Evolutionary Economic Systems

Program Leader: John Foster

We applied complex systems and network theory in economics and business to understand how evolutionary change occurs. There are strong connections with earlier approaches taken in evolutionary economics and in dealing with the economics of innovation. Consistent with other programs in the Centre, multi-agent modelling and associated simulation and calibration techniques are core components of the methodology that we were using. With regard to the economic statistics available to us, we aimed to develop new ways of testing for complex patterns in high frequency data. For example, we studied trade-by trade data in stock markets and in electricity markets and sought ‘pattern matches’ in artificially generated agent-based modelling data. We also aimed to develop new ways of dealing with spatial complexity. Visualisation techniques, rarely used in economics, were applied in a range of data-rich contexts to better understand the architecture and complex dynamics of systems. Although a key goal in this program was to make fundamental theoretical and empirical advances, care was taken to work within several applied areas: induction is viewed as very important in the development of new theories, particularly in emergent research fields. In this regard, we felt it to be essential that theories be ‘historically friendly’ in complex adaptive system settings. This necessitated the development of new methodological perspectives not previously used in economic research.


Complex behaviour in financial markets

Project Leader: Jason Potts
Researchers: Mark Bowden, John Foster, Kate Morrison,  Stuart McDonald

This projects studied financial markets using complexity based tools. Two sub-projects were initially completed: (1) real bubbles theory, which looked at the connection between stock market bubbles and evolutionary economic growth, and (2) a network based simulation model of decentralised trading over four asset classes. We also worked on models of fourth-order complexity in financial markets, which involved modelling expectation formation and interaction.

In 2004, Kate Morrison built Java-based models of financial market interaction, Jason Potts' 'Real Bubbles theory' hypothesis was published and Mark Bowden completed an extensive review of models of financial market interaction and made due progress in developing models.

The modelling of interactive expectations went well in 2005, with two key papers by Bowden (and McDonald) written and accepted to international conferences (including the prestigious Computational Finance conference in June 2006). Potts and Morrison have had a paper accepted for publication in The Journal of Economic Behaviour and Organization on how our complexity approach connects to computational theory of the evolution of market algorithms. Potts and Morrison completed interviews with 16 evolutionary economic and complexity theorists in the USA and Europe and have a book contract to Edward Elgar to deliver in 2006 (Title: Conversations with evolutionary economists).
  • Earl, P., Peng, T., Potts, J., 'Can speculative decision-rule cascades explain asset price inflation?', Journal of Economics and Psychology, 2007.
  • Potts, J., 'Can a better theory of rules make for a better theory of institutions?', Journal of Economics Issues, 2007.
  • Potts, J., 'Exchange and evolution', Review of Austrian Economics, 2007.
  • Potts, J., "Liberty bubbles", Policy, Vol. 20, No. 3, 2004, 15-21.
  • Potts, J., Morrison, K., 'Meso comes to markets', Journal of Economic Behavior and Organization, 2007.

Eutrophication of the Great Barrier Reef marine ecosystem

Project Leader: Rodney Beard, Liam Wagner
Researchers: Leighton Brough, John Foster, Stuart McDonald, James Patterson, John Quiggin, Walter Reinhardt,

The Great Barrier Reef stretches along the continental shelf of the North-East coast of Australia forming a shallow lagoon between the reef and the coast. Human activity along the coast appears to have led to an accumulation of sediments, fertiliser, pesticides and herbicides in the marine environment with unforeseen consequences. The primary driving force behind this has been economic in nature. Integrated socio-economic and environmental modelling is needed to address scientific and community concern about the possible impact of the coastal agriculture on the eutrophication of the Great Barrier Reef lagoon. Complex systems methodology such as non-linear dynamics and self-organised criticality and network modelling is likely to prove useful in analysing possible impacts of human economic activity on a complex marine ecosystem.

