Abstract
The first contribution of this study is to identify the economic growth patterns of the emerging knowledge-based society of the future, compared to the agricultural society or the industrial society, by analyzing the aspects of future technologies and new humankind and their effects on the value creation structure. The second contribution of this study is to highlight the characteristics of the new humankind in a knowledge-based society. A number of studies related to economic growth from the long and macro perspective have considered only the conventional aspects of individual humans—for example, a rational consumer or a labor supplier—but this study has considered newly emerging groups with different socio-economic characteristics and their effects on the economy and society.
Keywords
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- 1.
The definition of digital economy is described in Appendix 1.
- 2.
Calculation using the data from the annual issues of BT industry report by Ernst & Young.
- 3.
- 4.
Expanded reproduction is first mentioned by Karl Marx (1967) to explain economic growth in an industrial society: the new surplus value created by waged labor is reinvested in production so that accumulation and reproduction takes place on an Extended Scale. In this paper, we have added the value of “technology advancement” so that we can explain not only expansion of quantity in scale but also expansion of quality of product by advanced technology. The expanded reproduction system of the knowledge-based society includes the value creation structure of the industrial society. If the value creation structure of the industrial society should be separated, the traditional industrial society and knowledge based industrial society can be segregated from each other according to the mode of production.
- 5.
- 6.
The examples of digital economy are explained in Appendix 6.C.
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Appendices
Appendix 1 The Definition and Characteristics of the Digital Economy
6.1.1 A1.1 The Definition of the Digital Economy
The digital economy is considered as a step toward the knowledge-based society. The term ‘digital economy’ was first used by the US Department of Commerce in its 1998 annual report to describe an economy that grew much faster than previous societies accelerated by ICT innovation. One important property of this economy is its inclusion of knowledge and information in main production factors, besides three major production factors - labour, capital, and land—of an industrial society. The digitalization of core economic activities including production, distribution, and consumption of goods and services is another main property of the digital economy (US Department of Commerce 1999).
Brynjolfsson and Kahin (2000) also defined the digital economy with digitalization of information. According to Lyotard (1984), the development of IT technologies and the universal diffusion of knowledge make it possible to exchange knowledge as a good in the marketplace. Therefore, the development of IT technologies is regarded as a critical factor for the establishment of the digital economy. Advanced IT technologies have led to the advent of new media, such as network based databases, and the development of computer networks and the Internet have made it easy to collect information and knowledge from all over the world. Information or knowledge intensity enabled by IT technologies has increased the importance of information and knowledge as production factors of an economy.
6.1.2 A1.2 The Characteristics of the Digital Economy
6.1.2.1 A1.2.1 IT’s Contribution on the Efficiency Improvement in Traditional Industries
The development and diffusion of IT has increased the convergence between IT and existing technologies in other industries. The technological advancement due to increasing IT use in traditional industries has resulted in raising the added value and improving the productivity of traditional industries.
Computerization and digitalization of industries have influenced the entire production process, introducing faster and more efficient procedures. Solow (1987) provoked the productivity paradox dispute, but Brynjolfsson and Hitt (1998) refuted his statement by showing that IT does lead to productivity improvement. They contend that computerization changes the industrial structure, leading eventually to productivity improvement. However, computerization by itself does not automatically bring about productivity improvement. As computerization matures, productivity improvement accelerates, and so does economic growth.
Many traditional industries, including the automobile, mechanical, and shipbuilding industries, attempt to improve their added values by developing new convergence technologies that graft state-of-the-art IT into the existing systems. Below Table 6.2 shows some important examples of technology convergence between traditional industries and IT.
