Estimation of factors affecting the operational efficiency of real estate enterprises in Vietnam

Studying the debt ratio of enterprises, total assets, total loan and debt. The influence of these factors on the operational efficiency of enterprises. A basic analysis of small scale capital and large capital mobilization by banks and investors.

Рубрика Экономика и экономическая теория
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Academy of policy and development, Hanoi, socialist republic of Vietnam

Estimation of factors affecting the operational efficiency of real estate enterprises in vietnam Dong Ph.T.1, Hong Dien N.T.2 (Socialist Republic of Vietnam)

Dong Phung The - Candidate of Economic Sciences;

Hong Dien Nguyen Thi - Student,

Abstract

The article quantitatively analyzes the factors affecting the operational efficiency of real estate enterprises in Vietnam. Factors selected for the analysis include ROE, ROA, debt ratio of enterprises; total loan/total debt; total fixed assets/total assets; treasury stocks/total capital; inventories/total assets; (selling expenses + administration expenses)/total expenses; leader's gender and total asset growth rate; operation duration of enterprises. These factors have direct impacts on the operational efficiency of enterprises. The result of the study shows that, in general, real estate enterprises in Vietnam operate effectively; however, the risk prevention ability and resistance to market fluctuations is not high. The small capital scale and large capital mobilization from banks and investors have latent high risks. Besides, the legal framework in Vietnamese state management of real estate is still inadequate. Accordingly, enterprises need to mobilize capital from banks, investors in accordance with risk safety standards and better control macroeconomic variables.

Keywords: real estate enterprises, stock market, ROA, ROE, Vietnam.

ОЦЕНКА ФАКТОРОВ, ВЛИЯЮЩИХ НА ОПЕРАЦИОННУЮ ЭФФЕКТИВНОСТЬ ПРЕДПРИЯТИЙ НЕДВИЖИМОСТИ ВО

ВЬЕТНАМЕ

Донг Ф.Т.1, Хонг Зьен Н.Т.2 (Социалистическая Республика Вьетнам)

2Донг Фунг Тхе - кандидат экономических наук;

2Хонг Зьен Нгуен Тхи - студент,

Академия политики и развития при министерстве планирования и инвестиций, г. Ханой, Социалистическая Республика Вьетнам

Аннотация: в статье количественно анализируются факторы, влияющие на эффективность работы предприятий недвижимости во Вьетнаме. Факторы, выбранные для анализа, включают ROE, ROA, коэффициент задолженности предприятий; общая сумма кредита / общая задолженность; общая сумма основных средств / общая сумма активов; казначейские акции / общий капитал; запасы / общие активы; (коммерческие расходы + административные расходы) / общие расходы; пол лидера и общий рост активов; продолжительность работы предприятий. Эти факторы оказывают непосредственное влияние на операционную эффективность предприятий. Результаты исследования показывают, что в целом предприятия недвижимости во Вьетнаме работают эффективно; однако способность предотвращать риски и устойчивость к колебаниям рынка невелики. Малый масштаб капитала и большая мобилизация капитала со стороны банков и инвесторов имеют скрытые высокие риски. Кроме того, правовая база во вьетнамском государственном управлении недвижимостью по-прежнему неадекватна. Соответственно, предприятиям необходимо привлекать капитал банков, инвесторов в соответствии со стандартами безопасности рисков и лучше контролировать макроэкономические переменные.

Ключевые слова: предприятия недвижимости, фондовый рынок, ROA, ROE, Вьетнам.

Introduction

Real estate market is one of the markets with an important position and role for the national economy. This market has a direct relationship with other markets, such as the financial market, construction material market, labor market, etc. Besides, the real estate market also creates jobs, contributes to the state budget and attracts investment capital sources for social infrastructure. As a result, the effective operation of real estate market is significant for the socio-economic development of a country.

