Evaluating intangible asset using panel data applying for vietnam listed companies

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES HO CHI MINH CITY THE HAGUE VIETNAM THE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS BY LAI THANH BINH MASTER OF ARTS IN DEVELOPMENT ECONOMICS HO CHI MINH CITY, DECEMBER 2014 A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By LAI THANH BINH Academic Supervisor: Dr LE VAN CHON HO CHI MINH CITY, DECEMBER 2014 This research tends to investigate the effect of intangible assets to company’s performance In this research, some of methodology to evaluate sum of intangible assets will be represented and panel data will be used in model estimation All firms used in practical examination are chosen from 250 Vietnam listed companies standing for different industries Firms in industries could use these results to allocate investment on sum of all intangible assets other than just constructing new factories or opening new brands Estimation shows that intangible asset take a huge proportion on total company asset Intangible asset not only take an important part in the past performance but also explain their role as the key factor of future development When interpreting relationship among kinds of asset and firm’s value, we recognize that intangible asset significantly impact on firm’s added value, however it not show a clarify relationship with firm’s stock price Reason comes from fluctuation of stock market and some external factor affecting to stock price ABBREVIATION M&A: Merger and Acquisition R&D: Research and Development IAS: International Accounting Standard EBIT: Earning Before Interest and Tax CAPM: Capital Asset Pricing Model GSO: Vietnam General Statistics Office WTO: World Trade Organization SBV: State Bank of Vietnam WACC: Weighted Average Cost of Capital TABLE OF CONTENTS CHAPTER INTRODUCTION 1.1 Problem Statement 1.2 Research Objective 10 1.3 Research Questions 11 1.4 Structure of Thesis 11 CHAPTER LITERATURE REVIEW 12 2.1 What Are Intangible Assets 12 2.2 Types Of Intangible Assets 12 2.3 Intangible Asset Valuation Approaches 14 2.3.1 Cost Approach 14 2.3.2 Market Approach 15 2.3.3 Income Approach 15 2.3.4 Panel Data Approach 16 2.4 Conceptual Framework 17 CHAPTER ECONOMETRIC MODEL 18 CHAPTER EMPIRICAL RESEARCH 22 4.1 Data Sources 22 4.2 First estimation: Calculate α and β 25 4.2.1 Consumption 30 4.2.2 Banking 34 4.2.3 Steel Industry 37 4.3 Estimate Cost Function 40 4.4 Compute Firm’s Equity Value 42 4.5 Compute Firm’s Equity Value with Non Intangible Asset 44 4.6 Evaluating Firm’s Intangible Asset 45 4.7 Examine Relationships among Firm’s Revenue, Intangible Asset and Tangible Asset 45 4.8 Firm’s Intangible Asset and Policy Implications 51 CHAPTER CONCLUSION 59 REFERENCE 65 LIST OF TABLES Table 1: Category of Intangible Asset 13 Table 2: Categorized Intangible Assets 22 Table 3: Result of equation using fixed-effects and random-effects model27 Table 4: Hausman test 27 Table 5: Testing for heteroskedasticity using Wald test 27 Table 6: Testing for multicollinearity using VIF index 28 Table 7: Effect of Industry on Firm’s Output 28 Table 8: Estimation with all variables 48 Table 9: Effect of intangible asset and industry development on firm’s added value 48 Table 10: Effect of intangible asset on firm’s added value 49 Table 11: Association among intangible asset, tangible asset, industrial growth rate and stock price 50 Table 12: Association between tangible asset and stock price .50 Appendix 1: Fixed effect estimation without industrial dummy variables 61 Appendix 2: Random effect estimation without industrial dummy variables61 Appendix 3: Random effect estimation with industrial dummy variables 61 Appendix 4: Random effect estimation with industrial dummy variables after adjusted heteroskedasticity 62 LIST OF FIGURES Figure 1: Relationship between distribution channel and business of Masan Group 34 Figure 2: Steel scrap price in period from April 2008 to December 2014 38 Figure 3: Amazing performance of Hoa Sen Group 40 Figure 4: Change of total factor of production (TFP) 46 Figure 5: Ratio of Intangible asset on Total asset 47 CHAPTER INTRODUCTION 1.1 Problem Statement The fantastic merger and acquisition (M&A) stories of famous Vietnam brands make a lot of financial researchers actually confuse According to Kinhtedautu magazine (April 2014), foreign companies bargained these acquisitions at unexpected price, more higher than total tangible