Universität Augsburg, Institut für Volkswirtschaftslehre, Augsburg
One of the most recently observed stylised facts in the field of economic growth is the persistent bimodal shape of the world income distribution.. Of course, some theoretical explanations for this new stylised fact already have been provided by neoclassical growth theory within a maximising framework. Although innovation and technology are recognised as being the driving forces behind growth processes, these models maintain the restrictive assumption of a rational acting representative agent. In this paper we draw on a synergetic approach of evolutionary economics. In the model, the countries' productivity development is depicted as a sequence of relative technological levels and the movement from one level to the next higher one is governed by stochastic transition rates. The motivation for these transition rates is based on the knowledge-based approach of evolutionary economics, thereby taking into account depleting technological opportunities, the effects of technological infrastructure and permanent technological obsolescence due to an ubiquitous scientific progress. With this model we are able to show how a persistent bimodal distribution - the twin peaks - endogenously emerges via self-organisation. This simulated distribution matches well with the kernel density plot, calculated for GDP per worker data relative to the GDP per worker in the USA over the period 1960-90 for a sample of 104 countries. Both the empirical and theoretical results show an evolution of the density function toward bimodality with a decreasing number of countries with low relative productivity levels and an increasing number of countries with high relative productivity levels, indicating a prevalent catching-up during the period of investigation. However, the separation of both groups of countries is getting more significant over time and therefore further catching-up is expected to become increasingly difficult in the future.
Kernel density bimodal productivity structure technological spillovers catching up evolutionary process synergetic approach