Data Issues Of Human Capital Growth Theory Economics Essay

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Theory of human capital appeared as a potential important variable into the growth literature back in 1960's and 1970's. Economists such as Mincer (1958), Schultz (1960, 1961), Becker (1975), and Denison (1962, 1979), presented their view points on the concept, role and formation of human capital. Romer (1986, 1990) incorporated human capital as an endogenous variable [1] in his long-run growth model. He integrated knowledge as an endogenous factor into the production function in his two sector model. He captured the interrelation between technological growth and human capital and pointed out direction and path of the development. Since 1990, there has been a range of research work done on the topic, while covering its various aspects and dimensions by different economists till date. Broadly, in addition to others, these include growth accounting, labour productivity, human capital externalities and benefits of education.

The essay however chooses few areas and proceeds as follows: section 2 discusses critically and summarises some of the work done with regard to identification and solution of data issues of human capital. Section 3 focuses mainly on the modelling issues and contributions of different economists. Section 4 highlights R & D spillovers and section 5 discusses some reflections on the potential impacts of the 'Great Recession'. Concluding remarks are drawn in the last section of the essay.

Data Issues of Human Capital Growth Theory:

There have always been issues regarding measurement of human capital both conceptually and empirically. Conceptually, no single clear cut definition is found in the related literature on how capital should be represented. Years of schooling have generally been considered as a good proxy since long, however, having a look at the data, it is hard to believe that a country that increased its average years of schooling from 1 to 2 has doubled its stock of human capital and eventually doubled its output [2] (Cohen, 2007). Empirically the main problem is the inadequacy (Barro, 1993) and quality of the data itself as has been pointed out by De la Fuente & Domenech (2002, 2006). The later is of the opinion that the results of the contribution of human capital accumulation to economic growth have often been discouraging. While running growth regressions most of the times either the educational variable turn out to be insignificant or it has the wrong sign, particularly if they are estimated with first difference or panel specifications [3] .

Barro (1993) gave and described a new data set on educational attainment based on 129 countries covering a period from 1960 to 1985. He used census/survey figures to fill over 40 percent of the cells and the rest of the 60 percent are estimated from school enrolment data by a perpetual-inventory method. The data referred to male and female attainment of the adult population at four levels: no schooling, primary, secondary or higher. This also provided a rough break down into incomplete and complete attainment at the three levels of schooling. He believed that the improved data set can be used for empirical studies of economic development. As such it is now possible to use a broad set of data in order to examine and determine composition as well as overall years of school attainment by various levels of education. Further, the different influences of male and female human capital can also be assessed.

One of the important recent contributions came from De la Fuente & Domenech (2006) who estimated educational attainment for a sample of 21 OECD countries incorporating previously unexploited information and removing sharp changes in the data that can reflect only changes in classification criteria. They then constructed indicators of the information content of their estimates and a number of previously available data sets and examined their performance in several growth specifications. They constructed this data mainly as a result of their belief that the then existing data on educational attainment contained a considerable amount of noise.

Cohen and Soto (2007) presented a new data set for the period from 1960 to 2000 on schooling across countries. The main sources for the constructed data are OECD data base on educational attainment and surveys published by UNESCO. They lend the credit of their improved series over others particularly in first differences to (1) the use of surveys based on uniform classification systems of education over time and (2) an intensified use of information by age groups. The authors are of the opinion that the improved data can be substituted for Barro and Lee's (2001; Oxford Economic Papers, 3, 541-563) data for the purpose of empirical research.

Modelling Issues of Human Capital Growth Theory:

Lucas (1988) made one of the prominent contributions, which in turn, related to previous work done by Uzawa (1965). In these models the level of output is a function of the stock of human capital. The model of Lucas emphasized human capital accumulation through schooling, learning by doing, physical capital accumulation and technological change. Alternatively endogenous growth models notably Romer (1990) finds that the steady-state growth rate partly depends on the level of human capital i.e. human capital is a key input in the production of new ideas. In some of the endogenous models such as Acemoglu (1997) and Redding (1996) relaxes the assumption and allows the human capital to be exogenously determined and have considered what happens when individuals can choose to make investments in education or training while firms make investments in R & D (Temple, 2001).