assets of these companies, such as Phở 24 (about 20 million dollar) or ICP (higher than 60 million dollar) These businesses raised a question about original source of firm’s intrinsic value Firms are unable to fully evaluate benefit of intangible assets or misunderstood about importance of devoting money on invisible assets Because of these distortions, calculation about operation efficiency and payback period of project or firms could be inaccurate For instant, brand is one of intangible asset and it could make firm’s product sell at higher volume with higher price If analysts not evaluate strength of brand, he could get stuck in some problem with forecasting future revenue There are some reasons why intangible assets have to be correctly evaluated One of these reasons is about unstable characteristic of economy and it is the most important information not only for company’s management board but also for investor’s decision Companies always change themselves, from operating activities to expanding activities, to appropriate with market, if they don’t want to narrower their market share and to lower their income However, general financial statement might be unable to tell us all of company’s effort to change their business According to a research of Baruch Lev and Paul Zarowin (1999), our current report-system such as balance sheet, income statement or cash flow statement deteriorated their usefulness over the past several years A lot of money spends on R&D activities or advertising were not be showed on these statement and just record as expense Secondly, economic situation changes day by day and the firms will hard to keep their customers buying their product if it does not create any interesting thing By this reason, spending money on intangible asset seems to allocate fund on innovative activities Finally, if companies couldn’t appropriately assess value of intangible asset, they might be violated matching concept in accounting standard Each earned revenue need to suitable with expense creating it In addition, valuating intangible asset used to apply on some important sectors including financial reporting, commercial strategy and strategy for development It come to financial purpose, shareholders concentrate on company’s financial position and corporation’s expectation When these factors could be presented clearly, shareholder will be more loyalty with company and cost of equity could be lower also Beside financial purpose, some intangible assets such as brand or intellectual capital also help firm create differential rate of return via increasing customer loyalty and creating differential margin on sale (according to Parble Fernandez (2013)) A famous brand can sell their product at higher price and reduce their cost by negotiating price of input with suppliers In sense of strategy development, according to Mike Rocha (2014), manager of company could plan their investment strategy, how much for factory constructing and what proportion for marketing… After all, demand for measuring value of intangible assets is very clear Furthermore, finding an appropriate method places an important role in intangible asset research As Parble Fernandez (2013) said, we are just at the begin point on the way to evaluating intangible assets Up to now, there are three methods to calculate total value of these assets This research will apply a new method to this job 1.2 Research Objective Specially, this research measures magnitude of intangible asset effect on company performance in different industries This result will help firms decide to allocate their resources in different kind of asset New method, indirect approach using panel data method, will be used to calculate total value of intangible assets for Vietnam selected companies 10 According to Lawrence (May 2012), market power is the ability to generate excess profits of the company from the difference between the price and marginal cost Sources of market power are the difference of the product He concluded, based on research by Bain (1956) suggests that market power is observed as barriers to entry, and barriers to differentiate your product from Without differentiation, products are sold on the market as other products and buyers only interested in choosing the lowest selling price This will lead to the market to equilibrium and eliminate excess profits, not market power exists The difference of products from three main elements and the process is