Eng rev proposal ch.123_24 jan 20

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CHAPTER I
INTRODUCTION
1.1 Background of the Study
This study focused on the analysis of financial distress state-owned
enterprises or SOEs, taking into account several variables related to keywords. This
research is one of the topics of particular importance in a comprehensive manner the
phenomenon reveal financial difficulties state that the center of attention during this
time, because not able to fulfill the expectations, as mandated by law for State-
Owned Enterprises.
State-owned enterprises, as listed in Article 9 of Law No. 19 of 2003, consists
of two forms of enterprise, namely Public Company Limited and. SOEs in the way
of Persero, the intent and purpose are: (a) the supply of goods/services of high quality
and strong competitiveness and (b) the pursuit of profit to enhance shareholder value.
While the SOEs in the form of Public Enterprise, purpose and objectives are: (a)
organize a business for public benefit in the form of supply of goods/services of high
quality at affordable prices to the community based on the principles of managing a
healthy company, and (b) to support company goals, then with the approval of
Minister of State, General Company can make capital participation in other business
entities.
The phenomenon that occurs during this time, which is among the 115 SOEs
were reported in 2017 as an attachment 9; three groups of companies could
potentially experience financial distress, namely: (a) companies which rely
financially on government subsidies as annex-1, a total of 9 SOE to 8 services sector;
(b) companies that received additional capital as an attachment state or PMN-2, as
many as 27 state-owned enterprises; and (c) have experienced a loss until the end of
the first half of 2017 as appendix 3, a total of 24 SOEs.
Based on the potential for increasingly severe financial distress, the research
is essential in financial distress. It is expected to provide input to the main
stakeholders of SOEs to the key variables that must be considered in preparing
strategies and corporate policies. Research financial distress can also offer early
signals since the preparation of the operational, tactical planning, and strategic plan

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so that the implementation can be anticipated if there are changes to key variables
that affect the financial distress.
Financial distress as a challenge for the management of SOEs to solve it for
state-owned companies mentioned above can be achieved. To achieve this level of
profitability, increase the value of the company, and held firm by sound principles of
corporate management, practical operations should be realized. SOEs have the
opportunity to improve services at the same time seeking profits and supported by
the potential in terms of mastery of natural resources, government support; business
scale is economical, significant market share, likely to foster partnerships between
state-owned enterprises can improve efficiency, human resources in quantity and
quality which fulfill, can adapt the technology and mastery of information systems.
Based on the phenomenon of financial distress, so in this study, their gap
research, namely (a) the financial distress of SOEs as a possible gap and (b) the
improvement of the measurement of financial distress as the conceptual gap. This is
in line with the formulation of the problem, as described in Appendix 7. Practical
gap in this study, the gap or difference between operational conditions should happen
with the functional realization achieved by SOE (das sollen - das sein), Operational
requirements that should happen meant that SOEs have strong business prospects, so
there are opportunities or opportunity earn a decent level of profitability and the
ability to meet and manage their finances independently. The realization of these
SOEs achieved operational, the inability to meet the needs of funding and investment
operations, because the management of the company is not optimal, thus potentially
experiencing financial distress.
In connection with the phenomenon and a gap referred to above, the next
stage in this research is the formulation of the problem by taking into account the key
variables that affect the level of financial distress of SOEs. In contrast, the selection
of these variables is based on empirical conditions backed by company references
theory and previous research. References used in this study became the basis of the
submitted hypothesis, measurement variables, and prepare the analysis model to test
the hypothesis.
Measurement of financial distress as the dependent variable is still
constrained by a conceptual gap because previous studies used relatively simple

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measures of financial distress than the phenomenon of SOEs is relatively very
complex. Measurement of financial distress in previous studies as an attachment-12,
using qualitative data with a nominal scale was statistically recognized as the scale
of the simplest or the level most in one study, following the ordinal scale, interval
scale and the highest level is a ratio scale (Divine, 2016 and Nurizzati, 2012). This
is evident because the nominal scale that uses the criteria of 0 and 1 or 1 and 2, which
represents a group of companies experiencing financial distress and healthy
enterprise groups,
Variable measurement of financial distress prior studies as an attachment-11
tend to be the same as mentioned above, but there is a difference in the determination
of boundaries or definition of the group of companies experiencing financial distress,
such as the following:(a) Altman, Marco and Varetto (1994) and Yang, Platt and
Platt (1999), using the model of the neural network to distinguish companies that fail
and did not fail; (b) Lau (1987) and Hill et al. (1996), using the indicators of
companies experiencing financial distress, namely the existence of layoffs or
eliminate the payment of dividends; (c) Asquith, Gertner, and Scharfstein (1991),
using indicator defines interest coverage ratio for companies experiencing financial
distress; (d) Whitaker (1999), a measure of financial distress by using an indicator of
cash flows is less than the long-term debt maturing this time; and (e) John, Lang, and
Netter (1992), defines financial distress as the change in equity prices, (Gamayuni,
2009).
Besides the differences in the determination of boundaries or definitions to
companies experiencing financial distress, previous research has also tended to vary
in the use of analytical models and the selection of independent variables as well as
a brief history of the study of financial distress in the appendix-11.
Analysis of financial distress since it was first proposed by Beaver (1966)
until now generally use three models of analysis (Gamayuni, 2009), namely: (a) The
analytical model of multiple discriminant analysis, or MDA, using the measurement
of financial distress with nominal data category 1 and 2 in an earlier study initiated
by Beaver (1966), Edward Altman (1968), Gordon LV Springate (1978), Fulmer
Model (US, 1984), and Ca-score (1987). The discriminant analysis model is marked
with a special feature. Namely, the dependent variable data or categories of data

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should be required nominal independent variables and normal distribution. If
categorical data only two categories of so-called "Two-Groups Discriminant
Analysis" and if more than two groups called "Multiple Discriminant Analysis." (b)
logistic regression analysis model, using measurement of financial distress with
nominal data dichotomy of 0 or 1 on the research is conducted Ohlson (1980),
Thomaidis et al. (1998), Platt and Platt (2002), Almilia and Kristiaji (2003), Angelina
(2004), Berg (2005), Brahmins (2005) and Hsieh et al. (2006). In this logistic model,
the dependent variable using dichotomous scale data or nominal scale with two
categories, and the independent variables are not required normal distribution. (c)
The model of linear regression analysis, using the measurement financial distress
based on scores of previous studies mentioned above, such as the score Altman
(1968), score Springate (1978), score Fulmer Model (1984), and CA-score (1987),
in research such as Wilopo (2001), and Taufik Adnan (2001), Aryati and Manao
(2002), and others as noted in chapter 2 previous studies.
Of the three models of analysis in previous studies referred to above,
conceptually there are gaps or gaps because it is relatively simple to perform variable
measurement of financial distress as attachment-12 and there is no consensus in
defining boundaries or definition of companies experiencing financial distress as
attachment-11, so the results measurement variables can also differ from one study
to another. Further, when previous studies have gaps or weaknesses as mentioned
above, the study using measurement-based financial distress score Altman and others
also has the potential to have the same gap or weakness.
To fill gaps or gaps prior to studies referred to above and attachment-11, this
research develops novelty or newness measurement-based financial distress marginal
theory, as expressed in section 2.1 and section 3.3. Selanjtunya, as compared to the
previous research on attachment-12, this study used a multiple linear regression
model that is more comprehensive, which is, also, uses the independent variable to
predict the dependent variable of financial distress, is also equipped with an
intervening variable and variable control.
The independent variable is selected from the indicators or key financial
ratios affecting financial distress, i.e., investment growth, the growth of the working
capital, growth in retained earnings, earnings growth before interest and taxes,

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increase in contribution margin, growth equity, the level of efficiency and
productivity operation, real activities earning management, and accruals earnings
management. Intervening variables, chosen from cash flow from operating or CFO
because it has an important position that indicates the ability of the company's
management in controlling the cash inflow and cash outflow in order not to
experience financial distress. The variable control is selected from the size of the
company, leverage, and government subsidy and equity,
The model analysis of this study is expected to be able to explain the observed
phenomena. Still, it takes a variable measurement model, more realistic financial
distress corresponding experimental conditions of SOEs. And to achieve these
expectations, then in this research analysis model has been developed the concept of
newness or novelty variable measurement of financial distress to approach marginal
score. Measurement of these variables using a ratio scale data from financial reports
and the formulation was developed from the concept of marginal balance that has
been adapted to the needs of this study, as described in Chapter 2 and chapter 3.
Variable measurement of financial distress with a score of marginal able to
fill gaps or gaps previous studies, during which only uses a measurement is relatively
simple as mentioned above, the measurement of financial distress using the
categories 1 and 2 on the model of multiple discriminant analysis, using categories
dichotomy of 0 and 1 on the model logistic regression, and using the score obtained
from previous studies in multiple linear regression model, for example, using the
measurement of financial distress based on the score Altman (1968), score Sprigate
(1978), score Fulmer (1984), CA-score (1987), and score Plate and Plate (2002).
Compared with the measurement of financial distress in previous studies,
then the specificity or originality in the measurement of financial distress this study,
namely: (a) score of marginal use ratio data sourced from financial statements, (b)
score of marginal no separate category of healthy company with Companies
experiencing financial distress, and (c) the final results of research showing the
prediction of financial distress with a value score of marginal maximum one for the
company with the best conditions, approaching a meaningful near-optimal, and so
when the score value marginally close to zero then companies tend to experience
financial distress as attachments 6.