6.1.2.2 A1.2.2 Production Function of the Digital Economy
An economy driven by digital industries grows much faster than an economy based on traditional industries because of the increasing-returns-to-scale (IRS) production function of ICT industries. Whereas the traditional manufacturing industries of industrial societies show DRS, the production function of the digital economy has the IRS characteristic (Romer 1986; Ray et al. 2002). Computer and software industries are representative examples that show the IRS production function. IRS reflects the continual increase of productivity due to the decrease of marginal cost to produce additional outputs. The marginal production cost of the software industry is considered to be close to zero (Ellison and Fudenberg 2000). Besides, Romer (1986) claimed that technology development can lead to continuous economic growth, and many economists believed that the phenomenal economic growth of the New Economy in the US had been built on ICT technologies (Gordon 1999; Stiroh 2002).
Arthur (1994) mentioned that the economic growth of the digital society accelerated faster than that of the traditional industrial society. Arthur (1994) explained the acceleration effect of the digital economy based on the IRS characteristic in production and the path-dependent economy. Shy (2001) theoretically proved the network effect observed in the computer hardware and software industries. His research on the distinctive feature of markets according to the different characteristics of software products (e.g. ease of reproduction and network effects) indicated that the software market, unlike the traditional product market, is not a competitive one but is dominated by a single technology. This kind of tipping effect in production is the basis of the technology-oriented accelerating growth of the digital economy. Harrington and Reed (1996) also mentioned the virtuous cycle of e-commerce growth, which represented the accelerating increase of e-commerce revenue well, when e-commerce was regarded as one of the production indicators of the digital economy. According to them, the faster-accelerating growth of the digital economy is significantly different from the economic growth trend of the traditional industrial societies, which have the DRS production function.
6.1.2.3 A1.2.3 Social Changes in the Digital Economy
Not only does the ICT-based digital economy affect the economic area, it also brings about all-round social change. The digital economy brings about economic and social transformation, which accelerates economic growth by stimulating the cycle of the expansive reproduction system (ERS). There are five examples of such changes: (1) The digital economy creates new demand for digital products, (2) allows flexible economic structures, (3) helps manage fluctuation in prices, (4) restructures firms and employment types, and (5) facilitates the emergence of the digital generation.
Appendix 2 Time-Output Relationship with IRS Production Function when the Speed of Technological Change is the Same
In order to estimate the technological progress in Fig. 6.14, which measures how fast the production function shifts, the difference between the two time frames of a production function needs to be divided into two parts as in Fig. 6.14a: increase due to input changes and increase due to technological changes. Solow (1957) explained that because of the time lag between the two observed production points, the output movement along the production function and the shift of the production function itself are mixed in the shift of the production function estimated from the two sets of observations. Of the two movements, the shift of the production function itself is only related to the technical change between the two production points. In order to calculate the technical change, Solow (1957) drew a tangent line at P2, which was the input–output point at t = 2, and found P12, at which the tangent line met the input level of t = 1. Then, he calculated the technical change from the difference between P1 (the output level of t = 1) and P12 (the output at t = 2 adjusted to the input level of t = 1). Figure 6.14a illustrates this process. As regards the difference between the production functions at t = 1 and t = 2, the output increase due to an input increase at the same technology level, that is, along the same production function, is expressed as A1; the change of the production function itself from technological advancement is indicated as A2. B.1 represents the difference between the outputs with and without technological innovation at t = 2. B2 measures the output difference between t = 1 and t = 2.
When the DRS production function of the industrial economy changes to the IRS production function of the digital economy, it is generally assumed that technical progress becomes faster. However, even if the technical progress is assumed to be the same as with A2, the output increase would be much bigger (see Fig. 6.14b). Even if the production function only changes to the IRS type, the difference between the outputs with and without technological innovation at t = 2 (B′1) is much wider than with the DRS type of production function (B1 < B′1). As a result, the difference between the total outputs q = 1 and q = 2, at t = 1 and t = 2, respectively, is also much larger with an IRS than a DRS (B2 < B′2) production function.
Finally, the shift of the digital economy’s APF with time appears to be similar to Fig. 6.15a. Looking at Fig. 6.15b, which traces the output according to the time frame of Fig. 6.15a, the long-run output curve of the digital economy accelerates faster than the curve of the industrial society.
