34 CHAPTER 4 FIDIGS AD DISCUSSIO Descriptives Statistics Descriptive statistics result shows the minimum and the maximum value of each variable and also the mean and standard deviation of the variables. This statistics is used to summarize and explore the important aspects of the data sets (DeFusco 2007, p.62). The descriptive statistics for all variables tested from the 26 sample companies listed in LQ45 will be presented in Table 4.1 Table 4.1 Descriptive Statistics Minimum Maximum Mean Std.Deviation Tobin s Q 130.43 54.07 2.95 5.18 ROA 130-66.73 62.16 9.75 13.63 ROE 130-244.32 84.60 20.78 32.59 Valid 130 ROA = Return on Assets ROE = Return on Equity From the table above, the average Tobin s q of 26 listed companies in LQ45 is 2.95. Which shows that the 26 listed companies in LQ45 have invested in intangible assets. The minimum value of Tobin s q is the coefficient for TimahTbk. in 2008; this is due to 35
35 the fell of its share price from Rp 28,700.- in 2007 slumped into Rp 1,080.-in 2008 affected by the global financial market crisis. International ickel Indonesia Tbk.reached the maximum value of Tobin s q in 2007 due to the high share price in 2007 (Rp 92,500.-). Bakrie and Brothers Tbk. attained the minimum value for both Return on Assets and Return on Equity in 2008. The company reached -66.73% in Return on Assets and - 244.32% in Return on Equity. Global economy crisis has had significantly affect the company s performance. The drastic drop in share prices and the income loss of Rp 15, 855 billion is main cause of the fell of their Return on Assets and Return on Equity. For the maximum value of Return on Assets and Return on Equity, International ickel Indonesia Tbk. held the record of being most profitable company from the 26 companies in the sample with the return on assets reached 62.16% and return on equity reached 84.60%. Being one of the main supplier of nickel in the world and due to the global demand of nickel in the year of 2007 which resulted high income profit and the extreme increase in their share price. The mean column show the average value of the variables. Among the three variables, Return on Equity has the highest mean variable. High Return on Equity means that the company utilizes its equity effectively to generate profit. Moreover, Return on Assets also has the highest standard deviation value. Standard deviation in descriptive statistics measures the spread of a set observations, the larger the standard deviation means the more the observation are more spread out.
36 ormality Tests ormality test aims to test whether the three variables used in this paper have a normal distribution or not. Hypothesis: H 0 = Data is normally distributed H 1 = Data is not normally distributed Tobin s Q ROA ROE 130 130 130 ormal Parameters Mean 2.95 9.75 20.78 Std. Deviation 5.18 13.63 32.59 Most Extreme Absolute.323.185.214 Differences Positive.295.143.160 egative -.323 -.185 -.214 Kolmogorov-Smirnov Z 3.687 2.114 2.434 Asymp.Sig (2 tailed) 0.000 0.000 0.000 Table 4.2 Kolmogorov-Smirnov Test for 26 listed companies in LQ45 If sig < 0.05, H 0 is rejected If sig > 0.05, H 1 is accepted
37 Based on the result of SPSS output above, it can be seen that Tobin s q, Return on Assets, Return on Equity have significant value lower than 0.05. H 0 is rejected which means the data is not normally distributed. Given that the data is not normally distributed, the author will use a non-parametric test that it is applied when the data is not normally distributed. on-parametric test is necessary when the data have a ranking but does not have a clear numerical interpretation. For correlation analysis, the author will use Spearman s rank correlation because it is more efficient analysis for not normally distributed data. 4.3 Spearman s rank Correlation Analysis Spearman s rank correlation analysis is a non-parametric correlation analysis. onparametric can be described as distribution free test, where it does not require the assumption for data to be normally distributed. The strength of the association between two variables can be analyzed with ranging from the value of -1 < r < 1. The result of -1 means that the association between two variables is negativelyassociated, 0 means that there is no association between the variables, and 1 is strongly associated.