similar to the creation of intangible assets Lawrence indicated some origins formed the difference of products includes: - Resources owned monopoly: This resource can be a source of inputs exclusive, proprietary trade from the government (for example right to provide taxi service in the city) or a patent exclusive Exclusive inputs could be exclusive raw materials or mineral ingredients For example, to obtain inputs such monopoly companies must possess sufficient social capital and financial position, brand’s strength enough to ensure that providers only make business with them Similarly exclusive input, proprietary trade from the government is as well as a component of social capital These intangible assets come from a good relationship between business and government Patent invention is an extremely important asset This property may come from R&D activities, or from the acquisition But overall, a firm holds many patents prove that its leadership focuses on developing long-term orientation These are intangible assets from structural capital (Table 1) - Economic of scale: This is the origin of "natural monopoly" To participate in the industry, enterprises have accumulated an amount of capital needed and thereby create barriers to entry - The size and "sunkeness" of needed Investment: To join the industry, businesses have to spend a huge cost and if not used in this industry, the cost will not be reused for other sectors In other words, the decision to join the industry, businesses must be ready to face a request "sunk cost" very large Entering this market makes the potential business risks and inhibits companies to entry The expenses they facing include the cost of R&D, market research costs, the cost of advertising and promotion, brand building costs In other words, these are cost-intensive industries to invest in relational capital (Table 1) Coke and Pepsi are the best examples Obviously creating a product like Coca-Cola or Pepsi brittle is not too big challenge However, it could not say that their products easily are replaced completely by the other substitute products This is the result of building a strong brand and costly advertising strategy of Coca-Cola and Pepsi Obviously, according to game theory, to be able to survive in the market of Coca-Cola and Pepsi, the potential must now prepare for their financial resources to run its advertising and building up its brand against CocaCola and Pepsi This financial requirement is an actually barrier to entry, barrie of brand name Through the analysis of market power and the source of its formation, the study of Lawrence (1956) has pointed out the close relationship between the intangible assets of a firm's business and possession of market power If businesses want to make a beyond profit from holding market power, the need to next is the development orientation based on the construction of intangible assets Market power is really strong impact on the business of company However, there are many different opinions about its effect on the economy The economists make both good and bad perspective on the impact of market power to the market First, we will look at the negative side of market power Perfect competition market is the most ideal market with the highest level of competition The effect of this is derived from the studies about market structure In this market, the price reaches the optimal value and economic benefit equal to the market rate of return In other words, when fully competitive market, no one can enjoy an outstanding return ratio The story is different for the monopoly market, where competition is eliminated completely In monopoly markets, monopoly corporate has pricing power and output decisions Therefore, a dominant market occurs and they may maintain superior economic benefits in the long term For example, it is the case of Microsoft on the web browser market This firm had repeatedly been accused of monopoly power on this market Directly installing Microsoft Internet Explorer browser (IE) in Windows operating system leaded users to forget the existence of other browsers software In 2004, almost anyone using the Internet must also due to IE web browser software IE market share at this time accounted for 95% Two years later, although other companies had made a lot of effort to improve its products and many new entrants entered this market; IE's market share still remained at 85% This fact shows the power of monopoly power enormous