Appendix 3 The Case Studies of the Digital Economy
First, we present the New Economy of the US, the leader of industrial societies. Next, we consider Ireland and Finland, both early digital economies of Europe. Their economic growth surpassed that of other industrial countries in Europe, even though they lagged behind other countries during industrialization.
6.1.1 A3.1 The Digital Economy of the US
The economic growth of the US, though a technology leader, is often predicted to be slower than other countries adopting its innovation. However, in the middle and late 1990s, the US enjoyed the highest GDP per capita and the fastest economic growth among major industrial countries. In the Economic Report of the President (White House 2001), this period of high economic growth of the US during this period was described as the ‘New Economy’. The report mentioned that a notable feature of this period was the rapid growth of ICT industries.
During the New Economy period, the US grew faster than any other country, and ICT played a remarkable role in this rapid economic growth. Table 6.3 shows that in comparison with the EU total productivity recorded marked improvement in the US and the role of ICT increased rapidly between the early 1990s and the late 1990s, a period considered to be part of the New Economy phase. This means the US was one step ahead of the EU in its transition to a digital economy during this time.
Figure 6.16 depicts the change of GDP per capita for the US and OECD-Europe from 1960 to 2006. The US economy grew rapidly from the middle of the 1990s. From 1995 to 2000, the GDP per capita increased annually by 3.87 % on average 3. In the same time frame, the GDP per capita for OECD-Europe increased annually by 3.13 % on average, which resulted in an expanding gap between the US and OECD-Europe. We can see that the New Economy left a large gap between the US and the EU in terms of economic growth.
Figure 6.17 describes the change of labor productivity in the US nonfarm business sector from 1977 to 2006. Whereas the rate of increase of labor productivity on annual average was 1.7 % for the whole period, it increased to 2.3 % for the period 1995–2000. These data confirm the remarkable increase of labor productivity during this period. Many studies pointed out in common that ICT is the main cause explaining the rapid increase of labor productivity in the New Economy after the mid-1990s (Stiroh 1998, 2002; Jorgenson and Stiroh 1999; Jorgenson et al. 2003).
In order to look into this phenomena in detail, we will review research on Oliner and Sichel (2003), which estimated ICT contributions to labour productivity growth in the US from 1974 to 2001, categorized into ICT capital and ICT production (Table 6.4). Contributions from ICT capital was calculated by the capital deepening effect due to ICT assets, including computer hardware, software, and communication equipment. Contributions from ICT production was measured by multifactor productivity (MFP) from industries that produce ICT products, including semiconductors, computer hardware, software, and communication equipment. In other words, contributions from ICT capital are related to efficient uses of traditional industries by ICT, and contributions from ICT production are relevant to the creation of new industries by ICT. As the transition to the digital economy progresses, the proportion of its contribution to the improvement of labour productivity increases. ICT contributions to the growth of labour productivity for 1974–1990, 1991–1995, and 1996–2001 are estimated at 0.68, 0.87, and 1.79, respectivly, which translates to 50.0 %, 56.5 %, and 73.6 % of the total growth of labour productivity resulting from ICT capital and production. On the basis of this analysis, Oliner and Sichel (2003) concluded that the the accelerating growth trend of labour productivity in the New Economy after 1995 comes from ICT. In particular, the effect of ICT capital is noteworthy.
The GDP trend of ICT-producing industries in the US that influence the creation of new industries is drawn in Fig. 6.18. The GDP of ICT-producing industries in the US grew rapidly after the mid-1990s and reached about 4.2 % during 1995–1999. During the same period, contributions from ICT to the economic growth of the US reached about 30 % (White House 2001). Although the size of ICT industries is relatively small, they play a key role in economic growth as its driving force.