In 2004 we explored hydrological models from a complex systems perspective. We then developed a means of integrating cooperative game theoretic models of cost sharing/ benefit-sharing with hydrological models of fractal river networks. We then constructed a prototype model for a linear river network which computed the evolution of value (benefit/cost-share) through time and along the length of the river network. This allows us to determine how to share the costs of sedimentation and pollutants flowing into the Great Barrier Reef Lagoon in a fair way. The work was written up and presented at the World Conference on Natural Resource Modelling in Melbourne, the International Society for Dynamic Games Meeting in Tucson, Arizona and the 49th Conference of the Australian Agricultural and Resource Economics Society in Coffs Harbour.

In 2005 we submitted our paper ‘Time consistent fair water sharing agreements’ to the Annals of International Society for Dynamic Games, it was accepted for publication and is expected to appear in August 2006. The paper is concerned with the consistency of water trading contracts over time taking into account the direction in which water flows along a river. It is envisioned that the results can be applied to the problem of trading pollution permits when pollution, such as fertilisers, herbicides or sediments, flows downriver. In addition, we were able to complete a multi-agent simulation model using the simulation package DIAS. This extended earlier modelling using optimal control theory to a multi-agent setting with the application being the impact of fertiliser run-off on fishing activity in the Great Barrier Reef region. In addition, we collaborated with the computational game theory project and together developed a new approach to developing multi-agent simulation models using haystack games as a theoretical framework. This was applied to the development of a simulation model for fisheries fleet dynamics. (Included 2005/06 summer project)

Achievements in 2006 included joint research with Thilak Mallawaraachchi (ABARE and Risk and Sustainable Management Group, UQ) on non-point source pollution from agriculture. We developed a model of how information concerning pollution measures impacts on political behaviour. Other work included the presentation of a paper on using DIAS to model non-point source pollution from agriculture at the 2006 Australian Agricultural and Resource Economics Society Conference at Manly, NSW.

In 2007, a generalised model for catastrophe management and the placement of marine reserves was developed by Liam Wagner. This model examines the optimal spacing between marine reserves for maximizing the viability of a species occupying a reserve network. The closer the networks are placed together, the higher the probability of colonisation of an empty reserve by an occupied reserve, thus increasing population viability. However, the closer the networks are placed together, the higher the probability that a catastrophe will cause extinction of the species in both reserves, thus decreasing population viability. Using a simple discrete-time Markov chain model for the presence or absence of the species in each reserve we have determined the distance between the two reserves which provides the optimal trade-off between these processes, resulting in maximum viability of the species.

  • Beard, R., McDonald, S., "Dynamic recontracting of water rights", 11th International Symposium on Dynamic Games and Applications, December 2004.
  • Beard, R., McDonald, S., 'Time consistent fair water sharing agreements', Annals of the International Society for Dynamic Games, Vol. 9, March 2007.
  • Brough, L., Beard, R., ‘A multi-agent simulation model of the impact of eutrophication on the Great Barrier Reef Lagoon using the dynamic information architecture system DIAS’, Australian Agricultural and Resource Economics Society (AARES) 50th Annual Conference, 2006.
  • Wagner, L., Ross, J., Possingham, H., 'Catastrophe management and inter-reserve distance for marine reserve networks', Ecological Modelling, Vol. 201, No. 1, February 2007, 82-88.

Simulation studies of social networks

Project Leader: David Green
Researchers: David Cornforth, Sheree Driver, Alex Tee Neng Heng, Gary Leishman, Tania (Bransden) Leishman, Suzanne Sadedin, Don Schauder, Rob Stocker,

Links between people form networks by which ideas, opinions and attitudes can disseminate throughout societies. This project used simulation models of social networks to investigate questions such as the formation of social groups, the role of peer influence in marketing, and the effects of economic and resource issues on social behaviour.

In 2005, the Virtual Laboratory (www.complexity.org.au/vlab/) was expanded, adding more demonstrations (e.g. cascading failures,  spread of epidemics, law and order), and text explanations. In a study this year, we used simulations of social networks to show that both prescription and peer pressure are needed to achieve cooperation and social order in large societies. Our results show that in the absence of law enforcement in social networks, peer pressure acts either to maintain law-abiding behaviour, or to flip the entire society into law-breaking (e.g. speeding on the roads). However, if a social network is well-connected, then even a small incidence of punishment suffices to ensure conformity. In general law breaking increases as social interactions decrease.