Benhabib and Spiegel (1994) introduced a model in which human capital influences the growth of total factors productivity mainly through, one, human capital levels directly influence the rate of domestically produced technological innovation as in Romer (1990), and two, as in the spirit of Nelson and Phelps (1966) the human capital stock affects the speed of adoption of technology from abroad. Now in this model, keeping in view its empirical significance, the human capital stock in level play a role in the determination of per capita income.

Engelbrecht (2003) contributed significantly by giving a hybrid model. He explored the applicability of the Nelson-Phelps approach to the modelling of human capital in economic growth for the sample of OECD countries. Nelson approach was confined to the technology diffusion component and combined with Lucas approach. The study provides a consistent picture of the role of human capital in adopting technology from abroad. He found human capital to be positive and statistically significant. Further, higher schooling was used as a specific subcategory of schooling human capital and was found to be the largest. The author also commented as "The findings suggest that the often-quoted Benhabib and Spiegel (1994) rich country sample results for the NP approach are not typical for OECD countries" (Engelbrecht, 2003, pp.S49). The researcher, based on empirical findings of his work argues that the identification of the NP approach with the endogenous growth component as well as with the technology diffusion component is unfortunate.

Jones (2008) recently presented a model, in which human capital differences can explain several central phenomena in the world economy instead technology differences. The model shows that how large differences in the quality of skilled labour may persist across economies, nonetheless not appearing in the wage structure. The model provides an integrated perspective on cross country income and price differences, trade patterns, migrant behaviour, relative wages, poverty traps and other phenomena in a way that appears broadly consistent with important facts. Further, the model provides insights about migration, brain drain and the role for multinational in development.

R & D Spillovers and Transmission.

Though the importance of international R & D spillovers has long been recognized, however, it came to the highlight in 1990s especially with the development of new growth models such as Romer (1990), Grossman and Helpman (1991), and Aghion and Howitt (1992). A number of empirical studies on International R & D spillovers have been carried out and can be grouped into three broad categories: studies addressing the appropriate definition of the foreign R & D capital stock, studies proposing alternative econometric techniques and studies proposing additional determinants of TFP. (Coe & Helpman, 2008).

Coe and Helpman (1995) did the pioneering work on international R & D spillovers. They found that foreign R & D has beneficial effects on domestic productivity. They also noted that these effects are stronger if the economy is more open to foreign trade. Besides, it was observed that both in terms of domestic output and international spillovers, the estimated rates of returns are very high.

Engelbrecht (1997) extended the study of Coe and Helpman (1995) among OECD countries. He included a general human capital variable. This variable accounts for innovation outside the R & D sector and other aspects of the human capital, which are not captured by the formal R & D. This study is important in the sense that it not only confirmed the original findings of the study of Coe and Helpman (1995) but also established a role for general human capital alongside R & D capital. It was also found that human capital affect TFP directly as a factor of production and works as a medium for international knowledge transfer associated with productivity catch up amongst OECD countries.

Coe and Helpman (1997) expanded the scope of their initial study in 1995 regarding R & D spillovers to developing countries. According to the study based on UNESCO estimates [4] , most of the entire R & D is concentrated in the developed countries. Findings of the study reveals that since the industrial countries has greater stock of knowledge which has been accumulated through R & D activities, the developing countries may enhance its productivity by importing a larger variety of intermediate products and capital equipments embodying foreign knowledge and useful information. It might be costly for the developing countries to obtain this otherwise. They also found that R & D spillovers from the sample 22 industrial countries to the 77 developing countries were substantial during their sample period from 1971 to 1990.