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Excellence approach scores of marginal, i.e., enhance and develop the
measurement of financial distress that could fill gaps or gaps are the weaknesses of
previous studies, especially in the case of (a) the qualitative data nominal scale is too
simple compared to the complexities faced by companies experiencing financial
distress, (b ) does not occur uniformity in defining or determining limits as
companies experiencing financial distress, (c) the research model previously less
attention to the variety of companies experiencing financial distress, but generally
provide value by category 0 or 1 (d) of previous studies can not be done if only one
group of companies, because the dependent variable data does not vary, for example,
the overall sample comes from the same group of companies that are experiencing
financial distress (all values = 0 or 1), (e) measurement with a score based on the
results of previous studies are like score Almant others are less realistic because the
data used is less relevant to business conditions and industry today.
Based on the concept of novelty measurement-based financial distress score
is marginally mentioned above, it can be stated that this research can contribute
significantly to the implementation of financial distress studies on State-Owned
Enterprises. This study can be implemented in terms of giving feedback to the
company's main stakeholders like shareholders, management, employees, customers,
suppliers, banks, practitioners, researchers, and other parties interested in the
company. The results of this study in the form of multiple linear regression equation
estimations that can be used as an instrument or tool in the process of decision-
making SOEs.
Estimation of the regression equation can be used to predict the observed
score is marginal SOEs, by calculating the amount of the coefficient of influence of
each variable with realization figures last year financial statements of each SOE.
Score prediction calculation results show the achievement level of marginal financial
distress that can be inferred, i.e., when the marginal score (SMg) is equal to one, then
the company in the best condition and not optimal or financial distress. If the score
is marginally closer to the optimal approach means that the company, and if the
marginal score close to zero, then companies tend to experience financial distress.
Score prediction calculation results marginally as aforesaid can be used for
various internal interests of state-owned enterprises, especially in the case of (a) the

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achievement of corporate planning with a target score of certain marginal
increasingly from time to time; (b) assess the success of the company's management
in achieving the performance score is marginally programmed; (c) comparing the
level of achievement of marginal score between SOEs; (d) as an instrument
monitoring management performance of SOEs to be more focused on strategy and
policy on key variables to improve the performance of companies with a marginally
better score for the future; and (e) became the standard assessment company as
healthy or are likely to experience financial distress based on the amount of marginal
score.
Meanwhile, another benefit of this research, that can be developed
implementation on a broader context, such as (a) other state outside of the study, (b)
companies listed on the Stock Exchange, (c) group of companies according to sectors
that are more specific for example sector manufacturing, banking sector, the service
sector, and others, (d) small and medium businesses, and (e) cooperative.
Based on the contribution of newness or novelty measurement of financial
distress referred to above, this research is especially important because the level of
urgency that is more specific in terms of (a) mapping the rating achievements of
scores of marginal SOEs, which is still subsidized, receiving additional state equity
participation, and a loss, to know the level of financial distress each SOE in question,
(b) provide feedback to the management of SOEs to priority factor to consider in
improving scores marginally to overcome financial distress, and (c) a reference for
the management of SOEs in preparing strategies and policies related variables that
affect the marginal scores to overcome financial distress.
1.2 The motivation of the Study
In response to the phenomenon and the problems of the financial difficulties
faced by the State-Owned Enterprises, this research is motivated in the case, namely:
(a) study the factors that affect the financial distress of SOEs, and (b) to research and
develop methods of measuring financial distress, as a novelty to enhance the
measurement method of financial distress in the previous study.
Motivation study on the factors that influence financial distress
This research is motivated to analyze the influence of independent variables
on the dependent variable of financial distress. The impact will be analyzed by the

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direct method approach and indirect methods. The direct method by analyzing the
direct influence of the explanatory variables on the dependent variable of financial
distress.
Explanatory variables consist of a group of independent variables and control
variables, which has particularly groups that function as the independent variable key
variables analyzed and tested its effect because the independent variable is predicted
to have a significant impact on the financial distress. While the control group serves
as a control variable to anticipate the occurrence of bias in the analysis if this variable
is not included in the regression analysis model. With the existence of these variables,
the results of the study which shows the relationship between independent variables
with more realistic financial distress because of other variables as control variables
affecting the financial distress accounted for in the regression analysis.
The method of indirect influence is done by the analysis of explanatory
variables' influence on the intervening variables from the operating cash flow that
affect the dependent variable of financial distress. This analysis used two models of
analysis is the first model to analyze the effect of explanatory variables on an
intervening variable operating cash flow, then the second model to analyze the effect
of intervening variable operating cash flow to the dependent variable of financial
distress. Further test method path analysis to prove that the variable is the operating
cash flow as an intervening variable in the relationship between independent
variables with financial distress. If the test result is significant, it can be stated that
the independent variable significant effect on cash flow and a significant impact on
financial distress conversely, if the test results were not statistically significant, the
cash flow from operating not as an intervening variable, which means that the
independent variables directly affect the financial distress.
The results of the regression analyze an input for SOE management in
preparing strategies and policies of the components associated with the key variables
that affect financial distress. To achieve the target of increasing the marginal score,
which measures financial distress, the SOE management must pay attention to the
anatomy of the critical variables and makes the critical performance indicators of
various fields at lower management levels. Based on KPI indicator that follows the
anatomy of the key variables, then the target score is marginally projected by

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management, can be achieved through the support of the overall performance of the
field both horizontally between relevant operational areas, as well as vertically in
organizations ranging from the lowest unit to the central office.
Motivation to learn and develop methods of measuring financial distress
This research was motivated to create methods of measuring financial
distress a more realistic and enhance previous studies. Some of the weaknesses in the
measurement of financial distress in the study occurred in the use of a straightforward
categorical data, or less realistic for bankruptcy levels vary greatly, so there may be
generalized in sizes 0 to healthy companies and one for companies experiencing
financial distress. Previous studies are not uniform in the definition or define a
category of companies experiencing financial distress or healthy company as
outlined in Attachment 11. Subsequent research, the last few years using scores
generated from previous studies such as score Altman and others,
Of the phenomenon of the conceptual and methodological gap this gap, this
research is motivated to develop new methods as a novelty in the measurement of
financial distress. The variable measurement method was developed based on the
concept of marginal theory with mathematics approach to producing more realistic
financial measures, which resulted in scores of marginal or SM with a range that
varies from 0 to 1. The marginal Score varies so that the size of companies
experiencing financial difficulties or health can not be generalized because every
company has a different level, e.g., SM = 0 is experiencing financial problems, SM
= almost 0 likely to experience financial distress, SM = approximately 1 tend to be
healthy, and so on up to SM = 1 or fit.
This is where the advantage of measurement-based financial distress score
marginally developed as a novelty in this study, because empirically for each
company having financial difficulty levels and health levels varied. Previous
research only specifies a category 1 for companies experiencing financial distress
and a group 0 to good companies. Hence, it is less realistic when compared to the
level empires SOE's financial distress or the company in general.
1.3 Statement of the Problem
The problem statement in this study is the phenomenon of diminishing in the
management of State-Owned Enterprises (SOE) Indonesia. 2018 as Appendix 4, it

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was reported that about 43% state-owned companies are experiencing financial
difficulties due to losses, the need for subsidies to continue their business, and require
additional equity to meet its operational needs.
Based on the problem statement above, the purpose of this study is to analyze
the phenomenon faced by SOEs are experiencing financial difficulties so that the
state's financial burden and unable to pay dividends to the government as a
shareholder. This condition becomes interesting to study because SOE has
particularly strong potential that is not supposed to have financial difficulties.
Potential SOE includes extensive control of natural resources, market share, business
scale in the capital and labor-intensive, government support, the ability to adapt the
technology, a reliable human resources in terms of quality and quantity, and
experienced management.
This study will be an opportunity to assist in identifying the key variables that
significantly influence the financial difficulties encountered problems SOE. This
research analyzes the key variables that affect SOE financial distress and produces a
measurement used to assess the level of financial distress each SOE. Score marginal
as the level that describes the level of financial distress, and to increase those levels
should pay attention to the critical variables in the study. The results of this study can
be used to assess the success of SOE management because the marginal score of the
results of this study can be used to measure starting from companies experiencing
financial distress to the good companies. Score zero indicates tendencies have seen
financial distress, and vice versa approaching a marginal score indicates companies
tend healthily. The results of this study are also useful to give input to the
management of the SOE in setting corporate strategy and policy in the short and long
term. Like the shareholders or the government can be used in determining key
performance indicators (KPIs) and evaluate the results achieved by the SOE
management.
To research results more realistic, the study aims to develop a new method
(novelty) in the measurement of financial distress, to cover the weaknesses of
previous research measurement as outlined in appendix 11. This study developed a
measurement of financial distress or marginal scores based approach to the theory of
marginal as appendix 5. the marginal concept is often used in pricing policies and