In 2006, our simulations have shown that both prescription and peer pressure are needed to achieve cooperation and social order in large societies. Our results show that, in the absence of law enforcement in social networks, peer pressure acts either to maintain law-abiding behaviour, or to flip the entire society into law-breaking (e.g. speeding on the roads). However, if a social network is well-connected, then even a small incidence of punishment suffices to ensure conformity. In general, law-breaking increases as social interactions decrease.

In 2007, we investigated the role in social networks of a process, Dual Phase Evolution (DPE), which is a widespread mechanism that underlies self-organisation in many systems. The process occurs in systems that switch between two phases: a balance phase and a variation phase. Using simulation experiments we showed how DPE may play a role in creating cliques, clusters, modules and other kinds of order within social networks.

Boolean network models (BN) represent a society as a network in which individuals are the nodes (with two states, e.g. agree/disagree) and social relationships are the edges. In BN models, the behaviour that emerges from peer interactions differs in subtle, but important ways from equivalent mathematical models (e.g. Markov, dynamic systems). Despite their simplicity, BN models provide potentially important insights into many social issues. Work in 2008 focused on the evolution of network structure in response to social processes by which individuals forge new relationships and by which existing relationships are broken. The results revealed that selection on the basis of a single issue tends to fragment a society into cliques whereas a selection based on a overall similarity leads to long, branching chains of association (Leishman and Green 2008). We showed that dual phase evolution (DPE) plays an important role in mediating the emergence of these structures.

  • Bransden, T., Green, D., ‘Getting along with your neighbours – emergent cooperation in networks of adaptive agents’, Intelligent and Evolutionary Systems, November 2005.
  • Cornforth, D., Green, D., Newth, D., ‘Ordered asynchronous processes in multi-agent systems’, Physica D, vol. 204, May 2005, 70–82.
  • Green, D., Leishman, T.G., Sadedin, S., “The emergence of social consensus in Boolean networks”, Proceedings of the 2007 IEEE Symposium on Artificial Life, April 2007.
  • Green, D., Sadedin, S., Leishman, T.G., 'The emergence of social consensus in simulation studies with Boolean networks', Proceedings of the First World Conference on Social Simulation, 2006.
  • Leishman, T.G., Green, D., “Dual phase evolution - a mechanism for self-organisation and optimisation”, Proceedings of the 11th Asia-Pacific Workshop on Intelligent and Evolutionary Systems, Edited by Namatame, A., December 2007.
  • Leishman, T.G., Green, D., “Self-organisation in simulated social networks”, Proceedings of the International Conference on Computer Mediated Social Networking (ICCMSN), June 2008, 1–6.

Water usage modelling for the Murray-Darling Basin

Project Leader: John Quiggin
Researchers: Archie Chapman, James Patterson, Liam Wagner

The object of the modelling project was to build a multi-catchment model of land and water use in the Murray-Darling Basin, incorporating flexible producer responses to uncertain availability of water for agricultural production. The aim was to provide insights on the implications of alternative specifications for irrigation water rights, environmental flow regimes and other policy. The basic building blocks of the model were catchment specific farm level models, based on activity analysis, with parameters derived from published gross margin models. Summer Research Assistants assisted in the construction and checking of these models, and in initial applications. (Included Summer Project 2004/05)

In 2005, the main focus has been on the design of water rights in the presence of uncertainty. The aim has been to use concepts of state-contingent production to model alternative systems of property rights, and to relate the theoretical and modelling treatment of uncertainty to the policy goals set out in the National Water Initiative. Several articles on water policy have been completed (including joint work with Professor John Freebairn) and several have been accepted for publication in the Australian Journal of Agricultural and Resource Economics.

Murray-Darling work has responded to developments in the public debate with an increased focus on urban-rural water trade and problems associated with climate change and drought. The model has been extended to encompass these issues, and results will be presented at the Australian Agricultural and Resource Economics Society Conference in February 2007. Substantial contributions have been made to public debate in a variety of forums, including public inquires and media. There has been particular interest in a proposal for  repurchase of renewal rights for irrigation water.

