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Table of ContentsABSTRACT....................................................................................................................................iii

LIST OF TABLES AND FIGURES...............................................................................................iv

ACKNOWLEDGEMENT................................................................................................................v

1. INTRODUCTION........................................................................................................................1

1.1. Overview about real estate environment in Vietnam.......................................................1

1.2. Corporate Governance structure of stock-holding firms in Vietnam...............................2

1.3. Problems in Vietnamese corporate governance...............................................................3

1.4. Factors affecting firms’ performance...............................................................................4

1.1.1. Objective factors.......................................................................................................4

1.1.2. Subjective factors.....................................................................................................5

2. LITERATURE REVIEW.............................................................................................................7

2.1. Corporate Governance overview......................................................................................7

2.1.1. Definition of corporate governance..........................................................................7

2.1.2. Studies approaches to corporate governance............................................................8

2.2. Researches on Corporate Governance worldwide..........................................................11

2.2.1. In USA and UK......................................................................................................11

2.2.2. In Japan...................................................................................................................12

2.2.3. In Vietnam..............................................................................................................15

3. METHODOLOGY.....................................................................................................................18

3.1. Data collection method...................................................................................................18

3.2. Population selection........................................................................................................18

3.2.1. Dependent variables...............................................................................................19

3.2.2. Independent variables.............................................................................................20

3.3. Descriptive statistics.......................................................................................................22

3.4. Correlation analysis........................................................................................................24

4. REGRESSON MODEL ANALYSIS.........................................................................................25

4.1. Assumptions...................................................................................................................25

4.2. General model................................................................................................................26

4.2.1. Equation 1: Test all independent variables with dependent variable ROA............26

4.2.2. Test all independent variables with dependent variable ROE................................29

4.2.3. Summary.................................................................................................................32

4.3. Test several alternative models......................................................................................32

Page i

4.3.1. Test 7 independent variables with dependent variable ROA – Equation 3............32

4.3.2. Test 9 independent variables with dependent variable ROA – Equation 4............34

4.3.3. Test 9 independent variables with dependent variable ROE – Equation 5............35

4.3.4. Test 7 independent variables with dependent variable ROE (Equation 6).............36

4.4. Error detection in the model...........................................................................................38

4.4.1. Autocorrelation.......................................................................................................38

4.4.2. Heteroskedasticity..................................................................................................39

4.6. Findings and Discussion.................................................................................................41

5. CONCLUSION..........................................................................................................................45

5.1. Conclusion......................................................................................................................45

5.2. Limitations......................................................................................................................45

5.3. Recommendation............................................................................................................46

APPENDIX 1: LIST OF REAL ESTATE FIRMS LISTED IN VN..............................................48

APPENDIX 2: DATABASE USED FOR RUNNING EVIEWS..................................................50

APPENDIX 2: CONTINUING......................................................................................................53


APPENDIX 3: CORRELATION BETWEEN INDEPENDENT VARIABLES...........................59

APPENDIX 3: CONTINNNUING................................................................................................60


REFERENCE.................................................................................................................................63

Page ii

ABSTRACT

Corporate governance has become one of the most popular phenomena that draw the worldwide

attention recently. As corporate governance is one of factors that have significant influences on

the performance of almost every business, it deserves to a great deal of concern from

management of the firms. However, the adoption of good corporate governance in real estate

sector in Vietnam contributes to the success of firms is still statistically questionable. There is

limited research to quantifying the actual impact of corporate governance in firms’ performance.

The objective of this paper is to provide a deep look into the relationship between corporate

governance and performance of real estate sector from 2013 to 2014, especially in successful

companies in Vietnam by presenting both theoretical framework and empirical study. The part of

theoretical framework provides readers with profound knowledge about corporate governance in

general. In the empirical study section, a list of public real estate enterprises in Vietnam have

been fully chosen as a population to run econometric models which examine the effect of several

variables of corporate governance on the firm’s profitability. The overall result of study shows

that board size, executive size and coincident people between BOM and BOD has not clearly

significant effect on both ROA and ROE of these firms.

Key words: Real estate firm’s performance, ROA, ROE, corporate governance, board size,

executive size, coincident.

Page iii

LIST OF TABLES AND FIGURES

Table 1: Two types of corporate governance system worldwide.....................................................9

Table 2 : Descriptive Statistics.......................................................................................................20

Table 3: Testing result of all 15 independent variables with dependent variable ROA - Equation 1

........................................................................................................................................................24

Table 4: Testing result of 15 independent variables with dependent variable ROE - Equation 2. 27

Table 5: Test independent variables with dependent variable ROA – Equation 3.........................30

Table 6: Test 9 independent variables with dependent variable ROA – Equation 4......................32

Table 7: Test 9 independent variables with dependent variable ROE – Equation 5......................33

Table 8: Test 7 independent variables with dependent variable ROE (Equation 6)......................34

Table 9: Autocorrelation – BG Serial Correlation LM Test...........................................................36

Table 10: Heteroskedasticity Test: Breusch-Pagan-Godfrey.........................................................38

Table 11: Summarizing the results of regression models...............................................................39

Table 12: Summary to coefficient of controlling variables............................................................40

Page iv

ACKNOWLEDGEMENT

Page v

[CORPORATE GOVERNANCE IN PUBLIC REAL ESTATE FIRMS IN VIETNAM] Kieu Van Anh – MFBA6

1. INTRODUCTION

1.1. Overview about real estate environment in Vietnam

Vietnam is progressing to the next stage of urbanization. Basic infrastructures, affordable homes

and shopping malls are being developed in major Vietnamese cities like Hanoi and Ho Chi Minh

City. The continual flow of foreign investments, coupled with an export-driven economy, is

propelling Vietnam towards the goal of becoming an industrialized nation by 2020. With

Vietnam government’s determination to develop the economy further, there is a window of

opportunities for foreign firms in the building and construction industry to participate in

Vietnam’s real estate development. It is therefore, crucial for companies and organisations which

have an interest in Vietnam to acquire adequate knowledge of the culture, financial and legal

framework of Vietnam in order to develop long term partnerships with the related business firms

there.

As a result of joining WTO in 2007, property market surged in Vietnam, supported by high

economic growth and significant increase in foreign investment.

End of 2008 until now: property market halted due to the global economic crisis and domestic

economic uncertainties. The market saw large falls in prices in all sectors. With support from the

government, the real estate market is expected to recover in the short to medium term.

In 2015, the financial pressure on real estate enterprises is greatly reduced. Circular 36/2014 /

TT-NHNN is reducing the level of lending risk for loans invested in real estate from 250% to

150%. This movement is expected to help unfreeze credit flows to the real estate sector and

companies in the industry to help resume sales operations and investment projects in this sector.

Besides, lower deposit interest rates will ease the pressure on borrowing costs for businesses that

remains debts in the previous year. In addition, stock market is forecasted to be dynamic again,

increasing the likelihood of success for further public offers, which is in turn provide more funds

to pay down debt and improving financial situation.

Opportunities in Vietnamese real estate industry

According to Cushman & Wakefield Group, the research report for the third

quarter 2014 shows the disbursement of FDI increased by 4.5% compared to it in

the same period last year. This means that the expatriates working in Vietnam will

Literature Review Page 1


continue to grow. This is a chance for the apartment building service provider to

meet growing demand of customers.

Also the increase in the number of international visitors to Vietnam by 0.5% for

the first 9 months in 2014 compared with the volume in the same period in 2013

opens an opportunity for accommodation service and promotes hospitality

segment to attract tourists to stay and increase sales in the peak season.

Several FTAs will be completed in the near future.

Challenges in Vietnamese real estate industry

Despite of the gloomy economy surrounding, the rent per month is observed as a

steady increase in addition with other consumer’s product.

Another challenging point to real estate market is that the abundant and massive

supply of apartments and houses causing pressure on the price of the market.

1.2. Corporate Governance structure of stock-holding firms in Vietnam

Codes for corporate governance are essential sources for corporate governance for many

economies. Until March 2007, the Ministry of Finance issued Code of Corporate governance

for listed firms, which was developed under Enterprise Law 2005 and Securities Law 2006.

According to Le Toan (2008), "this code is, in fact, a piece of subordinate legislation (with

mandatory rules) and is therefore different from a voluntary code of corporate governance in

advanced economies such as the OECD Principles of Corporate Governance, the German

Corporate Governance Code, and the Chinese Code of Corporate Governance for listed

companies."

The main principles of corporate governance applicable to a listed company under the Code

include: Rights of shareholders, General meetings of shareholders, Board of Management,

Control Board, Conflict of interest and related party transactions and Information Disclosure

and Transparency.

The structure of stock-holding company in Vietnam is summarized as follows:

Figure 1: Corporate governance structure of a stock-holding company in Vietnam



1.3. Problems in Vietnamese corporate governance

According to Mr. Dinh Van An, Director of the Institute for Economic Central Management,

though the Enterprise Law is assessed to be suitable with the principles of market economy

and standards of international law, but many defects about protection shareholders' rights and

implementation corporate governance model still exist.

Currently, under the provisions of the Enterprise Law, for the corporation, shareholders have

the rights to receive important information, but not all information, records and documents of

the company is accessible. Shareholders are not guaranteed the right to review accounting

records, minutes of meetings of shareholders. Besides, despite the rights of the minority

shareholders is guaranteed when nominating, and convening the shareholders' meeting, the

law has not defined the principles for determining the number of people that they are allowed

to elect, as well as how to form and content requirements of the request to convene a meeting,

etc.

About implementing the model of corporate governance, Corporate Law does not specifically

refer to the issue of authorization holders. For the corporation, a common problem is that

persons who directly exercise the rights of shareholders are shareholder representatives.



Although they can be directly and closely supervised by shareholders, to some extent, it can

lead to the abuse for the purposes of self-interest.

Dr. Le Dang Doanh, who is senior advisor for the Ministry of Planning and Investment, said

that the shortcomings of corporate governance in Vietnam are the laws on accounting,

auditing, and transparency of information. This is the reason why violation is slowly detected;

the penalties for these faults have insufficient effect. This allows some non-executive director

at the abuse of power and position to earn illicit profits.

1.4. Factors affecting firms’ performance

Aspects influencing firms' performance could be divided into two separated fields: objective

and subjective factors, which are discussed more detailed as follows.

1.1.1.Objective factors

There are three factors that are considered as external factors affecting firms'

performance: international and regional environmental factors, national economic factor,

and industrial environmental factor.

1.4.1.1. International and regional environmental factors

Stable international and regional economical environment plays a vital role in the

success of firm. Political trend and open market impact firms' input and output

market. The economic environment and political stability in the region is a secured

basis for businesses to conduct business activities, contributing to improve business

efficiency.

1.4.1.2. National economic factor

National political environment has always been a prerequisite for the development

and expansion of investment activities of enterprises, organizations and individuals

locally and abroad. Those investment activities have an impact to the business

performance of enterprises. Besides, national laws and regulations are also very

important as businesses must comply strictly with the provisions to perform their

obligations to the state, to society and to employees. In another word, laws are

constraining or encouraging factors for the survival and development of enterprises,



thereby directly affecting the results and effectiveness of the business operations of

the business. Some other dimensions belonging to national environment includes

unemployment, education level, lifestyle, customs, habits, social psychology,

economic policy, the growth rate of the national economy, inflation, the average

income per capita, etc. Let take unemployment as an example as it could has both

positive and negative influence on firms' performance. Without unemployment,

workers have more opportunities to choose jobs; labor cost of the employer's business

will be certainly higher, thus reducing the efficiency of production, and vice versa. If

unemployment is high, the cost of the employer's business will be reduced, leading to

an increase in production efficiency of the business. But high unemployment will

cause the reduction in consumption, thus reducing business efficiency.

1.4.1.3. Industrial environmental factor

Industrial environmental factors consist of market competition, threats of new

entrance, substitute products, powers of buyers, and power of suppliers. The level of

competition between firms in the same industry directly influence products' supply

and demand of each business, affecting the price, speed of consumption, thus

impacting the performance of each business.

1.1.2.Subjective factors

Three most important internal aspects are corporate governance, labor, and financial

situation of business. Other factors could be named as features of the product, raw

materials, facilities, engineering and technologies, and business working environment.

1.4.1.4. Corporate governance

Corporate governance apparatus is particularly important for the survival and

development of enterprises, which simultaneously perform many other tasks as

below:

The first task is to develop business strategy. If corporate governance

mechanism has ability to build an appropriate business strategy in line with

the business environment, consistent with the ability of the enterprise, it will

be the basis of a good orientation to conduct business activities effectively.



Develop business plans on the basis of the business strategy.

Implement the plan, and the business activity proposed.

To examine, evaluate and adjust the above process.

Due to the critical functions and duties of corporate governance, we can confirm that

its quality has a huge impact on producing effective enterprise. If the machine is held

with management structure in line with the tasks of production and business

enterprises, be flexible, with clear separation of duty, a qualified and responsible

management team, it can be sure that the business would operate with high efficiency.

1.4.1.5. Financial situation of business

Enterprises being financially healthy would have the ability to ensure that the

business activities are stable, have capability in technological innovation and

application of that technology advanced in order to reduce costs, improve

productivity and product quality. Financial viability of businesses directly affected its

reputation, the ability to be active in the production, which influences the target of

minimizing costs by actively exploit and optimize the use of inputs. So, the financial

situation of enterprises has very strong impact on the efficiency of the business

enterprise.