and it is a real barrier to the development of other companies in the same industry Microsoft had created this monopoly by straightly integrating IE in the installation of the Windows operating system The policy makers try to reduce the market power of the monopolies to increase competition from other firms by the antitrust laws This is necessary because the impact of monopolies cause a DWL is very clear The problem of IE has faced strong reactions from countries around the world, because it actually inhibits creativity and new products on the web browser market One example is the punishment from the European market So far, Microsoft suffered multiple litigation involving antitrust laws which applied to both the Windows and Internet Explorer, with total fines of up to nearly 2.2 billion dollars Antitrust efforts bring visible results and make IE lost market share From a big account for most of the market share, in 2013, IE only holded 24% market share and other products constantly increased market share, including Firefox Chrome 35% and 29% However, beside the negative side, market power in its essence brings a very important positive impact To see this effect, we must first distinguish the difference between market power and monopoly power Based on Lawrence (2012), market power is the ability to generate excess profits generated based on differences in products, management and distribution system Meanwhile, monopoly power is a sum sufficient amount of market power In other words, a firm may have market power could only achieve monopoly power when it can maintain market power in a period of time long enough to accumulate sufficient market power needed Clearly, to achieve monopoly power is not simple Speaking to the formation of market power, it refers to the intangible value that is owned by firms The creation of intangible value is not simple To make a difference, or the remarkable improvement in the product, the management or the business methods, the founders have worked very hard to try and go through the great waterfall For example, the case of Bill Gates, to create Microsoft, he had to spend five years working with the duration of 15 consecutive hours per day It is the same in case of Travic Kalanick, founder of Uber He had experienced a lot of previous failures after created a product that are distinctive and have market power Each distinct product will be created and formed a new market and reduce competition from substitute products exist before Superior economic returns, low competitiveness are rewards promoting creativity and innovation in the economy This is the motivation to create resource in the long term growth of the economy, it is technology improvements The idea of technological improvements will bring long-term growth and value-added social welfare has been studied for a long time According to classical economics, D.Ricardo and K.Marx said that technological progress is the main resource for growth, against the diminishing marginal productivity of capital Another question posed, if market power is a source of inspiration for technological improvements and makes a difference in the product, so which elements of market power will be the key? In a study of Schumpeter (1942), he searched the empirical evidence on the relationship between market structure and technological innovation activities Factor structure of the market becomes the main representation of market power The more an industry accumulates market power, the closer it is with monopoly Schumpeter research on the relationship between the concentration in an industry with R&D costs of the firms in the industry He came to the conclusion that, in a competitive market, small businesses are the main means of generating new ideas and innovations to market In contrast, the market concentration, the large business is the key factor for the increase in total output in the long term In the other study, the tests also mainly revolves around two hypotheses: (1) the rate of expansion of firm’s scale often slower improvements generated by it and (2) the relationship covariates speed of technological innovation and market concentration Schumpeter's argument (1942) has faced opposition from the Harvard school of economics, as represented by the study of Mason (1951) He said that the study of the relationship between business size, concentration of market and technological improvements have no clear relationship to each other Conclusion