In 2008 we were commissioned by the Garnaut Climate Change Review to forecast the outcomes of climate change on the Murray-Darling Basin. In view of continuing uncertainty about the way in which the climate will be affected, forecasting the outcomes of climate change is a complex task. The model is solved by linear programming within each catchment. The two major outputs from this process were data to be used by Queensland Treasury on behalf of the Garnaut Review, and the report itself: ‘The implications for irrigation in the Murray–Darling Basin.’

  • Adamson, D., Mallawaarachchi, T., Quiggin, J., “Climate change and climate uncertainty in the Murray-Darling Basin”, 51st Australian Agricultural and Resource Economics Society Conference, February 2007.
  • Adamson, D., Mallawaarachchi, T., Quiggin, J, ‘Modelling basin level allocation of water in the Murray- Darling Basin in a world of uncertainty’, 49th Annual Conference of the Australian Agricultural and Resource Economics Society, Coffs Harbour, February 2005.
  • Adamson, D., Mallawaarachchi, T., Quiggin, J., 'State-contingent modelling of the Murray-Darling Basin: implications for the design of property rights', 50th Annual Conference of the Australian Agricultural and Resource Economics Society, February 2006.
  • Adamson, D., Mallawaarachchi, T., Quiggin, J., “Water use and salinity in the Murray–Darling Basin: A state contingent model”, Australian Journal of Agricultural and Resource Economics, Vol. 51, No. 3, September 2007, 263–281.
  • Chambers, R., Quiggin, J., "Technological and financial approaches to risk management in agriculture: an integrated approach", Australian Journal of Agricultural and Resource Economics, Vol. 48, No. 2, 2004, 199-233.
  • Freebairn, J., Quiggin, J., 'Water rights for variable supplies', Australian Journal of Agricultural and Resource Economics, Vol. 50, No. 3, 2006, 295-312.
  • Patterson, J., "A model of river flood insurance using stochastic co-operative game theory", Technical Report, 2004.
  • Quiggin, J., 'Averting an era of water wars', Presentation to the Australian Davos Connection's Australian Leadership Retreat, August 2006.
  • Quiggin, J., “Complexity, climate change and the precautionary principle”, Environmental Health, Vol. 7, No. 3, 2007, 15-21.
  • Quiggin, J., "Conjectures, refutations and discoveries: incorporating new knowledge in models of belief and choice under uncertainty", 22nd Australian Economic Theory Workshop, 2004.
  • Quiggin, J., "Discounting and policy options for sustainable management of the Murray-Darling River System", Working Paper, No. 1M04, Risk & Sustainable Management Group, University of Queensland, February 2004.
  • Quiggin, J., ‘Policy and modelling issues for sustainable management of the Murray-Darling Basin’, Presentation to the Productivity Commission, Melbourne, 17 March 2005.
  • Quiggin, J., 'Repurchase of renewal rights: a policy option for the National Water Initiative', Australian Journal of Agricultural and Resource Economics, Vol. 50, No. 3, 2006, 425-435.
  • Quiggin, J., ‘Risk and water management in the Murray- Darling Basin,’ Murray-Darling Program Working Papers WPM05-4, Risk and Sustainable Management Group, University of Queensland, Brisbane, 2005.
  • Quiggin, J., 'The uncertain future of water policy', Keynote address to the 35th Australian Conference of Economists, September 2006.
  • Quiggin, J., 'Urban water supply in Australia', Issues, Vol. 76, 2006, 41-44.
  • Quiggin, J., 'Urban water supply in Australia: the option of diverting water from irrigation', Public Policy, Vol. 1, No. 1, 2006, 14-22.
  • Quiggin, J., Adamson, D., Schrobback, P., Chambers, S., “The implications for irrigation in the Murray-Darling Basin”, Garnaut Climate Change Review, June 2008.
  • Quiggin, J., Chambers, R., "Drought policy: a graphical analysis", Australian Journal of Agricultural and Resource Economics, Vol. 48, No. 2, 2004, 225-51.
  • Quiggin, J., Chambers, R., 'The state-contingent approach to production under uncertainty', Australian Journal of Agricultural and Resource Economics, Vol. 50, No. 2, 2006, 153-169.
  • Quiggin, J., Tan, P., "Sustainable management of the Great Artesian Basin: an analysis based on environmental economics and law", Working Paper, No. 3M04, Risk & Sustainable Management Group, University of Queensland, 2004.
  • Venn, T., Quiggin, J., 'Accommodating indigenous cultural heritage values in resource assessment: Cape York Peninsula and the Murray-Darling Basin, Australia', Ecological Economics, Vol. 61, No. 2-3, 2007, 334-344.

