Complex Economic and Social Systems


Te Pūnaha Matatini is using methods from complex systems analysis and organisational-level data sets to understand the role of innovation in productivity growth, and to assess the importance of knowledge, network, and supply-chain spillovers on firm behaviour.


The last decade has seen dramatic advances in our understanding of complex economic networks. Researchers at Te Pūnaha Matatini are applying new methods from complexity science to better understand New Zealand’s economic and innovation performance. New Zealand’s failure to close the gap in GDP with other advanced economies has been attributed to our small scale and distance from major markets, but the manner in which these factors influence the New Zealand economy’s ability to capture and benefit from knowledge spillovers is largely unexplored. Understanding the potentiality of spillovers from diversity will inform government policy and decision-making, and will assist in the evaluation of the effectiveness and impact of government policies.



Knowledge flows and innovation networks

Much of the past analysis of economic growth has focused on aggregate properties of economies; however there is an increasing understanding that the structure of economies is important in determining future growth. Understanding how scale, diversity and connectivity affect the ability of firms to capture and benefit from knowledge spillovers is a crucial for developing better innovation policies for New Zealand. In this project we will study the relationship between these system-level empirical regularities and micro-economic models of the behaviour of firms and individuals, using a unique firm-harmonised, region-coded patent database built on millions of patent disclosures from across thirty advanced economies from the 1970s. We will combine empirical investigations and theoretical models of network architecture properties to optimise development and economic growth. We will investigate whether firms that are engaged internationally are more successful at importing new ideas into New Zealand, and also at innovating in New Zealand. This project will test these propositions using measures of international engagement and innovation derived from the Longitudinal Business Database.

Three-year outcome: effective innovation policies based on a microeconomic understanding of how economic geography affects the innovative performance of New Zealand firms


Innovation dynamics

The Waiting Time Distribution (WTD), that is the distribution of the time elapsed between two consecutive events, has been used to characterise different stochastic processes, including earthquakes, financial markets, and electronic transport in nanoscale devices. The filing of a patent application by a firm has been modelled as a stochastic arrival process with a rate that is a function of the R&D investment of the firm, as well as observable and unobservable firm characteristics. Sociologists have studied how the rate of entry into an existing patent “niche” is affected by the relationships among the patents already present in a niche. We will extract WTDs for patent applications, with the aim to elucidate whether and how applications are correlated, and to identify the characteristic time scales involved in the innovation process.

Three-year outcome: an understanding of global innovation dynamics at the firm level based on patent data that informs New Zealand innovation and industrial policy


Social change, inequality, and the early life course

There are large amounts of data concerning social change that are in principle open to combination and re-use for advanced analytical purposes with the application of sophisticated statistical techniques. A good example is the New Zealand Census which provides a “whole-of-society” data framework over time that has been little exploited and that potentially opens up linkages to other data systems. This is an immensely under-utilised resource, presenting major opportunity costs and providing barriers to the study of matters of great public importance. Like many other OECD countries, New Zealand has recently experienced rapid social and economic change combined with growing income inequality. Inter-country comparisons have established that this is reflected in growing inequality in key social outcomes e.g. infant mortality. Paradoxically, New Zealand is an outlier to this trend and has a steady improvement in infant outcomes. In this project we will seek to establish the causes for this positive trend, and investigate if those causes will help counter other negative social inequality outcomes.

Three-year outcome: evidence-based social policies and interventions that combat negative outcomes from social inequality