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policy determination of the quantity of production or sales that result in the best
condition or the maximum benefit for the company.
1.4 ResearchQuestions
Based on the background above, formulated several major problems the
State-Owned Enterprises below.
1. Has the growth of investment or capital expenditure (X1ΔCAPEX) direct and
significant effect on the financial distress (YFINDIS) State-Owned Enterprises,
or indirect impact through growth in cash flow from operating (ZΔCFO)?
2. Has the growth of working capital (X2ΔWC) direct and significant effect on the
financial distress (YFINDIS) State-Owned Enterprises, or indirect impact
through an increase in cash flow from operating (ZΔCFO)?
3. Has the growth of retained earnings (X3ΔRE) direct and significant effect on the
financial distress (YFINDIS) State-Owned Enterprises, or indirect impact
through an increase in cash flow from operating?
4. 4b. Is the earnings growth before interest and tax (X4ΔEBIT) direct and
5. Has the growth Contribution margin (X5ΔCM) direct and significant effect on
the financial distress (YFINDIS) State-Owned Enterprises, or indirect impact
through growth in cash flow from operating (ZΔCFO)?
6. Is the growth of equity or equity (X6ΔEQ) a direct and significant effect on the
financial distress (YFINDIS) State-Owned Enterprises or indirect impact through
an increase in cash flow from operating (ZΔCFO)?
7. Is the level of efficiency or productivity of the operation (X7EFSO) direct and
8. Are real earnings management activities (X8RAEM) direct and significant effect
on the financial distress (YFINDIS) State-Owned Enterprises, or indirect impact
through growth in cash flow from operating (ZΔCFO)?
9. Do accruals earnings management (X9ACEM) direct and significant effect on the
financial distress (YFINDIS) State-Owned Enterprises or indirect impact through
growth in cash flow from operating (ZΔCFO)?

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10. How to influence the growth of cash flow from operating (ZΔCFO) against
financial distress (YFINDIS) State-owned Enterprises?
1.5 contribution research
This research is important to analyze the research gap and explain the
phenomenon of the financial difficulties faced by state-owned business entities
(SOE). Also, this study developed a new method of measuring financial distress,
which is a novelty in the method of measurement of financial distress.
The phenomenon of financial difficulties as a possible gap, namely the
management of SOEs, has not been able to manage the company to achieve the
objectives as set out in the legislation establishing a BUMN no. 19, 2003, i.e.; (a)
SOE-PERSERO founding purpose is the pursuit of profit to increase the value of the
company, and (b) SOE-PERUM founding goal is the provision of goods and services
of high quality at an affordable price by the public based on sound principles of
corporate management. It is evident that out of 118 SOEs were recorded in 2018, and
there are a number of SOEs that are experiencing financial difficulties as appendix
4, which is 9 SOEs receive government subsidies as total revenue less than total cost,
The phenomenon of SOEfinancial difficulties should not have happened and
can achieve financial performance as outlined in the law no. 19, 2003, as SOE has
potential, especially in terms of government support as a shareholder, has a
significant market share, control of resources, trusted by financial institutions, and
has the human resources in the amount and quality of fulfilling.
Based on this phenomenon, the researchers were motivated to examine key
factors affecting the financial difficulties of state enterprises and provide input on the
management in the preparation of corporate policies and strategies to overcome
financial problems SOE.
This study also contributes to overcoming the weaknesses of financial
distress measurement is used for this weakness in financial distress measurements
used in previous studies as appendix 11.
The weakness of previous studies grouped into two stages of the study period,
namely: the first stage, starting from the review of financial distress by Beaver
(1966), followed by Altman (1968, 1977), and so on that using logistic models and
models discriminant. The study uses data categorical or nominal, with the method of

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measuring financial distress, the good company rated 0 or 1, and the company went
bankrupt rated 1 or 2. The weakness of categorical data 0 and 1 is especially true in
the case of (a)there is a difference in the determination of boundaries or definition of
a group of companies experiencing financial distress, and (b) the healthy category 0
and bankrupt one less relevant because the level of a healthy company can not be
generalized to score the same, for example, 0, because the health level varies, starting
from the very wholesome, healthy and less healthy. Likewise, the bankrupt company
can not be generalized with a score of 1 because the bankruptcy rate varied from very
broke, bankrupt, and started to go bankrupt. The first stage of this research to produce
a score to measure the rate of the bankruptcy of the company, then the score used in
future studies to measure financial distress.
The second phase, Studies that measure financial distress by using score
results of previous studies, for example, score Altman (1968), score Springate
(1978), score Fulmer Model (1984), Ca-score (1987), and others. Research for the
second stage can be seen in studies such as that conducted by Wilopo (2001), Adnan
and Taufik (2001), Aryati and Manao (2002), and others, which measures financial
distress based on the score, and then used regression models to analyze factors
affecting financial distress. The disadvantage of the measurement of financial
distress in the first stage of research, impact on the second stage of research because
it uses the scores of previous studies such as score Altman and others.
Based on the research of weakness first stage and the second stage, this study
contributes to explain the research gap not only to the phenomenon of SOE financial
difficulties but also contribute to enhancing the measurement of financial distress
than in previous studies.
This study contributes to the research gap, as in Hazierah and John (2017) in
the appendix-10, namely:
a. Theoretical gap, this study contributes in terms of using the theory of marginal
as sub-chapter 2.1.1, appendix-5, and Appendix 6, to develop the measurement
of financial distress, thus providing relevant results with empirical conditions on
the measurement of financial distress.
b. The conceptual gap, measuring the marginal score used in this study, provides
uniformity in the concept of measuring the level of financial difficulties, ranging

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from the most bankrupt up healthily, with a range of scores ranging from 0 to 1.
This study contributes to perfect previous research, especially in use Data
categorical 0 to good companies and one for the company goes bankrupt.
Definition and limitations of different categories of companies go bankrupt each
other or not uniform as appendix 11.
c. Empirical gap, this study contributes in the development of the measurement of
financial distress that can be used to generalize empirically, because the level of
financial distress is determined not only 0 or 1, but measured quantitatively by
level or score ranging from 0 to 1, measurement of marginal score approach
mathematics very realistic and verifiable quantitative data based audited financial
statements.
d. Methodological gap, this study contributes to the development of methods of
measurement of financial distress, so it's not just limited to the measurement
method is based on the scores of previous studies such as score Altman and
others, but using methods that are supported by theory and evidence in
mathematic.
e. Practical gap, this study measures the financial distress based on data from
audited financial statements. In the practical measurement of financial distress is
not affected by other factors beyond the conditions of financial indicators that
make up the marginal revenue, marginal cost, and marginal score on the
measurement of financial distress.
1.6 Significance of the Study
This research is very exhibited a significant role in efforts to overcome the
problems of financial distress, especially for SOEs that still depend on the financial
needs of the state budget subsidies, obtaining additional capital the country, and
suffered losses. The results could also be used to assess the level of success of
profitable state enterprises, for optimal success is achieved when the marginal score
is equal to one, on the contrary, tend to experience financial distress marginal when
the score is close to zero.
This research is significant from the aspect of the measurement model of financial
distress because the research previously has drawbacks as annex 11 and annex 12.
This study developed a model of novelty or newness measurement of financial

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distress that can fill in the gaps or weaknesses of previous research, so this study has
contributed very significantly in the measurement of SOE financial distress, it can
even be implemented in financial distress research company listed on the Stock
Exchange.
1.7 Objective of the Study
Research purposes
Based on the problems of the State-Owned Enterprises above, the primary
purpose of the research is presented below.
1. Analyzing the direct influence of investment or capital expenditure growth
(X1ΔCAPEX) against financial distress (YFINDIS) State-Owned Enterprises,
and examine the effect of indirectly through cash flow from operating (ZΔCFO).
2. Assessing the level of significance directly influence the growth of working
capital (X2ΔWC) against financial distress (YFINDIS) State-Owned Enterprises,
and examine the effect of indirectly through cash flow from operating (ZΔCFO).
3. Analyzing the direct influence of the growth of retained earnings (X3ΔRE)
against financial distress (YFINDIS) State-Owned Enterprises, and examine the
effect of indirectly through cash flow from operating (ZΔCFO).
4. Assessing the significance level of direct influence earnings growth before
interest and tax (X4ΔEBIT) against financial distress (YFINDIS) State-Owned
Enterprises, and examine the effect of indirectly through cash flow from
operating (ZΔCFO).
5. Reveal the significance level directly influence the growth Contribution margin
(X5ΔCM) against financial distress (YFINDIS) State-Owned Enterprises, and
examine the effect of indirectly through cash flow from operating (ZΔCFO).
6. Studied the direct effects of growth equity or equity (X6ΔEQ) against financial
distress (YFINDIS) State-Owned Enterprises, and examine the impact of
indirectly through cash flow from operating (ZΔCFO).
7. Analyzing the direct influence of the level of efficiency or productivity of the
operation (X7EFSO) against financial distress (YFINDIS) State-Owned
operating (ZΔCFO).

