Determinants of Tobin’s q: The Case of Listed Construction and Material Companies in Vietnam

When it is below 1, the firm value is undervalued denoting that the book value of the firm’s assets are higher than their expected market value and when Tobin’s q is higher than 1, the v

Determinants of Tobin’s q:

The Case of Listed Construction and Material

Companies in Vietnam

VU THI LAN PHUONG ERP FPT Service Limited Company - phuong.vulanphuong@gmail.com

NGUYEN KIEU HUNG

Joint Stock Commercial Bank for Investment and Development of Vietnam (BIDV) - hungnk16@gmail.com

Abstract

This paper aims to identify the determinants of Tobin’s q Exploring a sample of 152 construction and material companies listed on the Ho Chi Minh Stock Exchange (HOSE) and Ha Noi Stock Exchange (HNX), the study applies the method by James Tobin (1968) to evaluate Tobin’s q of the Vietnamese listed firms from 2013

to 2015 The multiple regression model is employed to estimate impacts of the main factors on Tobin’s q We find significantly positive effects of leverage and firm age on Tobin’s q, but a negative influence of firm size on this ratio The paper caters for the overall portrait of construction and material in Vietnam in order to clarify and reconcile the results

Keywords: Tobin’s q; firm performance; construction and material sector

1 Introduction

Tobin’s q, which is a ratio devised by James Tobin in 1969, plays an important role in assessing the firm performance by specific periods Defined as the ratio of the market value of a firm to the replacement cost of asset, Tobin’s q shows the comparison between the cost to replace a firm’s asset and the value of its stocks Tobin’s q is compared to 1 in order to assess the firm value When it is below 1, the firm value is undervalued denoting that the book value of the firm’s assets are higher than their expected market value and when Tobin’s q is higher than 1, the value of its assets are expected to be higher than book value (Tobin, 1969) Hence, by using Tobin’s q which comparing the book value and market value of companies, portraits of firms are more complete and support the decision making of investors or stakeholders

Tobin’s q compensates weaknesses of other indicators measuring firm performance such as ROE and ROA which impossibly indicate the market value of firms, hence, the combination between Tobin’s q and other ratios provides more adequate information about firm value Therefore, it is likely to support investors and researchers to investigate firm performance, assessing firm value or predict the development of firms and sectors Additionally, the correlations between Tobin’s q and determinants are different in diversity of samples depending on specific firms, sectors, and economies in periods Such the importance suggests us to investigate determinants of Tobin’s q in specific cases in Vietnam Therefore, the main objective of this research is to investigate the determinants of q of listed construction and material companies in Vietnam We also perform the package data, methodologies to measure the value of q, as well as the correlation between q and its determinants including financial and non-financial ratios Furthermore, we cater for the prediction about development of construction and material sector in Vietnam after data analysis, reconciliation with other firm performance ratios and sector background, which plausibly contributes to support decision-making procedure of investors and stakeholders

The remainder of the study is structured into five sections Section 2 presents the literature review, followed by methodologies in section 3 Section 4 demonstrates results and discussion whilst section 5 concludes the research

2 Literature review

A firm performance is derived from the value that firms create through their operation activities based on stakeholder perspective (Freeman, 1984) Additionally, Hartzell and Starks (2003) argue that institutional investors are likely to impact CEO behaviors and firm performance Ferreira and Matos (2008) also indicate that firms with higher levels of ownership by independent investors may have lower expenses and better governance, which is reflected on a better firm performance Therefore, firm performance has been examined for the consideration of investors, stakeholders, and researchers by virtue of several justifications Firstly, firm performance is affected by the financial circumstance, especially the financial distress that might harm the firm’s survival through cost

increasing (Taffler, 1982) Recession possibly causes the weakness exposure of corporations leading

to losses of profits and market share (Opler & Titman, 1994) Secondly, firm performance caters for the set of ratios to measure the “financial health” and corporate governance Most of investors have aspiration that effective management can support the firm to overcome the challenges, stabilize the growth, and assure the financial condition in period Thus, firm performance plausibly performs expectation from market perspective to the firms (Ehikioya, 2009)

There are two classifications of firm performance, in which the first is accounting-based class, mostly depending on accounting data and being criticized because of backward-looking data and limited capacity of forecasting The second classification is the market-based measurement which Tobin’s q belongs to It is considered in various previous researches because of its merits For instance, market price indicates the aggregate expectation for the firm growth in the future (Stickney

et al., 2007); operating cash flow per share ratio demonstrates cash covering capital expenditure and dividends for each share (Bernstein, 1993) To reconcile the advantages and disadvantages of two types of measure, Al-Matari et al (2014) suggest that it is advised to use a combination measure of the firm performance including accounting and market-based measures

