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HUMAN CAPITAL SKILL AND INNOVATION

PART 2 HUMAN CAPITAL AND SKILLS DEVELOPMENT

2.4 HUMAN CAPITAL SKILL AND INNOVATION

The topic of human capital has been studied since the 18th century. Adam Smith in his The Wealth of Nations (1776) stated that productivity depends on the division of labour.

The idea was later developed by various scholars in different fields that can be divided into those focused on: economic growth (Mincer, 1958, Thurow, 1970 and Benhabib &

Spiegel, 1994), education (Schultz, 1960, 1961, Bartel & Lichtenberg, 1987, Becker, 1993 and Griliches, 1997) and innovation (Nelson & Phelps, 1966, Mincer, 1992 and Livesay, Lux & Brown, 1996).

In economic terms, human capital theory has been analyzed in relation to the rate of returns of investment in human capital, job mobility, wages and expenditure on human assets. Rooted in neoclassical economics, the theory of human capital is derived from the assumption that the market is competitive, and access to information is freely available (Dobbs, Sun & Roberts, 2008). In the theory, knowledgeable humans are of equal importance as other resources in the production process (Livingstone, 1997). For Benhabib and Spiegel (1994), in general, countries with a high stock of human capital will also be the leaders in the world economy. This is because human capital is crucial in the technological adoption process and other technological enhancement activity.

Studies on human capital also have important links with theories of education. Among the scholars who are actively involved in the subject of human capital and education are Schultz (1960, 1961), Bartel and Lichtenberg (1987), Becker (1993) and Griliches (1997). They link education with knowledge and skills development activities. For them,

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the education level will determine the level of skills produced and this factor will increase revenue. According to Schultz (1961), formal education is a necessary condition to raise production capacity. Highly educated human capital will contribute to a high level of cognitive skill that increases economic returns.

Meanwhile, scholars such as Nelson and Phelps (1966), Mincer (1992) and Livesay et al. (1996) have focused their research on the relationship between human capital and the innovation process. For example, in the paper entitled Investment in Humans, Technological Diffusion and Economic Growth, Nelson and Phelps (1966) explained the importance of investment in education to foster growth in human capital as a way of speeding up rates of technological diffusion.

The human capital theory has also encountered some criticisms. First, the theory has been criticized because it did not take into account the complexity of real world situations. The ‘screening theory’7

7 According to Shahril (2007), “Screening theory refers to a range of theories that challenge the human capital assumption of the productivity – augmenting role of education. The term ‘screening’ is often used in two connotations: to indicate that education acts as a signal for pre-existing abilities and as mean for the already better off to get the best jobs. In the first form where education acts as signal, wages still equal to marginal productivity in equilibrium. In the second form which is termed the ‘credentialist’ view of education, education only serves as an admission ticket for certain profession. According to the ‘signaling’

view, education yields useful information to identify individuals with a higher expected productivity. This set of theories includes the filtering theory of Arrow (1973), the screening theory of Stiglitz (1975), and the signaling theory of Spence (1973). Henceforth, screening will be identified with signaling. The theories are molded in formalized models….Educational achievements serve as signals for employers and result in an efficient allocation of employees to a diversity of jobs. The signaling theory as developed by Spence (1973) starts from the assumptions: 1) individuals differ in productivity, and is fully person-specific and not affected by schooling; 2) more schooling entails more costs, and schooling costs are lower for the more productive; 3) individuals know their productivity, firms do not; and 4) educational qualifications can be observed without cost. Firms cannot observe individual productivity, and instead use schooling qualifications for hiring decision and for setting individual wages. Firms assume that the individuals with more schooling are more productive” (p78-79).

developed by Stiglitz (1975), argued that the market is not as perfect as claimed by many scholars using human capital theory. According to

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Dobbs, Sun and Roberts (2008), the reality is, the market is monopolized by a certain group of people. It is controlled by certain groups, such as the politicians and capitalists.

It is very rare or in fact almost impossible to see equality in the market. For example although an individual might in some contexts have all the required qualifications decision making is in the hands of the group that controls the market. Furthermore, this alternative theory also stresses the importance of skill development through on-the-job training. Formal education is adopted as a basic guideline in the selection of employees at the beginning of the employment process (Dobbs, Sun & Roberts, 2008). Employers will then train their human capital according to the needs of the firm. Table 2.3 shows the similarity and differences between human capital theory and screening theory.

