The concept of human capital has begun to be evaluated as a component and determinant of economic growth, particularly after the Second World War. Before the war, the main target of theoretical discussions about human capital was not to define or to measure its contribution to economies [1]. Kiker [2] notes six reasons about the concept of human capital which are unrelated to economic growth that the evaluations had been mostly centered around until the WWII. However, the studies made after the war have begun to associate the concept of human capital with the concept of economic growth. Schultz [3] attributes the major explanation of national output differences among countries to investment in human capital. He emphasizes that the main reason of wage differentials between workers is the human capital differentials which are gained by means of education and health. Investment in human capital is profitable like a physical capital investment according to him. Becker [4] states that the investments aiming to improve physical and mental health of labor force are significant human capital investments and the root cause of welfare differences between nations is the differences of human capital formation among countries rather than physical capital ones. Alongside these studies, there exist many studies explaining the determinants of human capital and its effects on growth up to the 1980s (some of which are [5–10]). Even though these and other different studies mention the importance of human capital on economic growth, beginning of its articulation to the growth theory is after the mid-1980s. Romer [11] develops a model assuming knowledge as a production input which has increasing marginal productivity. According to Romer, technological change is a consequence of accumulation of knowledge acquired by forward-looking and profit-maximizing firms’ production and research activities. Romer also uses the concept of “learning by doing” developed by Arrow [12] in order to explain the technological development process. According to him, technology is a product acquired by these types of firms by means of “learning by doing” process. Lucas [13] states that unskilled labor may be transformed into a skilled form by schooling. Schooling is the key to development of human capital. One of the determinants of steady state per capita output level is human capital developed by means of schooling according to him ([13], [14, pages 220–222]). Mankiw et al. [15] include the human capital in the neoclassical growth theory and state that the explanatory power of the model is increased as compared with the neoclassical model owing to this inclusion. Benhabib and Spiegel [16] use cross-country estimates of physical and human capital stocks as indicators and run the growth accounting regressions implied by a Cobb-Douglas production function. They find that human capital is insignificant at explaining per capita growth rates. They also develop a model in which the growth rate of total factor productivity depends on a nation’s human capital stock level. According to this alternative model, they find the result that human capital positively affects the growth rate of total factor productivity. Besides these studies, lots of empirical studies are made to determine the human capital and growth relationship [17–28]. While education expenditures and schooling are exploited as education indicators, health expenditures and life expectancy at birth stand out as health indicators in most of these studies. The majority of these studies indicate that both improvements in health and education indicators lead to a positive effect on growth and GDP due to the developments of human capital level of countries.
Because economic growth is a long-run phenomenon, it is so important to determine the long-run effects of physical and human capital variables. Due to this fact, the main purpose of this study is to test the effect of human and physical capital on GDP. The study aims to realize this by means of using gross fixed capital formation as physical capital indicator and education expenditures and life expectancy at birth as human capital indicators by analyzing the data of the 13 developed and the 11 developing countries. The remarkable feature of the study is that it uses the cointegrated panel regression models which are panels Dynamic Ordinary Least Squares (DOLS) [29] and Fully Modified Ordinary Least Squares (FMOLS) [30] methods. Because the precondition of these models is the existence of cointegration between variables, there is no need to take differences of variables to overcome nonstationarity. By this way, any loss of information concerning variables does not occur. Another objective of the study is to measure the magnitude of the effect of these explanatory variables on GDP according to these two different groups of countries. Hereby, we can understand which variable is more effective to increase GDP in which country group.
The rest of the study is as follows. Section 2 presents a brief summary about the relationship between education, health, and economic growth. The empirical results in Section 3 introduce the consequences of the cointegrated panel analysis which are panels DOLS and FMOLS. Section 4 presents an overall assessment about the consequences of the econometric analysis. Section 5 presents a conclusion