Application of an intangible asset valuation model using panel data for listed enterprises in Vietnam

Intangible assets play an important role in increasing the value of companies. The performance of companies increasingly depends on ideas, information, and professional services rather than tangible assets. The question of how to accurately measure intangible assets remains a challenge for many scientists. This study aims to measure intangible assets of 396 companies listed on Vietnam’s stock market between 2010 and 2014 using the panel data technique by Yamayuchi (2014). The estimation shows that intangible assets make up a large share of total assets of companies. In addition, construction, steel, building materials, mining, and food are sectors with high intangible assets in Vietnam. The study also finds a positive impact of intangible assets on improving company performance. The findings demonstrate the importance of investing in intangible assets, such as R&amp;D, technology, advertising, and human resources, to increase the value of a company in the future.


INTRODUCTION
Intangible assets are increasingly playing an important role for any company that wants to conduct production (Sveiby, 2010). Intangible assets are assets that do not have a specific physical form, such as a company's reputation, culture and value, brand name, technology, etc., but can make a significant contribution to creating business value (Osinski, Selig, Matos, & Roman, 2017). As a result of recent mergers and acquisitions, foreign companies have acquired Vietnamese companies at a higher price than total tangible assets of these companies. For example, Pho 24 was purchased by Highlands Coffee for USD 20 million, and ICP was sold for more than USD 60 million for Marico. An important question that should be addressed is: Where does the source of a firm's intrinsic value come from? It is due to intangible assets. These assets are one of the key sources of comparative advantages for companies (Boujelben & Fedhila, 2011). They also help companies to have better brand image and build customer loyalty (OECD, 2008). These assets widen the market value and increase the profit of a company (Jhunjhunwala & Mishra, 2009;Bhatia & Aggarwal, 2018). Although intangible assets are the primary source for the company performance, it is not easy to define and measure them. This is because these assets are not fully recorded in the balance sheets, and there is a lack of consistent data and definition. Previous studies show that researchers have not fully measured intangible assets. Bosworth and Rogers (1998) and Ehie and Olibe (2010) considered R&D as intangible assets in their research. Kundu, Kulkarni, and NK (2010) used advertising intensity as a proxy for intangible assets. Therefore, there is a need to use a better methodology to fully measure every aspect of intangible assets. This paper employs a valuation model using panel data from Yamaguchi (2014) to quantify intangible assets of 396 companies listed on Vietnam's stock market from 2010 to 2014. In addition, the impact of intangible assets on firm's performance and stock prices is also examined.
The study contributes to the current literature on intangible assets in several ways. First, it employs a comprehensive measure for intangible assets, which is applied to test the relationship among intangible assets, firm performance and stock prices. The valuation model for intangible assets employs unobserved firm-specific effects based on a panel analysis to fully measure all aspects of intangible assets. Intangible assets have attracted a lot of public attention; their valuation is extremely crucial to provide information for researchers, managers, investors and creditors. Second, most of intangible asset studies concentrate on developed or industrialized countries, and there is very little research on emerging economies. As pointed out by Kamal (2011, p. 21), "specific research into emerging markets is necessary, since the unique characteristics of emerging economies may prove many of findings in developed economy settings invalid in an emerging economy setting". In this context, the paper is the first evidence on the role of intangible assets in firm performance in Vietnam -an emerging country with rapid economic growth rates in recent years. Third, the paper confirms the prediction of an efficient financial market theory and a resource-based theory in the context of an emerging economy. Finally, the research proposes the practical implications to managers and executives to make decisions in the competitive business arena.
The remainder of the paper is structured as follows. Section 1 provides a literature review of intangible assets. Section 2 describes data and the methodology, while Section 3 presents results. The last section concludes the paper.