of Schumpeter (1942) offers a challenge to the view of the antitrust laws In a study of Wesley (1989), he gave evidence to prove the fact that all studies of Schumpeter (1942) cannot draw conclusions as had been The reason for this argument is that a business cannot be continuous access to basic resources for technology improvements Wesley gives three factors necessary for technological improvements include: the demand structure, the abundance of potential technological improvements and policy conditions for the interest generated from technology improvements He said that the study of Schumpeter (1942) is not enough data and does not include all the variables needed, thus leading to bias In a study of R.W Vossen (1996), he said that the study of Schumpeter unfinished, but not refute the arguments of Schumpeter Numerous other studies also agree with covariates relationship between industry concentration and costs for R&D activities There are two main reasons given First, firms have market power is concentrated enough internal resources to carry out research and development For the industry focused mainly small businesses, incentive for product innovation and technological development are not so high, so the R&D cost can become a risky investment to dominate business expenses of your business The second reason comes from the impact of the time company could take benefit from innovation, called protect period Almost arguments support the idea that the industry with the high concentration will has the small number of company and has a larger scale Meanwhile, firms perform R&D will face less competition and help to protect more prolonged period Nevertheless, some argue disagree with the views on the covariates between the concentration of industry and R&D activities Economists support this argument that firms in industries with a high concentration will have less incentive to compete, thus less pressure to implement innovative and differentiating products However, this argument is faced with a problem given by Vossen (1996) He said that the economic arguments did not mention the magnitude of barriers to entry If the industry has low barriers to enter, current market forces are facing the potential competitor When the firms in the industry create a profitable enough to attract other businesses involved in the sector, it will create a new competitive force, too Thus, the sector has a higher concentration of industry will tend to spend more improvement activities R.W Vossen (1996) also posed the question about no motivation to improve technology merely from industrial concentration factor? Vossen said that if the motivation to improve technology only for large companies, so why small companies are still born with breakthrough ideas? He also made one more question for the study of Schumpeter (1942) when the variable cost of R&D was used in research According to Vossen, an important issue is not how much the company gives money to the cost of R&D that is how many different products are created When looking at the overall picture of research on industrial concentration and effectiveness of improvement, the actual data is often not the obvious meaning (Weiss, 1963; Allen, 1969;; Scherer, 1965) or even negative results (Williamson, 1965; 1990; Schwalbach and Zimmermann, 1991; Koeller, 1995) about the relationship between industry concentration and effective technological innovations Researchers have used many different variables to represent effective technological improvements, such as growth rate of company, the number of patents, the number of new products announced in the journal The final results showed that the degree of industrial concentration only has the effect on increasing R&D expenses and not related to the effective technology improvements Nooteboom and Vossen (1995) had pointed out in his study of empirical evidence shows that the cost of R&D spent more than the value recorded Additionally, in a study of Nooteboom and Vossen (1996), the authors had shown an interesting result Small businesses have a lot more motivation for innovation and development, at the same time, R&D efforts of small businesses also bring more effective than large companies The reason is in the limitation of small companies funds Small businesses with limited financial resources will have fewer options for R&D activities Therefore, small businesses will choose the project with the highest potential In contrast, for