Soumendra K. Dash, [email protected] African Development Bank, HQs, Tunisia
Dhekra Azouzi, [email protected] Tunis El Manar University, Tunisia
An Empirical Analysis to Assess Intangible Assets in Tunisia and Its Relevance in the Knowledge - Based Economy
Abstract
It is the first work to measure intangible investment in Tunisia based upon the CHS methodology and different databases and statistics. Expenditures on intangibles in Tunisia amounted to around 11 billion US dollar, accounting for around 25% of GDP in 2008. This paper attempts to find out how important intangible assets are in the present knowledge based economy like Tunisia. Intangible assets are country’s weightless wealth which helps to obtain real growth and real profit for a company. Every country should understand that paying needed attention to knowledge management in general and to intangible assets especially may help to understand and nurture its core strength and competencies. This is how each developing and underdeveloped countries can create their own competitive advantage in the world market. More precisely, the country’s intangible assets should be priced at fair market value. The strategic relevance of intangible assets management for a country’s competitiveness, understanding the way these assets are converted into value is of paramount importance. It is very vital for the country to harness the value from its intangible assets. The further research in this field will develop not only the direction of testing researched models but also the direction of developing and testing other models of intangible assets valuation, management and optimal allocation of intangible assets in various countries.
1. Introduction
In today’s economy, the intangible assets play a key role and have become very important in achieving sustainable development. The developed economies are becoming knowledge based economy. These intangible assets are generally obtained from traditional factors like labour, land and capital. However, the differentiating factors among the developing and developed countries have been the quality of knowledge management and innovation management. The main characteristics of innovation based economies are: knowledge replaces traditional factors of production land and labour as the fundamental factors of production. Intangible assets create a significant part of the value differentiator between countries. Intangible assets are non-physical sources of value generated by discovery, unique organisation designs, or rare human resource practices. These are non-material sources or creating country’s value based on the cities capabilities, organisations’ capabilities. They are non-physical in nature, they are capable of producing future economic benefits, and they are protected legally through intellectual property rights. The country like Tunisia has been able to harness economic benefits significantly in the past but the momentum has been lost due to changing socio-economic and political priorities
. 2. Measurement of investment in intangibles
Various definitions of intangible capital are associated to various approaches to measuring intangibles: on the one hand, definitions of intangibles are mostly due to Schumpeter’s classification based on product and process development, organizational change, management, marketing and finance (Schumpeter 1934). However, despite this great variety in defining intangibles, the common and durable problem is the ‘invisibility’ of many of these intangible assets which makes their measurement difficult. On the other hand, According to Sichel (2008), there are three recent approaches that can be used to measure intangibles; these approaches are the financial market valuation (Hulten et al., 2008), the alternative performance measures (Cummins, 2005) and the direct expenditure approach (Nakamura, 1999 and 2001). The latter approach was adopted By Corrado, Hulten and Sichel (CHS 2005; 2009) who developed a wide array of expenditure based measures for many intangibles employed by American firms and distinguished between three categories of intangible assets: computerized information, innovative property, and economic competencies.
Originally, the CHS method was applied to American data and it has now been the corner stone of many studies focused on different countries.
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We use the same methodology as CHS (2005; 2009) for Tunisia for the purpose of creating a set of estimates for intangibles in Tunisia. It is worth to note that for some intangibles, it has been very difficult to construct reliable measures over time and it has been compulsory to make a number of assumptions to cope with the limited available information. Our estimates are a starting point in this area of study as it is the first attempt to apply the CHS methodology to measure intangibles in Tunisia.
2.1. Computerized Information
According to Corrado et al. (2005), computerised information consists of two elements: software and computerized database. In other terms and according to Miyagawa & Hisa (2013), ‘Computerized information consists of custom and packaged software, and own account software’. For the custom and packaged software, we have no indication about how to calculate their value. That’s why; we assume that this expenditure is about 35% of the total Information and communication technology (ICT) expenditure. These data is obtained from World Bank. However, we have total Information and communication technology expenditure per capita; to obtain the total of these expenditures for the whole population, we multiply the ICT expenditure by the population.
Since spending on software is not capitalized in the Tunisian System of National Accounts, we use the Miyagawa & Hisa’s (2013) estimation method inspired from the JIP database. Hence, we begin by estimating the number of workers who are involved in the development of software for their own firms and their salaries to be able to assess the value of own account software. These data are obtained from the World Bank and the National Institute of Statistics (INS); the number of these workers is available for a period of four years spanning from 2005 to 2008, but we have the wage data only for 2007, this salary is in Tunisian dinars and we have to convert it in US dollars. In these conditions, we have assumed that the average monthly salary of each worker does not fluctuate from 2005 to 2008. The next step is to multiply the number of workers by the annual salary to obtain an estimation of the own account software investment.
2.2. Innovative Property
Two categories of innovative property: research & development and oil & gas & mineral exploration. These data are available from the World Bank and the National Institute of Statistics (INS). However, data extracted from INS are in Tunisian dinars and should be converted in US dollars. It is worth to mention that the second category is the sum of three groups as they are mentioned in the INS: oil and natural gas extraction, mines and petroleum refining.
As in Corrado et al. (2009) and Barnes & McClure (2009), we find other categories of innovative property:
copyright and licence costs
development costs in financial industry;
new architecture and engineering design; and
other science and engineering services (purchased and own-account).
Copyright and licence costs are obtained from the World Bank as charges paid for the use of intellectual property.
The financial services industry consists in research and development of new processes and products.
Since it is not explicitly observed, development costs in the financial industry are approximated by only 20% of the total of financial services according to Corrado et al. (2005). These data are obtained from the INS and are in Tunisian dinars.
