Following the strongest beliefs of Adam Smith (1779) and beyond, and the famous American economists in the early 1960s, Schultz (1961), Becker (1964) etc, education and training are the most important investments in human capital. Their merely huge contributions to the welfare of individual students and their families and to economic development include the direct contributions of education to economic productivity plus indirect contributions through community structural effects. Furthermore, some basic economic analyses have no difficulty to explain why, throughout history, some countries (for instance U.S.A., Japan, UK and many other western European nations) have experienced very long periods of continual increasing growth in income per person. Presumably, the answer lies in the expansion of scientific and technical knowledge that raises the productivity of labor and other inputs in production. The methodical application of scientific knowledge to manufacture goods has greatly increased the value of education, technical schooling, and on-the-job training as the growth of knowledge has become embodied in people-in scientists, scholars, technicians, managers and other contributors to output. However, in order to gain deep and sustainable knowledge and to obtain good training, a foregone income of thousands of euros/dollars per individual is being spent both by him/herself (or his/her family) and by the public government authorities.
Recently, early research studies by Pantelous and Kalogeropoulos (2007, 2008) try to determine analytically (as well as more formalistically) an optimal lifetime path of schooling (or in other words, the stock of knowledge) for an average individual (particularly someone with limited income) and the public policy implications of his/her decision. Thus, some optimal continuous - time, deterministic or stochastic, control theory models to the education - investment’s decision strategy that maximizes some economically sustainable criteria for earnings of individuals are developed and discussed. The formulation of these models is quite general including several inputs variables, assuming only the rate of schooling as the control variable. However, many endogenous (such as family, community characteristics including crime rates, public health, political processes and stability, etc), exogenous (such as population growth, economical stability and growth, labor force participation etc), more personal (skills, psychology etc) and irregular parameters were not being included and considered, as well.
Thus, in this project, we describe briefly the conceptual, the mathematical and the empirical framework, both in micro and in macro environment, for measuring and controlling dynamically the benefits of schooling of a with-limited-income individual or a group of citizens with some common characteristics (for instance, job). In the same direction, we split the time interval into three main sub-intervals ([0, 25), [25, 65) and [65, w), where w is the terminal age), where the optimal path is designed. Many comments and remarks are finally derived.

Keywords: Modelling; Deterministic/Stochastic Optimal Control Theory; Allocation of Resources; Human Capital, Education - Investment decision.