Secondly, the human capital theory has been criticised for emphasizing education as the most critical element in influencing skills development. As stressed by scholars of the

‘filtering theory’, the effectiveness of education in determining productivity is more important than the education itself (Soukup, 2007). Prior to Soukup’s (2007), Teixeira (2002) also made a similar point. Teixeira combines ‘filter theory’ and ‘screening theory’:

According to filtering theory (Arrow, 1973) employers prefer workers high levels of education because the education system acts as a filter for individuals according to their innate productivity, thus education is a source of information not competencies. Screening (Thurow, 1975) or signalling (Spence, 1973) theories reject two basic assumptions of human capital theory: perfect competition and deficits of human capital (according to which human capital increases are always absorbed by demand). They recognise the possibility of human capital oversupply. In such condition there is competition for jobs not for wages. Education is nothing more than signal through which workers indicate to employers their capabilities to take on certain jobs (Spences, 1973) (Teixeira,

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2002, p10).

Table 2.3

Comparison of Human Capital and Screening/Signalling Theories

Human Capital Theory Screening/Signalling Theories

Root in Economic Thought

Neoclassical Economics Institutional Economics Theoretical

assumptions

-Perfect competition -Individuals are rational

“economic men”

-Free entry to and exit from labour market; job changing and turnover is free

-Imperfect market as represented by monopoly/monopsony or unions

-“Stupidity” in decision making -Substantial transaction costs involved in job-changing and turnover

Commonly accepted core

Individuals and organizations interested in education and training to forego present cost and raise their future value and earning

Role of education and training

Productivity augmenting skills are produced in school, and education and learning is a productive source

-Education and training serve primarily to sort out individuals according to their characteristics, employers are more likely to accept as signal of productivity, such as trainability and

adaptability

-Employers use education and training as a device to screen out right employees

-Potential employees use education as a signal to differentiate them from others Skills context General skills increases one’s

productivity to all organizations and specific skills does this for limited organizations

Focuses on specific skills obtained by on-the-job training, formal education is only a device for screening on individuals’

productivity and associated traits Source: Dobbs, Sun and Roberts (2008)

Finally, some branches of the human capital theory have been criticised for simplifying the association between a worker’s knowledge level and their level of formal education.

Critics question the idea that knowledge gained from formal schooling is sufficient to facilitate skills development. Skilled human capital is created from a continuous learning

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process that is gained during working life (Reich, 1991 and Senge, 1990). The time spent on schooling does not indicate the workers efficient performance and productivity.

Instead, workers’ skills and capability are developed after they enter the job market.

Specific knowledge related to their job is gained through non-formal learning at the workplace and this is more valuable to enhance a workers capacity as it will expedite the process of production and manufacturing.

Although these scholars emphasize the different dimensions of human capital, they agree on its central importance and that skills and knowledge embedded in human capital assist development. Through the years, several studies have emphasized the importance of skills to human capital development. These include Schultz (1961), Porter (1991), Levin and Kelley (1994), Yong and Jong (1999), Lall (2001, 1999), Mohnen and Röller (2005) and Leiponen (2005). Economist, Theodore Schultz (1961) was the first to link the need for skills and human capital development. Schultz’s research was basically focused on the importance of knowledge and education as the investment factors in human capital. He argued that investment in education and training are crucial for a country to increase its productivity. For Schultz, there are four contributions made by education towards human capital growth, namely; (i) developing research activity (ii) enhancing skills (iii) building capability to adjust to workplace changes and (iv) improving the teaching processes.

Skills possessed by an individual are generally divided into two types; general skills and specific skills (Becker, 1964). Normally, knowledge gained from schools or other formal

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means is categorized as general since the knowledge does not have any intention to build specific expertise. The main purpose of general skills is to develop high cognitive abilities in students (Serneels, 2008). Specific skills are conversely acquired from the workplace and they are usually derived from experience and on-the-job training. These types of skills depend on the work conditions and in general, different job specifications require different types of skills (Xiao & Lo, 2003).

In general, skill is defined as the ability to perform tasks. Nevertheless, there are a range of definitions given to skill. For Green, Machin and Wilkinson (1996), the word skill itself is given indefinite meaning. As explained by Teixeira (2002):

It can mean the ability to perform given tasks or to master various techniques, or, more broadly, it can refer the range of behavioural attributes such as reliability, ability to work without supervision, and stability of employment (Teixira, 2002, p6).

To get a better understanding of the term, Teixeira (2002) has categorized the definition of skills into two groups. The first group is based on the work of Cézard (1979) who classified skill into three types; job skills, workers skills and conventional skills. Each of these three definitions of skill is distinguished by the quality of job and human factor.

‘Job skills’ means the type of skill needed by an occupation; ‘workers skills’ is knowledge that a worker possesses which is developed through formal and informal education, meanwhile ‘conventional skills’ is based on workers’ occupational matrices.

The second group according to Teixeira belongs to sociologists such as Becker (1964), Braverman (1974), Ash (1988), Primoff and Fine (1988), Stevens (1994) and Ashton, Burchell, Felstead and Green (1997). These scholars identify skills as the stock of

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human capital acquired to perform their jobs and their effectiveness when carrying out these duties.