1.4.1.6. Inventory

Inventory is one of the most essential input factors, takes part in every activities, and

operating procedure of a real estate company. Quality and the day inventory on hand

directly impact process of construction, productivity, the consumption rate, so it

directly affects the efficiency of the business.



2. LITERATURE REVIEW

1.5. Corporate Governance overview

The literature review explores the following theme of the research questions: the impact of

corporate governance on real estate public firms in Vietnam from 2013 to 2014. After a brief

definition of corporate governance, a model was performed to find out the impact of corporate

governance, including board size of management, size of executive board and the coincident

people between BOM and BOD and disclosure, on firm profitability.

1.1.3.Definition of corporate governance

There are many definitions of corporate governance. OECD (2004) states that “Corporate

governance is a system by which companies are directed and controlled”. La Porta et al

(2000) considercorporate governance as a set of mechanisms in which outside investors

protect themselves against problems arising from conflicts of interest from the managers

and controlling shareholders. According to Pei Sai Fan (2004), “Corporate governance is

basically about putting in place the structure, processes and mechanisms by which

business and affairs of the company are directed and managed in order to enhance the

long term shareholder value through accountability of managers”.

At basic level, corporate governance problems arise when shareholders wish to control

their companies in a different way to the managers. These problems are further

complicated by conflicts among different shareholders due to the diversity in ownership.

To solve these conflicts, proper corporate governance frameworks are put in place. Five

mechanisms in corporate governance are used to manage the conflicts:

(i) hostile takeover,

(ii) partial concentration ownership and control in large shareholders or a group of

shareholders,

(iii) delegation of partial control to large creditors (e.g. financial intermediaries),

(iv) control of CEO by board of directors,

(v) Alignment manager’s interests with shareholder through remuneration policy.



Among these mechanisms, the role of board of directors in controlling CEOs is widely

used. Most corporate charters require that shareholders elect a board of directors, which

monitors the CEO on their behalf.

1.1.4.Studies approaches to corporate governance

1.1.4.1. Agency theory

Agency theory seems to be the most frequent used to develop the concept of

corporate governance, resulting in the practice of this approach to a variety of

researches. According to agency theory, shareholders (principals) would be the

owners of the companies, but do not run the operating activities on day-to-day basis.

Instead, they delegate decision making authority to the directors, called agents.

Because of the separation of duty between control and ownership, and the difference

of concern between two parties, there remains a situation that the agents act on their

own interest, which influences that of principals. This problem has been aggravated

in Anglo-Saxon economies by the development of modern firms with large number of

atomized shareholders whose delegation of multiple tasks as well as decision making

to managers has set room for managers’ engagement in moral hazard and adverse

selection. As a result, the agency cost exists unavoidably.

The main task behind agency theory is to produce a method that make sure the

efficient alignment of interest of principals and agents, leading to the reduction of

agent cost. Indeed, in accordance with Jensen and Meckling (1976) and Fama and

Jensen (1983), solutions to agency problems involve establishing a “nexus” of

optimal contracts (explicit as well as implicit) between the owners and management

of the company. These contracts, also known as the “internal rules of the game”,

identify the rights of agents in the organization, performance criteria against which

they will be evaluated and the resulting payoff functions they will tend to face.

1.1.4.2. Transaction cost economics theory

Cost and difficulties along with market transactions sometimes favor hierarchies and

sometimes act as an economic governance structure. Firms have two main sources of

funds, which are from debt-holders and shareholders. In which, debt is often the cost



effective way as involving non-specific assets and equity is the most economical for

investments that involves specific assets. Williamson (1985, 1996) characterized

specific assets or “asset specificity” by costly to redeploy when the contract breaks

down as there would be a loss of useful value. Williamson presumes that projects can

only be financed with debt initially. If governance structure works out of rules, failure

to make payment leading to bankruptcy, which makes the recovered rate to debt

holders proportionate to the extent that the assets are redeploy able. Because of the

fact that debt holders can anticipate values that they would be able to recover when

liquidation, the assets become less redeployable. Transaction Cost Economics

predicts debt financing are adjusted, making debt financing becomes more costly as

the degree of asset specificity increases (Williamson 1988).

1.1.4.3. Stakeholder theory

Originally created by R. Edward Freeman (1984), stakeholder theory gives a broader

overview about corporate governance than agency theory; hence it creates better look

for company performance from corporate governance. This theory is used in lots of

researches before across the world, and also discussed as the centerpiece among

governance theories in this research. In practice, there is a variety of stakeholders that

related to the corporation beside the shareholders, including employees, customers,

suppliers, banks, environmentalists, governments, etc. This concept is usually applied

to large corporation, where the impact of companies on society is so persuasive that

they should discharge responsibility to many more sectors of the society rather than

on their shareholders only (Solomon, 2004).

Freeman (1984) indicates that corporation must simultaneously satisfy the owners,

the employees, and their unions, suppliers and customers in order to be successful.

Besides, managers in different functional disciplines ought to be more responsive to

the external environment by carrying forward the notion of internal stakeholders” as

the conduits to external groups. In such an organization, the executives should act as

“corporate spokesperson, political and social participant and manager of the human

resources of the firm”.



Giving the same description like Freeman, Buchholz (1989) also showed the

importance of unity in interest between parties. He brought about some new findings

to solve this difficult problem such as increasing rights to shareholders to participate

in important management decisions, change in the composition of boards by

including more outside directors to alleviate concern boards that are too subservient

to management or employee representation at some level in corporate governance.

Besides, Donaldson and Preston (1995) analyzed stakeholder theory via its

descriptive accurateness, instrumental influence and normative legitimacy. Because

of being a powerful tool to examine empirical claims, guesstimate appropriately

stockholder concept, and to test the links between corporate management and its

performance, this approach is both descriptive and instrumental. First, this theory is

used to describe, and sometimes to explain, specific corporate characteristics and

behaviors. It is immoral if focus exclusively in the interest of shareholders, it should

be enlarged the concern by non-shareowners community. Second, applying in

instrumental way, stakeholder theory aims to recognize the bonds between

management and accomplishment in corporate objectives. By using different tools to

decrease information asymmetry, and enforcement devices including law, and

emphasis of fairness, stakeholder theory succeeds in suiting variety of stakeholder

concentrations.

In the world, corporate governance system is mainly divided into two systems, insider

type governance and open type governance. The characteristics of both types of

governance are shown as the table below:

Table 1: Two types of corporate governance system worldwide

Insider type corporate governance

system

Open type corporate

governance system

Characteristics Based on a long term relation and

mutual reliance

Not taking opportunity principle

mutually.

The bearer of corporate

Based on law, contracts and

self-responsibility

Numerous bearers of corporate

governance.

Various kinds of monitors.



governance is limited.

Monitoring is taken on by a main

bank.

Insufficient disclosure.

Assuming the existence of the

market, with free entry and

free withdrawal.

Sufficient disclosure.

Price mechanism works.

Strengths Stable management and stable

employment.

Retrenchment of monitoring cost.

Internalize adjustment cost.

Incentive mechanism works

for managers.

Easy to promote business

restructuring.

Limitations Uncertain management system

The system becomes invalid when

the management is unstable.

Burgeoning monitoring cost.

Generate free riders of

monitoring

Promote rent-seeking activities

Source: EPA (1998), Mitsubishi Research Institute, Inc

1.2. Researches on Corporate Governance worldwide

1.2.1. In USA and UK

Researches carried out by many authors in the world indicate that corporate governance

has strong relationship with firm’s performance. In USA, one of the first famous findings

belonged to McConnell and Servaes (1990), who conducted the quantitative analyses by

gathering data from 1.173 firms in 1976 and 1.093 US firms listed on NYSE or AMEX.

At first, these researchers base solely on agency theory, leading to hypothesis that value of

firm would depend on Proportion of shared owned by insiders. It is reasonable when they

pointed out that there is a motivation for the manager to adopt investment and financing

plans that profit him, but lessen the payoff to external stockholders. Thus, the greater the

percentage of the shares owned by insiders, the bigger the value of the firm.

When taking OLS, they decided to conduct the test four times. In the initial regression, Q

is regressed against insider ownership and insider ownership squared. In the next three

regressions, various measures of block-holder ownership were introduced into the model

as additional control variables. Second examination showed the relationship between



percentage of shares owned by the largest single block-holder and Q. The measure in third

test for block-holder ownership was the percentage of shares owned by all block-holders,

and the last had the measure which was an indicator variable that is assigned the value of

one if the firm has a block-holder and zero, otherwise. In no case, for either year, does the

measure of block-holder owner. The results significantly contributed to the world

civilization when there is a positive relation between Q and fraction of shared owned by

institutional investors, financial leverage, R&D intensity and advertising intensity.

Besides, curvilinear relationship between Q and percentage of shares owned by corporate

insiders comprised of officers and members of Board of Directors (BOD) were

discovered, which set the foundation to lots of researches afterward. In 1996, Nickell got

Panel data from EXSTAT 670 UK firms from 1972 to 1986. Adding new concept to firm

performance – market competition, Nickell observed the link between productivity

growth and market share, competition dummy and value-added. An important conclusion

was made, containing the reduction that market power takes on level of Productivity and

the increase in growth if competition rises.

In 1997, Nickell continued his work with colleagues — Nicolitsas and Dryden to regress

productivity with eight independent variables. Interestingly, the implication of dependent

variable in this case is far different from that in a year before as it derived from change in

log of real sales. Since basing on stakeholder theory, eight variables bringing both inside

and outside factors contains lagged productivity growth, change in log of employment,

change in log of capital stock, change in index of industry overtime hours, monopoly

power, size by log of employment, financial pressure and industry and time dummies. It

was logical when the outcome is productivity increasing significantly with ownership

control, market competition, and financial pressure. This paper focused entirely on

manufacturing sector via collecting data from 580 manufacturing firm in UK from 1985

to 1994, showing its valuable implication.

1.2.2. In Japan

Japan experienced the significant change in firm behavior in 1990s as the considerable

shift in corporate governance. In the past, investments of Japanese firms depended mainly

on external debt, especially on borrowing channel from banks. Until the mid 1980s, equity



and corporate bond finance rose dramatically, while short and long term bank borrowing

reduced in size. Kitamura (2001) expected that the lack of governance and leadership,

together with the balance sheet problem of banking and non-banking firm contributing to

long recession. Due to the similarities in situation between Japan and Vietnam, this paper

is decided to use as a corner stone throughout this thesis. In his paper, Kitamura not only

focused on how corporate governance affects performance of firms, but also market

competition. Using panel data from Basic Survey ofhpanese Business Structure and

Activities, hegathered information from 26,000 firms over 33 industrial categories from

1992 to 1995. Specifically, manufacturing industries accounted for 50%, wholesale and

retail industry made up 40%, the remainder belonged t° other industries. Seven types of

information were pulled together including types and Year establishment number of

employees and organization, assets, liabilities, capital, stock, and investment, intra-

industry trade and international trade, research and development, holding and use of

patents and licenses, and parent company, subsidiaries and affiliations.

Taking reference from Nickell (1996) suggesting idea that competition improves

corporate governance, Kitamura added this factor into his paper. In fact, Nickell shows

facts that rivalry, as quantified by increased amount of competitors or by lower levels of

rents, is coupled with a considerably higher rate of total factor productivity growth. In line

with the standard economic theory, perfect competition results in proficient allocation of

resource. In fact, Nickell ascertained that firms with higher market share tend to have

higher productivity growth. Consequently, it is vague to conclude that market competition

strengthens corporate performance on practical grounds.

However, after elaborating paper of Allen and Gale in 2000, Kitamura found out the

contradicting phenomenon as they ended up with the conclusion that although there is a

lack of outside discipline and monitoring, most firms seen to operate fairly efficiently.

Thus, they argue that a wider viewpoint than the standard agency view of governance is

essential. Particularly, firms must have entrepreneurial management teams that have

ability to make good decisions about prospect directions rather than only cost minimize. It

means that managers have more work to do to specify direction that firms should move in,

more willingly than being standing-ins. To test the accuracy of effect that corporate

governance associated with competition takes on firms' performance, the process that used



to conduct the investigation is describe more detailed as below. Kitamura developed the

model based on eight variables. In which, from the view point of corporate governance,

own capital ratio and return on equity (ROE) are classified as governance variables from

shareholders, while liquidity ratio, debt/equity ratio, and symbol ratio are those from debt-

holders. There were five control variables symbolizing for corporate governance

including Own capital, Debt-Equity ratio, Liquidity ratio, Leverage ratio, and Square of

leverage ratio. Besides, Labor and Capital stand for stakeholder factors, whereas sales

share represented for market competition. Especially, he chose ROA to be a symbol of

firm performance. ROA gives investors information about the profits generated from the

invested amount (or the amount of assets). ROA differs significantly between joint stock

companies and depends on the business and industry that firms get in. Assets of a

company are derived from loans and equities. Both of these funds are used to finance the

company's operations. The effect of the ability to transfer from capital to profit is

described via ROA. Because the company has the capability to earn more money on less

investment amount, so the higher the ROA, the better. All of the data were taken from

annual report of each firm.