The question on how to calculate the Tobin’s q is concerned by many scholars with the purpose

to find out the most accurate and appropriate formula The earliest method raised by James Tobin and William Brainard was published in 1968 Tobin’s q was defined as the ratio with the numerator is the firm market valuation made up sum of the market value of equity and book value

of liabilities while the denominator is the replacement or substitution cost, which is measured by total book value of equity and liabilities (Tobin, 1969)

Lindenberg and Ross (1981) build a computation of q, also known as L-R algorithm in order to measure Tobin’s q and to examine relationship between q and other indicators measuring monopoly power They divided firm assets into three components including plant and equipment, inventory, and other assets Although L-R algorithm was common estimation techniques for q, it was asserted

to be too complex and cumbersome to conduct and combine with other ratios to make the financial decisions (Sang, 1998) However, it is evident that L-R algorithm has been admitted and adopted by researches of Tamrineia et al (2013), Pruitt et al (1994), and Lang et al (1989)

On the other hand, the proposal of recursive model by Hall et al (1988) to calculate Tobin’s q was reputed to modify the drawbacks of L-R algorithm This method made the difference by using the age structure to adjust market value and replacement cost It is not only straightforward to measure but also convenient to access to the database However, the model by Hall et al (1988) takes a disadvantage that it might cause the upward bias by inflating the bond value estimation

Due to the disadvantages mentioned above, this paper focuses on the simple calculation that was developed by James Tobin and used widely to determine the value of q:

Tobin’s q = 𝐸𝑞𝑢𝑖𝑡𝑦 𝑀𝑎𝑟𝑘𝑒𝑡 𝑉𝑎𝑙𝑢𝑒+𝐿𝑖𝑎𝑏𝑖𝑙𝑖𝑡𝑖𝑒𝑠 𝑀𝑎𝑟𝑘𝑒𝑡 𝑉𝑎𝑙𝑢𝑒

𝐸𝑞𝑢𝑖𝑡𝑦 𝐵𝑜𝑜𝑘 𝑉𝑎𝑙𝑢𝑒+𝐿𝑖𝑎𝑏𝑖𝑙𝑖𝑡𝑖𝑒𝑠 𝐵𝑜𝑜𝑘 𝑉𝑎𝑙𝑢𝑒

Various factors that can impact Tobin’s q are considered as follows:

Leverage Leverage refers to the use of debt to acquire additional assets and is calculated by total

liabilities to sum of equity and total liabilities (total assets) It can be simplified to state how much debt can be used to buy a currency unit of asset Therefore, the higher the financial leverage is the higher amount of debt will be spent on acquiring new assets Financial leverage is preferred when the benefits generated by debt are greater than the interest expense associated with the debt Many companies use financial leverage instead of acquiring more equity, which could reduce the earnings per share of existing shareholders However, in the financial distress which can trigger the sharp decreases in revenue, distribution, or market shares, the high financial leverage possibly causes the risks and burden to the firms due to the high interest Along with the risk, most of investors expect that corporations having better financial condition can take the larger market shares with appropriate strategy and overcome the difficulties (Opler & Titman, 1994) Therefore, does financial leverage not only have benefits generally but also has more crucial role in firm’s survival and development in recession Similarly, papers by Jensen (1986) and Bolton and Scharfstein (1990) propose that financial leverage can significantly affect firm performance because it can provide managers incentives to make better investment decisions, which indicates the positive correlation between debt ratio and firm performance However, studies by Sunder and Myers (1999) and Abbasali et al (2012) show that there is a strong negative and significant relationship between debt ratio and firm performance in Iran The similar results are demonstrated in research by Onaolapo and Kajola (2010) while they observe the data of 30 companies listed on Nigeria Stock Exchange

Tangibility Tangibility is measured by the ratio of total tangible assets to total assets Campello

(2007) argues that tangibility is used to identify a causal link between financing and firm performance Because of higher capacity for reselling and repossessing, the more tangible asset, the more valuable Gilson et al (1990) suggest that high tangibility makes creditors to choose asset liquidation over contract renegotiation when firms underperform and become distress Sunder and Myers (1999) demonstrate a significant positive relationship between tangibility and debt ratio and

a negative relationship between debt ratio and firm performance; thus, it is likely to infer that tangibility and firm performance, proxied by Tobin’s q, have negative correlation However, Abbasali

et al (2012) argue that tangibility and firm performance have a significantly positive correlation

