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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