The result is summarized as follows:

ROAt = 0.043 + 0.261 * St + 0.003 * lnLt — 0.004 * lnKt — 0.03 * (D/A)t — 0.02 *

(D/A)2t + 0.051 * OwnCapRatiot — 0.03 * LiquidityRatiot

t-stat (resp) (13.03), (5.47), (13.68), (-25.1), (-7.55), (-11.7), (19.18), (-17.52)

In which: ROA: Return on Total Assets, St: (Sales share) Share of firm's output in total

output, Lt: (Labor) numbers of full-time employees, Kt: (Capital) Real Capital stock,

(D/A)t: Debt to Assets ratio, OwnCapRatiot: (Owned Capital Ratio) Shareholder equity to

Assets ratio, LiquidityRatiot: Liquid Assets to Liquid Debt ratio.

It is obvious to see that sales share, labor, own capital ratio positively relate to ROA,

meanwhile, capital factor, leverage ratio, square of leverage ratio and liquidity ratio have

inverse relationship with dependent variable. At the beginning, Kitamura proposed debt-

equity ratio as one of the explanatory variables, however, after thorough procedure of

testing, this ratio did not show any strong link to explained variable — ROA as the

coefficient term equaled 0 and t-stat was 1.53.



The second Japanese research that should be considered is from Hirotsugu Sakai and

HittoshiAsaoka. Taking data from 468 Japanese firms, they conducted three tests at the

sametime. Dependent variable was spent for value added, represented firm performance

and used throughout the 3 experiment. According to SNA, value added is defined as

(i)personnel cost (employees compensation, welfare expense and allowance for employee

retirement benefits), (ii) rental cost, (iii) financial cost, tax and public charge (excluding

the following taxes), (iv) corporate tax, residence tax, and enterprise tax, (v) current net

profit, (vi) depreciation allowance.

In the first test, they examined the relationship of firm performance with market

competition. Lagged market share, Leverage ratio, Capital stock and Labor were

employed to be predictor variables. The second test showed the bond linking ownership

structure and block holders. One of the most interesting things in this paper is that

Hirotsugu Sakai and Hitoshi Asaoka applied the same basic control variables listed above

for these 3 tests, with some additional variables in the subsequent examination to satisfy

the suitability in feature of each test. As a result, the second experiment existed additional

regressor namely ratio of block holders' shareholders of firm. The last test was the

association of ownership structure with financial institution, non financial institution,

foreigners and individual. The added stimulus variable was dummy variables that separate

ratio of block holders' shareholders of firm in the previous test into 3 main variables

containing foreign investors, individual investors and financial institution investors.

The result is impressive with some important relationships that were proved. Market

competition increased the firm performance but not so strong, meanwhile, leverage ratio

and block holderspositively affected ROA. Foreigner shareholder was the only variable

having impact on firm effectiveness and efficiency out of the other three.

1.2.3. In Vietnam

There are few quantitative researches that investigate about the connection between firm

performance and corporate governance in Vietnam as a reason of limited source of

information. Most of the studies in this issue in Vietnam focus on banking sector such as

the following two papers.



One of the first and foremost studies about this subject is conducted by PhD. Dao Binh

and Hoang Giang (2012). In which, they revealed the fact about banking sector, along

with the base of agency theory and stewardship theory. Besides, to support for the

consistence of model, they implement the external - internal and triangle framework of

bank corporate governance. A sample combined of the information within theperiod of

2008 and 2010 was gathered, after a check of extreme value, they obtained a sample of 30

data with a combination of cross-sectional and time-series data. Most of the data are

collected from annual reports and financial statement of 30 banks.

Chosen among variety of proxies for bank performance, ROE became the closest

measurement of return to shareholders' investment. In term of independent variables,

banks are standardized by SBV regulation, so there is one important variable standing for

risk management called CAR. Almost one third of Vietnamese commercial banks have

foreign strategic partners or foreign investors, foreign ownership is decided as

representative for shareholder characteristics. Their general model is made up one

dependent variable ROE — Return on Equity and three independent variables BS —

Board Size, CAR — Capital Adequacy Ratio and FOWN — foreign ownership. After

testing several alternative models, they brought out one significant result: Bank

performance is considerably affected by board size and CAR. Meanwhile, foreign

ownership is not the factor that has influence on ROE. Besides, they made up another six

tests with board composition variable; however, it is obvious from the models that the

composition of the Board of Directors has very little influence on the bank performance in

Vietnamese banking sector.

Another research that deserves to be mentioned is performed by Tran Tu and Pham Khanh

(2012). In thispaper, they pointed out the relationship between bank performance and

corporategovernance via using new base idea — corporate governance index (CGI). A

sample consisted of 36 commercial banks, with data was collected from 2010 to 2011, so

the totalobservations were 72. Financial data includes ROE -- return on equity, ROA on

assets, ratios of cost over income - COIs, equity over assets ratio, the size of total assets

which are obtained from audited financial reports or annual reports of banks. The

dependent variable is bank performance, which is measured by operational performance:

ROE, ROA or Cost over Income ratio. Independent variables include CGI, Total assets



and Leverage ratio. Corporate governance index (CGI) is selected to be proxy for

corporate governance. In constructing a corporate governance index, there are two main

approaches. First, CGI is built through a project joint between academic institutions.

Second, corporate governance index is built in researches in studying the relationship

between corporate governance and firm performance.

Based on method for CGI of all business (T.N.Thang, 2010), OECD principles and Basel

principles for enhancing corporate governance (2006), modifications from the first test in

March 2012, a scorecard is designed to estimate CGI. The main components of CGI for

Vietnamese banks composed of Shareholder and Shareholder's annual meeting, Board of

Director, Board of Supervisors, Disclosure, transparency and auditing and Violation.

After examining several models, they found out that CGI has positive impact on

performance of Vietnamese commercial banks in 2010-2011. However, •its impact is not

considerable. However, in young market like Vietnam, performance of commercial banks

is also influenced by many other variables such as number of branches (Nguyen Manh

Hung, 2010), quality of assets (Nguyen Duc Thank, 2012) and risk management (Vincent

Aebiet all 2012). Therefore, in their research, the explanation of control variables in

models is not high.



3. METHODOLOGY

1.3. Data collection method

In this section, I will explain the sampling method used to conduct the model. The population

of interest is real estate firms listed in Vietnam at the date of 30 May 2015. As the number of

real estate companies listed in Vietnam is limited to 59 firms, in which 44 firms on HOSE and

15 firms on HNX, this study is plan to consider the whole population of 59 stock codes for the

population size.

Further, this study is to collectdata for 59 firms for the period from 2013 to 2014.

Because the objective of this thesis is to learn lessons about corporate governance from

successful corporations, it is reasonable to take the additional condition of positive ROA and

ROE values.

ROA and ROE in 2013, 2014 are set to be dependent variables. Other figures are designated as

independent variables that were collected from firms’ annual financial reports. All of them are

inputs to Excel worksheet to process, and then imported to Eviews to perform the test and

further analysis.

1.4. Population selection

Based on prior research of Kitamura (2001) about “Corporate Finance and Market

Competition: Evidence from the Basic Survey of Japanese Business Structure and Activities in

the late 1990s” in Japan; this study have the basic idea to select some main variables that is

believed to be suitable to Vietnam. They are ROA and ROE as dependent variables, along

with Net income, Total Assets, Equity, Debt, Current Assets, Current Liabilities, Inventory,

Capital, Debt to Asset ratio, Equity to Asset ratio, Debt to Equity ratio, Quick ratio, Liquidity

ratio, as independent variables. Besides, this study developsother independent variables

including Board size (BOM), Executive size (BOD) and Coincident people between BOM and

BOD to find out the impact of corporate governance factors on the performance of the

company.

Methodology Page 18


1.4.1.Dependent variables

To finalize the model, this fieldwork is trying both ROA and ROE as dependent variables.

After conducting the test, which one better that create the most relevant model could be

selected as prediction variable.

1.4.1.1. Return on Assets – ROA

ROA provide investors with the information about the performance of the company,

particularly the profits generated from the invested amount of assets. Assets of a

company are derived from loans and equities. Both of these funds are used to finance

the company’s operations. The effect of the ability to transfer from capital to profit is

described via ROA. The higher the ROA is, the better it is. Because the higher ROA

means that company has the capability to earn more money on less invested amount.

That is the reason why ROA is the best indicator for firms’ performance evaluation.

ROA is calculated as in this equation:

In this thesis, ROA is calculated from Net income and Total assets which are

collected from annual audited reports of each chosen firms.

1.4.1.2. Return on Equity – ROE

ROE is the most important ratio with shareholders, measuring the profitability per

dollar of shareholder equity. This index is an accurate measurement to assess how

much profit could be generated by accumulated capital spending. High ROE means

that the company could demonstrate the effective usage of shareholder capital,

proving the harmonious balance between equity and debt to exploit its competitive

advantage in the process of raising capital and expanding scale of economy.

Therefore, the higher the ROE is, the more attractive the stock to investors is.

ROE is calculated in this equation:

Methodology Page 19


In this thesis, ROE is calculated from Net income and Total equity which are

collected from annual audited reports of each chosen firms.

1.4.2. Independent variables

1.4.2.1. Net income – NI

Net income is the amount of profit after tax collected in the income statement. For

most shareholders, net income is the most important benchmark to evaluate the

performance of an investment.

1.4.2.2. Current assets – CA

Current asset isan account on balance sheet that illustrates the value of all assets

which are reasonably expected to be converted into cash within one normal course of

business or one year. Current assets include cash, accounts receivable, inventory,

marketable securities, prepaid expenses and other liquid assets that can be readily

converted to cash.

1.4.2.3. Current liabilities – CL

A current liability is also an account on balance sheet that is due within one cycle of

business. However, it creates an obligationthat will require the use of a current asset.

1.4.2.4. Inventory – INVENTORY

The proper management of inventory is critical for any size business, particularly real

estate companies. The way a company values its inventory can be the difference

between a profit and loss. In fact, inventory valuation affects a company's profit

margin, working capital, assets and shareholder's equity.

1.4.2.5. Capital – CAPITAL

Capital in this thesis is also equity in the balance sheets as of the date 30 December.

1.4.2.6. Leverage ratio – DEBTASSETS

Most firms in real estate industry take huge debts to finance its operation. When used

prudently, financial leverage can enhance investment returns when investing in non-

Methodology Page 20


residential real estate. However, when leverage is deployed excessively or structured

inappropriately, the investment results can be catastrophic.

1.4.2.7. Quick ratio– QUICKRATIO

Quick ratio is calculated as the ratio of current assets minus inventory in comparison

to current liabilities. It shows the ability to carry out its obligation for maximum one

year or once business cycle.

3 independent variables that represent for firms’ corporate governance

1.4.2.8. Board size – BSIZE

Board size is the number of people elected by the annual shareholders meeting to be

in the Board of Directors. This data is extracted from the annual audited financial

statements of each firm. A larger board could also favor better decision making as a

result of diversified competency and experience. It is supposed that the larger the

board size is, the better the firm’s performances are.

1.4.2.9. Executive board – EXESIZE

Executive board is the number of people that are elected or appointed to be in charge

with the activities of organization. This information is taken out from the annual

audited financial statements of each firm. It is reasonable when company is managed

by bigger size of executive board would perform better than small size. This research

expects that EXESIZE and dependent variables are positively related.

1.4.2.10. Coincident people between BOM and BOD – COINCIDENT

This factor implies how many people have responsibility in both boards. The larger

the number of coincident people is, the smaller separation of duty in corporate

governance in firms is. This means that one person would be in charge of various

functions, resulting in the reduction in efficiency and effectiveness of management

team. Because of this reason, it is anticipated that the coefficient of this variable

would have a negative sign, which reflects the inverse relationship between number

of coincident persons and dependent variables. In case it acquires positive sign, it

could be interpreted as another case.

Methodology Page 21


1.5. Descriptive statistics

All of the data is collected from annual reports of each firm, which is gathered from their

official website. Due to the aim of this thesis which is to learn lesson from successful

companies, firms are selected on purpose. Condition to choose data is that ROA and ROE

must be higher than zero, showing the financial health of company. The mean and standard

deviation of each variable is summarized as follows:

Table 2 : Descriptive Statistics

Mean Median Maximum Minimum Std. Dev.

NI 197098.8 29463.50 6779512. 107.0000 788662.3

TA 5102483. 1653434. 90485307 118710.0 12807655

EQUITY 1809518. 610350.0 20396041 63537.00 3334443.

DEBT 3087112. 946934.5 63200674 24802.00 8995758.

CA 2765524. 1089090. 39844678 24940.00 5676981.

CL 1544120. 531801.0 26675265 11504.00 3850535.

INVENTORY 1482174. 459966.0 18913717 0.000000 2895603.

ROA 0.029080 0.017922 0.140316 0.000113 0.030791

ROE 0.074669 0.043536 0.556955 0.000402 0.094599

CAPITAL 1809518. 610350.0 20396041 63537.00 3334443.