For new architecture and engineering design, Corrado et al. (2005) estimated their value as 50% of total expenditure on architectural and engineering. For our work, these data are obtained from the INS and are in Tunisian dinars.
Own-account other science and engineering investment is given by ‘internal expenditure in research
& development’ calculated by the National Observatory of Science and Technology. However, purchased
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other science and engineering investment were taken into account in other parts of expenditures as it is mentioned by Baldwin et al. (2009).
2.3. Economic Competencies
The third category of intangible assets is economic competencies. It consists of the brand equity, the firm specific human capital and the organizational capital.
Inspired by anterior studies focused on intangible assets, this study includes advertising expenditure as brand equity, direct and indirect firm expenses on training as firm-specific human capital and purchased and own-account organizational capital in the economic competencies category.
Advertising expenditures are estimated as 60% of total expenditures on advertising services and products. These data are due to MediaScan agency and Sigma Group.
Direct firm expenses are the costs of developing workforce skills such as training and indirect expenses consist of the opportunity cost of employee time spent on formal and informal training. Only direct expenses are available in the National accounts of Tunisia. Hence, we consider that investment on firm-specific human capital is given by the data on direct firm expenses.
Investment in organizational capital is composed of purchased investment in organizational structure and own-account investment in organizational structure. According to Corrado
et al. (2005),purchased investment in organizational structure is approximated by the total revenue of the management consulting services industry which is between 10 and 20 TND million (UTICA Survey, 2011). To cope with this lack of data, we consider that this expenditure is of 15 TND million for the period of study. For the own-account investment in organizational structure, it is estimated as 20% of labour compensation of total management occupations (Corrado et al., 2005). For this reason, we multiply the number of managers by their average salary. These data are obtained from the INS. However, it is important to mention that we have only the average salary for 2007. That’s why we assume that this salary does not fluctuate for the period of study.
3. Results
In this part, we measure intangible assets in Tunisia in nominal terms for the period spanning from 2005 to 2008.
TABLE 1. NOMINAL INTANGIBLE INVESTMENT IN TUNISIA (IN BILLIONS OF US $)
2005 2006 2007 2008
Computerised information:
*Custom and packaged software
* Own account software
0.97 0.52 0.45
1.05 0.58 0.47
1.12 0.66 0.46
1.16 0.73 0.43 Innovative property:
* Scientific R&D
* Mineral exploration
* Copyright and licence costs
* Development costs in financial industry
4.06 2.97 0.56 0.07 0.03 0.12
5.22 3.3 1.63
0.1 0.03 0.12
6.93 3.8 2.51
0.1 0.04 0.13
8.49 4.6 3.09 0.12 0.04 0.13
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* New architecture and engineering design
* Other product development, design and research
0.31 0.33 0.35 0.41
Economic competencies Brand equity
Firm-specific human capital
Organisational capital
0.8 0.02 0.38 0.4
0.83 0.04 0.39 0.4
0.84 0.04 0.4 0.4
0.91 0.05 0.45 0.41 Total intangible
investment 5.83 7.1 8.89 10.56
Intangible assets as a %
of the GDP 16.95 18.27 19.87 24.21
Source: Authors’ calculations
As it is shown in Table 2 and figure 1 and referring to Barnes and McClure’s (2009) work, we can see a clear similarity between Tunisia, Japan and Germany in the composition of intangible investment (in terms of the main categories) with an important weight for the innovative property (Table 2). The share of the innovative property in the total amount of nominal investment in intangibles was more than 60%. Scientific research & development is the most important component of the innovative property. This result is, however, in contradiction with Muntean’s (2013) findings mentioning that the economic competencies are the dominant category in intangible assets. Computerised information and economic competencies have approximately the same proportion in the composition of intangible assets in Tunisia.
FIGURE 1. COMPOSITION OF THE TOTAL INTANGIBLE INVESTMENT IN TUNISIA
Source: Authors’ calculations
Figure 1 gives us an idea about the evolution of the intangible assets, three categories between 2005 and 2008; it seems clearly that only the innovation property has been growing during this period while
0 1 2 3 4 5 6 7 8 9
2005 2006 2007 2008
Computerised information Innovative property
Economic competencies
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computerised information and economic competencies have known a steady stagnation. This can be explained by the government’s efforts to encourage innovation.
To build just a small idea about the contribution of intangible investment to economic growth, we have calculated, in the last row of table 1, the percentage of these assets in the GDP.
The corresponding percentages are so high and exceed the rates mentioned in anterior studies. In fact, intangible assets account for 9% of GDP in Japan (Miyagawa and Hisa, 2013), 11% for United Kingdom in 2004 (Marrano and Haskel, 2006), 9.1% for Finland in 2005 (Jalava and Alenen, 2007), 5.2%
in Italy and Spain, 7.1% in Germany and 8.8% in France (Hao, Manole and van Ark, 2008), 10% for the Netherlands over 2001-2004 (Van Rooijen et al., 2008), 13.2% for Canada in 2008 (Baldwin et al., 2011).
4. Conclusion
In Tunisia, it is found that innovation is playing a dominant role in intangible assets where are economic competencies and computerized information do have very small contribution to the overall economic growth and both of them have very small contribution. Intangible assets like Economic efficiencies and computerization, information & technology are not growing over the years in Tunisia. However, it seems that the government does encourage the growth of one type of intangible assets to improve i.e. innovation. The aggregate impact of intangible assets could be much more widely felt in the growth of Tunisian economy if the government could understand and encourage the simultaneous growth of all the intangible assets in the country. The knowledge, innovation are the intangible assets which have become a locomotive that defines the contemporary development of all the countries in the modern knowledge based world.