Gary Becker in his work entitled Human Capital (1964) suggested that education or training received by workers will increase productivity through investment in useful knowledge and skills. On the other hand, Thurow (1975) emphasized that education increased productivity rather than human capital itself. To him, over time employers prefer to employ new workers with better educational qualifications since better educated workers are easier to train. This is supported by the researches by World Bank (1997) and Ritchie (2001). Based on studies done in firms in Malaysia, Thailand and Singapore, it was found that human capital with high literacy rates received more ongoing training compared to those with lower initial formal education (Ritchie, 2001).

Porter (1991) takes a similar line to Schultz. Porter claimed that spending on education and training is significant to a nation’s competitive advantage. He also expanded Schultz’s study by noting the importance of universities’ quality, research activities and skills training in influencing the production of quality workers. Levin and Kelley (1994) extended the human capital development idea by focusing on the training function to enhance productivity. They claimed that education could improve the productivity if it is complemented by training and good management practices.

The relationship between human capital and technology growth has also been studied by Yong and Jong (1999). In their research, they found that progress in technology will

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increase the investment in human capital.8 The more advanced the technology, the higher the quality of human capital is required as high quality human capital is needed to develop the latest and sophisticated technology. In Yong and Jong’s work, quality human capital refers to individuals that possess knowledge and the capacity to adopt new technology.

Sanjaya Lall (1999, 2001) reiterates the above views. Lall sees skills embedded in human capital as the factor that determines a country’s competitiveness. According to Lall, the effective use of technologies depends on human skills. He also stressed the importance of developing a wide and diverse skill base because different technologies require different skills. For Lall, if skills are present, technologies will be imported, absorbed and used efficiently without cost and risk.

The new technological paradigm calls for more skills, for higher levels of skill and for different kinds of skill. The reasons for these trends are obvious. The pace and ubiquity of technical progress means that all activities have to improve their technologies, and so the skills needed to operate them, if they are compete.

With the liberalization of trade and investment, even non-trade activities are increasingly exposed to international competition, and have to improve their competitive base to survive and grow. The need for increased skills rises with the level of development, but even the least developed countries have to improve their human capital base if they are to grow and prosper (Lall, 1999, p3).

8 Yong and Jong’s (1999) research is departs from the idea of whether technology-skill substitutability or complementarity. In their research, they suggest an overlapping generation model to show the effect of technology change on human capital, “the model is an overlapping generations model where human capital plays an essential role in adapting new technologies. We assume that agents, when young, make investments in human capital and old agents adopt new technologies by using the human capital stock that they have accumulated when young. A distinguishing feature of the model is that it explicitly models the different roles of width and depth of human capital structure in adopting new technologies and in creating new human capital stock. In the model, the width of human capital determines the cost of technology adoption. Width of human capital represents the number of various specific knowledge points that human capital contains. Because each knowledge point helps to decipher and understand various characteristics of the future technology, wider human capital structure lowers the cost of adopting technologies. In contrast, the depth of human capital determines the level of the technology that can be adopted. In other words, higher quality human capital can adopt higher level technology” (p2).

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Research by Mohnen and Röller (2005) indicate that skilled human capital is significant for innovative activities in an industry and a country as a whole. They showed that the innovation process is retarded if it is not accompanied by sufficient skilled human capital.9 The importance of skills was also stressed by Leiponen (2005). Leiponen examines how skills and innovative activities are related to each other. Based on the innovation activities in firms and employees’ skills, he noted that skills influenced innovation process in firms and the innovation success could bring profit to the firms.

He added that skilled human capital is not only needed for research and development but by all sectors, including the marketing, manufacturing, research and design and development sectors.

Although these opinions are accompanied by strong arguments, it is important to note contrasting views. Not all agree that scientific and technological change has brought more good than harm. Instead technological development has reduced the role of the human element in economic activities (see Box 2.2). These opinions suggest that due to rapid technological development, manufacturing and production activities are controlled by machines, and this has reduced the importance of human capital.

Leach and Wagstaff (1986) argued that a consequence of new technologies is the creation of unemployment and underemployment. They claim that new technology has reduced job opportunities and it is difficult for a country to achieve full employment.

The development of sophisticated technology has meant that economic growth relies on

9 According to Toner (2011), there are four contribution of skills to innovation; i) to accelerate technological change; ii) to fast adapt to technological change; iii) to complement education and training and iv) to achieve the productive potential of new capital investment.

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the long term investment in technology rather than on the amount of skilled human capital. In addition, progress in technology is the dominant factor that controls the market.