Real estate enterprises are the key actors in the real estate market, playing an important role, reflected in various aspects such as a bridge between production and consumption, real estate construction and real estate trading. Enterprises in the real estate market will constantly promote the application of science and technology for technological innovation, improvement of real estate goods quality, protection and improvement of land resource use efficiency. The enterprise operation in the real estate market is always closely linked to the State's management mechanisms and policies as the majority of real estate is owned by the State, whereby enterprises operate in the real estate market will send out messages to the State of necessary catalysts needed to be completed and supplemented for the market. Enterprises operating in the real estate market have close relationships with a wide range of industries, helping to expand the market, such as: construction, finance - banking, etc.

Actual situation of business activities of enterprises on the stock market

After the crisis in 2011-2014, Vietnam's real estate market has gradually recovered and developed evenly in all segments. Accordingly, enterprises have been more flexible in structuring the type and scale of products. People also have more experience in signing contracts to buy, purchase and invest in real estate. More completed projects are put into use, while the product structure of enterprises is also closer to the actual needs of people. Although the market is witnessing a good growth in terms of both demand and liquidity, in the short term, difficulties in accessing capital and implementing administrative procedures are making the market grow slowly.

According to statistics in 2019 [1], Vietnam has more than 10,000 real estate enterprises but most are medium-sized ones, mainly operating in real estate brokerage and services. The number of newly established real estate enterprises has increased by 21% compared to 2018; this is the highest increase compared to other industries. Nonetheless, only about 65 real estate enterprises are listed on the stock market. Moreover, the real estate sector also recorded an increase in FDI capital sources. As of the third quarter of 2019, FDI inflows to real estate reached 742.3 million USD, accounting for 11.5% of FDI inflows into Vietnam, ranking the second in foreign investment attraction, only after the processing and fabrication industry.

If the additional registered capital of licensed projects from previous years and the form of capital contribution, share purchase by foreign investors are included, this capital source is 1.38 billion USD, accounting for 8.2% of the total registered investment capital.

Fig. 1. Inventory value of 54 listed real estate enterprises (Source: Report DNSE [2])

In 2019, inventories are valued at about 202 trillion VND. These inventories include those during distribution and circulation; inventories that are proactively scheduled by enterprises to be brought to the market and unconsumed goods. In fact, the amount of inventories is still very large, so it is necessary to pay special attention to resolve inventories to ensure the liquidity and the stable, healthy development of enterprises and the real estate market.

In 2018, the profit of listed real estate enterprises hit the record, 104% higher than that in 2017. According to Vietstock's statistics [7], among 64/66 real estate enterprises listed on the stock market, there are 57 enterprises having profit, 24 enterprises with grown profit, 3 enterprises shifting from having loss (Quarter 1 of 2018) to profit (Quarter 1 of 2019), 29 enterprises with reduced profit, 6 enterprises shifting from having profit to loss and 7 enterprises suffered from losses. In the first half of 2019, listed real estate enterprises generated more than 51,217 billion VND in revenue and 6,726 billion VND in after-tax profit. This result decreased by nearly 5% in revenue and 13% in profit compared to the same period in 2018, equivalent to the loss of 2,894 billion VND and 961 billion VND respectively.

Table 1. Loans of listed real estate enterprises

Year

2016

2017

2018

2019

Short-term loan

31,661

45,897

52,475

53,761

Long-term loan

60,669

64,276

130,499

135,360

Cash and cash equivalents

28,111

35,773

52,736

41,046

(Source: Report DNSE [2])

Decreased rate of successful sales, coupled with the credit tightening policy, has led to low commandeered capital of customers, which makes real estate enterprises borrow more, especially in 2018, to finance next construction stages. Total liabilities of listed real estate enterprises by the end of accounting period of the second quarter recorded nearly 286,357 billion VND, increased more than 7% compared to the beginning of the year. In particular, short-term liabilities accounted for 189,252 billion VND, accounting for 66% and decreased 10% compared to the beginning of the year. Besides, long-term debt also accounted for the main proportion with 135 trillion VND whereas short-term debt was only 53 trillion VND and increased more slowly over the past 3 years.