DEBTASSETS 0.539945 0.546076 0.847689 0.192194 0.153410

EQUITYASSET 0.439546 0.432037 0.796901 0.152311 0.150910

DEBTEQUITY 1.574134 1.269346 5.565519 0.254860 1.125264

QUICKRATIO 1.215077 0.776762 12.83162 0.102944 1.639485

LIQUIDRATIO 2.507949 1.986253 14.06737 0.494470 1.973657

BSIZE 5.829787 5.000000 11.00000 5.000000 1.372842

EXESIZE 3.872340 3.000000 9.000000 1.000000 1.667101

COINCIDENT 2.106383 2.000000 6.000000 0.000000 0.955663

Firstly, as regards to characteristics of dependent variables, it is clear that there is a significant

spread among all observations and their mean.ROE ranges from 0.04% to 55.69% with mean

Methodology Page 22


value equals to 7.47%. While ROA ranges from 0.01% to 14.03%, with mean value equals to

2.9%. Mean value of ROE is much higher than that of ROA in addition that ROE’s standard

deviation is also higher than ROA’s (9.5% and 3.08%). IDV - VinhPhuc Infrastructure

Development Joint Stock Company in 2014 gained the highest return of equity of 55.69%,

while in 2013 PPI - Pacific Property And Infrastructure Developement Joint Stock Company

obtained the lowest percentage of ROEas 0.04%.When it comes to ROA, the best return on

assets is the percentage of 14.03% in 2013 of REE - Refrigeration Electrical Engineering

Corporation and the least return on assets is also in 2013 with the percentage of 0.01% of

UDC - Urban Development and Construction Corporation.

As for the features of independent variable BSIZE (board size), the table indicates that the

average of board size among all real estate firms in Vietnam from 2013 to 2014 is 5.8 with a

wide range from 5 to 11 members. Most of firms have their board size of 5 persons over the

period of 2013 and 2014. Meanwhile most of them kept smaller size of executive board –

EXESIZE, only 3 persons and varying from 1 to 9 members. The COINCIDENT in almost

firms studied in this thesis is 2 persons. The particular circumstances areSCR - SaiGonThuong

Tin Real Estate Joint Stock Company without coincident and HQC – Hoang Quan Consulting

– Trading – Service Real Estate Corporation with the largest coincident of 6 people.

Further, leverage ratio (DEBTASSETS) and total debts to owner equities ratio

(DEBTEQUITY) and equity to total assets ratio (EQUITYASSET) reflect comprehensively

characteristics of real estate sector. Real estate firms often operate with high level of debts,

most of capital comes from debts. That is the reason why all three variables remain high on

average.

The last independent variable need to be classified is INVENTORY which is used to measure

the outstanding inventory from 2013 to 2014. The data shows that the average inventory in the

studying period remained very high of 1,482 billion VND. The only one firm having without

inventory in both 2013 and 2014 is DRH - Dream House Investment Corporation. The

exceptional case of VIC - VinGroup Joint Stock Companykept its inventory at the very high

and rising level with the amount from 16,598 billion VND in 2013 to 18,913 billion VND in

2014.

Methodology Page 23


1.6. Correlation analysis

Before the regression model is run, the matrix correlation between our variables (dependent

and independent) is performed in the Appendix 4. The matrix shows that variables in the

model are not highly correlated.

Methodology Page 24


4. REGRESSON MODEL ANALYSIS

1.7. Assumptions

Econometric methodology is applied in this thesis to examine the link between corporate

governance controlling mechanism and performance of Vietnamese real estate listed firms.

More specifically, ordinary least square – OLS method is utilized for testing.

As the requirement in application of OLS, several assumptions as follows should be concerned

and accepted:

1. Linear regression model: the regression model is linear in the parameters

(With i = 1,…..n)

2. X values are fixed in repeated sampling

Values taken by the regressor X are considered fixed in repeated samples, or in other

words, X is assumed to be nonstochastic.

3. Zero mean value of disturbance µi. Given the value of X, the mean or expected value of

the random disturbance term µiis zero. E(µi|Xi) = 0

4. Homoskedasticity or equal variance of µi. Given the value of X, the variance of µ i is the

same for all observations. Var (µi|Xi) = σ2

5. No autocorrelation between the disturbances. Given any two X values, Xi and Xj (i#j),

correlation between any twoµiand µj is zero. Cov(µi,µj|Xi,,Xj) = 0

6. Zero covariance between µiand Xi, or Cov(µi,Xi) = 0

7. The number of observations n must be greater than the number of parameters to be

estimated (explanatory variables).

8. Variability in X values. The Xa values in a given sample must not all be the same.

Technically, Var(X) must be a finite positive number.

9. The regression model is correctly specified. There is no specification bias or error in the

model used in empirical analysis.

10. There are no perfect multicollinearity. There are no perfect relationships among the

explanatory variables.

Data Analysis Page 25


Besides, aiming to conduct the examination using Eviews software and simplify the tests, it is

understandable that all the data are assumed to be normally distributed. It is reasonable to test

the model under one level of significant, α being 5% , as it is a prevalent benchmark in

econometric study.

1.8. General model

After analyzing quantitative model of corporate governance and real estate firms’ performance

by using statistic description of variables and correlation analysis among all variables, the

general econometric models are formed as the following combination of dependent and

independent variables.

1.8.1.Equation 1: Test all independent variables with dependent variable ROA

Firstly, this part generates a regression model as equation 1 including one dependent

variable ROA – return on assets which represent for the performance of real estate

corporations listed in Vietnam. Also, the model has 15 independent variables including

Net income – NI, Total Assets – TA, Debts – DEBT, Current Assets – CA, Current

Liabilities – CL, Inventory – INVENTORY, Capital – CAPITAL, the ratio of debt to total

assets – DEBTASSETS, the ratio of equity to total assets – EQUITYASSET, the ratio of

Debt to total Equity – DEBTEQUITY, the quick ratio – QUICKRATIO, the liquidity ratio

– LIQUIDRATIO, the board size – BSIZE, the executive board – EXESIZE, the

coincident people between BOM and BOD – COINCIDENT.

The aim of the general model is to test the effect of corporate governance on the

performance of real estate firms listed in Vietnam from 2013 to 2014.

Table 3: Testing result of all 15 independent variables with dependent variable ROA -

Equation 1

Dependent Variable: ROA

Method: Least Squares

Date: 05/30/15 Time: 17:06

Sample: 1 94



Included observations: 94

Variable Coefficient Std. Error t-Statistic Prob.

C -0.040483 0.087809 -0.461029 0.6461

NI 6.84E-08 1.15E-08 5.956582 0.0000

TA 5.32E-08 1.63E-08 3.261717 0.0016

DEBT -6.14E-08 1.89E-08 -3.255265 0.0017

CA -9.76E-09 4.83E-09 -2.022411 0.0466

CL 1.53E-09 6.08E-09 0.251561 0.8020

INVENTORY 6.19E-09 4.58E-09 1.352689 0.1801

CAPITAL -4.59E-08 1.56E-08 -2.938545 0.0043

DEBTASSETS 0.096292 0.083128 1.158361 0.2503

EQUITYASSET 0.073903 0.090877 0.813219 0.4186

DEBTEQUITY -0.001808 0.005689 -0.317854 0.7514

QUICKRATIO 0.005927 0.003336 1.776673 0.0795

LIQUIDRATIO -0.000416 0.002981 -0.139654 0.8893

BSIZE -0.002922 0.002383 -1.226364 0.2238

EXESIZE 0.000113 0.001754 0.064356 0.9489

COINCIDENT 0.000682 0.002951 0.231074 0.8179

R-squared 0.491713 Mean dependent var 0.029080

Adjusted R-squared 0.393966 S.D. dependent var 0.030791

S.E. of regression 0.023970 Akaike info criterion -4.470155

Sum squared resid 0.044817 Schwarz criterion -4.037254

Log likelihood 226.0973 Hannan-Quinn criter. -4.295295

F-statistic 5.030450 Durbin-Watson stat 1.824805

Prob(F-statistic) 0.000001

Where: the name of variables are presented in Sample selection part

Individual partial coefficient test: p-value solution

Hypothesis: H0: βi = 0 (the variable i has no influence on dependent variable)



Hi: βi ≠ 0 (the variable i has influence on dependent variable)

Significant level: α = 5%

Decision rule:

H0 is rejected if p-value of the coefficient is less than 5%

H0 is not rejected if p-value of the coefficient is greater than 5%

Based on the result on Equation 1, there are five variables which have probability less

than 5%. These are Net Income, Total Assets, Debt, Current Assets and Capital. The null

hypothesis for these variables is rejected. This means thatthese variables have a statistical

significance on the firm performance when it comes to ROA.

The remaining variables includeCurrent liabilities, Inventory, Debt to Assets, Equity to

Assets, Debt to Equity, Quick ratio, Liquidity ratio, Board size, Executive size, and

Coincident.Because the null hypotheses for the remaining variables are not rejected,

leading to further testing of adding or removing these variables from the model.

As can be seen from equation 1:

R-squared of this model equals to 0.491713 means that 49.17% of ROA

movement that can be explained by movements of independent variables.

Adjusted R-squared of this model is 0.393966 means that these 15 independent

variables give an explanation of 39.39% movements of ROA.

Corporate governance independent variables in Equation 1 have tiny

significance on the firm’s ROA.

Board size show a negative relationship with return on assets;

That the coefficient of BSIZE equals to -0.002922 is interpreted

that ROA is expected to decrease to 0.29% on average if the board

of management increases by one person, holding other variables

constant.

Whereas, executive board and coincident present a positive

relationship with ROA.

That the coefficient of EXESIZE equals to 0.000113 is interpreted

that ROA is expected to increase to 0.011% on average if the



executive board increases by one person, holding other variables

constant.

That the coefficient of COINCIDENT equals to 0.000682 is

interpreted that ROA is expected to increase to 0.068% on average

if the coincident increases by one person, holding other variables

constant.

1.8.2.Test all independent variables with dependent variable ROE

Secondly, this part generates a regression model as equation 2 including one dependent

variable ROE – return on equity which represent for the performance of real estate

corporations listed in Vietnam. Also, the model has 15 independent variables including

Net income – NI, Total Assets – TA, Debts – DEBT, Current Assets – CA, Current

Liabilities – CL, Inventory – INVENTORY, Capital – CAPITAL, the ratio of debt to total

assets – DEBTASSETS, the ratio of equity to total assets – EQUITYASSET, the ratio of

Debt to total Equity – DEBTEQUITY, the quick ratio – QUICKRATIO, the liquidity ratio

– LIQUIDRATIO, the board size – BSIZE, the executive board – EXESIZE, the

coincident people between BOM and BOD – COINCIDENT.

The aim of the general model is to test the effect of corporate governance on the

performance of real estate firms listed in Vietnam from 2013 to 2014.

Table 4: Testing result of 15 independent variables with dependent variable ROE -

Equation 2

Dependent Variable: ROE


Date: 05/30/15 Time: 17:06

Sample: 1 94



C -0.254863 0.221513 -1.150557 0.2534



NI 1.54E-07 2.89E-08 5.310868 0.0000

TA 9.45E-08 4.12E-08 2.294145 0.0245

DEBT -1.13E-07 4.76E-08 -2.369190 0.0203

CA -1.95E-08 1.22E-08 -1.603567 0.1129

CL 1.71E-08 1.53E-08 1.112639 0.2693

INVENTORY 1.06E-08 1.15E-08 0.916417 0.3623

CAPITAL -8.51E-08 3.94E-08 -2.158117 0.0340

DEBTASSETS 0.331122 0.209704 1.578998 0.1184

EQUITYASSET 0.252105 0.229253 1.099680 0.2749

DEBTEQUITY 0.014444 0.014350 1.006516 0.3173

QUICKRATIO 0.025513 0.008416 3.031461 0.0033

LIQUIDRATIO 0.003310 0.007519 0.440239 0.6610

BSIZE -0.003830 0.006010 -0.637297 0.5258

EXESIZE -0.000932 0.004424 -0.210688 0.8337

COINCIDENT 0.002662 0.007444 0.357518 0.7217








Individual partial coefficient test: p-value solution

Hypothesis: H0: βi = 0 (the variable i has no influence on dependent variable)

Hi: βi ≠ 0 (the variable i has influence on dependent variable)

Significant level: α = 5%

Decision rule: H0 is rejected if p-value of the coefficient is less than 5%

Based on the result on Equation 2, there are five variables which have probability less

than 5%. These are Net Income, Total Assets, Debt, Quick ratio and Capital. The null



hypothesis for these variables is rejected. This means that these variables have a statistical

significance on the firm performance when it comes to ROE.

The remaining variables include Current assets, Current liabilities, Inventory, Debt to

Assets, Equity to Assets, Debts to Equity, Liquidity ratio, Board size, Executive size, and

Coincident. Because the null hypotheses for the remaining variables are not rejected,

leading to further testing of adding or removing these variables from the model.


In this second trial, Adjusted R-squared of this model equals to 0.591399, much

higher than that of ROA’s regression model with all 15 independent variables in

Equation 1 (Adjusted R-squared of Equation 1 is 0.393966).

Adjusted R-squared of ROE’s model with 15 independent variables means that

59.14% of ROE movement that can be explained by movements of these

independent variables.

Similarly to the Equation 1, corporate governance independent variables in

Equation 2 also have tiny significance on the firm’s ROE.