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8. Studying the direct influence of the real practice of earnings management
activities (X8RAEM) against financial distress (YFINDIS) State-Owned
operating (ZΔCFO).
9. Reveal a direct influence accruals earnings management practices (X9ACEM)
against financial distress (YFINDIS) State-Owned Enterprises, and examine the
effect of indirectly through cash flow from operating (ZΔCFO).
10. I am analyzing the effect of growth in cash flow from operating (ZΔCFO) against
financial distress (YFINDIS) State-Owned Enterprises.
Benefits of research
This research resulted in a new concept in measurement of financial distress
by using a series of variables related to comprehensively so that it can provide
benefits in terms of:
a. (a) Development of science to the study of financial distress with a more
comprehensive analysis.
b. (b) Provide input to the management of SOEs in the formulation of corporate
policies related to financial distress factors affect on SOEs. Provide information
to investors and creditors of financial distress faced by SOEs.
c. (c) Ensuring that the data can be used by financial practitioners who can help
anticipate financial difficulty SOE.
d. (d) Be a reference for the research came, both to the study of financial distress of
SOEs and other companies.
1.8 Organization of Thesis
The research proposal for State-Owned Enterprises is assembling
systematically, i.e.:
Chapter I Introduction consists of Background of the Study, Motivation of
the Study, Statement of the Problem, Research Questions, Contribution of the Study,
Significance of the Study, Objective of the Study, and Organization of Thesis
Chapter II Literature Review, consisting of Agency Theory, Signaling
Theory, Marginal Approach, Financial Distress, Marginal Approach Research, and
SOE Research

17
Chapter III Conceptual Framework and hypothesis development, consisting
of Conceptual Framework and Hypothesis Development.
Chapter IV methodology, consisting of Research Design, Sample Selection,
Measurement of Variable, and Research Model

18
CHAPTER II
LITERATURE REVIEW
2.1. Agency Theory
The cornerstone of the theory used in this study is agency theory was developed by
Jensen and Meckling (1976), arguing that this theory explains the two parties have
different interests, namely the shareholders or principals who want to maximize the
receipt of dividends per share or earnings Per-share, while corporate managers who
want to optimize the receipt of compensation. Managers can manage the company
mentioned to achieve the desired goals of shareholders, and managers will be paid a
decent amount of compensation to be motivated in carrying out its duties and
responsibilities.
The management of the company by a manager is very important because it is
closely related to the variables that affect the financial distress that will affect the
value of the company that ultimately serves the interests of the company, as presented
in Figure-1. This indicates that the agency theory as the basis of relevant theories
used in this study, especially in responding to the problem, test or prove the
hypothesis, and explain the results of the analysis. Management strategy and policies
of the company (agent) to meet the interests of shareholders (principal) affects key
variables associated with financial distress.
Figure 1: Agency theory and financial distress
2.2 Signaling Theory
Melewar and Tucker(2005) suggest that the signaling theory shows that the

19
company will give a signal through action and communication. The company
adopted these signals in revealing the hidden attributes to stakeholders (stakeholder).
The company seeks to inform the financial statements, give a signal about the various
factors that affect the company's financial condition, and communicate the strategy
and policy measures to improve financial performance.
This study uses signaling theory as a basis for analyzing financial distress,
mainly due to management actions in setting corporate strategy and policy, is closely
related to the variables that affect the level of the score of marginal or financial distress
that occurred in SOEs as noted in Figure 2 which shows the linkage among the
variables used in this study following the signaling theory.
Figure 2: Signaling theory and financial distress
2.3 marginal Approach
The marginal approach is the application of differential calculus on the
behavior of consumers and producers, as well as the determination of market prices
at the optimal quantity (Kastan and Restiati, 2013). Implementation approach is

20
marginal as attachment-5 is also used to (a) determining the minimum cost per unit
on condition that the marginal cost is equal to average cost (MC = AC), (b) the level
of profits maximum or losses to a minimum with the requirements of marginal
revenue equals marginal cost ( MR = MC), and (c) the maximum income requirement
is equal to zero marginal revenue (MR = 0).
Kauder (1965), in his writings on a history of marginal utility theory, suggests
that this marginal theory was first developed by Hendrick Gossen (1810-1858)in
explaining the satisfaction (utility) from consumption of similar goods (Kauder,
1965). According to him, the satisfaction of marginal (Marginal Utility) from the
consumption of wide goodwill falls if the same products are consumed more (Law
Gossen I). In the second Gossen law, explaining that the resources and funds
available are always limited in relative terms in fulfill various needs are relatively
limited. At the time of this theory received less attention from economists, but some
40 years later, a group of economists who are members of the School of Austria, such
as Jevons, Menger, Böhm-Bawerk, and Von Wieser, give recognition and
appreciation for the work of Gossen. Since then, the concept of marginal recognized
as a significant contribution to the Austrian school.
In development by Kauder (1965), this theory has been used for the findings
of a new theory, mainly since the period neoclassical such as (a) the Austrian school
with the main characters Karl Menger who developed the theory of marginal utility
in his Grusatze der Volks Wirtshaftslehre (1817), ( b) schools of Cambridge
pioneered by Alfred Marshal with his main works include the pure theory of foreign
trade (1829), and (c) the school of Lausanne, led by Leon Walras, with his work
elements of pure economics (1878).
In this study, the marginal concept was developed by adding the formula as
a novelty in the measurement of financial distress as outlined in the discussion of the
measurement of the marginal score on item 4 and appendix 6.
The development process of measurement of financial distress formula, based
on a marginal approach used in the derivative function of demand and supply
function analysis, marketing analysis, cost theory, production theory, utility theory,
decision management companies in various market structures, and others. The

21
method of analysis in the marginal concept is using a mathematical approach and the
approach chart analysis, as in Debertin (2012) and annex 5.
1) Mathematics Approach
Optimum condition or maximum profit is reached an equilibrium marginal
cost and marginal revenue to obtain profit (π) from the total revenue (TR) minus total
cost (TC) with the formula as in Debertin (2012), the following.
Π = TR - TC
Where: Π, TR, and TC is a function of the quantity (Q)
To maximize profit, the company must produce a certain amount on condition
MR = MC, so the maximum profit obtained in the first derivative of the equation or
the following profit function.
dΠ
dQ
=
dTR
dQ
−
dTC
dQ
= 0
or
dTR
dQ
=
dTC
dQ
In other forms, the maximum profit is obtained when the marginal revenue
(MR) equals marginal cost (MC). MR is the change in output per unit total receipts
or sales. While the MC is the change in total costs per unit change in output, Debertin
(2012), the following.
Δπ
ΔQ
=
ΔTR
ΔQ
−
ΔTC
ΔQ
= 0
ΔTR
ΔQ
−
ΔTC
ΔQ
= 0
ΔTR
ΔQ
=
ΔTC
ΔQ
That balance can be simplified into or with the balance of MR = MC.MR −
MC = 0
Based on that balance, developed a formula measuring the marginal score
(SMg), which in the first stage with a comparison between MR with MC below.
MR
MC
= 1

22
ΔTR/ΔQ
ΔTC/ΔQ
= 1
The next stage, to suit the needs of statistical or econometric analysis, it is
simplified as stated in more detail in the subsequent description of the novelty
measurement of financial distress and Annex 6, namely:
SMg = 1 -√(
(
ΔTR
ΔQ
)−(
ΔTC
ΔQ
)
(
ΔTR
ΔQ
)
)
2
Where:SMg = score marginal, MR = marginal revenue, MC = marginal cost,ΔTR = change
in total revenue, ΔTC = change in total cost, ΔQ = change in quantity sold.
2) Chart Analysis Approach
Analysis relationship curve TC, TR, MR, MC, AVC, and AC described with
optimal quantity of sales of Q1 at a price of P1 occurs at point A, while the sales
quantity Q1 at a price of P3 is on condition serious of financial distress, it is better to
stop operational company so as not to cause more significant losses, as the price of
P3 on the quantity of sales Q1 were unable to cover variable on the AVC curve.
Figure 3: Balance Marginal Revenue and Marginal Cost (MR = MC)
Where: MR = marginal revenue, MC = marginal cost, AC = average cost, AFC = average
fixed cost, P = price, Q = quantity of sales, D = demand.