Nonlinear econometric modelling: A complex systems perspective

Project Leaders: John Foster
Researchers: Melvin J Hinich, Phillip Wild

Complexity in real world systems is intrinsically generated by nonlinear interactions amongst system components that generate unanticipated emergent behaviour commonly associated with complex systems. This project sought to develop econometric techniques capable of identifying underlying emergent complexity in time series data. This involved applying a battery of nonlinear tests to both confirm the existence and identification of nonlinear interactions. This was principally based on using relative power of different nonlinearity tests to identify and categorise different types of nonlinear generating mechanisms and confirming complexity through rejections of tests of time reversibility.

The second year of this project, 2004, involved continued writing and commencement of testing and validation of FORTRAN code to: (a) activate various nonlinear and time reversible test statistics including trispectrum code; and (b) activate code which will allow the simulation of complex nonlinear artificial data series in a controlled setting. This involved performing a large number of replications so that the actual performance of test statistics under the controlled environment can be objectively assessed and compared with their expected theoretical properties. This was one important step used in the testing and validation of the FORTRAN code that we have developed. The other approach we used to validate our programs was to see if the code could reproduce known results. We have constructed and undertaken significant testing using a bridge program that incorporates all test statistics within the one general program. This step was judged to be crucial so that the results from running the program can be strictly controlled.

In 2005, we completed program testing and validation of the bispectrum and trispectrum based tests. Preliminary attempts have been undertaken at applying the trispectrum tests to high frequency finance data. The trispectrum tests allow direct assessment of nonlinear serial dependence associated with excessive kurtosis, and, as such, are a very powerful testing procedure when applied to high frequency finance data. The actual properties of all the test statistics have been examined using simulation methods to assess their actual (empirical) properties against their expected theoretical properties. These tests have allowed us to examine how large the sample sizes need to be to get actual rejection rates which match the theoretically expected rejection rates for the various test statistics. We have also begun using simulation methods to apply the tests to a wide assortment of nonlinear models to examine the relative power of the various test statistics. This information will be used to identify specific nonlinear structures associated with artificial data generated from various nonlinear models as well as confirming the structure contained in simulations of empirically estimated non-linear models. An article entitled ‘Structural change in macroeconomic time series: A complex systems perspective’ was accepted for publication in the Journal of Macroeconomics.

In 2007, we finalised work on the software including the trispectrum and have worked on applications to electricity price and load data with a view to generating an assortment of publications over the period 2008-09. This research effort will dovetail with the continuing research on electricity markets in the Centre project ‘Optimal allocation of embedded renewable electricity sources throughout the distribution network’.
  • Foster, J., Hinich, M., Wild, P., “A note on DFT filters: cycle extraction and Gibbs’ effect considerations”, Macroeconomic Dynamics, January 2009.
  • Foster, J., Hinich, M., Wild, P.,“Randomly modulated periodic signals in Australia’s national electricity market”, The Energy Journal, Vol. 29, No. 1, 2008, 105-130.
  • Hinich, M., Foster, J., Wild, P., 'A statistical uncertainty principle for estimating the time of a discrete shift in the mean of a continuous time random process', Computational Statistics and Data Analysis, 2007.
  • Hinich, M., Foster, J., Wild, P.,‘Structural change in macroeconomic time series: a complex systems perspective’, Journal of Macroeconomics, vol. 28, no. 1, 2006, 136-150.

