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This paper uses a multi-equation model to achieve an overall study of two key factors which explain growth, technology and institutions. The paper focuses on the process of the accumulation of these factors and the interrelationship arising among them. A theoretical model is given, together with empirical evidence for the joint impact of these factors on economic growth in a wide-ranging sample of countries between 1985 and 1997. This paper also contributes certain novel aspects in the variables employed. Thus, an indicator of human capital and an index reflecting institutional infrastructure have been used. The human capital indicator considers health, formal education, informal education and accumulated experience. It embraces a wider range of factors than the variables conventionally used in empirical studies. As to the institutional infrastructure index, it has been constructed on the basis of six institutional sub-indices, comprising voice and accountability, political stability, government effectiveness, regulatory quality, rule of law and control of corruption. Thus, the index constructed captures a greater wealth of the items commonly covered by the concept of institutions.

Empirical literature finds difficulties specifying and selecting proxies for human capital. These difficulties may explain why the indicators used in several international empirical studies are not closely linked to economic growth and its sources.This study offers an innovative perspective with an international indicator of human capital that takes into account the quantitative and the qualitative dimension of the concept, through the calculation of working hours corrected by productivity on the basis of differences in educational attainment and differences in skills and knowledge which exist between countries.The study also applies Granger’s test to analyse, in a sample of 14 OECD countries, the causality between the new indicator of human capital and GDP and the new indicator and innovation, concluding that the multidimensional indicator possesses a relation of causality that does not appear when tests are carried out with traditional measures of human capital (gross enrolment rate in secondary and average schooling years).

Understanding how growth factors contribute to explaining the large differences in growth rates across countries remains an important research agenda. The common approach to exploring this issue is based on the use of multiple linear regression analyses. This work contributes to growth literature by applying a new perspective based on the use of variance decomposition procedures: Shapley–Owen–Shorrocks and Oaxaca–Blinder. These methodologies have four main advantages with respect to traditional methodologies: they make possible the quantification of the relative contribution of each factor to economic growth, they allow us to estimate the efficiency in the use of the endowments of each factor, they can be used with any functional form and they can be used with estimation methods that are robust regarding endogeneity issues. We illustrate these advantages by analyzing the causes of the economic growth gap between Latin America and East Asia over the period 1980–2014. We find that the economic growth divergence between the two regions can be primarily explained by the differences in institutions and physical capital. In addition, the results indicate that the higher East Asian performance is not only due to its higher levels of endowments in these factors, but also to the higher efficiency in its use. We connect our results with the 2030 Agenda for Sustainable Development.