23
The balance of the marginal yield optimal conditions with mathematical
approach and graphs, examples presented in appendix 5.
4. Novelty of Financial Distress Measurement (Score Marginal)
A novelty in this research is the measurement of financial distress or financial
difficulty level SOEs. Measurement of financial distress using a formula based on
the marginal approach that has been adapted to the purpose of research. To show the
identity of the measurement of the financial distress formula, then used the title as a
marginal score (SMg).
Score marginal as a derivative of the formula MR = MC balance that results
in optimal condition or maximum profit-making, as noted earlier in mathematical
equations and graph analysis.
In the early stages of development SMg measurements, use formulas
comparison, the SMg =
MR
MC
. The optimal condition when
MR
MC
= 1 or MR = MC or MR
- MC = 0, and the conditions are not optimal when
MR
MC
> 1 or MR – MC > 1; and
MR
MC
< 1 or MR - MC < 1, so that the ratio MR and MC or marginal scores formulated
with the absolute value of the SMg = MR - MC, or SMg = √(MR − MC)2 with SMg
optimal value is equal to zero. Then for the purposes of statistical or econometric
analysis in this study, the marginal score formula is adjusted to the optimum value
of SMg, which is equal to one, as the example calculation in Appendix 6, with the
following formula.
SMg = 1 -√(
MR−MC
MR
)
2
Marginal revenue (MR) and marginal cost (MC) is formulated as previously
explained, i.e.
Marginal revenue (MR):
MR =
ΔTR
ΔQ
Marginal cost (MC):

24
MC =
ΔTC
ΔQ
Where:
ΔTR = TR (t) - TR (t-1)
ΔQ = Q (t) - Q (t-1)
ΔTC = TC (t) - TC (t-1)
So in the end, score calculation marginal (SMg) more operational formulated into:
SMg = 1 -√(
(
ΔTR
ΔQ
)−(
ΔTC
ΔQ
)
(
ΔTR
ΔQ
)
)
2
Where:SMg = score marginal, MR = marginal revenue, MC = marginal cost,ΔTR = change
in total revenue, ΔTC = change in total cost, ΔQ = change in quantity sold.
SOE's financial distress can be described through a marginal approach,
assuming the SOE market forming a horizontal MR curve because the government
controls pricing. The selling price is relatively constant for a certain period on a
variety of sales quantity (Q), thus forming the MR curve similar to the assumption
of the company in a perfectly competitive market structure as described below.
Level price P and MR with a balance point E on structure perfectly
competitive market that the company received the price established by the market
mechanism is based on the balance of demand and supply. This research is used to
explain that the level price P and MR formed through the mechanism of government
policy, shareholders, and company management to establish equilibrium at point E.
Figure 4: Curves of Marginal (MR = MC)
Where: MC = marginal cost, MR = marginal revenue, AC = average cost, S = supply, D =
demand, P is price and Q = quantity sold

25
Companies that are in a Marginal position revenue (MR) equals marginal cost
(MC) show that the management of these companies produce the best operating
performance or optimal so that it can be stated that the company is experiencing
financial distress. The optimal conditions described in the calculation and analysis in
appendix 5 and appendix 6.
The balance condition occurs at point E, i.e.: MR = MC or MR-MC = 0 or
MR / MC = 1. If there is a gap between the MR and MC are getting higher, so
companies tend to experience financial difficulties or financial distress, as described
in the distance between the MR and MC curves before and after the point E on the
curve marginal balance.
2.4 Financial Distress
Financial distress is defined as a stage company that can not meet the payment
schedule or when the cash flow projections indicate that the company is unable to
meet its obligations (Brigham and Daves, 2007). Meanwhile, Platt and Platt (2002),
argued that financial distress is the stage of decline in the financial condition
experienced by a company, which occurred prior to the bankruptcy or liquidation.
Other Definitions slightly different, put forward by Darsono and Ashari (2005),
which states that financial distress can be defined as the inability of the company to
pay its financial obligations at maturity that led to the bankruptcy of the company.
Meanwhile, Gamayuni (2011),
Based on the above-mentioned point of view, it can be stated that the financial
distress the financial condition of the company is in trouble, crisis, or unhealthy
happened before the company went bankrupt. In other words, financial distress
occurs when a company fails or no longer able to meet obligations to the debtor
because of deficiency and insufficiency of funds to carry out or continue the business
again.
Historically, as appendix 11 financial distress study was first conducted by
Beaver (1966), followed by Athman (1968) and others. Altman's models (1968),
using the model of Multiple Discriminant Analysis and variables measured financial
distress with category 1 and 2 for healthy companies and companies experiencing
financial distress while the independent variables were used: working capital / total

26
assets; retained earnings / total assets; earnings before interest and taxes / total assets;
market value of equity/book value of total liabilities, and sales / total assets.
Then by Springate's Model (1978), the Multiple Discriminant Analysis model
and the variables measured financial distress with categories 1 and 2 for healthy
companies and companies experiencing financial distress while the independent
variables were used: Working Capital / Total Assets; Net Profit before Interest and
Taxes / Total Assets; Net Profit before Taxes / Current Liabilities, and Sales / Total
Assets.
Followed by Fulmer's Model (1984), using the model of Multiple
Discriminant Analysis and variables measured financial distress with category 1 and
2 for good companies and companies experiencing financial distress. While the
independent variables were used, namely: Retained Earnings / Total Assets; Sales /
Total Assets; EBT / Equity; Cash Flow / Total Debt; Debt / Total Assets; Current
Liabilities / Total Assets; Log Tangible Total Assets; Working Capital / Total Debt;
and Log EBIT / Interest.
Then by CA-Score (1987), using the model of Multiple Discriminant
Analysis and variables measured financial distress with categories 1 and 2 for good
companies and companies experiencing financial distress. While the independent
variables were used, namely: shareholders' investments / total assets, earnings before
taxes and extraordinary items; financial expenses / total assets; and sales / total assets.
Furthermore, Platt and Platt (2002), using a logistic analysis model, and the
variables measured financial distress with the dichotomy of 0 and 1 for healthy
companies and companies experiencing financial distress. The independent variable
that is used consists of several financial ratio variables key areas: EBITDA / sales,
current assets / current liabilities, cash flow growth rate, net fixed assets / total assets,
long-term debt/equity, and notes payable/total assets (Gamayuni , 2009).
Other research, generally using a measurement of financial distress based on
the score generated by the study mentioned above. From these results, Weston and
Copeland (1997) found that bankruptcy is a failure that occurs in a company that can
be distinguished on the economic failures (economic distressed), and financial failure
(financially distressed).

27
Later research Hidayat, MA et al. (2014), Mas'ud, I. et al. (2012), Altman
(2000), Tzong and Lin (2009), Brockett, et al. (2006), Salehi and Abedini (2009),
Janes (2003), Kordestani, Biglari and Bakhtiari (2011) and Zhang et al. (2001)using
financial measurements based on the score mentioned above, suggests that financial
distress influenced by financial performance based on financial ratios.
While other studies not only see the financial aspects, proposed by Loui and
Smith (2006), Gilson danVetsuypens (2005), Pranowo, Achsani, and Manurutng
(2010), and Elkamhi, Ericsson, and Parsons (2009) uses the measurement of financial
distress based on the score mentioned above, found that financial distress influenced
by financial based on the ratio of financial and non-financial factors.
2.5 Marginal Approach Research
The marginal approach as a concept was first developed by Hendrick Gossen
(1810-1858) was then used to some new theory, as mentioned in the discussion of
Section 2.3. The marginal approach is widely used in business practices such as
pricing and sales volume of production, known as the marginal cost pricing, the price
level and quantity of sales that generate optimal conditions in terms of maximum
profit or minimum loss.
Against companies whose price is controlled by the government, because of
subsidies and related to the lives of many people and the approach to economic
feasibility, then the optimal conditions apply losses to a minimum. While the
company or SOE operating company based profit-oriented and uses the size of
financial feasibility, then the optimal condition is the maximum profit.
To achieve these optimal conditions, the necessary strategy and policy on the
cost structure and revenue structure that produces a balance of marginal revenue and
marginal cost. This can be achieved through SOE management competence in
managing the potential of the company's internal resources, overcome internal
weaknesses, exploit or optimize potential external opportunities, and anticipate
external threats.
Research with marginal approach byYustiana et al. (2015) and Hall (1988),
suggests that Marginal Cost Pricing has several advantages, among others that this
mechanism is considered the most efficient and avoid underpriced or assessments

28
under the price. For a company that equates marginal cost-competitive with the
market price of their products will gain maximum benefit.
Research other marginal approach by Coase (1972), Hellyward (2015),
Misanam (2007), Septiantoro and Utomo (2015), and Widyantara and Goddess
(2016) illustrates that the curve of the balance of demand, MR and MC and argued
that the price and quantity of the curve demand formed on the intersection of the
curve MR = MC generate maximum profits. Inversions are virtually identical,
researchDamayanti, et al. (2014) suggested that benefit is the difference between
total revenue (TR) and total cost (TC). And to obtain the maximum profit, then the
price and sales volume was set at MR-MC = 0.
While research Sutjati et al. (2015) in the determination of transfer pricing,
suggests that profit in transfer pricing optimization can be achieved when the
marginal revenue (MR) of the marketing division is equal to marginal cost (MC),
resulting in equilibrium point to be projected into the demand curve to obtain the
transfer price and the amount of product to be manufactured.
2.6 ResearchSOE
State-owned enterprises (SOE) as a government-owned company with a
reported value of the assets in 2018 amounted to Rp 8,092 trillion, is engaged in
various business sectors. PERSERO separate business entity and PERUM in
accordance with Law No. 19 of 2003. SOE in the form PERSERO established with
the purpose of the pursuit of profit to enhance corporate value, while SOEin the form
PERUM established with the aim is to undertake for the public benefit in the form of
supply of goods/services quality at an affordable price by the public based on sound
principles of corporate management.
Both forms of business entities of the SOE, in principle, should be managed
in a healthy and achieving sure profitability in order to run their business sustainably.
But empires showed that of 115 SOEs in 2018, there were 50 state-owned companies
are experiencing financial difficulties as stated pad appendix 4.
SOE, as a government-owned company received much attention from the
public and researchers from academia, to assess and analyze the phenomena and
problems of SOE experiencing financial difficulties.