Board size and executive board show a negative relationship with

return on equity;

That the coefficient of BSIZE equals to -0.003830 is interpreted

that ROE is expected to decrease to 0.38% on average if the board

of management increases by one person, holding other variables

constant.

That the coefficient of EXESIZE equals to -0.000932 is interpreted

that ROE is expected to decrease to 0.09% on average if the

executive board increases by one person, holding other variables

constant.

Whereas, only 1 controlling variable thatcoincident presents a

positive relationship with ROE.

That the coefficient of COINCIDENT equals to 0.002662 is

interpreted that ROE is expected to increase to 0.26% on average if



the coincident increase by one person, holding other variables

constant.

1.8.3.Summary

The table below summarizes the variables which are statistical significance to a real estate

company listed in Vietnam based on the criteria of ROA and ROE.

No ROA ROE

1 Net Income Net Income

2 Total Assets Total Assets

3 Debts Debts

4 Current Assets Quick ratio

5 Capital Capital

1.9. Test several alternative models

To find out the completed model, this study runs the regression model again with the statistic

significant variables as well as keeping several controlling variables to corporate governance

and removing the remaining variables.

1.9.1.Test 7 independent variables with dependent variable ROA – Equation 3

Table 5: Test independent variables with dependent variable ROA – Equation 3



Date: 05/30/15 Time: 17:15

Sample: 1 94



C 0.030848 0.018581 1.660134 0.1005

NI 6.03E-08 9.53E-09 6.325457 0.0000

TA 5.40E-08 1.49E-08 3.614412 0.0005

DEBT -6.48E-08 1.72E-08 -3.767037 0.0003



CAPITAL -4.86E-08 1.41E-08 -3.459066 0.0008

DEBTASSETS 0.010229 0.021029 0.486395 0.6279

QUICKRATIO 0.005229 0.001547 3.380287 0.0011

BSIZE -0.002289 0.002266 -1.010140 0.3153









In this third trial, Adjusted R-squared of this model equals to 0.394734, higher

than that of ROA’s regression models (Adjusted R-squared of Equation 1 is

0.393966), but lower than that of ROE’s regression model with all 15 independent

variables in Equation 2 is 0.591399.

Adjusted R-squared of Equation 3 means that only 39.47% of ROA movement

that can be explained by movements of these independent variables.

Similarly to the Equation 1, corporate governance independent variable in

Equation 3 also has tiny significance on the firm’s ROA.Board sizevariable shows

a negative relationship with return on assets;

That the coefficient of BSIZE equals to -0.002289 is interpreted that ROA is

expected to decrease to 0.22% on average if the board of management increases by

one person, holding other variables constant.

1.9.2.Test 9 independent variables with dependent variable ROA – Equation 4

Table 6: Test 9 independent variables with dependent variable ROA – Equation 4





Date: 05/30/15 Time: 17:14

Sample: 1 94



NI 6.97E-08 8.77E-09 7.943492 0.0000

TA 4.63E-08 1.28E-08 3.623303 0.0005

DEBT -5.19E-08 1.47E-08 -3.519866 0.0007

CA -1.26E-08 4.18E-09 -3.020630 0.0033

LOG(CL) 0.003835 0.000991 3.870784 0.0002

INVENTORY 7.64E-09 3.72E-09 2.051225 0.0433

CAPITAL -4.03E-08 1.25E-08 -3.228639 0.0018

QUICKRATIO 0.006494 0.001477 4.398332 0.0000

BSIZE -0.003872 0.002121 -1.825718 0.0714






Durbin-Watson stat 1.866743


In this forth trial, Adjusted R-squared of this model equals to 0.447173, higher

than that of ROA’s regression models (Adjusted R-squared of Equation 1 is

0.393966). (Adjusted R-squared of Equation 3 is 0.394734). However, adjusted R-

squared of models on ROA and independents results in a lower number in

comparison to results of models on ROE and holding remained independent



variables. Adjusted R-squared of Equation 4 is much lower than that of ROE’s

regression model with all 15 independent variables in Equation 2 is 0.591399.

Adjusted R-squared of Equation 4 means that only 44.71% of ROA movement

that can be explained by movements of these independent variables.

Similarly to the Equation 1 and Equation 3, corporate governance independent

variable in Equation 4 also has tiny significance on the firm’s ROA. Board size

variable shows a negative relationship with return on assets;

That the coefficient of BSIZE equals to -0.003872 is interpreted that ROA is



1.9.3.Test 9 independent variables with dependent variable ROE – Equation 5

Table 7: Test 9 independent variables with dependent variable ROE – Equation 5



Date: 05/30/15 Time: 17:14

Sample: 1 94



NI 1.39E-07 2.38E-08 5.821433 0.0000

TA 3.02E-08 3.48E-08 0.869025 0.3873

DEBT -2.88E-08 4.01E-08 -0.719114 0.4740

CA -2.40E-08 1.14E-08 -2.110453 0.0378

LOG(CL) 0.009286 0.002694 3.447246 0.0009

INVENTORY 1.57E-08 1.01E-08 1.546208 0.1258

CAPITAL -3.24E-08 3.39E-08 -0.954896 0.3423

QUICKRATIO 0.033096 0.004014 8.244259 0.0000

BSIZE -0.013323 0.005766 -2.310752 0.0233










In this model, Adjusted R-squared of this model equals to 0.567057, higher than

that of ROA’s regression models (Adjusted R-squared of Equation 1 is 0.393966),

(Adjusted R-squared of Equation 3 is 0.394734), (Adjusted R-squared of Equation

4 is 0.447173), ; higher than that of ROE’s regression model with all 15

independent variables in Equation 2 is 0.591399.

Adjusted R-squared of Equation 5 means that only 56.70% of ROE movement that

can be explained by movements of these independent variables.

Similarly to the Equation 2, corporate governance independent variable in

Equation 5 also has tiny significance on the firm’s ROE. Board size variable

shows a negative relationship with return on equity;

That the coefficient of BSIZE equals to -0.013323 is interpreted that ROE is



1.9.4.Test 7 independent variables with dependent variable ROE (Equation 6)

Table 8: Test 7 independent variables with dependent variable ROE (Equation 6)



Date: 05/30/15 Time: 17:15

Sample: 1 94





C -0.033840 0.046518 -0.727461 0.4689

NI 1.55E-07 2.39E-08 6.485191 0.0000

TA 9.85E-08 3.74E-08 2.632054 0.0101

DEBT -1.18E-07 4.30E-08 -2.740999 0.0074

CAPITAL -9.28E-08 3.52E-08 -2.637929 0.0099

DEBTASSETS 0.187170 0.052647 3.555197 0.0006

QUICKRATIO 0.027972 0.003872 7.223416 0.0000

BSIZE -0.004726 0.005673 -0.833054 0.4071









In this trial, Adjusted R-squared of this model equals to 0.598094, higher than

that of ROA’s regression models (Adjusted R-squared of Equation 1 is 0.393966),

(Adjusted R-squared of Equation 3 is 0.394734), (Adjusted R-squared of Equation

4 is 0.447173), ; higher than that of ROE’s regression models (Adjusted R-squared

of Equation 2 is 0.591399), (Adjusted R-squared of Equation 5 is 0.567057).

Adjusted R-squared of Equation 6 means that only 59.81% of ROE movement that

can be explained by movements of these independent variables.

Similarly to the Equation 2 and Equation 5, corporate governance independent

variable in Equation 6 also has tiny significance on the firm’s ROE. Board size

variable shows a negative relationship with return on equity;

That the coefficient of BSIZE equals to -0.004726is interpreted that ROE is





1.10. Error detection in the model

1.10.1. Autocorrelation

Autocorrelation exists when residuals in the model at present are related to the residuals at

previous or next. The Breusch – Godfrey test is employed to test for autocorrelation.

Table 9: Autocorrelation – BG Serial Correlation LM Test

Breusch-Godfrey Serial Correlation LM Test:

F-statistic 1.075935 Prob. F(2,83) 0.3457

Obs*R-squared 2.374693 Prob. Chi-Square(2) 0.3050

Test Equation:

Dependent Variable: RESID


Date: 05/30/15 Time: 17:25

Sample: 1 94


Presample missing value lagged residuals set to zero.


NI -1.48E-09 8.83E-09 -0.167642 0.8673

TA -1.92E-09 1.29E-08 -0.149428 0.8816

DEBT 2.25E-09 1.48E-08 0.151590 0.8799

CA 1.70E-10 4.18E-09 0.040652 0.9677

LOG(CL) 0.000221 0.001008 0.219252 0.8270

INVENTORY -2.07E-10 3.73E-09 -0.055529 0.9559

CAPITAL 1.73E-09 1.25E-08 0.138181 0.8904

QUICKRATIO -0.000375 0.001499 -0.250063 0.8032

BSIZE -0.000425 0.002160 -0.196860 0.8444

RESID(-1) 0.063564 0.111996 0.567560 0.5719



RESID(-2) -0.158958 0.116605 -1.363213 0.1765

R-squared 0.025263 Mean dependent var -6.34E-05

Adjusted R-squared -0.092176 S.D. dependent var 0.021887





Where: NI: Net Income, TA: Total Assets, DEBT: total debts, CA: Current Assets,

LOG(CL): Current Liabilities, INVENTORY: Inventory, CAPITAL: Capital,

QUICKRATIO: Quick ratio, BSIZE: board size of BOM.

Hypothesis: H0: no autocorrelation

H1: autocorrelation exists

Critical value: level of significance: α = 5%, n = 32, df = 2 ->

Test statistic: BG = n * R2 = 32 * 0.025263 = 0.808416

Conclusion, since BG = 0.808416< , do not reject H0 at α = 5%

Do not reject the hypothesis that there is no autocorrelation exists in this model.

Therefore, there is insufficient statistical evidence to infer at 5% level of significance that

the autocorrelation exists in the model.

1.10.2. Heteroskedasticity

This error is due to the change of variance residual along with the change of independent

variables. This causes some other consequences.

Heteroskedasticity arises because of some reasons:

Ordinary least squares (OLS) estimates are no longer best linear unbiased estimators

(BLUE). That is, among all the unbiased estimators, OLS does not provide the estimate

with the smallest variance.



Other sources of heteroscedasticity are the presence of outliers and the skewness in the

distribution of one or more regressors (Damodar 2009, p.391).

This thesis proposes to test whether the variances of µ iare variable, in other words, check

the model’s heteroskedasticity. The heteroskedasticity can cause several consequences to

OLS estimators; for instance, βi is no longer BLUE, and t-statistics and F-statistics

become unreliable. Therefore, detecting and correcting this error are really necessary.

Table 10: Heteroskedasticity Test: Breusch-Pagan-Godfrey

Heteroskedasticity Test: Breusch-Pagan-Godfrey

F-statistic 1.356627 Prob. F(9,84) 0.2211

Obs*R-squared 11.92922 Prob. Chi-Square(9) 0.2173

Scaled explained SS 11.58892 Prob. Chi-Square(9) 0.2375

Test Equation:

Dependent Variable: RESID^2


Date: 05/30/15 Time: 17:26

Sample: 1 94



C 0.002397 0.001277 1.877794 0.0639

NI 3.87E-10 2.92E-10 1.322787 0.1895

TA 1.65E-10 4.08E-10 0.403648 0.6875

DEBT -1.40E-10 4.68E-10 -0.299364 0.7654

CA -1.27E-10 1.47E-10 -0.859775 0.3924

LOG(CL) -8.89E-05 9.89E-05 -0.898987 0.3712

INVENTORY 3.99E-11 1.24E-10 0.322338 0.7480

CAPITAL -1.55E-10 4.00E-10 -0.386778 0.6999

QUICKRATIO -2.61E-05 5.67E-05 -0.460559 0.6463



BSIZE -0.000109 6.83E-05 -1.600425 0.1133




Sum squared resid 4.38E-05 Schwarz criterion -11.25783




Where: NI: Net Income, TA: Total Assets, DEBT: total debts, CA: Current Assets,

LOG(CL): Current Liabilities, INVENTORY: Inventory, CAPITAL: Capital,

QUICKRATIO: Quick ratio, BSIZE: board size of BOM.

Hypothesis: H0: no heteroskedasticity(Var(µi) = σ2)

H1: heteroskedasticity exists (Var(µi) = σi2)

Critical value: level of significance: α = 5%, n = 32, df = 12 ->

Test statistic: W = n * R2 = 32 * 0.126907 = 4.041024

Conclusion, since W = 4.041024< , do not reject H0 at α = 5%

Do not reject the hypothesis that there is no autocorrelation exists in this model.

Therefore, there is insufficient statistical evidence to infer at 5% level of significance that

the heteroskedasticity exists in the model.

1.11. Findings and Discussion

The table below summarizes the results of regression models based on the benchmark of R-

squared:

Table 11: Summarizing the results of regression models

Dependent

variable

R - squared Adjusted R -

squared

No of variables



Equation 1 ROA 0.491713 0.393966 15 ROA

Equation 2 ROE 0.657302 0.591399 15 ROE max

Equation 3 ROA 0.440292 0.394734 7 ROA min

Equation 4 ROA 0.494728 0.447173 9 ROA

Equation 5 ROE 0.604299 0.567057 9 ROE

Equation 6 ROE 0.628345 0.598094 7 ROE

The first thing is found out is that models on ROE are better resultto ROA’s.