Definition of intangible assets
There are many definitions of intangible assets due to different perceptions about them. The International Accounting Standard Board, Standard 38 (IAS 38), defines an intangible asset as "an identifiable non-monetary asset without physical substance. An asset is a resource that is controlled by the entity as a result of past events and from which future economic benefits are expected to flow to the entity" (IAS 38,1997). According to this definition, computer software, patents, copyrights, licenses, motion picture films, customer lists, fishing licenses, and import quotas are considered as intangible assets. Goodwill that is obtained in a business combination is not recognized as intangible assets according to the IAS 38 scope. Goodwill that is generated internally belongs to the scope of IAS 38 but is not accounted as an asset, since it is not an identifiable resource. The costs of creating an intangible asset in a company are difficult to differentiate from the costs of maintaining or improving the entity's operations or goodwill. As a result, internally generated brands, mastheads are not considered as intangible assets. Research spend-ing is considered as an intangible asset. In addition, development spending that satisfies specified criteria is considered as the cost of an intangible asset. An intangible asset with a finite life will be amortized and it is subject to impairment testing. An intangible asset with an indefinite life will not be amortized, but it will be tested yearly for impairment. In addition, the IASB framework considers an intangible asset as future economic benefit gained by a particular entity due to transactions in the past. OECD (2011) states that "intangible assets are assets that do not have a physical or financial embodiment". OECD (2011) distinguishes the concepts of an "intangible asset" and an "intellectual asset". From their point of view, an intellectual asset is a part of an intangible asset. Intangible assets consist of three different parts, namely, innovative property, computerized information and economic competencies.

Approaches to the assessment of intangible assets
Traditionally, there are three approaches to measure intangible assets, including: (i) cost approach, Employing costs in the past would bring many difficulties in calculating the depreciation. In addition, another problem of the cost approach is that it does not consider profits created by these assets (Yamayuchi, 2014). The income approach uses the methodology of discounted cash flow to evaluate intangible assets, which are based on income or expenditure data. This approach will discount the future benefits that are created with intangible assets to present value. One of the problems with this approach is that one cannot exactly estimate the future profits of firms. The market approach employs sales information of similar assets traded in the market. This approach is also considered as a "sales comparison" approach. The main problem with this approach is that it requires an active market, and assets are sold at fair prices.

Panel data approach
Panel data approach uses unobservable firm effects with panel analysis (Yamayuchi, 2014). Unobservable firm effects are explained as unobservable factors, such as technology innovation, employee motivation, management ability, and R&D costs (Motohashi, 2005). The panel data approach of Yamaguchi (2014) is based on the idea of measuring the production function and developing the cost function with a duality approach to calculate equity of a firm. Next, the added value and costs are discounted to estimate intangible assets. The panel data model from Yamaguchi (2014) also combines the income approach. One of the advantages of the model is that it allows us to compute the profits resulting from intangible assets. In addition, the weakness of the market and cost approaches is solved.
Lev and Radhakrishnan (2003) developed a production function to interpret firms' sales growth based on rising production inputs. Capital, labor, R&D and total factor productivity are included in the regression function with panel analysis. Ramirez and Hachiya (2006) also defined a regression model with panel analysis to interpret sales growth and the market value of equity with inputs such as R&D and general administrative expenses. In the research of total factor productivity as an impact of an organization capital, Sadowski and Ludewig (2003) use a similar method for panel analysis to assess the production function with firm value added as a dependent variable. Production factors, such as capital, labor, human capital, and social capital, are included as independent variables. The added value that can be obtained from organization capital is discounted with the risk-free rate to determine the asset value. Yamaguchi (2014) also uses the panel data analysis with fixed effect as effects of intangible assets, but Yamaguchi's (2014) valuation method differs from previous studies in calculating corporate asset values by discounting costs and obtaining value added from intangible assets.

Theoretical framework
This paper is based on two important theories that are relevant to the effect of intangible assets on a firm's value added, profits and stock prices. These theories are an Efficient Market Hypothesis Theory and a Resource Based Theory.

Efficient Market Hypothesis
According to the theory of efficient financial markets, stock prices reflect all available information of the stock, and price valuation varies if investors have new data about the expected future cash flow of a company (Malkiel & Fama, 1970). The efficient market would provide accurate signals for resource allocation, as market prices are a representative of each stock intrinsic worth. Malkiel and Fama (1970) classified market efficiency into three forms: (i) weak form, which is based on information on historical data, (ii) semi-strong form is based on the information of public data, and (iii) strong from is based on private information (or insider information). Since the information on intangible assets is not reported in public financial statements, all intangible assets internally generated are considered as private information. Specifically, intangible assets are reflected in the financial statements of a firm only if they are acquired assets and assets with identifiable value and useful lifespan, which is, therefore, can be amortized. Internally developed intangible assets are not registered in the financial statements. This is because these assets were developed internally and have no price. The theory of an efficient market hypothesis is relevant for this study, since it helps to explain that the increase in stock prices is a result of the growth of intangible assets. This discussion leads to the first hypothesis: H1: Firms with higher intangible assets have higher stock prices.