Funk (2001) however found contrary results to that of Coe and Helpman (1995) and others, which suggests that international research spillovers occur primarily through imports. In order to determine the relationship between trade and growth, the study re-examined the role of trade in international transmission of the knowledge created in R & D. The study while employing the panel cointegration tests produced no evidence that research spillovers among the OECD countries are transmitted through imports, however it produced strong evidence indicating that exporters receive substantial research spillovers from their customers.

Madson (2007) while using a new data set on key variables such as imports of technology and total factor productivity for 16 OECD countries for the past 135 years tried to test Coe and Helpman hypothesis that whether knowledge has been transmitted internationally through the channel of trade? Empirical results of the study revealed strong relationship between TFP and imports of knowledge. It showed that around 93 percent of the increase in TFP over the sample period can be owed to imports of knowledge. Acharya and Keller (2007) also found in their study that imports are often a major channel in international technology transfer, while highlighting that international technology transfer varies importantly across countries.

Coe and Helpman (2009) sought to revisit the empirical analysis in Coe and Helpman (1995) on an expanded data set constructed for the purpose of the study. New estimates were found to confirm the key results in its previous study in 1995 about the impact of domestic and foreign R & D capital stocks on TFP. Further, institutional variables were included and were found important determinants of TFP. It was found that the countries with a relatively ease of doing business and high tertiary education system tend to benefit more from their own R & D efforts, international R & D spillovers and human capital formation.

Great Recession and Some Potential Reflections on Human Capital:

The debate for how the economic crisis might affect human capital formation and its effects on economic growth could be done extensively, though requiring sufficient time and thorough analysis of relevant sectors' data of different variables across the globe. However, for the purpose of this essay, only the potential links are discussed cursorily. It can safely be argued that all economies of the world have been seriously affected, however, the direction and intensity of the blows may differ across the globe [5] . The potential damage could largely be inflicted through financial and trade channels. Further it would be relevant to state that the intensity of damage (impact) also depends on the nature and stage of the economy. Advanced economies and U.S might be hit hard largely due to the financial sector issues especially in the housing sector. Western Europe and advanced Asia might be affected both through trade and financial problems. Emerging economies might be impacted mainly through trade channels. In summary the blow in terms of growth rates would largely depend on the share of the particular sector being affected in overall GDP of that economy.

In the same way the human capital would be affected depending on the share of the overall labor force that particular problem sector of the economy employs. An explanatory example could be that if the economy has employed its major human capital in export sector, the unemployment will increase coupled with a decrease in the GDP growth rates, provided the export sector is the hard hit sector. Private sector credit worldwide has declined which has both the bad impact on the employment as particularly the consumer credit sector is labour intensive. The problem can also be viewed from the perspective that the recession would lead to decline in overall economic activity, low incomes in turn would affect aggregate demand, which in turn would affect the production and as a result low employment. This would continue depending on the corrective measures taken. Low standards of living of the people and lower spending in R & D sectors by the governments as well as by the entrepreneurs due to lower incomes would further lower the quality of the human capital. All these in turn will put down-ward pressure on the economic growth.

Concluding Remarks:

Human capital and growth is an important topic and economists have tried to cover its various aspects extensively. During the process, in addition to others, data and modelling issues have frequently been identified and suggestions for improvement thereof, based on research have come forth from different economists. Data problems often tend to render the results ineffective and non-representative of the intuitive theory. In order to overcome the noise in the data, new series have been developed by economists by applying various techniques to do the job effectively. In the same way, a number of models have been presented over the period, problems have been identified in them and solutions either in the form of slight changes in the existing models or new models have been suggested. R & D and spillover effects of human capital have recently gained importance and numerous theories have been given explaining and exploring its transmission mechanism and impact. Great recession can potentially impact the human capital and growth mainly through financial and trade channels. To give an ending comment, the discussion reveals that there is a need to explore further, and especially carry out some in-depth and detailed studies in the area being discussed in section 5 of the essay.

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