Later, similar to the IT productivity paradox pointed out by Solow (1987), ICT contributions to economic growth were challenged since the GDP share of ICT-producing industries in the US dropped heavily in the early 2000s. Regarding this issue, the Economic Report of the President (White House 2002) explained that the ICT sector declined because the overheated stock market driven by the rapid growth of ICT calmed down and the demand for ICT capital decreased after the heavy investments by companies in 2000 to prepare for Y2K were no longer needed. Oliner and Sichel (2003) and Martinez et al. (2010) refuted the IT paradox and showed that ICT contributed to the growth of labour productivity even after 2000. The decline of ICT in the early 2000s was only temporary, and ICT is still the key growth engine for the US economy.
6.1.2 A3.2 The Digital Economy of Ireland and Finland
Despite the polarization in industrial societies, it is possible that following countries will overtake the leading countries if they adopt and develop a digital economy ahead of other countries. Figure 6.19 illustrates the process by which a faster-accelerating economy overtakes an accelerating industrial economy.
The speed of accelerating economic growth is measured by the slope of the time-output curve in Fig. 6.19. If the economies of leading countries are ahead in informatization, the gap between the leading and following countries will go on widening. However, if the following countries intensively invest in ICT to establish a faster-accelerating digital economy, the gap can be closed. In Fig. 6.19, the gap is broadening until t2 in the process of industrialization. When the following countries enter the digital economy at t2, the slope of economic growth becomes faster, and eventually the following countries overtake the leading countries at t3. This paper presents two real-world examples among the following countries that show an outstripping economic growth curve: Ireland and Finland.
Ireland experienced a serious financial crisis in the 1980s because of political instability and excessive government expenditure, and its GDP per capita dropped below 70 % of the European average. In the 1990s, however, Ireland intensively promoted ICT industries and, as a result, achieved a rapid 9 % annual growth, on average, in the mid- and late 1990s. This growth rate was the highest among OECD countries at that period of time. As shown in Fig. 6.20, Ireland grew remarkably faster than other economies, starting from the early 1990s. In the late 1990s, Ireland’s GDP per capita surpassed the OECD and EU-15 averages, and the country emerged as one of the richest in Europe. In 2006, its GDP per capita, at $30,736, ranked ninth in the world.
Government policies that fostered software companies and focused on high-value-added ICT industries were the one factor that led Ireland into rapid economic growth. The country’s domestic companies are technically inadequate, and the domestic market relatively small. From the 1990s, therefore, Ireland concentrated on policies that developed ICT industries by attracting competitive foreign companies. The Industrial Development Authority (IDA) offered various incentives such as tax benefits and financial support to attract foreign investments. As a result, many software companies, in particular, moved in and made considerable investments in Ireland. The development of ICT industries played an important role in the economic growth of Ireland, and the country achieved an annual average 4–5 % of economic growth, which was higher than the OECD average until the mid-2000s. However, Ireland began to experience economic downturn from the first half of 2008. According to IMF (2009), though, the main causes of the economic bubble lie in the finance and construction sectors.
Table 6.5 shows the average contributions from each component to GDP growth of Ireland during 1990–1994 and 1995–1999. The total gross value added increased 2.27 times from the first to the second half of the 1990s. Moreover, contributions from ICT capital during this period increased 2.84 times, exceeding those from other components. The table confirms that the economic growth of Ireland accelerated as ICT industries matured, and the proportion of ICT capital’s contribution to this growth continued to increase.
ICT also contributed substantially to the improvement of labor productivity of Ireland after the 1990s (see Table 6.6). Van Ark et al. (2002) estimated the contributions of ICT industries to the improvement of labor productivity of Ireland in the 1990s under three categories, following the international standard industrial classification of all economic activities (ISIC Rev. 3): ICT-producing, ICT-using (where the ratio of ICT capital is relatively high), and non-ICT industries. Contributions from ICT-producing industries represent the effects of ICT on the creation of new industries, and those from ICT-using are none other than ICT’s effects on efficient uses of traditional industries. According to their analysis, the role of ICT industries, particularly the producers, was crucial to the improvement of labor productivity of Ireland.