38 Table 4.3 Coefficient Interval and Level of Correlation Coefficient Interval Coefficient Level 0.01-0.199 Very Weak 0.20 0.399 Weak 0.40 0.599 Medium 0.60 0.799 Strong 0.80 0.999 Very Strong Hypothesis: H 0 = There is no association between two variables H 1 = There is a association between two variables The correlation coefficient between two variables needs to be tested based on the significant value of: Sig(t) > 0.05, H 0 is accepted Sig(t) < 0.05, H 0 is rejected
39 Table 4.4 Spearman Correlation Tobin s q and Return on Assets Tobin's Q ROA Tobin's Q 1,000,640(**).,000 130 130 ROA,640(**) 1,000,000. 130 130 ROA = Return on Asset Table 4. 5 Spearman Correlation Tobin s q and Return on Equity Tobin's Q ROE Tobin's Q Association Coefficient 1,000,465(**).,000 130 130 ROE Association Coefficient,465(**) 1,000,000. 130 130 ROE = Return on Equity The author used Spearman test to test the association between Tobin s q as a proxy for intangible assets and company s profitability (ROA and ROE) to see whether Intangible assets has positive association with company s profitability. Based on the table above,
40 the association between Tobin s q and ROA has the value of 0.64, which indicates a strong association between the two variables. With a significant value 0.000, it means that there is a significant association between Tobin s q and ROA. The association between Tobin s q and ROE has a value of 0.465, indicating that there is a moderateassociation between Tobin s q and ROE. The significant value of the two variables is also 0.000, means that the association between Tobin s q and ROE is significant. Consequently, the result supports the author s hypothesis where there is a positive association between intangible assets and company s profitability. This result also support previous study by Belen Vilallonga (2004),which proved that there is a positive association between intangible assets and company s profitability 4.4 Association Within Industry According to Belen Villalonga (2004), the impact of intangible resources on the performance of the company differences across firms is most likely to differ by industry. The main reason that cause the differences that occur among industries is the difference of their source of advantage which is their intangible assets are mostly different in the nature of their business.
41 4.4.1 Mining Industry Table 4.6 Spearman Association Tobin s q and ROA in Mining Industry ROA ROA 1,000,492**.,003 35 35,492** 1,000,003. 35 35 Table 4.7 Spearman Association Tobin s q and ROE in Mining Industry * ROE ROE 1,000,346*.,042 35 35,346* 1,000,042. 35 35 Mining industry plays a very important role in Indonesian economy. Indonesia is one of the major suppliers of coal mining, nickel, crude petroleum, metal and mineral mining. In mining industry, there are four major activities: exploration, development and construction, production and refinery. The result from the association shows the association of Tobin s q and ROA in mining industry has a value of 0.492 indicating a medium positive association, with a significant value of 0.03, which means that there is significant association between Tobin s q and ROA in mining industry. For the association between Tobin s q and ROE has a value of 0.346 indicating a weak association. With a significant value of 0.042, still indicating that the association of
42 Tobin s q and ROE in mining industry is significant. This result shows that the association between intangible assets and industry s profitability is relatively moderate. 4.4.2 Agriculture Industry Table 4.8 Spearman Association Tobin s q and ROA in Agriculture Industry * ROA ROA 1,000,607*.,016 15 15,607* 1,000,016. 15 15 Table 4.9 Spearman Association Tobin s q and ROE in Agriculture Industry ROE ROE 1,000,243.,383 15 15,243 1,000,383. 15 15 Agricultural sector covers plantation, forestry, fishery, and animal husbandry. This industry essentially deals with biological transformation of plants and animal to be processed into consumer products. From the result of Spearman association between Tobin s q and ROA in agriculture industry, it shows a value of 0.607 and a significant value of 0.016. This means that there is a significantstrong association between Tobin s q and ROA. However, based on Table 4.9Theassociation value of Tobin s q and ROE
43 has the value of.243 and a significant value of 0.383. This result indicates that there is no significant association between Tobin s q and ROE in agriculture industry. 4.4.3 Banking Industry ROA ROA 1,000,308.,134 25 25,308 1,000,134. 25 25 Table 4.10 Spearman Association Tobin s q and ROA in Banking Industry ROE ROE 1,000,355.,082 25 25,355 1,000,082. 25 25 Table 4.11 Spearman AssociationTobin s q and ROE in Banking Industry Based on the result in table 4.10, the association coefficient of Tobin s q and ROA has value of 0.308, while its significant value is 0.134 which is higher than 0.05. Therefore, it accepted the hypothesis where there is no association between Tobin s q and ROA. For the association of Tobin s q and ROE, it also shows that there is no association between the two variables with the association coefficient of 0.352 and a significant value of 0.082. These results indicate that there are no association between intangible assets and company s profitability in banking industry.