The model 6 is the best regression model because it has the highest adjusted R-squared in

addition to the least number of variables.

Based on the criteria of highest adjusted R-squared model and least quantity of variables in the

model, the equation is recalled for evaluation as Equation 6:

ROE = 0.002397 + 3.87E-10NI + 1.65E-10TA - 1.40E-10DEBT-1.27E-10CA -8.89E-05

LOG(CL)+ 3.99E-11INVENTORY - 1.55E-10CAPITAL - 2.61E-05QUICKRATIO -

0.000109BSIZE

To summarize, the test points out these most important ideas:

Performance of public real estate firms in Vietnam is not clearly affected by

corporate governance whichrepresented by 3 variables such as the number of

people in the board of management, the number of people in the board of

directors, the number of coincident persons between BOM and BOD.

The influencing factors to public real estate firms’ performance are Net Income,

Total Assets, Debt, Current Assets, Quick ratio and Capital.

In which: Net Income, Total Assets, and Quick ratio have positive relationship

with firms' performance. Debt, Current Assets, and Capital negatively influence

firms' performance.

Discussion in detail:

Summary to coefficient of controlling variables



Table 12: Summary to coefficient of controlling variables

Coefficient of BSIZE Coefficient of EXESIZE Coefficient of

COINCIDENT

Equation 1 -0.002922 0.000113 0.000682

Equation 2 -0.003830 -0.000932 0.002662

Equation 3 -0.002289 // //

Equation 4 -0.003872 // //

Equation 5 -0.013323 // //

Equation 6 -0.004726 // //

The number of people in board of management unexpectedly takes negative affect to

firms’ performance regardless of ROA or ROE. There are a number reasons explaining

why large board size will lead to better performance of banks. However, the results in

models above are in contrary to normal convention. The smaller BOM, the better

performance. It can be explained that larger board size is to gather the probability of

power concentration into the hand of small group of directors who have the advantages in

skills and expertises.

There are also several researches that imply a contradictory result. For instance,

Praptiningsih (2009) found an insignificant impact of board size on bank performance in

several countries in Asia. In addition a negative relationship between corporate

governance was found in the research of Bellthir (2008). The lack of ultimate conclusion

on the impact of board size on performance of real estate firms may be explained by the

fact that there is no "one size fit all"in corporate governance field. In other words,

performance benchmark for the sector of real estate is not tremendously affected by the

size of the board, depending on other feature of each firm.

Number of coincident persons between BOD and BOM unexpectedly take positive

advantage to firms' performance. We often anticipate that when separation of duty exists,

firm would operate effectively and efficiently in objective way. However, the situation

seems to be contradicting in Vietnam. Only when people invest their money into

company, and run their firms at the same time could they are responsible for their



investment. Especially, the more coincidence happens, the less agentproblem occurs.

There is no need for fear of interest difference between two parties — management and

executive board.

In general, in this research the influences of these corporate governance proxies on performance

of Vietnamese public real estate firms are only observed in a short period of two years along with

the occurrence of the gloomyglobal economy. Therefore, there may a change in the result when

the time series is expanded to more than 10 years.



5. CONCLUSION

1.12. Conclusion

The finding obtained from the analysis of dependent and independent variables shows that the

performance of public Vietnamese real estate firms generated from 2013 to 2014 was statistical

explained by other factors rather than corporate governance and there was a significant spread in

ability of producing ROE among firms.

In terms of independent variables, majority of firms had medium size of board with 5 members

on average. Also, the medium size of directors of most firms was 3 on average. While the

coincident between two boards is 2 persons, relatively high compared to the total number of

BOD.

1.13. Limitations

The research is more valuable if I could surmount a couple of difficulties listed below:

Firstly, due to time limitation and complexity of corporate governance issue, it is hard for me to

cover all dimensions of real estate corporate governance system. This research is only able to

consider some certain aspects of the selected proxies. For example, regarding to the board of

management and board of directors, only the size of these proxies is taken into account and

tested, while there are some other aspect of these proxies can affect the company performance

such as the quality of the BOM and BOD.Thus other aspects such as transparency in information,

assurance in equitable shareholders' rights and problems when governing corporations are

anticipated to be assessed and discussed in further research.

Further, due to a fairly short period of time between 2013 and 2014, in this research, BSIZE and

EXESIZE show a negative relationship with firm performance.

In terms of Foreign Ownership ratio, the study did not present and test it because the period of

two years is not adequate to see clearly the impact of the presence of foreign ownership in

shareholding structure. Also, the other areas distributed by foreign ownership should be taken

into consideration rather than only focusing on capital distribution.

Recommendation Page 45


Secondly, this study only concentrates on financially healthy real estate firms, not on inefficient

operating firms, evidencing by taking data from positive value of ROA, positive value of ROE

firms only. Currently, the aim of this thesis is learning the lesson from successful firms, so the

bad performance firms are not the subject to be tested. Sample size is simply represented for

financially healthy part, not the real estate sector as a whole.

Thirdly, due to time restriction, sample size in regression model is not large enough. As a result,

researcher would find it less accuracy to use only the sign of each independent variable's

coefficient to generalize the relationship with dependent variable.

Lastly, resulting from data restriction, data for market share is inaccessible.

These are some main obstacles that exist in my thesis, making it become less accurate and

helpful. Therefore, in further study, researcher strongly suggests to have a better model, analysis

methodology as well as data source in this particular knowledge.

1.14. Recommendation

In my model, there are six significant factors that contributing to the real estate firms'

performance: Net income, Total Assets, Debt, Capital, Current Asset and Quick ratio. To

improve the efficiency and effectiveness of company, the responsibility of managers is

significant. Of the potential ones, the following will be recommended in my research.

The first thing a firm should focus on is its efficiency in employing its debts to finance for its

activities. The high leverage ratio and having negative relationship with firms' performance

means that firms focus too much on utilizing debt to supply their operations, which can lead to

low return on asset (ROA) and low return on equity (ROE).

Along with this, a ratio firms need to take into account if they want to enhance their governance's

performance is the number of coincident persons between BOM and BOD. Its low negative

coefficient indicates that firms in Vietnam would be better if they are set up and directly run by

shareholders, who contribute their funds and operate their business with entire their efforts.



Furthermore, the model suggests that Capital has negative relationship, while total assets have a

contradictory link with ROA and ROE. Firms that have tremendous total asset and small capital

will have the capability of earning more money on less investment amount. However, firms'

capital should be strong enough to become a cushion in (high productivity, urgent and difficult

case.


65[CORPORATE GOVERNANCE IN PUBLIC REAL

ESTATE FIRMS IN VIETNAM] Kieu Van Anh – MFBA6

APPENDIX 1: LIST OF REAL ESTATE FIRMS LISTED IN VN

NoStock code Name

Index membership

1 VIC VinGroup Joint Stock Company HOSTC2 HAG HAGL Joint Stock Company HOSTC3 REE Refrigeration Electrical Engineering Corporation HOSTC4 KBC KinhBac City Developement Share Holding Corporation HOSTC5 ITA Tan Tao Investment Industry Corporation HOSTC6 IJC Becamex Infrastructure Development Joint Stock Company HOSTC7 PDR PhatDat Real Estate Development Corporation HOSTC

8 SJSSong Da Urban & Industrial Zone Investment and Development Joint Stock Company HOSTC

9 DIG Development Investment Construction Joint Stock Company HOSTC10 HDG Ha Do Joint Stock Company HOSTC11 BCI BinhChanh Construction Investment Shareholding Company HOSTC12 NBB NBB Investment Joint Stock Company HOSTC13 DLG Duc Long Gia Lai Group Joint Stock Company HOSTC

14 DXGDatXanh Real Estate Service And Construcstions Corporation HOSTC

15 SCR SaiGonThuong Tin Real Estate Joint Stock Company HNX

16 HQCHoang Quan Consulting – Trading – Service Real Estate Corporation HOSTC

17 QCG Quoc CuongGia Lai Joint Stock Company HOSTC18 ASM SAO MAI GROUP CORPORATION HOSTC19 OGC Ocean Group.,JSC HOSTC20 NTL TuLiem Urban Development Joint Stock Company HOSTC21 TDH Thu Duc Housing Development Corporation HOSTC22 TIX Tan Binh Import - Export Joint Stock Corporation HOSTC23 API Asia - Pacific Investment Joint Stock Company HNX24 SC5 Construction Joint Stock Company No 5 HOSTC

25 HDCBa Ria – Vung Tau House Development Joint Stock Company HOSTC

26 SZL Sonadezi Long Thanh Joint Stock Company HOSTC27 IDI International Development & Investment Corporation HOSTC28 D2D Industrial Urban Development Joint Stock Company No. 2 HOSTC29 VPH Van Phat Hung Corporation. HOSTC30 NVT Ninh Van Bay Travel Real Estate Joint Stock Company HOSTC31 LHG Long Hau Corporation HOSTC32 IDV VinhPhuc Infrastructure Development Joint Stock Company HNX



33 SDUSong Da Urban Investment Construction And Development Joint Stock Company HNX

34 TIG Thang Long Investment Group Joint Stock Company HNX35 KAC Khang An Investment Real Estate Joint Stock Company HOSTC

36 PPIPacific Property And Infrastructure Developement Joint Stock Company HOSTC

37 NDNDanang Housing Investment and Development Joint Stock Company HNX

38 CLGCotec Investment And Land-House Development Joint Stock Company HOSTC

39 UICIDICO Urban and House Development Joint Stock Company HOSTC

40 UDC Urban Development and Construction Corporation HOSTC41 RCL ChoLon Real Estate Joint Stock Company HNX42 TKC Tanky Construction Real Estate Trading Corporation HNX

43 VRCVung Tau Real Estate and Construction Joint Stock Company HOSTC

44 DRH Dream House Investment Corporation HOSTC

45 NHAHa Noi South Housing And Urban Development Corporation HNX

46 CCLCuu Long Petro Urban Development And Investment Corporation HOSTC

47 D11 Real Estate 11 Joint Stock Company HNX



APPENDIX 2: DATABASE USED FOR RUNNING EVIEWS

NO YEAR NAME NI TA EQUITY DEBT CA CL1 2014 VIC 3,158,583 90,485,307 20,396,041 63,200,674 34,875,608 24,603,8012 2013 VIC 6,779,512 75,772,648 14,471,837 57,156,106 39,844,678 26,675,2653 2014 HAG 1,474,256 36,368,864 14,237,728 20,978,624 10,112,493 9,257,2024 2013 HAG 846,073 29,813,179 12,852,649 16,293,243 9,740,545 4,959,2715 2014 REE 1,061,972 8,403,186 5,910,154 2,064,936 2,966,586 1,551,0936 2013 REE 975,819 6,954,450 5,196,623 1,753,251 2,561,941 1,420,5077 2014 KBC 325,617 13,048,822 5,376,098 6,792,341 10,649,033 3,302,9508 2013 KBC 72,499 12,532,339 4,050,480 7,617,564 9,989,721 6,520,8559 2014 ITA 144,363 11,996,725 7,937,954 4,009,197 6,735,871 2,488,27310 2013 ITA 87,230 10,760,315 7,133,591 3,606,513 5,854,561 2,152,23111 2014 IJC 230,445 6,730,499 3,066,255 3,664,244 4,994,309 2,374,83412 2013 IJC 161,533 4,807,856 3,007,699 1,800,157 3,023,628 1,206,18213 2014 PDR 41,642 6,052,986 1,468,294 4,584,692 5,705,424 1,126,77714 2013 PDR 2,342 5,657,966 1,427,534 4,230,432 5,362,887 676,21615 2014 SJS 156,395 5,419,827 1,752,006 3,653,906 4,868,895 3,321,42716 2013 SJS 70,127 5,607,236 1,595,831 3,978,413 4,856,366 3,259,45617 2014 DIG 43,921 5,034,820 2,410,858 2,576,685 3,560,284 1,065,41518 2013 DIG 53,333 4,634,308 2,372,406 2,216,475 3,139,079 1,516,65919 2014 HDG 148,275 2,293,764 857,650 1,242,449 1,715,675 1,236,66620 2013 HDG 122,776 2,327,799 750,176 1,479,149 1,847,445 1,476,42821 2014 BCI 97,241 3,237,056 1,770,888 1,466,169 2,463,589 524,59222 2013 BCI 95,671 3,439,644 1,753,488 1,600,176 2,638,893 746,33323 2014 NBB 35,514 3,138,727 1,576,950 1,551,746 2,758,260 709,78424 2013 NBB 25,256 3,084,056 1,309,792 1,764,824 2,629,853 1,018,76725 2014 DLG 52,796 4,111,652 1,558,654 2,444,547 1,901,481 648,15326 2013 DLG 2,131 2,420,313 808,481 1,508,807 1,218,447 461,04627 2014 DXG 167,834 2,160,453 1,002,760 1,088,225 1,678,871 965,36328 2013 DXG 82,764 1,268,215 633,133 604,600 934,032 531,22629 2014 SCR 26,540 5,404,229 2,284,128 3,087,476 4,014,917 1,554,05230 2013 SCR 7,960 5,586,857 2,260,530 3,317,192 4,139,898 1,755,70131 2014 HQC 30,118 4,056,044 1,786,020 2,270,025 2,731,120 1,384,00532 2013 HQC 23,013 3,140,079 955,902 2,184,178 2,116,099 1,539,15533 2014 QCG 32,858 6,885,285 3,795,224 2,951,448 5,293,144 783,19334 2013 QCG 14,784 6,360,750 2,309,529 3,856,908 4,686,058 1,894,08235 2014 ASM 89,151 2,481,244 1,267,206 1,203,535 1,953,211 778,82636 2013 ASM 25,479 1,673,512 702,896 969,098 1,069,348 566,208