29
Research SOE electricity sector by Assagaf (2015) find that to optimize the
management of PLN needs a series of policies in an integrated manner on four main
pillars that affect the success of the company, namely: (a) management of fuel
independently, (b) restructuring of a contract to purchase electricity from the mains
especially in the rescue of private income or cost-saving opportunity for PLN, (c)
restructuring of tariffs on the economic level through tariff-based mechanisms
marginal cost pricing, and (d) optimizing the management of subsidiary companies
through the restructuring of the company management authority independently.
SOE subsidy policy research, by Handoko and Patriadi (2005) argued that the
subsidy policy of positive effects and negative effects on socio-economic life. Then
Munawar and Main (2013) suggested that government subsidies policy has always
posed an opinion of the pros and cons. While SOE capital structure research, by
Mandana and Artini (2012) indicated that the structure of assets, the rate of sales
growth, profitability, and growth of the company has a significant effect on the
capital structure.

30
CHAPTER III
METHODOLOGY
3.1 Conceptual Framework
The conceptual framework, as Figure 5 below, consists of several groups of
variables, namely: independent variable, intervening variables, control variables, and
the dependent variable. To test the effect of variable consistency independent of the
financial distress of the SOE, then the dependent variable measurement is equipped
with a sensitivity analysis, or using an alternative measure as a comparison against
the measures used in this analysis model.
Figure 5: Conceptual framework
1. Dependent variable
the dependent variable financial distress (YFINDIS) in this study is to show
the level of the financial difficulties faced by state-owned enterprises still depend
primarily funded from government subsidies, receive assistance state capital
participation (PMN), and suffered losses. Financial distress shows the financial

31
performance generated by the management in running the corporation, and it is
marked by achievement level score is marginal (SMg).
The value of the maximum score of the mean marginal financial performance
optimal management of resources because these conditions cause the company to
achieve maximum profit or minimum loss. Conversely, when the marginal score
value less than one, then the financial performance can be improved through action
strategies and management policy of the factors that affect the marginal score.
The results of this study can be used to assess the marginal score each SOE
as attachments-8. The effect can be evaluated and compared the scores of marginal
or financial distress of each SOE, making it useful in terms of (a) assess the success
of SOE from time to time; (b) develop marginal score ranking achievements or
financial distress of SOEs, as well as comparing between SOE; (c) determine the
performance targets marginal score the next period in the short term and long term
business plan SOEs; (d) to reach the target score is marginal attention to the key
variables that affect financial distress.
Sensitivity analysis of dependent variable
To compare the results of the regression equation with measurement of
financial distress based approach marginal score, then in this study used sensitivity
analysis by using measurements of financial distress based approach models Altman
(1968), and Springate (1978) as tabel 1 and appendix 12.
2. Independent variable
The independent variable as variables influencing the dependent variable, so
the change in the independent variable will cause the effect of the change in the
dependent variable.
Reasons for the selection of independent variables based on a theoretical
approach, results of previous studies, and empires condition indicating that the
independent variables affecting the financial distress of SOEs, as in figure 5, the
following conceptual framework.
3. Intervening variable
intervening variables growth in cash flow from operating (ZΔCFO) effect on
the financial distress (YFINDIS), as picture-5. Reasons to use cash flow from
operating (ZΔCFO) as an intervening variable, due to the financial distress dependent

32
variable determined by the management of operating cash flow. While the
intervening variables from the operating cash flow were influenced by independent
variables and control variables.
The test intervening variable in this study can be done through path analysis
was first developed by Sewall Wright in 1934 (Sarwono, 2011).
4. Control variable
Researchers do not have to enter all of the predictor variables in our model;
however,againstthe predictorvariablesthatallegedlyveryinfluential butare beyondthe
scope of the topic of study, the researchers didcontrol to explain better research results.
Control variables used in this study, consisting of (a) the size of the company
(X10SIZE), (b) leverage (X11LEV), and (c) government subsidy and equity
(X12SUBE). All three of the control variables affect financial distress (YFINDIS),
but function only as a control, as described above.
Reasons firm size (X10SIZE) as a control variable, especially since this
variable has an essential role in business scale has particularly the tendency of policy
patterns in overcoming financial difficulties, i.e., small companies easier to divert its
business and compete with the middle class and to make improvements needed
funding relatively too much. While companies with large size need substantial
funding to overcome financial difficulties and difficult to find a financial institution
that can meet the end of the financial distress. Based on these reasons, then this
variable is used as a control tool for the avoidance of bias if neglected.
The reason the use of leverage (X11LEV) as a control variable, especially
since this variable has a role in the level of financial hardship. Companies with
different ratios of the use of debt to meet its funding will result in different levels of
financial difficulties. Companies that have more dominant funding using pieces will
be difficult to obtain additional debt financing from banks in financial distress;
compare dominant company uses its capital. Based on these reasons, then this
variable is used as a control variable for the avoidance of bias to ignore in the
regression analysis.
The reason the use of government subsidy and equity (X12SUBE) as a control
variable, primarily due to some of the companies that still rely on the funding, needs
additional equity support or government subsidies, making them different from

33
another state in overcoming financial difficulties. Therefore, this variable is then used
as a control variable to the measurement as a dummy variable, i.e., D = 1 when it
receives a subsidy or additional capital, and D = 0 for the other.
Test the control variables using a hierarchical regression procedure, which is
the development of the moderated regression equation proposed by Cohen & Cohen,
Schmitt & Klimoski, 1991 (Harsono, 2002). Hierarchical regression is the regression
analysis performed many times with different variable compositions, may be
increased, or reduced, to see the difference in the degree of influence on each level
(step) testing.
3.2 Hypothesis Development
Based on the theory and the results of previous research, the development of
the hypothesis to answer the problems of this study is presented below.
1. Capital Expenditure (Hypothesis H1a and H1b)
Selection of independent variables capital expenditure (X1ΔCAPEX)closely
related to the agency theory and signaling theory. Management actions to meet the
interests of shareholders and give a signal to the stakeholders, impact on the variable
capital expenditure (X1ΔCAPEX) to affect on company's financial distress, such as
in Figures 1, 2 and 5.
impact on cash flow from operating occurs because of the necessity to meet
the operational needs of the company. The imbalance that occurs in the management
of capital expenditure (X1ΔCAPEX), causing a deficit cash flow from operating and
financial distress affecting SOE. Therefore, the management of capital expenditure
(X1ΔCAPEX) SOE important role in order not to complicate the operational cash
flow from operating.
Several previous studies found that capital expenditure (X1ΔCAPEX) affect
the success or financial difficulties. And based on the importance of variable capital
expenditure (X1ΔCAPEX) mentioned, then This study proposes the following
hypothesis H1a and H1b.
H1a: Growth in investment or capital expenditure (X1ΔCAPEX) positive and
significant impact on the financial distress (YFINDIS) State-Owned Enterprises.

34
H1b: Growth in investment or capital expenditure (X1ΔCAPEX) positive and
significant impact on the growth of cash flow from operating (ZΔCFO), and the
impact on the financial distress (YFINDIS) State-Owned Enterprises.
2. Working capital (Hypothesis H2a and H2b)
Selection of independent variables Working capital (X2WC)closely related to
the agency theory and signaling theory. Management actions to meet the interests of
shareholders and give a signal to the stakeholders, impact on the variable Working
capital (X2WC) to affect on company's financial distress, such as in Figures 1, 2 and
5.
The impact on cash flow from operating occurs because of the necessity to
meet the operational needs of the company. The imbalance that occurs in Working
capital management (X2WC), causing a deficit cash flow from operating and
financial distress affecting SOE. Therefore, management Working capital (X2WC)
SOE important role in order not to complicate the operational cash flow from
operating.
Several previous studies have found that Working capital (X2WC) affect the
success or financial difficulties. And based on the importance of variables Working
capital (X2WC) mentioned, then This study proposes the following hypothesis H2a
and H2b.
H2a: Growth Working capital (X2ΔWC) positive and significant impact on the
H2b: Growth Working capital (X2ΔWC) positive and significant impact on the
growth of cash flow from operating (ZΔCFO), and the impact on financial distress
(YFINDIS) State-Owned Enterprises.
3. Retained Earnings (Hypothesis H3a and H3b)
The selection of independent variables retained earnings (X3RE) closely
related to the agency theory and signaling theory. Management actions to meet the
interests of shareholders and give a signal to the stakeholders, impact on the variable
retained earnings (X3RE) to affect on company's financial distress, such as in Figures
1, 2 and 5.