However, the relatively high proportion of ICT industries in its economy helped Ireland achieve a faster-accelerating economic growth compared to the established industrial societies such as the UK, Germany, France, and Italy. Figure 6.21 shows the GDP trend of Ireland’s ICT-producing industries.
On the other hands, Finland experienced high economic growth compared to OECD Europe in the early 1980s, as financial institutions became free to raise and manage funds after financial and capital liberalization policies were applied. However, this period is also characterized by careless management of finances with financial institutions buying real estate and providing loans excessively (Fig. 6.22a). In addition to this problem, the collapse of the Soviet Union, which was the most important export market, caused Finland to face a serious financial crisis after the late 1980s (Fig. 6.22a). The foreign exchange shortage and the severance of trade with the Russian Federation forced the industrial structure of Finland to change. As a result, ICT industries, including the mobile phone and other hardware-manufacturing sectors, were developed as key industries. Fuelled by ICT, the economy of Finland has been growing faster than OECD-Europe ever since (Fig. 6.22c).
Statistics reveal that the GDP growth from 1995 to 2001 was 5 %, on average, compared to 3.5 % from 1950 to 2001 (OECD 2002). In order to overcome the economic crisis, Finland announced an ICT promotion policy in 1994, before other countries did so (Fig. 6.22). The government proposed a new policy aimed at ‘education, training and research in the information society’, and pursued the adoption and development of information technologies as the key national policy. As a result of these policies, Finland enjoyed a high economic growth and is now one of the most competitive countries among EU members.
Jalava and Pohjola (2008) divided the period between 1980 and 2004 into two sub-periods, 1980–1990 and 1990–2004, and analyzed factor contributions to the output growth of Finland for each sub-period (Table 6.7). Regarding the effect of each component on GDP growth, contributions from ICT to GDP were investigated by three categories: ICT production, ICT capital, and spillovers from the use of ICT capital. ICT production includes ICT manufacturing for electrical and optical equipment, and post and telecommunication services. ICT capital refers to the assets invested in ICT industries. The spillover effects by the use of ICT capital are estimated by investigating 21 industries- including agriculture, mining, manufacturing, gas, and water-classified by Nordhaus (2002). In other words, these three categories correspond to the previously mentioned impacts of the digital economy on the ERS: ICT production is an equivalent term for the creation of new industries by ICT, and ICT capital and spillovers from the use of ICT capital represent the efficient uses of traditional industries.
Table 6.7 shows ICT’s total contribution to GDP growth from 1990 to 2004 was almost three times the 1980–1990 rate. Contributions from ICT production increased 3.5 times, but the increase from ICT capital was not significant. Even if the spillover effect is excluded, the contributions from ICT production and ICT capital to GDP growth from 1990 to 2004 increased almost 2.5 times (about 3 times if the spillover effect is included).
According to Jalava and Pohjola (2007), Finland’s labor productivity grew 2.87 % from 1995 to 2005. Table 6.8 shows ICT’s contributions to labor productivity. The data confirm that the influence of ICT on the creation of new industries is substantial. The ICT impact on total labor productivity, which is the sum of ICT capital and ICT-related contribution, was found to be about 65 %.
Figure 6.23 illustrates the GDP share of the ICT sector in Finland. The proportion of the ICT sector increased at an accelerating rate from the early 1990s and doubled by the early 2000s to reach 10 %. On the other hand, the percentage of the forest industry, which was traditionally strong, dropped lower and lower, to nearly 3 %. The figure reveals the effects of the creation of new industries by ICT, and shows that ICT was the driving force of the rapid growth of Finland in the 1990s.
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Kim, TY., Jung, MA., Kim, E., Heo, E. (2014). The Faster Accelerating Growth of the Knowledge-Based Society. In: Economic Growth. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40826-7_6
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DOI: https://doi.org/10.1007/978-3-642-40826-7_6
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