37 2014 OQC 404,392 11,944,409 3,491,886 7,445,022 5,412,662 4,773,307NO YEAR NAME NI TA EQUITY DEBT CA CL38 2013 OQC 55,381 11,424,464 3,205,935 7,373,886 6,096,048 3,502,43639 2014 NTL 36,675 1,367,020 850,384 505,273 1,293,695 474,62440 2013 NTL 91,875 1,323,357 850,387 455,331 1,233,750 424,03241 2014 TDH 51,055 2,439,213 1,405,343 924,771 1,188,570 532,37642 2013 TDH 21,677 2,259,697 1,361,151 810,716 993,984 485,67443 2014 TIX 67,731 1,021,635 584,624 436,811 543,177 187,40044 2013 TIX 60,971 964,026 563,709 400,117 489,550 98,08345 2014 API 1,030 574,238 278,888 295,330 195,685 246,18846 2013 API 45,947 505,360 277,858 227,492 161,025 179,34947 2014 SC5 33,354 2,190,244 333,598 1,856,646 1,767,245 1,446,15148 2013 SC5 53,722 2,099,450 332,898 1,766,552 1,513,999 1,374,31949 2014 HDC 22,689 1,207,709 592,807 597,923 1,050,590 433,83950 2013 HDC 26,090 1,271,924 561,725 694,014 1,108,831 511,51051 2014 SZL 43,403 1,234,439 460,518 773,920 495,651 79,99852 2013 SZL 39,433 1,143,268 470,577 672,691 401,909 77,56253 2014 IDI 90,419 1,950,652 627,893 1,322,759 1,159,976 1,216,23754 2013 IDI 41,099 1,845,614 577,507 1,268,107 1,063,980 1,200,86955 2014 D2D 57,299 1,114,028 360,005 723,914 765,528 291,29856 2013 D2D 44,749 1,112,361 333,106 747,389 860,317 418,60457 2014 VPH 2,944 1,712,821 487,559 1,225,262 1,658,119 866,49758 2013 VPH 6,276 1,791,406 484,615 1,245,027 1,709,620 1,155,22559 2014 NVT 5,612 1,434,704 845,395 435,044 457,851 125,98960 2013 NVT 20,614 1,390,408 839,784 391,324 344,383 265,23561 2014 LHG 25,170 1,475,559 638,868 836,691 803,573 447,18162 2013 LHG 24,191 1,648,494 643,367 1,005,127 823,654 500,98163 2014 IDV 50,454 442,091 90,589 351,502 299,963 32,33364 2013 IDV 27,324 339,495 63,537 275,958 161,831 11,50465 2014 SDU 2,698 983,909 334,723 649,185 520,565 644,44466 2013 SDU 1,588 799,571 332,025 467,546 277,700 441,47967 2014 TIG 29,520 512,154 300,571 141,665 295,577 52,70268 2013 TIG 7,911 279,931 170,581 53,801 89,807 37,30069 2014 KAC 1,343 426,612 248,314 178,298 359,106 70,21170 2013 KAC 1,818 383,353 246,971 136,382 311,664 83,98271 2014 PPI 22,917 885,198 336,907 548,291 861,923 476,74772 2013 PPI 107 777,368 266,325 511,043 751,322 448,11473 2014 NDN 51,018 479,857 228,941 248,666 278,761 155,32774 2013 NDN 19,171 509,250 142,783 366,467 412,199 188,89875 2014 CLG 13,203 1,600,716 254,280 1,202,868 645,530 818,666



NO YEAR NAME NI TA EQUITY DEBT CA CL76 2013 CLG 29,407 1,131,132 237,121 842,701 685,719 571,60977 2014 UIC 27,004 397,461 181,772 215,689 255,652 215,56178 2013 UIC 26,080 423,897 171,963 251,933 271,649 236,80679 2014 UDC 1,546 1,658,374 365,378 1,258,182 1,144,136 842,25980 2013 UDC 204 1,807,913 367,968 1,338,307 1,154,681 936,49481 2014 RCL 21,484 292,678 178,081 114,597 229,159 70,64282 2013 RCL 19,589 314,557 168,583 145,974 239,927 106,85383 2014 TKC 3,229 318,408 128,495 189,913 231,298 182,73884 2013 TKC 2,365 349,288 127,860 221,428 281,057 219,40885 2014 VRC 772 342,998 177,962 162,787 280,775 128,96786 2013 VRC 663 330,457 173,424 152,684 255,726 108,85587 2014 DRH 11,249 300,362 202,771 97,591 77,439 97,49088 2013 DRH 2,204 292,215 178,190 114,025 56,332 113,92489 2014 NHA 5,504 122,118 97,316 24,802 24,940 24,80290 2013 NHA 402 118,710 91,812 26,898 26,534 26,89891 2014 CCL 2,193 551,210 277,427 273,784 480,515 138,27792 2013 CCL 2,124 531,735 275,453 256,282 450,065 134,82493 2014 D11 1,366 161,321 81,584 79,737 156,374 78,75794 2013 D11 1,208 171,527 87,124 84,402 165,740 83,413



APPENDIX 2: CONTINUING

NO YEAR NAME INVENTORY ROA ROE CAPITAL DebtAssets EquityAsset1 2014 VIC 16,598,351 0.0349 0.1549 20,396,041 0.6985 0.22542 2013 VIC 18,913,717 0.0895 0.4685 14,471,837 0.7543 0.19103 2014 HAG 2,084,906 0.0405 0.1035 14,237,728 0.5768 0.39154 2013 HAG 1,838,006 0.0284 0.0658 12,852,649 0.5465 0.43115 2014 REE 1,238,029 0.1264 0.1797 5,910,154 0.2457 0.70336 2013 REE 869,187 0.1403 0.1878 5,196,623 0.2521 0.74727 2014 KBC 7,616,350 0.0250 0.0606 5,376,098 0.5205 0.41208 2013 KBC 7,473,006 0.0058 0.0179 4,050,480 0.6078 0.32329 2014 ITA 4,303,915 0.0120 0.0182 7,937,954 0.3342 0.661710 2013 ITA 3,361,871 0.0081 0.0122 7,133,591 0.3352 0.663011 2014 IJC 3,944,541 0.0342 0.0752 3,066,255 0.5444 0.455612 2013 IJC 2,606,302 0.0336 0.0537 3,007,699 0.3744 0.625613 2014 PDR 5,413,250 0.0069 0.0284 1,468,294 0.7574 0.242614 2013 PDR 5,164,363 0.0004 0.0016 1,427,534 0.7477 0.252315 2014 SJS 4,364,150 0.0289 0.0893 1,752,006 0.6742 0.323316 2013 SJS 4,377,080 0.0125 0.0439 1,595,831 0.7095 0.284617 2014 DIG 2,114,386 0.0087 0.0182 2,410,858 0.5118 0.478818 2013 DIG 1,970,922 0.0115 0.0225 2,372,406 0.4783 0.511919 2014 HDG 889,048 0.0646 0.1729 857,650 0.5417 0.373920 2013 HDG 1,121,823 0.0527 0.1637 750,176 0.6354 0.322321 2014 BCI 2,119,942 0.0300 0.0549 1,770,888 0.4529 0.547122 2013 BCI 2,147,175 0.0278 0.0546 1,753,488 0.4652 0.509823 2014 NBB 2,416,420 0.0113 0.0225 1,576,950 0.4944 0.502424 2013 NBB 2,304,756 0.0082 0.0193 1,309,792 0.5722 0.424725 2014 DLG 381,765 0.0128 0.0339 1,558,654 0.5945 0.379126 2013 DLG 333,644 0.0009 0.0026 808,481 0.6234 0.334027 2014 DXG 499,214 0.0777 0.1674 1,002,760 0.5037 0.464128 2013 DXG 432,787 0.0653 0.1307 633,133 0.4767 0.499229 2014 SCR 1,011,910 0.0049 0.0116 2,284,128 0.5713 0.422730 2013 SCR 860,950 0.0014 0.0035 2,260,530 0.5937 0.404631 2014 HQC 788,927 0.0074 0.0169 1,786,020 0.5597 0.440332 2013 HQC 611,294 0.0073 0.0241 955,902 0.6956 0.304433 2014 QCG 4,120,109 0.0048 0.0087 3,795,224 0.4287 0.551234 2013 QCG 4,073,536 0.0023 0.0064 2,309,529 0.6064 0.363135 2014 ASM 861,193 0.0359 0.0704 1,267,206 0.4851 0.510736 2013 ASM 502,828 0.0152 0.0362 702,896 0.5791 0.4200



37 2014 OQC 265,946 0.0339 0.1158 3,491,886 0.6233 0.2923NO YEAR NAME INVENTORY ROA ROE CAPITAL DebtAssets EquityAsset38 2013 OQC 404,034 0.0048 0.0173 3,205,935 0.6454 0.280639 2014 NTL 1,055,517 0.0268 0.0431 850,384 0.3696 0.622140 2013 NTL 963,248 0.0694 0.1080 850,387 0.3441 0.642641 2014 TDH 674,551 0.0209 0.0363 1,405,343 0.3791 0.576142 2013 TDH 448,443 0.0096 0.0159 1,361,151 0.3588 0.602443 2014 TIX 167,297 0.0663 0.1159 584,624 0.4276 0.572244 2013 TIX 205,040 0.0632 0.1082 563,709 0.4150 0.584745 2014 API 13,811 0.0018 0.0037 278,888 0.5143 0.485746 2013 API 10,182 0.0909 0.1654 277,858 0.4502 0.549847 2014 SC5 1,011,910 0.0152 0.1000 333,598 0.8477 0.152348 2013 SC5 860,950 0.0256 0.1614 332,898 0.8414 0.158649 2014 HDC 871,736 0.0188 0.0383 592,807 0.4951 0.490950 2013 HDC 940,491 0.0205 0.0464 561,725 0.5456 0.441651 2014 SZL 81,607 0.0352 0.0942 460,518 0.6269 0.373152 2013 SZL 85,159 0.0345 0.0838 470,577 0.5884 0.411653 2014 IDI 522,604 0.0464 0.1440 627,893 0.6781 0.321954 2013 IDI 222,401 0.0223 0.0712 577,507 0.6871 0.312955 2014 D2D 396,940 0.0514 0.1592 360,005 0.6498 0.323256 2013 D2D 477,758 0.0402 0.1343 333,106 0.6719 0.299557 2014 VPH 1,493,844 0.0017 0.0060 487,559 0.7153 0.284758 2013 VPH 1,474,407 0.0035 0.0130 484,615 0.6950 0.270559 2014 NVT 41,866 0.0039 0.0066 845,395 0.3032 0.589260 2013 NVT 40,624 0.0148 0.0245 839,784 0.2814 0.604061 2014 LHG 272,148 0.0171 0.0394 638,868 0.5670 0.433062 2013 LHG 320,623 0.0147 0.0376 643,367 0.6097 0.390363 2014 IDV 63,902 0.1141 0.5570 90,589 0.7951 0.204964 2013 IDV 14,216 0.0805 0.4300 63,537 0.8128 0.187265 2014 SDU 330,322 0.0027 0.0081 334,723 0.6598 0.340266 2013 SDU 165,179 0.0020 0.0048 332,025 0.5847 0.415367 2014 TIG 49,120 0.0576 0.0982 300,571 0.2766 0.586968 2013 TIG 6,994 0.0283 0.0464 170,581 0.1922 0.609469 2014 KAC 315,061 0.0031 0.0054 248,314 0.4179 0.582170 2013 KAC 281,722 0.0047 0.0074 246,971 0.3558 0.644271 2014 PPI 381,120 0.0259 0.0680 336,907 0.6194 0.380672 2013 PPI 471,489 0.0001 0.0004 266,325 0.6574 0.342673 2014 NDN 181,303 0.1063 0.2228 228,941 0.5182 0.477174 2013 NDN 326,445 0.0376 0.1343 142,783 0.7196 0.280475 2014 CLG 87,651 0.0082 0.0519 254,280 0.7515 0.1589



