89 (b) 1.45 *
Mean -1.83 (c) 1.88 (b) 2.28 (b)
Observations 29 33 33
Performance Matched Non-issuer's Adjusted ROS
Median -0.36 (c) 0.77 (c) 1.08 (b)
Mean -1.21 (b) 1.87 (b) 2.06 (b)
Observations 29 33 33
Performance Matched Non-issuer's Adjusted ACFO
Median 0.91 (b) 0.73 0.54
Mean 1.17 * 1.08 0.89
Observations 29 33 33
Year +1 +2
Performance Matched Non-issuer's Adjusted ROA
Median -1.24 (b) -1.18 *
Mean -1.93 (b) -2.63 (c)
Observations 30 28
Performance Matched Non-issuer's Adjusted ROS
Median 0.45 -1.24 (b)
Mean -1.96 (b) -1.51
Observations 30 28
Performance Matched Non-issuer's Adjusted ACFO
Median 1.06 (c) 1.17 (b)
Mean 1.65 (c) 1.98 (b)
Observations 30 28
The table reports mean and median values of three matched-firms
adjusted operating performance measures based on time series.
These are return on assets (ROA-net income divided by beginning
of year total assets); return on sales (ROS-net income over
total sales); and asset-scaled cash flow from operations (ACFO
-cash flow from operations divided by beginning of year total
assets). Matched firm is chosen from the same industry as the
privatised firm, with the closest ROA from year t-1 (the year
preceding the privatisation year). While choosing a matched
firm, we exclude firms that have been privatised in the previous
two years to avoid any contamination effects. Mean values are
tested using conventional t-test and medians are tested using
Wilcoxon sign-rank test. Superscripts b and c represent
significance at the 5 percent and 10 percent levels.
Table 4
Discretionary Current and Long Term Accruals of SOEs Around
Privatisations
Panel A: Matched Firm Adjusted Discretionary Current and
Long Term Accruals
Year (t) -2 -1 0
Discretionary Current Accruals
Mean 0.041 0.049 (a) 0.055 (b)
SE 0.030 0.019 0.026
p-value 0.181 0.016 0.046
Discretionary Long-term Accruals
Mean 0.043 -0.073 -0.197 (c)
Standard Error 0.049 0.054 0.108
p-value 0.384 0.187 0.076
Panel B: Number of Positive and Negative Values of Matched
Firm Adjusted Discretionary Current and Long Term Accruals
-2 -1 0
Discretionary Current Accruals
No. of Observations 29 33 33
No. of Positive
Observations 17 24 23
Percentage Positive 59% 73% 70%
No. of Negative
Observations 12 9 10
Percentage Negative 41% 27% 30%
Discretionary Long-Term Accruals
No. of Observations 29 33 33
No. of Positive
Observations 16 13 13
Percentage Positive 55% 39% 39%
No. of Negative
Observations 13 20 20
Percentage Negative 45% 61% 61%
Panel A: Matched Firm Adjusted Discretionary Current and
Long Term Accruals
Year (t) +1 +2
Discretionary Current Accruals
Mean -0.121 (b) -0.042 (c)
SE 0.060 0.024
p-value 0.054 0.091
Discretionary Long-term Accruals
Mean -0.148 (c) 0.169 (a)
Standard Error 0.086 0.056
p-value 0.096 0.005
Panel B: Number of Positive and Negative Values of Matched
Firm Adjusted Discretionary Current and Long Term Accruals
+ 1 +2 Total
Discretionary Current Accruals
No. of Observations 30 28 153
No. of Positive
Observations 10 13 87
Percentage Positive 33% 43% 56%
No. of Negative
Observations 20 15 66
Percentage Negative 67% 57% 44%
Discretionary Long-Term Accruals
No. of Observations 30 28 153
No. of Positive
Observations 10 16 68
Percentage Positive 33% 57% 44%
No. of Negative
Observations 20 12 85
Percentage Negative 67% 43% 56%
Panel A of the Table reports mean values, standard errors,
and p-values of matched-firm adjusted discretionary current
and long term accruals, estimated using the modified Jones
model (as explained in Appendix 1), for 2 years before and
after the privatisation event. Statistical significance of
mean values is tested using conventional t-test. Superscripts
a, b, and c represent significance at 1 percent, 5 percent,
and 10 percent levels. Panel B reports the number and
percentages of positive and negative observations of
these matched-firm adjusted mean discretionary current
and long term accruals for each event year.
Table 5
Results of Wilcoxon's Sign-rank Test and Spearman Rank Correlation
Panel A: Wilcoxon Sign-rank Test
Year -2 -1 0 +1
Discretionary Current Accruals
Z-score 1.16 1.963 (b) 1.842 (c) -1.846 (b)
Observations 29 33 33 30
Discretionary Long Term Accruals
Z-score 0.892 -1.937 (b) -1.863 (b) -1.410
Observations 29 33 33 30
Panel B: Spearman Rank Correlation
ROA
0 +1 +2
[DCA.sub.-1] -0.198 (a) -0.236 (a) -0.228 (a)
[DLTA.sub.-1] -0.103 (c) -0.128 (b) -0.082
Panel A: Wilcoxon Sign-rank Test
Year +2
Discretionary Current Accruals
Z-score -1.431 (c)
Observations 28
Discretionary Long Term Accruals
Z-score 1.767 (c)
Observations 28
Panel A of the table reports z-scores and relevant significance using
Wilcoxon sign-rank test for matched-firm adjusted discretionary
current and long-term accruals for five years around the
privatisation year (year 0). Panel B reports Spearman rank
correlation between discretionary current and long term accruals
for year -1 and change in matched-firm adjusted return on assets
(ROA) for years 0, +1, and +2. Superscripts a, b, and c
represent significance at the 1 percent, 5 percent, and 10
percent levels.
