Date Published: March 21, 2019
Publisher: Public Library of Science
Author(s): Henry Laverde-Rojas, Juan C. Correa, Klaus Jaffe, Mario I. Caicedo, Lubos Buzna.
The accumulation of knowledge required to produce economic value is a process that often relates to nations economic growth. Some decades ago many authors, in the absence of other available indicators, used to rely on certain measures of human capital such as years of schooling, enrollment rates, or literacy. In this paper, we show that the predictive power of years of education as a proxy for human capital started to dwindle in 1990 when the schooling of nations began to be homogenized. We developed a structural equation model that estimates a metric of human capital that is less sensitive than average years of education and remains as a significant predictor of economic growth when tested with both cross-section data and panel data.
Substantial evidence shows that human capital plays a critical role in nations economic growth [1, 2]. Since its initial conception [3, 4], human capital is said to capture the stock of knowledge and cognitive abilities required to produce economic value. Many authors regard human capital as a result of schooling, and therefore employ educational variables such as average years of education (AYE) as a proxy indicator [5, 6]. Some scholars have criticized this latter metric for several reasons: i) it omits the quality of education, ii) it assumes homogeneity among individuals, iii) it is insensitive to educational systems, iv) it ignores human capital from unschooled people and v) it only evaluates a single component of a broader concept [7–9].
In the following tables, we present the non-standardized coefficients. However, to compare the influence of both ihc and AYE we interpret the results upon standardized coefficients. Table 1 shows the results of the regressions without controlling the problems previously mentioned (e.g., endogeneity, omitted variables, etc.).
The aim of this paper was to propose a new index of human capital whose direct and indirect effects could be estimated so as to disentangle the relationships that exist between the process of accumulating knowledge required to produce economic value (e.g., education, health, household background) and their returns and outcomes (e.g., productivity, generation of new knowledge, etc.).