Resource-based theory
According to the resource-based theory, intangible assets are considered a key factor explaining the sustainability of companies (Villalonga, 2004).
The theory provides an explanation of the competitive advantage of firms in 1980s and 1990s thanks to major publications by Wernerfelt (1984), Porter (1991), Grant (1991), and Barney and Clark (2007). The scholars supporting this theory suggest that we should look inside the firms to explore their sources of competitive advantage. Itami (1987, p. 1) pointed out that "intangible assets, such as a particular technology, accumulated consumer information, brand name, reputation and corporate culture, are invaluable to the firm's competitive power. In fact, these invisible assets are often the only real source of competitive edge that can be sustained over time". The theory also predicts the role of intangible assets in achieving better firm performance by saying "the more intangible resources a firm has, the greater the sustainability of its competitive advantage" (Itami, 1987, p. 1). Lev and Sougiannis (1996) state that R&D investments will enhance firm's profits in the future. This theory is relevant to the current study because it suggests that firms with higher intangible assets will achieve higher profitability and firm value. This discussion leads to the second and third hypotheses: H2: Firms with higher intangible assets have higher profitability.
H3: Firms with higher intangible assets have higher value added.

Previous empirical studies
For decades, scholars have been examining the impact of intangible assets on firm performance. However, the relationship between intangible assets and firm performance is still ambiguous. Some authors have found a positive influence of intangible assets on firm performance ( (Darabi & Vojohi, 2013), and other researchers simply calculate intangible assets as the difference between market value of equity and book value of equity (Salamudin, Bakar, Ibrahim, & Hassan, 2010). Therefore, we need a comprehensive method for intangible assets valuation that captures every aspect of intangible assets. In Vietnam, the research gap is even wider. Therefore, this paper is designed to fill the research gap by using the panel data approach from Yamayuchi (2014) to measure intangible assets and then examine their impact on firm performance.

Model description
To evaluate intangible assets based on Yamaguchi's method, this study starts with the Cobb-Douglas (1928) production function: where it Q is the value added of firm i in year , Parameter a i in equation (1) describes the impact of technology (or total factor productivity) on value added Q rather than other production factors. The factors include know-how, motivation of workers and sale power (Yamaguchi, 2014). In general, a i is the impact of intangible assets on growth rates of firms. The impacts of intangible assets a i can be divided into company-specific effects i A and growth rate λ of industry h in time . β However, there is no value of . i A it is necessary to take the differential of equation (4) where ( ) d  is the difference form of variables.
The profit π function has the following formula: --.
The profit of firm i th in year t can be computed: The cost function based on duality approach can be identified. Duality approach is a basic concept of microeconomics to specify cost function and production function. This concept has been discussed by Samuelson (1947), Fuss and McFadden (1978). According to the duality approach, firms can produce products by combining production factors to minimize costs. To make his model simpler, Yamaguchi (2014) replaced β with 1, α − and he assumed that firms had constant returns to scale. This paper does not assume a type of economy of scale at the beginning. Therefore, the cost function is different from that of Yamaguchi (2014): The intangible asset's value from equations (13) and (14) can be computed:

First estimation:
Compute α and β Equation (6) is employed to estimate α and β. The data on companies will be classified by sectors based on the industry division of the General Statistics Office. There are 47 industries, and 46 dummy variables are created for the regres-sion model. Panel data regression with fixed and random effect models is used. Hausman test shows that the random effect model is more appropriate that the fixed effect model. An industry dummy is also included to examine the effect of the industry growth rates on company performance. The "robust" command in Stata is used to eliminate the problem of heteroskedasticity. In addition, the VIF value is smaller than 10. It means that there is no multicollinearity in the model.
The regression results of equation (6) show that coefficients α and β are similar in three regression equations. The regression results of the random effects model with the dummy variable of the industry show that the sum of coefficients α and β equals 1. It means that Vietnamese listed enterprises have constant returns to scale. It means that when firms double their capital and labor, operating profit turnover will double. Table 3 presents the results for top 10 industries with highest intangible assets, including construction, steel and steel products, mining, and food, while Table 4 provides top 10 firms in Vietnam by intangible asset value.