Computational game theory

Project Leader: Stuart McDonald, Liam Wagner
Researchers: Rodney Beard, John Foster, John Hawkins, Narender Rana, Liam Wagner

This project examined the potential for applying global optimisation techniques, based on directed search and machine learning algorithms, for use in computing the equilibria of both static and dynamic non-cooperative games. The emphasis was on designing algorithms that converge on a sample Nash equilibrium that is a Nash refinement and assessing potential gains in computational efficiency from using these algorithms. From this perspective, the focus of this project was on using these algorithms to increase the likelihood of game theory being used as a modelling tool for large, complicated multi-agent systems.

The project was split into two sub-projects. In 2005, the first sub-project focused on applying directed search and machine learning algorithms to the problem of finding Nash equilibria in non-cooperative games. Research from this sub-project focusing on the computational complexity is being written into a monograph that is currently being reviewed by Edward Elgar Publishing. Two papers based on this research have been accepted for publication with the IEEE Transactions on Evolutionary Computation and the Journal of Network Security. The second sub-project focused on modelling spatial interactions between agents and is nearing completion. The main objective of this research has been to develop a haystack model that can be used as paradigm for modelling network formation and agent self-organisation. This model was used to simulate fishery fleet dynamics. The results of these simulations will be reported at the Australian Agricultural and Resource Economics Conference in Sydney during February 2006. We are currently investigating the application of these tools to the auctioning of airport landing slots.

During 2006, we continued our modelling work applying the haystack game to fishery fleet dynamics and the Byzantine game to network security. Research student Gillian Salerno completed her master's thesis examining rent seeking in the dynamic lake game problem. A paper by honours student Luke Boosey submitted for Australian Economics Honours Student Symposium examined the implementation of binary public goods via population surveys. Based on this work, Luke was offered a PhD fellowship at Caltech.

In 2007, research undertaken by Liam Wagner has led to a game theoretical model for electricity pricing on the National Electricity Market (NEM) for the pending National Emissions Trading Scheme (NETS). This dominant firm with competitive fringe model allows for market participants to examine the impacts of carbon trading on wholesale electricity spot prices. This work examines the impact of NETS on market power and whether generators will be able to recover their carbon cost from the wholesale market under perfect and imperfect competition scenarios.

  • Hawkins, J., Beard, R., McDonald, S., 'A multi-agent simulation model of fishery fleet dynamics for the Queensland coral reef line fishery', AARES 200.
  • McDonald, S., "The design and maintenance of secure communications networks", 48th Australian Mathematical Society Meeting, 2004.
  • McDonald, S., Wagner, L., "Uncovering message spoofing in secure networks", 2nd World Congress on Game Theory, 2004.
  • Menezes, F., Quiggin, J., “Games without rules”, Theory and Decision, Vol. 63, No. 4, October 2007, 315-347.
  • Wagner, L., McDonald, S., 'Finding traitors in secure networks using Byzantine agreements', International Journal of Network Security, 2007.

Complexities of homelessness

Project Leader: John Quiggin
Researcher: Rhea Coleman

Since the mid-1970s, homelessness has grown to become an issue affecting, according to the ABS, roughly 100,000 people in Australia. Government policy to address this issue has focused primarily on the individual and their ‘deficits’. The increasing trend towards homeless families, women and young people - a shift from the traditional stereotypical ‘core’ population of older, homeless men with substance abuse issues - suggests that individual ‘deficits’ are not the only factors affecting vulnerability to homelessness and, in turn, that a broader policy focus needs to be adopted to address this social pathology. This project looked at the complex interaction between macroeconomic conditions, including housing market conditions, and individual characteristics, which create vulnerability to homelessness, by examining varying rates of homelessness across Australia. Understanding the broader forces at work upon homeless individuals will aid the better formulation of policy, at both a federal and state level, accounting for the factors which have been largely ignored to date.

Temporal complexity

Project Leader: Penelope Sanderson
Researcher: Rizah Memisevic

In this project we investigated temporal complexity in the hydropower system and air traffic control domains. Temporal complexity refers to the emergence of stability or instability in a complex system as a result of the timely coordination of different elements of the system. The goal of the research was to develop visualisations of complex system performance that will promote activity within effective temporal contexts.