Fig. 3. Revenue awaiting final accounting (Source: Report DNSE [2])

The unearned revenue value was approximately 100 trillion VND in 2019, equivalent to approximately 50% of the inventory value at enterprises. The level of revenue awaiting final accounting increased slightly compared to the end of 2018 and decreased by approximately 12% compared to the end of 2017. Along with the decline in successful transaction rates in both large markets, Hanoi and Ho Chi Minh City, successful sold apartments and houses will reduced in terms of both supply and demand; consequently, the profit of real estate industry in the medium term will not have much change. Enterprises with profit growth will be the group owning bottom land and can increase the price sharply due to the development of surrounding infrastructure.

Research methods

In fact, the operation of the real estate business sector is affected by various factors in both macro and macro aspects. In the case of Vietnam, the author divided the factors affecting the operational efficiency of real estate enterprises into two groups, specifically:

Group of quantitative factors: calculated based on secondary data of real estate enterprises including: ROE (return on equity); ROA (return on assets); debt ratio of enterprises; total loan/total debt; total fixed assets/total assets; treasury stock/equity; inventories/total assets; (selling expenses + administration expenses)/total expenses; leader's gender; total asset growth rate and operation duration of enterprises. These factors have direct impacts on the operational efficiency of enterprises. This group of factors belongs to the potential that enterprises can control to some degree. Assessing the potential appropriately allows enterprises to develop the right business strategy and plan while taking advantage of business opportunities bringing high results.

Group of qualitative factors: considered based on the operational environment of enterprises, divided into two groups, endogenous and exogenous factors. In particular, exogenous factors include natural factors (location, physical size, area of the real estate, location terrain, soil properties, surrounding environment); macroeconomic factors (real estate supply and demand, average income, credit system, land price, labor market); legal factors; social factors (population density, service quality) and technology elements.

Endogenous factors include: customer and distributors; competitors; suppliers and alternative products.

In order to analyze factors affecting the operational efficiency of real estate enterprises currently listed on Vietnam's stock market, the research uses secondary data taken from the financial statements of real estate enterprises. As the data is taken over 3 years, there are many economic and political fluctuations affected the operation of enterprises to some extend during the years. As a result, the data in the topic is adjusted to limit the asymmetrical factors over the years by taking the average of 3 years (except for gender dummy variable). Therefore, to some extent, the multivariate linear regression model by OLS method of Eview 7 software can be used to estimate the factors affecting the operational efficiency of enterprises.

On that basis, the linear regression model in this research has the following general form:

E(Y/Xt) = P0 + piXlt +p2X2t + p3X3t + p4X4t + p5X5t + p5X5t + p6X6t +

+ p7X7t + p8X8t + p9X9t + ut

Where, dependent variables (E(Y/Xt)) are return on equity (ROE) and return on assets (ROA). Independent variables (Xit) respectively are the debt ratio of enterprises (X1), total loan/total debt (X2), total fixed assets/total assets (X3), treasury stock/equity (X4), inventories/total assets (X5), selling expense and administration expenses /total expenses (X6), leader's gender (X7), total asset growth rate (X8) and operation duration of enterprises (X9).

Table 2. Expected sign of variables in the model

Variables

Expectations

X1

Total debt/Total equity

-

X2

Total loan/Total debt

-

X3

Total fixed assets/Total assets

+/-

X4

Treasury stock/equity

+

X5

Inventories/total assets

-

X6

(Selling expenses + Administration expenses)/total expenses

+

X7

Leader's gender: The dummy variable receiving value 1 as female and 0 as male

+

X8

Total asset growth rate, calculated by comparing total assets of the following year to that of the previous year

+

X9

Operation duration of enterprises, calculated by the number of actual operating years of enterprises

+

Regarding variable X1, capital structure influences the enterprise value; maintaining a high debt ratio will negatively affect the operational efficiency of enterprises. However, in some cases, debt ratio is considered as a financial leverage for enterprises. As stated in some research, in general, an enterprise with the too high debt rate in the total capital will be bad for enterprises, adversely affecting ROE. Therefore, variable X1 is expected to be negative.

For variable X2, like X1, the operation of Vietnamese enterprises is based not on available assets but much on long-term and short-term loans. The fact that an enterprise has loans accounting for major proportion of total debt is quite dangerous if the enterprise is insolvent, which easily leads to bankruptcy, adversely affecting both ROE and ROA variables. Thus, the expected sign of this variable will be negative.