35
of retained earnings (X3RE), causing a deficit cash flow from operating and financial
distress affecting SOE. Therefore the management of retained earnings (X3RE)
important role in order not to complicate the operational state enterprises from
operating cash flow.
Several previous studies have found that the retained earnings (X3RE) affect
the success or financial difficulties. And based on the importance of the variables
retained earnings (X3RE), then This study hypothesized H3a and H3b follows.
H3a: Growth Retained earnings (X3ΔRE) positive and significant impact on the
H3b: Growth Retained earnings (X3ΔRE) positive and significant impact on the
growth of cash flow from operating (ZΔCFO), and the impact on the financial
distress (YFINDIS) State-Owned Enterprises.
4. Earning Before Interest And Taxes (Hypothesis H4a and H4b)
Selection of independent variables earnings before interest and tax (X4EBIT)
closely related to the agency theory and signaling theory. Management actions to
meet the interests of shareholders and give a signal to the stakeholders, impact on the
variable earnings before interest and tax (X4EBIT) to affect on company's financial
distress, such as in Figures 1, 2 and 5.
of earnings before interest and tax (X4EBIT), causing a deficit cash flow from
operating and financial distress affecting SOE. Therefore, management earnings
before interest and tax (X4EBIT) important role in order not to complicate the
operational state enterprises from operating cash flow.
Several previous studies have found that earnings before interest and tax
(X4EBIT) affect the success or financial difficulties. And based on the importance of
variable earnings before interest and tax (X4EBIT), then This study hypothesized
H4a and H4b follows.
H4a: Growth Earning before interest and tax (X4ΔEBIT) positive and significant

36
H4b: Growth Earning before interest and tax (X4ΔEBIT) positive and significant
impact on the growth of cash flow from operating (ZΔCFO), and the impact on the
5. Growth Contribution Margin (Hypothesis H5a and 5b)
Selection of independent variables growth in contribution margin (X5ΔCM)
closely related to the agency theory and signaling theory. Management actions to
meet the interests of shareholders and give a signal to the stakeholders, impact on the
variable growth in contribution margin (X5ΔCM) to affect on company's financial
distress, such as in Figures 1, 2 and 5.
of the contribution margin growth (X5ΔCM) causes a deficit cash flow from
operating and financial distress affecting SOE. Therefore, management of increase
in contribution margin (X5ΔCM) important role in order not to complicate the
operational state enterprises from operating cash flow.
Several previous studies have found that the growth in contribution margin
(X5ΔCM) affect the success or financial difficulties. And based on the importance of
growth variable contribution margin (X5ΔCM), then This study hypothesized H5a
and H5B follows.
H5a: Growth Contribution margin (X5ΔCM) positive and significant impact on the
H5B: Growth Contribution margin (X5ΔCM) positive and significant impact on the
6. Growth Equity (Hypothesis H6a and H6b)
Selection of independent variables growth equity (X6ΔEQ) closely related to
the agency theory and signaling theory. Management actions to meet the interests of
shareholders and give a signal to the stakeholders, impact on the variable growth
equity (X6ΔEQ) to affect on company's financial distress, such as in Figures 1, 2 and
5.
The impact on cash flow from operating occurs because of the necessity to
meet the operational needs of the company. The imbalance that occurs in the growth

37
of equity (X6ΔEQ) causes a deficit cash flow from operating and financial distress
affecting SOE. Therefore, the management of growth equity (X6ΔEQ) important role
in order not to complicate the operational state enterprises from operating cash flow.
Several previous studies have found that the growth of equity (X6ΔEQ) affect
the success or financial difficulties. And based on the importance of growth variables
equity (X6ΔEQ), then This study hypothesized H6a and H6b follows.
H6a: Growth in equity or equity (X6ΔEQ) positive and significant impact on the
H6b: Growth in equity or equity (X6ΔEQ) positive and significant impact on the
7. The level of efficiency or productivity of Operations (Hypothesis H7a and
H7b)
Selection of independent variables level of efficiency or productivity of the
operation (X7EFSO) closely related to the agency theory and signaling theory.
Management actions to meet the interests of shareholders and give a signal to the
stakeholders, impact on the variable level of efficiency or productivity of the
operation (X7EFSO) to affect on company's financial distress, such as in Figures 1,
2 and 5.
the operational needs of the company. The imbalance that occurs at the level of
efficiency or productivity management operations (X7EFSO) causes a deficit cash
flow from operating and financial distress affecting SOE. Therefore, the management
level of efficiency or productivity of the operation (X7EFSO) important role in order
not to complicate the operational state enterprises from operating cash flow.
Several previous studies have found that the level of efficiency or
productivity of the operation (X7EFSO) affect the success or financial difficulties.
And based on the importance of variable levels of efficiency or productivity of the
operation (X7EFSO), then This study hypothesized H7a and H7b follows.
H7a: The level of efficiency or productivity of the operation (X7EFSO) positive and
significant impact on the financial distress (YFINDIS) State-Owned Enterprises.

38
H7b: The level of efficiency or productivity of the operation (X7EFSO) positive and
significant impact on the growth of cash flow from operating (ZΔCFO), and the
8. Earning Management (Hypothesis H8a, H8b, H9a and H9b)
variable selection earnings management closely related to the agency theory
and signaling theory. Management actions to meet the interests of shareholders, and
give a signal to the stakeholders, impact on the variable earnings management to
affect on company's financial distress, such as in Figures 1, 2 and 5.
of earnings management, causing a deficit cash flow from operating and fin affecting
SOE. Therefore, earning an important role in the operational management of SOEs
in order not to complicate the cash flow from operating.
Several previous studies have found that earnings management affect success
or financial difficulties. And based on the importance of earnings management
variables, then This study hypothesized H8a, H8b, H9a, and following H9b.
H8a: Real earnings management activities (X8RAEM) positive and significant
H8b: Real earnings management activities (X8RAEM) positive and significant
impact on the growth of cash flow from operating (ZΔCFO), and the impact on the
H9a: Accruals earnings management (X9ACEM) positive and significant impact on
the financial distress (YFINDIS) State-Owned Enterprises.
H9b: Accruals earnings management (X9ACEM) positive and significant impact on
the growth of cash flow from operating (ZΔCFO), and the impact on the financial
9. Cash Flow From Operating (Hypothesis H10)
variable selection cash flow from operating (ZΔCFO) closely related to the
agency theory and signaling theory. Management actions to meet the interests of
shareholders and give a signal to stakeholders, cash flow from operating (ZΔCFO)
to affect on company's financial distress, such as in image one and image 2.

39
of cash flow from operating (ZΔCFO affect on SOE's financial distress. Therefore,
the management of cash flow from operating (ZΔCFO) important role in order not
to complicate the operational SOE corporate finance.
Several previous studies have found that the cash flow from operating
(ZΔCFO) affect the success or financial difficulties. And based on the importance of
intervening variable cash flow from operating (ZΔCFO), then This study proposes
the following hypothesis H19.
H10: Growth in cash flow from operating (ZΔCFO) a positive and significant impact
on the financial distress (YFINDIS) State-Owned Enterprises.

40
CHAPTER IV
METHODOLOGY
4.1 ResearchDesign
The design of this study indicates that the research implementation process is
structured to achieve results that objective, efficient, and effective.
Some things need to be put forward in the design of this study, namely: (a)
This study included as a type of hypothesis testing to test the hypothesis whether to
answer the problem of the research is acceptable or consistent with the predictions.
(b) This study examined the hypothesis based on causality to indicate the level of
significance of independent variables that influences the dependent variable, either
directly or indirectly, through intervening variables. (c) The data used in this study
is a cross-section data, time-series data, and panel data or pooled data using a
combination of data between the data cross-section with time-series data. (d) The
source of data in this study was obtained from50 SOEs in the past observation period
of 5 years (2013-2017) as an attachment-4. (e) The study was conducted with a real
environment that is in accordance with the operational and financial condition of the
company. (f) This study uses analysis unit entity SOEs to assess and understand the
various operational aspects of SOEs, especially in terms of organization of state-
owned companies studied, industry-related, the capital market which presents
information related to state-owned enterprises, the government through the ministry
of SOEs as a shareholder of SOEs and related technical departments. It is intended
to obtain a complete picture related to the analysis of the issue and the purpose of
this research. (G) This research requires resources in the form of online information
systems to facilitate the acquisition of the necessary data,
4.2 Sample Selection
The population of this study is the overall state enterprises are still operating
actively. At the same time, the sample is determined by using purposive sampling
techniques, i.e., the determination of sample by choosing some particular samples
were assessed in accordance with the purpose or research problem that the data
obtained will be more representative or representative of the population. Samples
were selected based on criteria as Annex 4, namely: (a) state that receive subsidies

41
as much as 9 SOEs to 8 sectors of services, (b) state that received additional state
capital participation in 2016 as many as 27 state-owned companies, and (c) state that
suffered losses semesters 1 2017 as many as 24 state-owned companies. A total of
nine state-owned companies grouped in overlapping, the two state-owned enterprises
received subsidies. They received PMN, two state-owned companies receive
subsidies and losses, and 5 SOEs receive PMN and loss.
Observations were made in brackets the last five years (2013-2017), because
of obtaining a complete picture in one cycle of the company's long-term plan (RJPP),
so that the number of observations in this study was 250-year SOE (BUMN 51 x 5
years = 255-year SOE).
Methods of data collection in this research is secondary data based document
SOE financial statements and other documents related to the variables used in this
study. And as the completeness of the analysis, data collection also using personal
observation and interviews of key state-owned enterprises into the unit of analysis of
this research.
4.3 Measurement of Variable
The dependent variable, the intervening variables, independent variables, and
control variables, are defined and measured as follows.
Dependent Variable
The dependent variable is a variable that is affected by various factors that will be
analyzed to explain the phenomena and problems of this research. Financial distress as a
dependent variable that will analyze using several key variables to explain the issues of
financial distress faced by SOEs.
Financial distress (YFINDISt)
Financial distress, i.e., as a dependent variable that shows the level of
financial difficulties faced by state-owned enterprises (SOE) from the scale of the
difficulties small, medium to bankruptcy. Financial distress as that term is standard
in the literature and previous research both nationally and internationally so that this
study uses the term or variable name of financial distress, for reasons do not limit the
meaning in the analysis of financial difficulty SOE. Measurement variables used
financial distress SOE approach marginal score (SMg) as described in section 2.1,
appendix 6, and Table 1 below.