large companies, due to higher financial capacity, so, the selection of investment projects is easier Large firms will therefore have an average rate of return from the project is lower than small businesses, in other words, the efficiency of investment in R&D activities will be lower From these studies, we will go to two policy proposals for two types of market; the market has a high concentration and low concentration The public sector enterprises have focused much more intangible assets will accumulate more and more market power and high concentration These industries will spend costs in R&D but the effect will be limited To improve the efficiency improvement, development direction of the industry need to toward the larger market Larger market means about export markets So, with industries in Figure which have high proportion of intangiable asset in firm’s total asset, such as consumer goods, steel, container etc, government should support them via policies to help these industries accessing to world markets, increase their export business For the industry with small value of intangible assets, the Government should have some special policies with industries which is potential to create more efficient innovation In addition, there should be clear and specific policies to stimulate R&D in these markets, such as financial supporting, free management training for profitable innovations, tax supporting for enterprisers etc These policies should go towards non-financial advantage because of the potential and necesseness of small company’s projects CHAPTER CONCLUSION In conclusion, we clearly see the influence of intangible assets and its rewards for businesses to pursue the development of intangible assets Intangible assets not only bring remarkable profits for businesses but also to create incentives for the sustainable development of enterprises In this paper, panel data are used to value intangible assets in accordance with the indirect approach Results showed that Vietnam companies is mostly decrease economic of scale and can not maintain continuous growth based solely on capital and labor Resources of long-term growth for the companies were expressed through specific TFP calculation The study brought an approach to the valuation of intangible assets and hopes to bring another perspective, more comprehensive studies in this direction The calculations show a very clear picture of the intangible asset allocation between sectors in the economy About the company angle, the paper gives a very clear direction for the allocation of limited resources on the different options The cost for the wrong decision is enormous and if companies want to survive longer in the competitive market, they need an investment perspective that base on the future survival of their business On the macroeconomic policy perspective, the paper combined the previous studies with the calculation of the value of intangible assets to make development-oriented policies These orientations gain flexibility for policy makers The policies not use mass for all individuals in the economy that have the clear classification Through it, the economic effects of macroeconomic policies will larger and minimize the negative externalities for the economy Although based on the advantage of previous studies, this study also exist some limitationa First, the data of Vietnam is studied in the period 2008 to 2012 that is a period of downtrend in the business cycle, so that data should not be tested for recovery phase of economic Second, due to economic policy changes so often, assuming growth rate of economic in the future is only relative In the future, when the businesses will be affected by economic cycles and macroeconomic policies change, these assumptions may be violated and change the regression results However, this limitation can be overcome when the data is more extensive, and this will be the next research orientation of this topic 60 APPENDIX Appendix 1: Fixed effect estimation without industrial dummy variables Coef Std Err t P>t [95% Conf Interval] dlnQ dlnK 0.62 0.05 11.63 0.51 0.72 dlnL 0.24 0.06 3.93 0.12 0.37 _cons 0.65 0.04 14.71 0.56 0.74 F test that all u_i=0: F(213, 404) = 0.34 Prob > F = 1.0000 Appendix 2: Random effect estimation without industrial dummy variables dlnQ dlnK dlnL _cons Coef Std.Err z P>z 0.63 0.04 14.3 0.24 0.05 4.78 0.65 0.04 16.78 [95% Conf Interval] 0.54 0.72 0.14 0.34 0.57 0.72 Appendix 3: Random effect