NO YEAR NAME INVENTORY ROA ROE CAPITAL DebtAssets EquityAsset76 2013 CLG 79,012 0.0260 0.1240 237,121 0.7450 0.209677 2014 UIC 133,344 0.0679 0.1486 181,772 0.5427 0.457378 2013 UIC 127,786 0.0615 0.1517 171,963 0.5943 0.405779 2014 UDC 718,111 0.0009 0.0042 365,378 0.7587 0.220380 2013 UDC 700,531 0.0001 0.0006 367,968 0.7402 0.203581 2014 RCL 124,505 0.0734 0.1206 178,081 0.3915 0.608582 2013 RCL 170,396 0.0623 0.1162 168,583 0.4641 0.535983 2014 TKC 73,514 0.0101 0.0251 128,495 0.5964 0.403684 2013 TKC 150,417 0.0068 0.0185 127,860 0.6339 0.366185 2014 VRC 240,872 0.0023 0.0043 177,962 0.4746 0.518886 2013 VRC 244,520 0.0020 0.0038 173,424 0.4620 0.524887 2014 DRH - 0.0375 0.0555 202,771 0.3249 0.675188 2013 DRH - 0.0075 0.0124 178,190 0.3902 0.609889 2014 NHA 5,703 0.0451 0.0566 97,316 0.2031 0.796990 2013 NHA 5,610 0.0034 0.0044 91,812 0.2266 0.773491 2014 CCL 420,658 0.0040 0.0079 277,427 0.4967 0.503392 2013 CCL 394,468 0.0040 0.0077 275,453 0.4820 0.518093 2014 D11 6,504 0.0085 0.0167 81,584 0.4943 0.505794 2013 D11 1,072 0.0070 0.0139 87,124 0.4921 0.5079




NO YEAR NAMEDEBTEQUITY

QUICKRATIO

LIQUIDRATIO BSIZE EXESIZE COINCIDENT

1 2014 VIC 3.09867 0.7429 1.417488623 11 7 32 2013 VIC 3.94947 0.7847 1.493693802 11 6 33 2014 HAG 1.47345 0.8672 1.092391956 8 5 34 2013 HAG 1.2677 1.5935 1.964108233 7 5 35 2014 REE 0.34939 1.1144 1.912577776 5 3 16 2013 REE 0.33738 1.1917 1.803539863 5 3 27 2014 KBC 1.26343 0.9182 3.224097549 5 5 28 2013 KBC 1.88066 0.3859 1.531964903 5 4 19 2014 ITA 0.50507 0.9774 2.707046614 5 3 210 2013 ITA 0.50557 1.1582 2.720228916 5 3 211 2014 IJC 1.19502 0.4420 2.103013937 7 5 112 2013 IJC 0.59852 0.3460 2.506775926 5 3 113 2014 PDR 3.12246 0.2593 5.063489936 6 2 114 2013 PDR 2.96345 0.2936 7.930730713 6 3 315 2014 SJS 2.08556 0.1520 1.465904565 5 5 116 2013 SJS 2.493 0.1470 1.489931449 5 5 117 2014 DIG 1.06878 1.3571 3.341687511 5 4 218 2013 DIG 0.93427 0.7702 2.06973288 6 6 419 2014 HDG 1.44867 0.6684 1.387339023 8 4 320 2013 HDG 1.97174 0.4915 1.251293663 7 4 421 2014 BCI 0.82793 0.6551 4.696200095 7 3 122 2013 BCI 0.91257 0.6588 3.535811762 7 3 123 2014 NBB 0.98402 0.4816 3.886055476 7 7 224 2013 NBB 1.34741 0.3191 2.581407721 6 6 125 2014 DLG 1.56837 2.3447 2.933691582 8 6 226 2013 DLG 1.86622 1.9191 2.642788355 5 6 227 2014 DXG 1.08523 1.2220 1.739108501 5 3 228 2013 DXG 0.95493 0.9436 1.758257314 5 4 229 2014 SCR 1.35171 1.9324 2.583515223 6 5 030 2013 SCR 1.46744 1.8676 2.357974393 6 5 031 2014 HQC 1.271 1.4033 1.973345472 7 9 632 2013 HQC 2.28494 0.9777 1.374844639 7 5 433 2014 QCG 0.77767 1.4978 6.758415869 5 3 334 2013 QCG 1.67 0.3234 2.474052338 5 3 335 2014 ASM 0.94975 1.4021 2.507891365 6 9 4



36 2013 ASM 1.37872 1.0006 1.888613372 6 8 4


QUICKRATIO


37 2014 OQC 2.13209 1.0782 1.133943826 5 4 138 2013 OQC 2.30007 1.6252 1.7405166 5 2 139 2014 NTL 0.59417 0.5018 2.725726048 5 5 240 2013 NTL 0.53544 0.6379 2.909568146 5 5 241 2014 TDH 0.65804 0.9655 2.232576224 5 6 342 2013 TDH 0.59561 1.1233 2.046607395 5 6 343 2014 TIX 0.74717 2.0058 2.898489861 5 2 144 2013 TIX 0.70979 2.9007 4.991180939 5 4 345 2014 API 1.05896 0.7388 0.794860026 7 2 246 2013 API 0.81873 0.8411 0.897830487 5 1 147 2014 SC5 5.56552 0.5223 1.222033522 5 4 348 2013 SC5 5.30659 0.4752 1.101635792 5 4 349 2014 HDC 1.00863 0.4123 2.421612626 8 2 250 2013 HDC 1.2355 0.3291 2.167760161 8 2 251 2014 SZL 1.68054 5.1757 6.195792395 7 3 352 2013 SZL 1.4295 4.0838 5.181777159 7 3 353 2014 IDI 2.10666 0.5241 0.953741746 8 4 254 2013 IDI 2.19583 0.7008 0.886008382 8 4 255 2014 D2D 2.01084 1.2653 2.627989207 5 2 256 2013 D2D 2.2437 0.9139 2.055204919 5 3 257 2014 VPH 2.51305 0.1896 1.913588853 5 2 258 2013 VPH 2.56911 0.2036 1.479902184 5 2 259 2014 NVT 0.5146 3.3018 3.634055354 10 2 260 2013 NVT 0.46598 1.1452 1.298407073 9 2 261 2014 LHG 1.30965 1.1884 1.796974827 5 3 262 2013 LHG 1.56229 1.0041 1.644082311 5 2 263 2014 IDV 3.88018 7.3009 9.277301828 5 2 264 2013 IDV 4.34326 12.8316 14.06736787 5 3 165 2014 SDU 1.93947 0.2952 0.807773833 5 3 266 2013 SDU 1.40817 0.2549 0.629021992 5 3 267 2014 TIG 0.47132 4.6764 5.608458882 5 4 268 2013 TIG 0.3154 2.2202 2.40769437 5 3 269 2014 KAC 0.71803 0.6273 5.114668642 5 4 270 2013 KAC 0.55222 0.3565 3.711080946 7 2 271 2014 PPI 1.62743 1.0085 1.807925378 5 6 372 2013 PPI 1.91887 0.6245 1.676631393 5 6 373 2014 NDN 1.08616 0.6274 1.794671886 5 4 3



74 2013 NDN 2.5666 0.4540 2.182124745 5 4 3


QUICKRATIO


75 2014 CLG 4.73049 0.6814 0.788514486 5 5 176 2013 CLG 3.55389 1.0614 1.199629467 5 7 177 2014 UIC 1.18659 0.5674 1.185984478 5 5 278 2013 UIC 1.46504 0.6075 1.147137319 5 5 279 2014 UDC 3.44351 0.5058 1.358413505 5 3 280 2013 UDC 3.63702 0.4849 1.232982806 5 3 281 2014 RCL 0.64351 1.4815 3.243948359 5 3 382 2013 RCL 0.86589 0.6507 2.245393204 5 3 383 2014 TKC 1.47798 0.8634 1.265735643 5 3 284 2013 TKC 1.7318 0.5954 1.280978816 5 3 285 2014 VRC 0.91473 0.3094 2.177107322 5 2 186 2013 VRC 0.88041 0.1029 2.349235221 5 1 187 2014 DRH 0.48129 0.7943 0.794327623 7 5 188 2013 DRH 0.63991 0.4945 0.494469998 7 5 189 2014 NHA 0.25486 0.7756 1.005564067 5 2 290 2013 NHA 0.29297 0.7779 0.986467395 5 2 291 2014 CCL 0.98687 0.4329 3.475017537 5 3 292 2013 CCL 0.9304 0.4124 3.338166795 5 3 293 2014 D11 0.97736 1.9029 1.985525096 5 3 294 2013 D11 0.96876 1.9741 1.986980447 5 3 2



APPENDIX 3: CORRELATION BETWEEN INDEPENDENT VARIABLES

NI TA EQUITY DEBT CA CL INVENTORYNI 1.000000 0.874806 0.742279 0.895048 0.894987 0.914760 0.794033TA 0.874806 1.000000 0.924038 0.992038 0.965725 0.975063 0.859764

EQUITY 0.742279 0.924038 1.000000 0.869319 0.865705 0.849763 0.753323DEBT 0.895048 0.992038 0.869319 1.000000 0.968801 0.985300 0.868426

CA 0.894987 0.965725 0.865705 0.968801 1.000000 0.976775 0.946213CL 0.914760 0.975063 0.849763 0.985300 0.976775 1.000000 0.886967

INVENTORY 0.794033 0.859764 0.753323 0.868426 0.946213 0.886967 1.000000ROA 0.303762 0.124871 0.136059 0.116198 0.093179 0.128686 0.035262ROE 0.469552 0.294683 0.198620 0.318937 0.296125 0.337345 0.230405

CAPITAL 0.742279 0.924038 1.000000 0.869319 0.865705 0.849763 0.753323

DEBTASSETS 0.126924 0.170816 0.023219 0.218651 0.209492 0.233240 0.210660

EQUITYASSET -0.17149 -0.22657 -0.06941 -0.27409 -0.26331 -0.29184 -0.251348

DEBTEQUITY 0.215001 0.220341 0.064298 0.267999 0.253181 0.285434 0.246165

QUICKRATIO -0.04237 -0.06655 -0.07046 -0.06429 -0.09809 -0.09493 -0.157014

LIQUIDRATIO -0.0989 -0.09683 -0.0854 -0.09631 -0.06458 -0.14724 0.008069BSIZE 0.529972 0.558728 0.466233 0.572301 0.524678 0.549735 0.445137

EXESIZE 0.213538 0.273789 0.254749 0.272609 0.278089 0.281831 0.236898

COINCIDENT 0.127423 0.133893 0.115139 0.137619 0.099002 0.113121 0.061890



APPENDIX 3: CONTINNNUING

ROA ROE CAPITAL DEBTASSETS EQUITYASSET DEBTEQUITYNI 0.303762 0.469552 0.742279 0.126924 -0.171491 0.215001TA 0.124871 0.294683 0.924038 0.170816 -0.226572 0.220341

EQUITY 0.136059 0.198620 1.000000 0.023219 -0.06941 0.064298DEBT 0.116198 0.318937 0.869319 0.218651 -0.274094 0.267999

CA 0.093179 0.296125 0.865705 0.209492 -0.263306 0.253181CL 0.128686 0.337345 0.849763 0.233240 -0.291835 0.285434

INVENTORY 0.035262 0.230405 0.753323 0.210660 -0.251348 0.246165ROA 1.000000 0.803921 0.136059 -0.15465 0.151073 -0.053101ROE 0.803921 1.000000 0.198620 0.253383 -0.264843 0.368769

CAPITAL 0.136059 0.198620 1.000000 0.023219 -0.06941 0.064298

DEBTASSETS -0.15465 0.253383 0.023219 1.000000 -0.973646 0.887436

EQUITYASSET 0.151073 -0.26484 -0.06941 -0.973646 1.000000 -0.904486

DEBTEQUITY -0.0531 0.368769 0.064298 0.887436 -0.904486 1.000000

QUICKRATIO 0.309829 0.519889 -0.070457 0.081925 -0.103495 0.161902

LIQUIDRATIO 0.157878 0.345609 -0.085404 0.064793 -0.048347 0.098324BSIZE -0.01013 0.127533 0.466233 0.039513 -0.086906 0.025646

EXESIZE -0.05301 0.005913 0.254749 0.148446 -0.152728 0.091105

COINCIDENT 0.026630 0.054182 0.115139 0.078669 -0.067512 0.036914




QUICKRATIO LIQUIDRATIO BSIZE EXESIZE COINCIDENTNI -0.042372 -0.098899 0.529972 0.213538 0.127423TA -0.066554 -0.096831 0.558728 0.273789 0.133893

EQUITY -0.070457 -0.085404 0.466233 0.254749 0.115139DEBT -0.064291 -0.096312 0.572301 0.272609 0.137619

CA -0.098089 -0.064578 0.524678 0.278089 0.099002CL -0.094925 -0.147238 0.549735 0.281831 0.113121

INVENTORY -0.157014 0.008069 0.445137 0.236898 0.061890

ROA 0.309829 0.157878 -0.01013-

0.053005 0.026630ROE 0.519889 0.345609 0.127533 0.005913 0.054182

CAPITAL -0.070457 -0.085404 0.466233 0.254749 0.115139

DEBTASSETS 0.081925 0.064793 0.039513 0.148446 0.078669

EQUITYASSET -0.103495 -0.048347 -0.08691-

0.152728 -0.067512

DEBTEQUITY 0.161902 0.098324 0.025646 0.091105 0.036914

QUICKRATIO 1.000000 0.766530 -0.01167-

0.079348 -0.029473

LIQUIDRATIO 0.766530 1.000000 -0.06494-

0.152053 -0.022076BSIZE -0.011669 -0.06494 1.000000 0.192428 0.186062

EXESIZE -0.079348 -0.152053 0.192428 1.000000 0.386569

COINCIDENT -0.029473 -0.022076 0.186062 0.386569 1.000000

65

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