Box 2.2:

Technology and Unemployment: A Classical Debate

Since the emergence of the Industrial Revolution, the extensive substitution of labour by machinery incorporating the new technology of the time has led economists and policy makers to debate the economic and social consequences. At the end of the eighteenth century, James Steuart drew attention to the difficulty of reabsorbing the unemployment caused by sudden mechanization, in spite of the positive effects from the construction of the new machines and price reductions, and already envisioned a role for the government. Adam Smith linked the invention of machines to the division of labour and emphasized its labour-saving effects. Jean-Baptiste Say had less doubts about the ability of markets to adjust, while Thomas Malthus emphasized the positives effects resulting from the strong demand dynamics experienced by England at the time. The optimism of classical economists in the early nineteenth century contrasted with the dramatic impoverishment of the English working classes – industrial workers, small artisan, and displaced peasants – who had started to organize trade unions and to launch Luddite struggle against the job losses and deskilling brought about by mechanization.

David Ricardo was convinced that the economy could compensate the negative employment effects, but in a famous passage in the chapter “On machinery,” added in the third edition of his Principles of Political Economy and Taxation argued that “The opinion, entertained by the labouring class, that the employment of machinery is frequently detrimental to their interests, is not founded on prejudice and error, but is conformable to the correct principles of political economy” (Ricardo 1951:392).

The most articulate criticism of compensation theory was developed by Karl Marx, who emphasized the losses for workers in term of jobs, skills, wages, and control over their resulting from the way mechanization was proceeding at the time. Arguing that unemployment grows as technical change displaces labour more rapidly that the accumulation of capital demands new workers, Marx developed important insights on the functioning capitalism. The drive to capital accumulation leads to a constant search for new production techniques and new products (a key starting point in Joseph Schumpeter’s theory of innovation). High unemployment assures lower wages and greater control over workers, but capital accumulation ultimately encounters the problems of finding adequate markets and demand, and making adequate profits.

Source: Pianta, M 2005, ‘Innovation and Employment’, in J Fagerberg, D Mowery & R Nelson, The Oxford Handbook of Innovation, Oxford University Press, Oxford, pp571-572.

For Leach and Wagstaff (1986), the use of skills in production activity is determined by science and technology. High usage of technology will reduce job opportunities.

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However, they do not hold technology per se as responsible but rather the failures is to gain the full possible benefits from innovation. For example, they assert that if markets know how to handle the advantage of innovative activities the problem of unemployment may not occur. They also found that technological development does not contribute to new job opportunities but instead creates the division of workers. Their view is that when technology develops, instead of changes in the quantity of workforce required, it creates two different levels of workforce i.e. highly skilled and semi-skilled groups.

Aronowitz and DiFazio (1994) also hold similar opinions. They claim that the technological revolution has affected the structure of work, skills and occupations. Jobs help to increase the standard of living and combat social problems such as poverty, hunger and homelessness. However, the arrival of a new technological era has reduced the quantity of jobs that could be offered. Sharing a similar opinion to Leach and Wagstaff (1986), they claim that the higher the investment made on technology, the more employment opportunities are destroyed. For them, when knowledge becomes a production factor, the manual workforce is useless. Work is restricted to the availability of job opportunities and reduces the number of workers. The contribution of skills is minimized since all the work is done by automated process. The technological revolution has not only reduced the availability of jobs, but also created specifications of jobs. Technological progress has diversified the skills into three categories namely, intellectual, technical and manual workforce.

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Whilst intellectual work is seen as superior, knowledge is also controlled by technology.

This was stated by Aronowitz and DiFazio in Jobless Future, (1994):

Science and technology (of which organization is an instance) alter the labor process nature, not only the rationalized manual labor but also intellectual labor, especially the professions. Knowledge becomes ineluctably intertwined with, even dependent on, technology, and even so called intensive work labour becomes increasingly mechanized and begins to be replaced by capital-and technology-intensive – capitech-intensive – work (Aronowitz & DiFazio, 1994, p17).

They further stress that both culture and technology are the factors that contribute to the success of production. Skills, on the other hand, are no longer the factor that catalyzes the operation process. In manufacturing, all the processes are conducted by machines, thus less human involvement is required in production activities.

From the explanation above, one common argument between Leach and Wagstaff (1986), and Aronowitz and DiFazio (1994) is that they both agree that productivity and economic growth do not depend on the level of education nor on the skills an individual has but it is determined by the latest machinery and tools used. Skilled human capital is not the factor that influences the manufacturing process rather it is sophisticated technology that is the important player.

This tradition within the human capital literature raises some important questions reminding the analyst of the problems of short term structural challenges to employment patterns flowing from new technology. A weakness in these critical approaches is that they tend to overstate the role of technology acting in relative isolation contributing to

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the problem of unemployment and underemployment. Other factors such as job selection, job pattern, skills mismatches, and changes in the economy and the failure in forecasting a country’s development direction are also extremely significant. As this thesis takes its lead from recognising technology as part of a NIS, where technology is a key part of a network, it favours approaches to human capital which interpret it as a crucial part of long term successful technological innovation.