42
Table 1: Measurement of Dependent and Intervening Variables
This study uses a measurement-based approach to financial distress marginal, as a
novelty in the method of measurement of the variables that contribute to the perfection of
the measure of financial distress in the earlier study. For sensitivity analysis in examining
and comparing the consistency of other measurement methods, this research use score
Altman measurement method (1968) and score Springate (1978), as table 1.
Intervening variable
Cash flow from operating growth (ZΔCFOt)
Cash flow from operating growth (ZΔCFO), i.e., as an intervening variable
that describes the amount of cash flow from the operations of the company in period,
e.g., one year. The reason for using this variable as an intervening variable and the
accompanying statistical tests, which were performed as subchapter 2.2 on the
description of the conceptual framework.
The measurements of these variables are based on the calculation of operating
cash flow from the financial statements presented at the end of the year as the study
Chen et al. (2010) in Table 1.
Independent Variables

43
The independent variable, namely as a factor affecting financial distress
according to empirical conditions of the SOE, and the measurement used as
references and previous studies Table 2.
Table 2: Measurement of Dependent and Intervening Variables
1. Investment growth (X1ΔCAPEXt)
Investment growth (X1ΔCAPEXt), i.e., as an independent variable that
indicates the amount of investment spending a certain period known as capital
expenditure period t. This variable was measured by using a formula as research
Chen et al. (2010) in Table 2.
2. Working Capital Growth (X2ΔWCt)
Working Capital Growth (X2ΔWCt), the change in working capital between
time, while working capital as the difference between current assets to current
liabilities, which describes the networking capital of the company period t.

44
Measurement of these variables using a formula Brigham and Daves (2007) in Table
2.
3. Retained Earnings Growth (X3ΔREt)
Retained Earnings Growth (X3ΔREt), the change in retained earnings of the
time, while retained earning part undistributed profits to shareholders, and can be
used by the company to strengthen its financial needs both for operational and
financing for development or investment period t. Variable measurement is done by
using the formula as in Gitman and Zutter (2010) in Table 2.
4. Growth in Earnings Before Interest and Tax (X4ΔEBITt)
Growth in Earnings Before Interest and Tax (X4EBITt), the change in EBIT
between time, while EBIT showed the achievement of the company's operating
profitability before reckoned load and other revenues and operating outside the tax
burden period t. Measurement of these variables using the formula as in Brigham and
Daves (2007) in Table 2.
5. Growth in the contribution margin (X5ΔCMt)
Growth in the contribution margin (X5ΔCMt), i.e., the change contribution
margin between time. In contrast, the contribution margin shows the difference
between the total sales of the total variable costs, or the difference between the
average price per unit variable cost period t. Measurement of these variables using a
formula as researchRamadan (2015) in Table 2.
6. Growth equity (X6ΔEQt)
Growth equity (X6ΔEQt), the owner good capital growth rates due to the
increase of profitability as well as an additional capital injection from the owner of
period t. Measurement of these variables using the formula as Gitman and Zutter
(2010) in Table 2.
7. The efficiency or productivity of the operation (X7EFSOt)
The level of efficiency or productivity of the operation (X7EFSOt), the level
of the comparison between the value of operating income (output) by the number of
operating assets used in the operations process (input) in the period t. This variable
was measured by using a formula as research Warrad and Omari (2015) in Table 2.
8. Real earnings management activities (X8RAEMt)

45
Real earnings management activities (X8RAEMt), namely the independent
variable that shows the action-based earning management company activity period
t.Real Activities Earnings Management is defined as the management measures that
deviate from normal business practices that are conducted with the main objective to
achieve profit targets (Cohen and Zarowin 2008; Roychowdhury, 2006). Real
earnings management activities can be done in three ways, namely the manipulation
of the sale, the excessive production (overproduction), and a decrease in
discretionary expenditures.
This variable was measured by using abnormal operating cash flow, the cost
of the abnormal product, and abnormal discretionary expenses. The independent
variable of real earnings management activities are actions taken by management to
influence the financial statements through policies related to corporate activity such
as production, sales, accounts receivable, inventory, and more. Measurement of real
variables as well as research activities using the equationRoychowdhury (2006)in
Table 2.
Research Setiawan et al. (2011) modifying the model of real variable earnings
management activities mentioned above, that is, without indicator At-1, the equation
CFO, PROD, and DEXP to calculate residual or abnormal real activities.
9. Accruals earnings management (X9ACEMt)
Accruals earnings management (X9ACEMt), namely the independent
variable that shows the earnings management action based on accruals transaction
period t.Measurement of accruals earnings management variables using the formula
as the study Habib (2004), Baharuddin and Setyanugraha (2008) in Table 2.
Control Variable
Control variables as factors used to avoid bias on the influence of independent
variables on financial distress. This study uses several variables that control the
measurement method as Table 3.
1. Firm size (X10SIZEt)
The size of the company (X10SIZEt), the operational capacity reflected by the
value of property or assets owned by the company period t. This variable was
measured by using a formula as research Ramadan (2015) in Table 3.

46
Table 3: Measurement of control variables
2. Leverage (X11LEVt)
The level of leverage (X11LEVt), namely the level of a comparison between
the number of long-term debt (debt capital) to total equity (equity capital) owned
firm period t. Pengukuran leverage variable is using the formula as in the capital
structureGitman and Zutter (2010) and research Chen et al. (2010) in Table 3.
Formula structure of this capital, are relevant to the practice of bank financing
in SOEs such as electricity and other development projects, with the composition of
debt capital and equity capital in the ratio of 65%: 35% to 70%: 30%.
3. Government subsidy and equity (X12SUBEt)
Government subsidy and equity (X12SUBE), i.e., as a control variable,
additional equity financing, and government subsidies or PMN. Reasons for using
these variables as control variables due in part SOEs obtain assistance subsidies and
additional capital, to SOEs are different from another state in the face of financial
distress, so it is important to use as a variable control to avoid bias in the analysis if
this variable is not calculated regression analysis, Based on the policy of the specific
BUMN obtain subsidies and additional capital, the measurements of these variables
in Table 3, using a dummy variable as research Dough Keplow (2009), i.e., D = 1 to
BUMN obtain subsidies or additional equity, D = 0 for the other.
4.4 ResearchModel
Substantially this research is a new concept in the dependent variable
measurement of financial distress based on the theory and the results of previous
research to examine factors associated with financial difficulties or financial distress

47
experienced by SOE. And to test the hypothesis proposed in this study, the analysis
model used is as follows regression equation.
Model 1: Testing the hypothesis variables that directly affect the financial distress of
the State-Owned Enterprises (H1a up to H9a), with the following equation models.
YFINDISt = β0 + β1 X1ΔCAPEXt + β2 X2ΔWCt + β3 X3ΔREt + β4 X4ΔEBITt +
β5 X5ΔCMt + β6 X6ΔEQt + β7 X7EFSOt + β8 X8RAEMt +
β9 X9 ACEMt + β10 X10SIZEt + β11 X11LEVt + β12 X12SUBEt +
β13 ZΔCFOt + et .,…………………………………………….….. (1)
Model 2: Test the hypothesis that variable indirect effect on financial distress of
State-Owned Enterprises, through cash flow from operating (H1b up to H9b), using
the equation model 2 and model 3 below.
ZΔCFOt = β0 + β1 X1ΔCAPEXt + β2 X2ΔWCt + β3 X3ΔREt + β4 X4ΔEBITt +
β5 X5ΔCMt + β6 X6ΔEQt + β7 X7EFSOt + β8 X8RAEMt +
β9 X9ACEMt + β10 X10SIZEt + β11 X11LEVt + β12 X12SUBEt + et ……(2)
Model 3: Testing the hypothesis of the influence of cash flow from operating against
Financial distress (H10) and examine the indirect impact as model 2, using the
following equation models.
YFINDISt = β0 + β1 ZΔCFOt + et ………………………………………………. (3)
Where:
YFINDISt = financial distress based on the score marginal (SMg) in the period t,
ZΔCFOt = growth from operating cash flow in period t
X1ΔCAPEXt = growth capital expenditure in period t
X2ΔWCt = growth in working capital in period t
X3 ΔREt = retained earnings growth in period t
X4ΔEBITt = growth in earnings before interest and tax period t
X5ΔCMt = contribution margin growth period t
X6ΔEQt = growth equity in period t
X7EFSOt = level of efficiency or productivity of the operation in period t
X8RAEMt = real earnings management activities in period t
X9ACEMt = accruals earnings management in period t
X10SIZEt = size of the firm in period t
X11LEVt = level of leverage in period t
X12SUBEt = government subsidy and equity in period t
β0: constants; β1 ... β13: regression coefficient; et = error period t

48
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