During 2006, we developed further our theoretical and methodological thinking about temporal complexity, drawing from hydropower system control, air traffic control, and healthcare. Using general principles drawn from Cognitive Work Analysis, we proposed innovative visualisations of hydropower system information that convey temporal properties and promote better human management and control of the system in light of temporal properties. Our analysis revealed some shortcomings in Cognitive Work Analysis for arriving at effective support of human activity in temporal context, which will be the subject of future research. Research is being written up for journal publication.

  • Li, X., Sanderson, P., Wong, W., Memisevic, R., Choudhury, S., 'Evaluating functional displays for hydropower system: Model-based guidance of scenario design', Cognition, Technology, and Work, Vol. 8, No. 4, 2006, 269-282.
  • Memisevic, R., Sanderson, P., Wong, W., Choudhury, S., Li, X., 'Investigating human-system interaction with an integrated hydropower', IEEE Transactions on Power Systems, 2007.

Complex networks and the world trade web

Project Leader: John Steen
Researchers: John Foster, Tim Kastelle, Peter Liesch, Sam MacAulay, Jason Potts, 

The study of complex networks is a growing part of the complexity literature that is characterised by the use of statistical mechanics to examine the network properties of a variety of biological, technological, social and economic systems (see Newman 2002 for detailed review). While some work has been done showing that complex network properties exist in directorship networks (Davis 2003), banking investment syndicates (Baum et al. 2004) and inter-firm alliances (Verspagen and Duysters 2004), little has been done in terms of understanding what these properties actually mean for the functioning of these systems. To this extent, the study of world trade networks is still at an embryonic stage that is ripe for theory building and empirical testing. Essentially, we used network parameters as independent variables that affect other performance related variables such as system robustness, information flow and economic growth.

In 2006, the world trade web project achieved significant milestones. Analytically, we have advanced our understanding of the statistical mechanics of the world trade web while simultaneously achieving publication and conference outcomes in both academic and industry forums. The project has achieved exposure through the foreign affairs magazine ‘The Diplomat’ and an invited presentation on Globalization and Business Strategy to the annual Certified Practising Accountants Congress. A number of papers have been submitted to prestigious journals. An invited chapter on international trade networks and terrorism is being written for a Sage handbook on international management in conjunction with two leading US researchers in the field, who have previously advised US Congress committees on the impact of terrorism upon international trade.

In 2007, the research team has investigated the use of probabilistic methods to analyse the dynamics of the world trade web. These statistical techniques and associated software such as PNet and SIENA are able to determine the mechanisms that drive the evolution of the world trade web as a complex system. For example, applying SIENA to the world trade dataset over the last 100 years has revealed that preferential attachment (i.e. the rich get richer) can partly explain the most recent evolution of the world trade web. It is possible that these longitudinal analyses can be applied to the mechanisms behind the evolution of complex networks more generally.

In 2008 the research team made further progress in the study of complex networks. Tim Kastelle completed his PhD ‘Analysing the evolution of international trade: A complex networks approach’. There are currently five papers from this work under editorial review. The research team is using the analytical techniques developed in this project to analyse innovation networks within project-based firms. Data collection for this project with industry partners Rio Tinto Coal Australia and Hatch Engineering commenced at the end of 2008.

  • Kastelle, T., 'Trading places: globalisation myths', The Diplomat, Vol. 41, August 2006.
  • Kastelle, T., Potts, J., 'The economic evolution of the world trade network', 11th International Schumpeter Society Conference, June 2006.
  • Kastelle, T., Steen, J.T., Liesch, P.W., 'Measuring globalisation: An evolutionary economic approach to tracking the evolution of international trade', DRUID Summer Conference, June 2006.
  • Kastelle, T., Steen, J.T., Liesch, P.W., 'The evolution of international trade: a network approach to measuring globalisation', Academy of International Business Annual Meeting, June 2006.
  • Kastelle, T., Steen, J.T., Liesch, P.W., 'Globalisation and connectedness: A network approach to international business', Academy of International Business Annual Meeting, June 2006.
  • Liesch, P., Steen, J., Knight, G., Czinkota, M., “Internationally managing in the face of terrorism-induced uncertainty”. In C. Wankel (Ed.), 21st Century Management, Thousand Oaks: Sage, 2008, 200–208.
  • Steen, J.T., Liesch, P.W., Knight, G., Czinkota, M., 'The contagion of international terrorism and its effects on the firm in an interconnected world', Public Money and Management, Vol. 26, No. 5, November 2006, 305-312.
  • Steen, J., MacAulay, S., Kastelle, T., “New tools to map and manage innovation networks”, in Inside the Innovation Matrix—Finding the hidden human dimensions, Australian Business Foundation, 2008, 82–95.