Growth rate Growth rate of firm is measured by percentage of change in sales Frank (1988)

suggests that growth is a good indicator of the expectation of firm’s performance; hence, it implies a positive correlation between growth and firm’s survival as well as firm performance Besides, a research by Brush et al (2000) investigates the relationship between growth rate and firm performance that was under the hypothesis with and without free cash flow It is revealed that the firms that have strong governance with free cash flow that trigger the significantly positive relationship between sale growth and Tobin’s q Indeed, rarely do the firms operate without free cash flow, especially in construction and material companies, thus their results are more likely to be referred in many cases

Firm size Firm size data is collected by total assets or the natural logarithm of assets The

viewpoints of relationship between firm size and firm performance are various under many research aspects and authors’ hypotheses For instance, under the investigation of listed companies in Tehran Stock Exchange, Abbasali et al (2012) identify a significant and positive correlation between firm size and financial performance This can be explained by the expectation of researchers and investors that the larger firms are more likely to use flexible manufacturing systems and have more opportunities to access the public resources and bank loan than small ones Nevertheless, other scholars hold contrast results that there is no relationship between firm size and firm performance when investigating the information technology companies (Kalkan et al., 2011) Therefore, the relationship between firm size and firm performance should be researched and conclude by specific sectors Moreover, Nametag et al (2015) emphasize that firm size has an ambiguous effect on the firm performance It is argued that as the size increases, efficiency may be reduced due to the decreases of strategic management and operational activities, then causing the negative relationship

In other cases, the size has a positive effect on firm performance as firms with more assets tend to raise their capital

Age of firm There are many theoretical models presenting the same fundamental concept about

relationship between firm age and firm performance and how firm age affects firm performance Abbasali et al (2012) indicate that age and Tobin’s q have a positive relationship However, the quantile regression analysis in studies by Reichstein et al (2010) and Serrasqueiro et al (2010) reveals that firm age has a significantly negative impact on firm growth and performance The contrast results can be explained by the changes in firm behaviors when they become older According to Berger and Udell (1998), when firms become more experienced, they are more likely to have access to public equity or long-term debt financing, which implies a positive correlation Likewise, Coad et al (2010) both demonstrate the positive relationship and clarify the deterioration

of firm performance with age The latter is explained that younger firms are more successful at converting employment growth into growth of sales, profits, and productivity Furthermore, Loderer and Waelchli (2010) indicate that cost of goods sold and overhead expenses go up with age and growth slows down, which cause the negative correlation between age and firm performance

To conclude, our study aims to examine the influences of financial leverage, tangibility, growth rate, firm size and firm age on Tobin’s q of listed construction and material companies in Vietnam Our research is expected to provide a deeper understanding of construction and material sector from 2013-2015 and explain its characteristics based on the empirical results as well as the previous researches

3 Methodology

3.1 Overview of the Construction and Material Sector in Vietnam

Construction and material sector is field that has strong interaction and distinct characteristics

Firstly, construction and material firms often have large scale of tangible asset such as plants, machines, and equipment Generally, the construction and material companies having good performance possibly improve revenue by their efficiency of using tangible assets The appropriate rate of asset tangibility is one of signs that can indicate the potential in firm performance and survival

in each company (Le & Truong, 2007) In Vietnam, the ratio of fixed asset turnover (FATO) is widely used to measure the efficiency of tangible asset investment.)

Secondly, firms in the construction and material sector in the period 2013-2015 had a significant financial leverage that is defined by the ratio of total liabilities to total assets This ratio, which fluctuated from 66 percent to 75 percent, indicates that the preferring debts can lead to high risks in companies It is pointed out that this ratio will cause risks if it is higher than 40 (Le & Truong, 2007)

It will also refer to a hazard for firms if the ratio is over 70 percent

Thirdly, a noticeable feature of the listed construction and material companies in Vietnam is that most of them have small size with the low capitalization which account for 3 percent of the capitalization of the national market Among those listed in the stock markets, there are 20 biggest companies that make up 79 percent of total sector capitalization (Construction Sector Analysis of FPTS, 2015) Additionally, the level of capitalization of the Vietnam construction companies in Vietnam is low when they are compared to those in ASEAN This is regarded as a drawback of the sector in this period

Fourthly, the construction and material sector follows to the economic cycle The period

2013-2015 witnessed the post-crisis recovery of the economy by the growth rate increasing and stabilized inflation Although sales growth of the sector slightly increased in this period, it may suggest a potential growth in the future after the economic recession