In terms of variable X3, total fixed assets/total assets, the determination of whether fixed assets positively affect the operational efficiency of enterprise or not depends on various cases. In case fixed assets are invested by enterprises and improved for working efficiency, fixed assets can help enterprises to operate better. On the other hand, if enterprises cause backlog of fixed assets, the working efficiency as well as revenue and profit for the enterprises will be considerably affected. Hence, the variable X3 is expected to be positive/negative.

About X4, the fact that enterprises have capital balance to buy back treasury stocks and sell them at a suitable time to collect the surplus, or the redemption of treasury stocks makes the equity and total assets of enterprise decreased, leading to the increase in ROE and ROA of enterprises. For that reason, the variable X4 is expected to be positive.

If real estate enterprises have a large amount of inventories, their business activities will be affected. Therefore, X5 is expected to be negative. Regarding variable X6, a typical feature of real estate enterprises is selling goods, and at the same time paying commissions to sellers or brokers, so the more payment for sales and management, the more positive effect on the operational efficiency of enterprises is. Thus, the variable X6 is expected to be positive.

Regarding X7, leader's gender is also a significant factor deciding the operational efficiency of enterprises. It can be suggested from a wide range of research that female leaders will have a positive influence on the enterprise operation.

For X8, the size of enterprises has a positive effect on their operational efficiency. The larger the enterprise size is, the more efficiently the enterprise operates. In this topic, the size of enterprises is measured by the total asset growth rate. Hence, the variable X8 is expected to be positive.

In terms of variable X9, operation duration of enterprises, the longer the enterprise operates, the higher its operational efficiency is, because of built reputation and brand in the market. For that reason, X9 is expected to be positive.

Estimation results

After the estimate of coefficients, the results are as follows:

Table 3. Statistical results of data used in the model

Variables

Average

number

Median

Maximum

value

Minimum

value

Standard

deviation

X1

1.94

1.55

9.76

0.06

1.79

X2

0.33

0.35

0.77

0

0.22

X3

0.09

0.025

0.54

0

0.14

X4

0.0017

0

0.104

-0.026

0.018

X5

0.27

0.195

0.94

0

0.24

X6

0.53

0.56

0.88

0.16

0.18

X7

-

-

-

-

-

X8

0.19

0.125

0.96

-0.27

0.27

X9

15.7

14

45

4

8.19

ROE

0.07

0.105

0.93

-0.72

0.22

ROA

0.03

0.04

0.18

-0.17

0.07

(Source: Calculation of the author from Eview 7.0)

Prob (F) statistic values in both models are significantly small, which are 0.001 and 003 for ROE and ROA, respectively. This shows that the safety level rejects the H0 hypothesis, meaning that there exists a linear relationship between the operational efficiency of real estate enterprises (measured by the return on equity (ROE) and the return on total assets (ROA)) with the independent variable from at least one of the factors. As a result, the given linear regression model is suitable for the data.

Variables

ROE

ROA

Coefficient

Prob.

Coefficient

Prob.

Constants

0.24

0.055

0.15

0.0006

Total debt/total equity

X1

-0.06

0.0015

-0.009

0.099

Total loan/total debt

X2

-0.28

0.047

-0.1

0.027

Fixed assets/total assets

X3

-0.28

0.209

-0.09

0.221

Treasury stock/total equity

X4

0.95

0.551

0.56

0.278

Inventories/total assets

X5

0.24

0.069

0.03

0.431

Selling expenses and administration expenses/total expenses

X6

-0.23

0.186

-0.15

0.011

Leader's gender

X7

-0.02

0.855

0.01

0.725

Total asset growth rate

X8

0.09

0.363

0.07

0.051

Operation duration of enterprises

X9

0.006

0.12

-0.0002

0.853

R-squared

0.55

0.55

0.53

Durbin Watson

2.41

2.41

1.77

F-statistic

4.07

4.07

3.74

Prob (F-statistic)

0.001

0.001

0.003

(Source: Calculation of the author)