Assessment of the impact of intangible assets on firm performance
The impact of intangible assets on value added of firm, EBIT (earnings before interest and taxes) and stock price is examined. In the authors' regression models, tangible assets, intangible assets and industry growth rates (lamda) are added as independent variables.
The regression results from Table 5 with the random effects model show that intangible assets have a positive and statistically significant impact on firm value added. Therefore, H3 is accepted at the 1% level of significance. When the value of intangible assets increases by 1%, the added value of a company will increase by 0.92%. The finding supports the Resource Based Theory that states that intangible assets are considered as key factor that explains firms' sustainability. These findings   Note: * shows the 1% level of significance, ** shows the 5% level of significance, and *** shows the 10% level of significance.
are new in the context of emerging economies, but are consistent with the previous research findings in the developed economies (Bae & Kim, 2003;Ehie & Olibe, 2010). It is important to note that intangible assets have a greater contribution to the value of a company than tangible assets. The finding is consistent with Kamasak (2017) who investigates the contribution of tangible and intangible resources and capabilities to Turkish firms' performance. The authors find that intangible resource contributes more to firm performance than tangible resource.
The regression results from Table 6 show that only intangible assets have a positive and statistically significant impact on earnings before interest and taxes (EBIT). Specifically, if the value of intangible assets increases by 1%, EBIT of firms will increase by 1.03%. Therefore, H2 is accepted at the 1% level of significance. One can see that intangible assets 1 The information is collected from http://blog.trginternational.com play an important role in increasing the profits of companies. Intangible assets provide firms with competitive advantages and help them to achieve future profitability. The finding is similar to that obtained by Bhatia, Khushboo Aggarwal (2018). In addition, this result is similar to the research of Ocean Tomo Consulting Company 1 , which concluded that intangible assets currently account for more than 80% of the market value of S&P 500 companies. Similarly, a study by McKinsey Group showed that intangible assets helped firms increase profits by 31% compared to firms without intangible assets. This is evident in supporting Resource Based Theory in the context of emerging markets. Table 7 presents the results of the impacts of tangible and intangible assets on company's stock price. In fact, there are many factors that can affect the stock price of a company, includ- Note: * shows the 1% level of significance, ** shows the 5% level of significance, *** shows the 10% level of significance.

CONCLUSION
It is well-documented that intangible assets play an important role in enhancing firm performance. The performance of companies increasingly depends on ideas, information, professional services rather than tangible assets. However, the empirical question of how to conduct an accurate measurement of intangible assets remains a challenge for many scholars. Previous studies show that intangible assets are not fully measured. Many scholars use R&D investment as a proxy for intangible assets (Bosworth & Rogers, 1998;Ehie & Olibe, 2010), while others employ advertising intensity as intangible (Kundu et al., 2010). Therefore, there is a need to use a better methodology to fully measure every aspect of intangible assets. The paper measures intangible assets of 396 enterprises listed on Vietnam's stock market by using the panel data method from Yamayuchi (2014) in the period of 2010-2014. The production function is first estimated and then the cost function of firms is constructed.
In the next step, the study computes the value of company's equity and the equity of a company with tangible assets. The value of intangible assets is calculated by subtracting the value of equity of the total assets to equity value of firms without intangible assets. The results show that construction, steel, building materials, mining, and food are the industries with high intangible asset value in Vietnam. The positive impact of intangible assets on enhancing firm performance is also found.
This study extends the intangible assets literature in several ways. First, it provides new evidence on the impact of intangible assets on firm performance in the context of Vietnam, an emerging market with rapid economic growth rates. Second, the results confirm the theoretical prediction in the context of an emerging market. According to the efficient financial markets theory, stock prices reflect all available information on the stock, and price valuation varies if investors have new information on the companies' expected future cash flows. The evidence from Vietnamese firms suggests that an increase in stock prices of listed companies is a result of an increase in intangible assets. The findings also confirm the prediction of resource-based theory, which states that intangible assets are considered a key factor that explains firm sustainable performance of. Third, the research finding implies that managers of companies should take into account the importance of intangible assets for improving firm performance. Therefore, they should invest more in R&D activities, technology, advertising, brand name, reputation and human resources to enhance the value of a firm in the future.
The paper has some limitations. First, the problem of an omitted variable may arise in this study. Due to the data availability, the study only includes tangible assets, intangible assets and industry growth rates as independent variables. Future research should consider other variables that represent firm characteristics, such as firm age and firm size, which may affect firm performance. Second, the study period is limited from 2010 to 2014. Therefore, further research in Vietnam should extend the study period to examine the relationship between intangible assets and firm performance.