The summary of financial ratios of construction and material sector is described in Table 1 Earnings per share (EPS) indicate the profit allocated to each common share - the higher EPS is likely

to raise the stock price Although the negative value of EPS in 2013 indicates that owning stocks of construction and material companies in this period cannot bring profits to investors, this ratio increases annually to 110.37 percent in 2015 That performs the expectation of optimistic profitability and development in the future of sector Return on Assets (ROA) and Return on equity (ROE), which demonstrate the percentage of how profitable a company relates to its assets and equity correspondingly, have an upward tendency from 2013 to 2015 That means the management board

of construction and material companies are more efficient in using its assets and equity to generate earnings

Beside the profitability ratios, Table 1 shows the financial conditions and efficiency of companies

in construction and material sector in period 2013-2015 Fixed asset turnover (FATO) and tangibility are proportions which illustrate how likely company is to generate revenue from fixed asset investment and portion of tangible asset on total asset respectively FATO increases from 2.29 to 4.16 before falling to 2.6 in 2015, which indicates that the capacity of generating revenue from tangible

asset in 2015 is lower than that in 2014, whilst the percentage of tangible asset rises from 14.83 percent to 24.54 percent Therefore, despite the boost of tangibility, the efficiency in using fixed assets

to generate sales decreases sharply The ratio of debt to revenue in this period is higher than 1, which demonstrates that these companies depend on large amount of debt to generate revenue This illustration may be a sign of risk that the companies have been facing

Table 1

Financial ratios of Construction and material sector from 2013 to 2015 in Vietnam

Moreover, the structure of sector is indicated through the value of sub-sectors Civil construction and infrastructure construction make up with the largest proportion of 41.2 percent and 40.6 percent respectively whilst the industry construction accounts for the remainder with 18.2% The period

2013 – 2015 indicates the most significant portion of 43 percent of North in geographic structure followed by South and the Middle with 32.4 percent and 24.6 percent Additionally, private companies account for the largest percentage of more than 80 percent in sector structure and remain the upward tendency (see Figure 1)

Figure 1 Proportion of participants in construction and material sector from 2007 – 2014

Source: General Statistics Office of Vietnam

34.20%

9.90%

61.50%

83.60%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

State enterprises Private enterprises Foreign - investment enterprises

Beside the characteristics, it can be seen the prospective of the construction and material industry through the impacts of government policies on civil construction, industrial construction and infrastructure construction Firstly, the Law of Housing passed in 2014 has permitted the foreigners who work in Viet Nam to have right to own their houses Furthermore, the government conducted both policies including consumer stimulus package and decreasing the basic rate of interest in order

to encourage consumption and uplift the sale of construction and material sector Therefore, by the decisions and policies of the government in the period 2013-2015, the industry of civil construction has opportunities to improve their performance and market shares Secondly, the negotiations of six free trade agreements (FTAs), especially the success of Trans-Pacific Partnership Agreement (TPP), contribute to the development of this sector through the increase of Foreign Direct Investment (FDI) Investment for industrial construction accounts for 40 percent of total FDI capital structure, which

is equivalent to 4 – 5 billion dollar per year Thirdly, the statistical data indicates that 40 percent of traffic infrastructure has poor standard of quality (Construction sector analysis of FPTS, 2015) Hence, the budget for upgrading may occupy 48 – 60 billion dollar till 2020, which leads to the potential development in the infrastructure construction

3.2 Data source

The data set used in this paper is collected from websites cophieu68.com and vndirect.com.vn, which covers financial statements of 152 construction and material companies from 2013 to 2015 in Vietnam They are listed on Ho Chi Minh and Ha Noi Stock Exchange (HOSE and HNX correspondingly)

To guarantee the accuracy and objectivity analysis, we apply some rules in data collection Firstly,

we collected and cleaned up the data from audited financial statements For instance, data from financial statements is extracted from the audited balance sheets and income statements of firms, while other data about outstanding shares is collected from the audited financial statement reports Secondly, we only select stocks that have been traded at least one year to the beginning of the research period in order to assure that all the observations have values of firm age that are different from zero Additionally, we remove companies that have tangibility ratios approximate zero or their share prices are valueless

3.3 Method

To identify the determinants of Tobin’s q, this research uses a multiple regression specified as follows:

q = β 0 + β 1 Leverage it + β 3 Tang 1it + β 4 Tang 2it + β 5 G it + β 6 Size it + β 7 Age it +ε it

(i: entity and t: time)

q: Tobin’s q (q) that is measured as:

Tobin’s q = 𝐸𝑞𝑢𝑖𝑡𝑦 𝑀𝑎𝑟𝑘𝑒𝑡 𝑉𝑎𝑙𝑢𝑒+𝐿𝑖𝑎𝑏𝑖𝑙𝑖𝑡𝑖𝑒𝑠 𝑀𝑎𝑟𝑘𝑒𝑡 𝑉𝑎𝑙𝑢𝑒

𝐸𝑞𝑢𝑖𝑡𝑦 𝐵𝑜𝑜𝑘 𝑉𝑎𝑙𝑢𝑒+𝐿𝑖𝑎𝑏𝑖𝑙𝑖𝑡𝑖𝑒𝑠 𝐵𝑜𝑜𝑘 𝑉𝑎𝑙𝑢𝑒

Due to the unavailability of data on Liabilities Market Value in Vietnam market, this value will be replaced by Liabilities Book Value that is equal to total liabilities in balance sheet (Lai & Vo, 2015) Equity Market Value is identified as share price multiplies by number of outstanding shares while Equity Book Value is owner’s equity in balance sheet Thus, the formula to determine Tobin’s q as follows:

Tobin’s q = 𝐸𝑞𝑢𝑖𝑡𝑦 𝑀𝑎𝑟𝑘𝑒𝑡 𝑉𝑎𝑙𝑢𝑒+𝐿𝑖𝑎𝑏𝑖𝑙𝑖𝑡𝑖𝑒𝑠 𝐵𝑜𝑜𝑘 𝑉𝑎𝑙𝑢𝑒

𝐸𝑞𝑢𝑖𝑡𝑦 𝐵𝑜𝑜𝑘 𝑉𝑎𝑙𝑢𝑒+𝐿𝑖𝑎𝑏𝑖𝑙𝑖𝑡𝑖𝑒𝑠 𝐵𝑜𝑜𝑘 𝑉𝑎𝑙𝑢𝑒 Leverage: financial leverage = total liabilities/ total asset This information is collected from balance sheets of companies

Tang1 = Tangibility*code

Code is a dummy variable which takes the value of 1 if a firm is listed in HNX, of 0 otherwise Tang2 = Tangibility* Firm Age

G = growth* Firm Age This variable is measured by the sales variation in current year compared

to that in previous year and is collected from the Income statements in 2012, 2013, 2014 and 2015 Firm Size is measured by logarithm of total assets

Firm Age is the number of years since a firm started to operate and was permitted in Operation Registration Certification to the year of research

4 Results and discussion

4.1 Descriptive statistics

Table 2 presents the summary of descriptive statistics of the listed companies in the period

2013-2015 As seen in Table 2, the average value of Tobin’s q (q) is 0.93, which means that market value and performance was underestimated However, the values of its minimum and maximum are 0.46 and 2.61 correspondingly, which shows the fluctuation of q in three years Thus, the q in this period has had evident variability

The statistical description of Leverage showing the minimum value of 0.059 and the maximum

of 0.93 illustrates the variation of firms’ preferable level in using debts of construction and material companies There are various companies which prefer using debts to acquire assets; even there are firms to conduct approximately 93 percent of asset acquisition by using credit However, others which tend to restrict to use mortgage in asset investment will have lower financial leverage The input variables Tang1 and Tang2 are the multiplication of Tangibility with code and firm age

of corporations respectively G is calculated by multiplying firm growth and firm age The large range

of these variables shows the diversity of sample that covers the companies have both uptrend and downtrend in average sale and various firms that have high and low asset tangibility ratio in research

period The descriptive statistics of size and the age demonstrate the variety of samples spreading small, medium, and large companies and various ages such as long-standing and new ones

Table 2

Summary of descriptive statistics

4.2 Correlation matrix

Table 3 presents the correlation matrix among the variables used for the multiple regression model to investigate the dependence between multiple variables As indicated in Table 3, Leverage and Tang1 have negative correlation with q while the remainders have positive relationship with Tobin’s q Notably, firm size has a significant relation with q at the 99 percent confidence level Moreover, the correlation coefficients of variables applied to the regression are at the value less than

0.8, which illustrates that the probability of getting multi-collinearity in the model is significant low

Table 3

Correlation matrix

Leverage -0.0493 1.0000

Size 0.1382*** 0.4413*** -0.0181 0.1443*** -0.0259 1.0000

Note: ***, ** and * denote the significance at 99%, 95% and 90% confidence levels, respectively

To provide better understanding on the relationship between Tobin’s q and other factors namely leverage, tangibility, growth, size and age of companies, this research applies econometric models to find out determinants

4.3 Multiple regression

The regression result which illustrates the factors affecting Tobin’s q is shown in Table 4 In the case of listed construction and material companies in Vietnam, the fixed-effects model (FEM) is