estimation with industrial dummy variables dlnQ dlnK dlnL V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 V19 V20 V21 V22 Coef Std.Err z P>z [95%Conf Interval] 0.63 0.04 14.03 0.54 0.72 0.24 0.05 4.64 0.14 0.34 0.21 0.34 0.63 0.53 -0.45 0.88 -0.25 0.4 -0.62 0.54 -1.04 0.54 -0.61 0.56 -1.1 0.27 -1.71 0.48 -0.28 0.16 -1.72 0.09 -0.61 0.04 -0.02 0.56 -0.03 0.97 -1.11 1.07 0.1 0.56 0.18 0.86 -1 1.19 0.1 0.3 0.33 0.75 -0.49 0.68 0.23 0.44 0.53 0.6 -0.63 1.09 0.03 0.56 0.05 0.96 -1.06 1.13 0.11 0.4 0.26 0.79 -0.69 0.9 -0.2 0.56 -0.36 0.72 -1.29 0.89 0.23 -0.02 0.98 -0.45 0.44 0.14 0.34 0.41 0.68 -0.52 0.8 -0.12 0.34 -0.37 0.72 -0.78 0.54 -0.04 0.4 -0.1 0.92 -0.83 0.75 -0.15 0.56 -0.27 0.79 -1.25 0.94 69 V23 V24 V25 V26 V27 V28 V29 V30 V31 V32 V33 V34 V35 V36 V37 V38 V39 V40 V41 V42 V43 V44 V45 V46 V47 V48 V49 _cons -0.09 -0.08 0.02 0.36 -0.32 0.34 -0.11 -0.17 0.03 0.19 0.2 0.23 0.26 -0.32 0.07 -0.3 0.49 0.11 -0.41 -0.19 -0.01 -0.25 -0.19 0.09 0.03 0.65 0.26 0.26 0.4 0.34 0.44 0.34 0.38 0.56 0.24 0.56 0.18 0.4 0.28 0.3 0.25 0.4 0.36 0.2 0.34 0.34 0.56 0.4 0.2 0.49 0.4 0.23 0.19 0.12 -0.34 -0.31 -0.01 0.05 0.82 -0.95 0.91 -0.2 -0.72 0.06 1.05 0.5 0.81 0.88 -1.26 0.17 -0.85 2.41 0.33 0.01 -0.74 -0.47 -0.05 -0.5 -0.46 0.39 0.14 5.34 0.73 0.76 0.99 0.96 0.41 0.34 0.36 0.84 0.47 0.96 0.3 0.62 0.42 0.38 0.21 0.86 0.39 0.02 0.74 0.99 0.46 0.64 0.96 0.61 0.65 0.7 0.89 -0.6 -0.59 -0.8 -0.65 -0.5 -0.98 -0.4 -1.21 -0.64 -1.06 -0.16 -0.59 -0.32 -0.32 -0.82 -0.72 -1 0.09 -0.55 -0.66 -1.51 -0.98 -0.41 -1.2 -0.98 -0.36 -0.34 0.41 0.42 0.43 0.79 0.68 1.22 0.34 1.08 0.98 0.3 1.13 0.54 0.77 0.85 0.18 0.86 0.39 0.89 0.77 0.67 0.68 0.6 0.39 0.71 0.61 0.53 0.39 0.88 Appendix 4: Random effect estimation with industrial dummy variables after adjusted heteroskedasticity dlnQ dlnK dlnL V7 Robust z P>z [95%Conf Interval] Std.Err 0.63 0.11 5.6 0.41 0.85 0.24 0.1 2.29 0.02 0.03 0.44 0.21 0.13 1.6 0.11 -0.05 0.48 Coef V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 V19 V20 V21 V22 V23 V24 V25 V26 V27 V28 V29 V30 V31 V32 V33 V34 V35 V36 V37 V38 V39 V40 V41 V42 V43 V44 V45 -0.25 -0.61 -0.28 -0.02 0.1 0.1 0.23 0.03 0.11 -0.2 0.14 -0.12 -0.04 -0.15 -0.09 -0.08 0.02 0.36 -0.32 0.34 -0.11 -0.17 0.03 0.19 0.2 0.23 0.26 -0.32 0.07 -0.3 0.49 0.11 -0.41 -0.19 -0.01 0.1 0.04 0.11 0.04 0.05 0.14 0.48 0.07 0.05 0.04 0.07 0.09 0.08 0.09 0.05 0.16 0.06 0.08 0.13 0.34 0.18 0.19 0.07 0.07 0.05 0.07 0.36 0.15 0.09 0.14 0.04 0.36 0.13 0.05 0.1 0.04 0.22 0.08 -2.45 -14.39 -2.58 -0.45 2.05 0.67 0.49 0.47 2.04 -4.56 -0.07 1.62 -1.48 -0.44 -3.28 -0.54 -1.34 -0.05 0.12 1.07 -1.75 1.78 -1.61 -2.36 0.62 2.57 0.57 1.54 3.04 -2.23 1.61 -0.83 3.85 2.47 0.04 -9.41 -0.86 -0.12 0.01 0.01 0.65 0.04 0.5 0.63 0.64 0.04 0.94 0.1 0.14 0.66 0.59 0.18 0.96 0.91 0.28 0.08 0.07 0.11 0.02 0.54 0.01 0.57 0.12 0.03 0.11 0.4 0.01 0.97 0.39 0.91 -0.45 -0.7 -0.5 -0.1 -0.19 -0.7 -0.1 -0.29 -0.14 -0.03 -0.29 -0.21 -0.24 -0.41 -0.2 -0.16 -0.24 -0.3 -0.68 -0.03 -0.25 -0.31 -0.07 0.04 -0.49 -0.06 0.09 -0.6 -0.02 -1.01 0.24 0.02 -0.19 -0.5 -0.62 -0.17 -0.05 -0.53 -0.07 0.06 0.19 0.38 1.17 0.16 0.21 -0.11 0.13 0.31 0.04 0.14 -0.06 0.23 0.04 0.15 0.27 1.02 0.04 0.72 0.02 -0.03 0.13 0.33 0.9 0.51 0.43 -0.04 0.15 0.41 0.74 0.2 0.19 -0.33 0.24 0.16 V46 V47 V48 V49 _cons -0.25 -0.19 0.09 0.03 0.65 0.25 0.08 0.08 0.06 0.04 -1 -2.23 1.04 0.45 14.4 0.32 0.03 0.3 0.65 -0.73 -0.35 -0.08 -0.09 0.56 0.24 -0.02 0.25 0.14 0.74 REFERENCE Asonitis, P A (2009) Intangible assets for academic Library Management, 419429 Dimson, E., Marsh, P., & Stauton, M (2003) Global Evidence on the Equity Risk Premium Journal of Applied Corporate Finance, 27-38 Fama, E., & Kenneth, F (1992) The Cross Section of Expected Stock Return Journal of Finance, 427-465 Fernandez, P (2013) Valuation of brands and intellectual capital IESE Business School, CH25-1 to CH25-19 IFRS 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Non Intangible Asset 44 4.6 Evaluating Firm’s Intangible Asset 45 4.7 Examine Relationships among Firm’s Revenue, Intangible Asset and Tangible Asset 45 4.8 Firm’s Intangible Asset. .. resources in different kind of asset New method, indirect approach using panel data method, will be used to calculate total value of intangible assets for Vietnam selected companies 10 This thesis... between intangible asset and intellectual asset Base on OECD definition, intellectual assets are a part of intangible asset Besides that, intangible asset include three different: “computerized information”;