44 4.4.4 Infrastructure Industry ROA ROA 1,000,337.,147 20 20,337 1,000,147. 20 20 Table 4.12 Spearman Association Tobin s q and ROA in Infrastructure Industry ROE ROE 1,000,334.,150 20 20,334 1,000,150. 20 20 Table 4.13 Spearman Association Tobin s q and ROE in Infrastructure Industry Infrastructure industry covers telecommunication, transportation, construction, toll road, airport and harbour. The telecommunication sector provides telecommunication service and network in national and international area. For the transportation sector is to provide transportation service by air, land or sea. Based on the result of the association between Tobin s q and ROA, it shows that the association coefficient has a value of 0.337 and a significant value of 0.147 means that there is no significant association between Tobin s q and ROA in infrastructure industry. The result of the association between Tobin s q and ROE also shows that there is no significant association since the significant value is
45 greater than 0.05. Therefore, it leads to the conclusion that there is no association between intangible assets and company s profitability in infrastructure industry. 4.4.5 Consumer Goods Industry ROA ROA 1,000,925**.,000 15 15,925** 1,000,000. 15 15 Table 4.14 Spearman Association Tobin s q and ROA in Consumer Goods Industry ROE ROE 1,000,911**.,000 15 15,911** 1,000,000. 15 15 Table 4.15 Spearman Association Tobin s q and ROA in Consumer Goods Industry Consumer goods industry is included in manufacturing business since it process raw materials into finished goods. This industry covers food and beverage, tobacco manufacturers, pharmaceutical, cosmetic and house-ware. From the 26 listed companies in LQ45, the companies included in consumer goods industry is Unilever Tbk., Kalbe FarmaTbk., and Indofood Tbk. It has been recognized that brand names are very valuable in creating profits and these companies are well known in having a certainly high brand valuation, since in consumer goods industry the point of difference in their
46 product is branding. From the result we can see that the association coefficient between Tobin s q and ROA has a very strongassociation with a value of 0.925 and a significant value of 0.000. This indicating that there is a significant very strongassociation between Tobin s q and ROA. The same with the association between Tobin s q and ROE, the association coefficient has a value of 0.911 and a significant value of 0.000. This means that there is a significant association between Tobin s q and ROE. This result supports previous empirical study by Simon and Sullivan (1993), which proved that brand equity is highly correlated with company s profitability. 4.4.6 Trade and Service Industry ROA ROA 1,000,588.,074 10 10,588 1,000,074. 10 10 Table 4.16 Spearman Association Tobin s q and ROA in Trade and Service Industry ROE ROE 1,000,685*.,029 10 10,685* 1,000,029. 10 10 Table 4.17 Spearman Association Tobin s q and ROE in Trade and Service Industry
47 In trade and service industry, there are wholesale, retail trade, hotel and tourism, restaurant, advertising, printing and media, healthcare, computer and other investment companies. Being service industry, there should be a high association between intangible assets and company s profitability in this industry. However, looking at the result it indicated that there is no significant association between Tobin s q and ROA because the significant value is greater than 0.05. On the other hand, the association coefficient between Tobin s q and ROE has a value of 0.685 and a significant value of 0.29, which point out that there is a significant strong association between Tobin s q and ROE in trade and service industry in Indonesia.
48 4.4.7 Miscellaneous Industry ROA ROA 1,000,418.,229 10 10,418 1,000,229. 10 10 Table 4.18 Spearman Association Tobin s q and ROA in Miscellaneous Industry ROE ROE 1,000,406.,244 10 10,406 1,000,244. 10 10 Table 4.19 Spearman Association Tobin s q and ROE in Miscellaneous Industry Miscellaneous industry includes machinery and heavy equipment, automotive and components, textile, electronics and cable. Miscellaneous industry is similar to manufacturing industry where it produced finished goods through industrialized processes. From the result we can see that there is no significant association for both association between Tobin s q and ROA, and also between Tobin s q and ROE since both association has a significant value over 0.05. Therefore, it can be concluded that there is no association between intangible assets and company s profitability in miscellaneous industry.
49 4.5 Research Questions and Answers In this research, the author is going to answer two questions regarding intangible assets and profitability of a company. Hence, the research questions and the respected answers are explained below. 4.5.1 It is generally believed today that an intangible asset isassociated with company s profitability. Is that true in Indonesia? Questions Does Tobin s q has association with ROA? Does Tobin s q has association with ROE? Results YES YES Based on the result above, it can be seen that Tobin s q as a proxy for intangible assets is positively correlated with both Return on Assets and Return on Equity. According to the result of Spearman s rank association analysis in table 4.4 and 4.5, the author found that intangible assets has a strong effect towards company s return on asset with a significant association coefficient of 0.640 with ROA and 0.465 with ROE. This result indicates that in Indonesia, intangible assets have started getting attention from companies and management. Through out the year 2005 until 2009, Tobin s q from each company in LQ45 has increased though from 2007 to 2008 the Tobin s q had a fall down, but it bounced back in the year 2009. From these results, the answer to the question above is yes, that in Indonesia intangible assets is proven to be associated with company s profitability. These results support prior studies by Chaeronsuk and Chansa (2008), Belen Villalonga (2005), Johnson and Kaplan (1987), Itami (1987) where they stated
50 that intangible assets is one of the main driver of economy and has a positive relationship with company s profitability. 4.5.2 Does association between intangible assets and company s profitability vary across industry? The answer to this question is yes, the association between intangible assets and company s profitability across industry vary. The most outstanding result of the association is in consumer goods industry where the association coefficients with both ROA and ROE have a significant value above 0.90. This result shows that intangible assets hold a very important role in creating profits in the consumer goods industry.