General EES publications

  • Bell, P., “Adaptive interactive profit expectations and small world networks”, Journal of Evolutionary Economics, 2008.
  • Bell, P., “Adaptive interactive profit expectations and small world networks”, SPIE Symposium on Smart Materials, Nano- and Micro-Smart Systems, 2008; Proceedings of SPIE, Vol. 7270.
  • Bowden, M. “Confirmatory bias and the sharing of information within social networks”, In: Arabnia A, Yan M and Yang J (Eds), Proceedings of the 2007 International Conference on Artificial Intelligence. 2007, 62-70.
  • Bowden, M., McDonald S “The impact of interaction and social learning on aggregate expectations” Computational Economics, Vol. 31, No. 3, April 2008, 289-306.
  • Chambers, R., Quiggin, J., 'Dual approaches to the analysis of risk aversion', Economica, 2006.
  • Dopfer, K., Foster, J., Potts, J., "Micro-meso-macro", Journal of Evolutionary Economics, Vol. 14, No. 3, 2004, 263-280.
  • Earl, P., Peng, T., Potts, J., “Can speculative decisionr ule cascades explain asset price inflation?”, Journal of Economic Psychology, 2007.
  • Foster, J., “Complex economic systems”, Philosophy of Complex Systems, Handbook of the Philosophy of Science Series, Elsevier, 2009.
  • Foster, J., "From simplistic to complex systems in economics", Cambridge Journal of Economics, vol. 29, 2005, 873–892.
  • Foster, J., “Joseph Schumpeter and Simon Kuznets: Comparing their evolutionary economic approaches to business cycles and economic growth”, Journal of Evolutionary Economics, Vol. 9, January 2009.
  • Foster, J., 'Macro-econometrics', The Elgar Companion to Neo Schumpeterian Economics, Edward Elgar, 2006.
  • Foster, J., ‘The self-organisation perspective on economic processes: a unifying paradigm?’, The Evolutionary Foundations of Economics, Edited by Dopfer, K., 2005.
  • Foster, J., 'Time', The Elgar Companion to Alfred Marshall, Edward Elgar, 2006.
  • Foster, J., 'Why is economics not a complex systems science?', Journal of Economics Issues, 2006.
  • Foster, J., Holzl, W., Applied Evolutionary Economics and Complex Systems, Edward Elgar, 2004.
  • Foster, J., Metcalfe, J., Evolution and Economic Complexity, Edward Elgar, 2004.
  • Foster, J., Metcalfe, J., “Introduction and overview”, Economics of Innovation and New Technologies, Vol. 18, January 2009.
  • Foster, J., Potts, J., 'A micro-meso-macro perspective on the methodology of evolutionary economics: integrating history, simulation and econometrics', Schumpeterian Perspectives on Innovation, Competition and Growth, Springer, 2009.
  • Foster, J., Potts, J., 'Complexity, evolution and the structure of demand', Flexibility and Stability in the Innovating Economy, Oxford University Press, April, 2006.
  • Foster, J., Raine A., Potts, J., 'The new entropy law and the economic process', Ecological Complexity, 2007.
  • Metcalfe, J., Foster, J., Ramlogan, R., "Adaptive economic growth", Cambridge Journal of Economics, Vol. 30, No. 1, 2006, 7-32.
  • Ghoneim, A., Barlow, M., Abbass, H., “Rounds effect in evolutionary games”, Progress in Artifi cial Life, 12 2007; Lecture Notes in Computer Science, Vol. 4828, 72-83.
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