In general, the regression model is satisfactory in terms of expected signs. Constants are positive, which indicates that when the quantitative factors are 0, the ROE and the ROA are 0.24 and 0.15 respectively. For the factors X1, X2, X3 in both models with negative signs as expected, these factors will negatively affect ROE and ROA. Regarding X4, it will have positive impact on the operational efficiency, so it will be positive. The factor X5 is expected to negatively impact the operational efficiency but in both models it is shown that this factor have a positive effect, proving that the real estate environment is at a stage where Investors are interested in inventory. As for the three factors X7, X8, X9, although they are expected to have positive effects, X7 has a negative effect on ROE and X9 has a negative effect on ROA.

The determination coefficient R2 in ROE models is 55% and in ROA model is 53%, which is moderately reasonable. This index shows that the general fluctuation of the influencing factors explains about 55% and 53% of the operational efficiency of real estate enterprises, corresponding to ROE and ROA targets. The non-measurable portion of the regression model which is about 45% for the ROE dependent variable and 47% for the ROA dependent variable refers to other important factors affecting the operational efficiency of enterprises. Nonetheless, these factors cannot be included in the regression model as they are nonquantifiable. For instance, the situation of real estate supply and demand, competitors, suppliers, substitutes, etc. will significantly affect the operational efficiency of enterprises.

Of all 9 variables included in the model, 3 variables explaining the impact on the operational efficiency of real estate enterprises through the ROE dependent variable at the significance level from 1% to 10% are: Total debt/total equity (X1), Total loan/Total debt (X2), Inventories/total assets (X5). For the ROA dependent variable, results show that there are 4 variables affecting this target in different directions and with significance levels from 1% to 10%, including: Total debt/total equity (X1), Total loan/Total debt (X2), Selling expense and administration expenses/ total expenses (X6) and total asset growth rate (X8).

The remaining variables including fixed assets/total asset (X3), treasury stock/equity (X4), leader's gender (X7) and operation duration of enterprises (X9) hardly affect the operational efficiency of these enterprises. Regarding the variable X1, the effect on the operational efficiency of enterprises is that the total debt/total equity negatively impacts ROE target with the significance level of 1%, has statistical significance to ROA target with the significance level of 10% and have an adverse effect on ROA target. It means that if enterprises have a high debt ratio to equity, the operation is less efficient. Especially for those maintaining high long-term bank loans, the greater the interest payment pressure is, the more difficult it is for enterprises to operate. However, enterprises still need to maintain debts to have more financial leverage for promoting their operation more such as easy-to- pay debts and long-term bonds. According to the model results, the estimated value for ROE is 0.24, meaning that when the debt/equity ratio increases by 1%, the ROE will decrease by 24%; the estimated value for ROA is 0.15, meaning that when the debt/equity ratio increases by 1%, the ROA will decrease by 0.15%.

The next variable affecting the operational efficiency of enterprises is total loan/total debt in both ROE and ROA targets with the significance level of 5%. These targets all adversely affect the operational efficiency of real estate enterprises if they maintain the high bank debts, especially long-term ones, or have high interest and principal payment pressure. It will be considerably dangerous for enterprises in case of frozen real estate market where a large amount of inventories are impossibly sold. It can be seen that the estimated value for ROE is -0.28, that is, when the total loan/total debt ratio increases by 1%, the ROE decreases by 28%; the estimated value for ROA is -0.1, meaning that when the total loan/total debt ratio increases by 1%, ROA decreased by 10%. This shows that it is essential for enterprises to limit the increase in capital from loans to ensure better operations.

The next variable is the inventories/total assets ratio, which affects the ROE with the significance level of 10%. This target shows that it has a positive effect on the operational efficiency of enterprises. Nevertheless, when we look back at each stage of the real estate market, there are stages when inventories has a negative impact on the enterprise operation but there is also a stage when inventories bring a positive factor. That is the bottom-down stage when enterprises buy excess inventories until the market is vibrant again to make a profit. It can be concluded that the fact that enterprises have inventories is not necessarily a negative effect but they must not have too much backlog which proves the enterprises' limited capacity in controlling goods. The estimated value of X5 for ROE is 0.24, that is, when X5 ratio increases by 1%, ROE increases by 24%.

