Transformational complexity, systemic complexity and economic development

Abstract

Economic development is a multi-dimensional and co-evolutionary process, in which several factors interact with each other in a complex manner. The paper develops two new notions of economic complexity based on the study of interactions between different development factors. (1) Transformational complexity denotes a country's pace of structural transformations over time, arguing that an economy is more complex if a large number of factors are able to drive the system out-of-equilibrium and towards new growth paths. (2) Systemic complexity represents a country's overall density of causal relationships that link together its development factors, based on the idea that an economy is more complex if its growth path is simultaneously driven by several co-evolving factors. We build up a system dynamics model that develops these ideas, and then test its predictions using time series analysis. Making use of the Johansen cointegration approach, and using annual time series data for the period 1970-2015, we apply the new notions of complexity to the study of economic development for 134 countries. The results show that transformational complexity is positively correlated with GDP per capita growth during the period, and that systemic complexity is positively correlated with the level of GDP per capita at the end of the time span. Our results suggest that there may be different paths to achieve greater complexity and economic growth, depending on the core set of capabilities that each national system has, and that it is able to develop over time.