The variable X6, the ratio of selling expenses and administration expenses/total expenses, has impacts on the operational efficiency of enterprises and ROA variable. This variable adversely affects ROA. According to the expected sign, X6 must have positive impacts on the operational efficiency of enterprises as much money is paid for selling expenses. In the opposite direction, the enterprises' application of new methods in sales can not only save administration expenses for enterprises but only help them run more efficiently. The estimated value for ROA is -0.15, meaning that when X6 increases by 1%, ROA decreases by 15%.

The last variable affecting the operational efficiency of enterprises is the total asset growth rate (X8). Generally, the fact that an enterprise has the even growth rate of total assets annually proves it has been developing well. X8 has a positive influence on the ROA variable. The estimated value of X8 for ROA is 0.07, that is, when the X8 ratio increases by 1%, the ROA increases 7%.

The model results show that there are two variables which are total debt/total equity (X1) and total loan/total debt (X2) affect the operational efficiency of enterprises in both ROE and ROA. Both of these targets have negative impacts on the enterprise operation. In addition, the inventories/total assets ratio positively affect ROE, the variable X6 has a negative impact on ROA and the variable X8 has a positive impact on ROA.

Conclusion

It can be shown from the above analysis that real estate enterprises in Vietnam depend heavily on loans from customers. Nonetheless, because short-term mobilized capital accounts for a large proportion, banks have not met the capital needs of the real estate market. As prescribed by the law, the project employer must have the equity accounting for 15-20% of capital, the remaining 80-85% is mainly based on bank credit and capital mobilized from customers. In 2018, commercial banks only achieved the use of short-term mobilized capital for medium-term loans, including real estate. The proportion of real estate loans accounts for about 7.5% of the total outstanding credit in the economy. Therefore, the Government needs to gradually reduce credit sources to pressure real estate enterprises to seek other additional source of funding. In addition, finding capital from domestic real estate investment funds is not feasible because Vietnam has only one real estate investment fund belonging to a commercial bank with a significantly small charter capital of 50 billion VND, which has not been able to mobilize huge domestic dormant capital and also has not met the huge capital demand of the real estate market. Lending interest rate for real estate enterprises is 20-22%/year [5]. Characterized by the area where assets are financed primarily by debts, as well as with the fact the capital structure of majority of enterprises listed on the stock market is mainly debt, debt to equity ratio is higher than 1, even up to 2-3, enterprises may find it difficult to gain profits while revenue also declines due to difficulties in the market. asset capital bank investor

From the above reasons, Vietnam needs to promote the implementation of approved land use planning and urban planning, support investors to accelerate the progress of approved projects to increase the investment in the primary market. Besides, it is crucial to improve the legal system on real estate activities, further reform administrative procedures related to land, especially procedures for land allocation and land lease to investors.

References / Список литературы

1. Ministry of Construction. Department of house and real estate market management.

2. Dai Nam securities. Real estate industry analysis report.

3. Dong P.T., Thanh Thuy T.T., Thanh Tra N.T. Foreign investment, corporate governance and firm performance in Vietnam listed companies. Indian Journal of Economics and Development, Vol. 15 (4), 2019. Р. 499-507

4. Dong P.T., Hong Nham N.T. Research overview on the credit accessibility to capital of Small and medium enterprises. Review of Business Research, October 2018, Vol. 18, Issue 2. Р. 73-78.

5. Le Ngoc Nuong, 2018. Factors affecting the development of industrial medium and small sized enterprises in Thai Nguyen province. Thai Nguyen University.

6. The State Bank of Vietnam's Circular 36/2014/TT-NHNN stipulating limits, safety assurance ratio in activities of credit institutions and branches of foreign banks.

7. The State Bank of Vietnam's Circular 16/2018/TT - NHNN amending, supplanting some regulations on limits, safety assurance ratio in activities of credit institutions and branches of foreign banks.

8. VinaCorp Journal. The profit of real estate enterprises listed on Vietnamese stock market.

9. Vietstock Financial and Stock Portal.

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