2. New Paradigms and Approaches for Economic Growth and Well-being
It is argued that economics needs to change radically since the socio-economic system is changing and self-organising itself in a way which is difficult, if not impossible, to reconcile with existing theory. In an increasingly complex and interdependent system, the aggregate phenomena that emerge do so as a reflection of the interaction between all the participants. The system is constantly evolving and is neither in, nor converging towards, a steady state. Thus, forecasting cannot be based on extrapolations from the past or analysis of the behaviour of an isolated individual. To position economic growth and analysis in a wider systems perspective requires both innovation of economic tools, methodology and policy, and the repositioning of the field of economics in relation to other critical fields such as the environment, society, and politics at the analytical and rhetorical levels and through the integration of policies in practice.
The 2008 crisis has provoked a debate on whether our existing economic models and analysis can be incrementally adapted to incorporate the many ideas that were missing and the new insights that have emerged, or whether a paradigm shift is needed. This chapter argues that economics will not be able to avoid a radical change since the socio-economic system is changing and self-organising itself in a way which is difficult, if not impossible, to reconcile with existing theory. Even in the “hard sciences”, it is very difficult to come up with encompassing theories that satisfactorily deal with and explain quite simple systems of interacting particles, molecules, or cells. An apparently very simple, but, in reality, extraordinarily complex, example is the evolution of patterns in John Conway’s Game of Life. It is even more difficult to argue that we can treat a complex system like the socio-economic one in the same way that we can treat systems of interacting particles, for, as Murray Gell-Mann is supposed to have said: “Imagine how hard physics would be if electrons could think”. We can learn a lot from the way complex physical systems evolve, but as Richard Feynman noted, “In physics the truth is rarely perfectly clear, and that is certainly universally the case in human affairs. Hence, what is not surrounded by uncertainty cannot be the truth.”
We have been led down a path traced by many economists that had as its goal to establish an overall theory, with laws that Walras claimed would be as “incontrovertible as those of astrophysics”. This theory has been honed and modified over time to include many insights from other disciplines, but without putting into question the basic “benchmark” model. This model, epitomised by the “perfectly competitive” economy and regarded as an idealisation of a real economy, still dominates the field, and deviations from its assumptions are regarded as “imperfections”, “frictions”, or due to exogenous “shocks” which periodically knock it off course.
In other disciplines, there are phenomena which evolve but which are thought of as being governed by some basic underlying laws. A paradigm shift occurs, as Kuhn suggested, when a major change in this underlying system of laws is proposed and when that change is accepted and adopted by the members of that discipline. We are seeing such a shift now in the theory of evolution with a replacement of the simple idea of individualistic survival and competition between individuals with a much more subtle view of evolution with selection, competition, and co-operation at various levels from very micro to large groups. By viewing evolution as a complex adaptive system, this change, epitomised by the work of Corning (2005), Sloan Wilson (2016) and other evolutionary biologists, undermines the basic evolutionary analogy that economists have long used. As Corning (2005) says, “the emerging new paradigm is focused on a different set of questions… Indeed, the new paradigm is more about competition via co-operation than some conflict between them”.
In economics, we are faced with a system that is not only changing fast, but is changing in part in response to the conscious choices of those who make it up. That makes it even less predictable than biological or physical systems. Worse, the onset of the Anthropocene era has meant that we can no longer afford to ignore the relation between the environment and the individuals that inhabit it. The whole socio-economic system bears little or no relation to that which existed in the preceding centuries and it is vain to believe that there is some overarching framework based on 19th century liberal principles that embodies the rules by which the system functions. Many developments have taken our system away from that portrayed in theory, even with all the “epicycles” that we have developed to include the systematic deviations from the underlying model.
There are three distinct ways of thinking about the future development of economic modelling, theory, and philosophy. First, that current economic models capture reality with sufficient accuracy, so no further changes should be made. The second school of thought is centred on the belief that while current economic models may not be perfect, their limitations can be overcome through incremental improvements, for instance by incorporating some bounded rationality. This appears to have been the case since the stagflation of the 1970s and the global financial crisis of 2008 showed that the original neoclassical and Keynesian pictures of the economy did not capture all its features. Since then, we have come a long way in making economic models more complicated.
The third school of thought considers that current theory and modelling are heading down the entirely wrong path, and there is a pressing need for a paradigm shift. Without disregarding how far economic thought has already taken us, the idea is that the underlying principles of rationality and general equilibrium do not accurately represent reality. The theoretical underpinnings of traditional economic growth theory, for example, tend to build upon mathematical representations with (rational) homogeneous representative agents, derived from the theoretical setting provided by Solow (1956) and the paradigmatic structure based on infinitely-lived rational individuals proposed by Ramsey (1928). However, in spite of the large amount of knowledge about the mechanisms leading to income growth gained by using these models, the focus on homogeneous agents implies that topics such as the linkage between economic development and intra- and intergenerational inequality have been significantly under-researched.
Linkages affecting everything from trade to well-being exist across both time and space, within the economic system and from the economic to the social, political, financial and environmental systems. The global financial crisis of 2008 highlighted some of the shortcomings of then state-of-the-art economic models in the sense that, with the exception of some non-traditional economists, the crisis was by and large not predicted. The crisis emerged endogenously from within the financial system and spread into the world economy. This went against economic predictions that frequently consider only exogenous shocks perturbing a general equilibrium, and only barely included the financial system in macroeconomic models.
What is required is a systems approach to incorporate the non-linearities, evolution, interlinkages, tipping points, emergence, trade-offs, synergies, and other characteristics of the systems we inhabit. This would be a paradigm shift in economic thought. One of the implications is a shift in the basis of economic models towards promising avenues in agent-based modelling, network models, and machine learning. In these models, non-linear relationships can be determined and addressed. Furthermore, agent-based models reflect the bottom-up nature of the economy by considering the interactions of individually modelled agents (such as households or firms) and determine the emergent macroeconomic trends through large-scale simulation. In this way, the broad implications of policy implementations on a variety of emergent properties can be studied and the complex outcomes of policy proposals recognised. Additionally, realisation of the multitude of network structures that exist in various systems will help identify key risks and allow policymakers to design policy to improve resilience. (See for instance chapter 13 of this publication on financial networks and transaction risk). Such a framework also allows easy adaptation of new insights in behaviour, the environment, sociology, and economics.
Change is also needed beyond modelling. For example, IIASA argues for the inclusion of age in national accounts, and the study of age-specific patterns of key economic activities. Only by considering the whole system of public and private inter-generational transfers can analysts adequately explain and project the impacts of transfers on public finances and derive evidence-based options for policy reforms.
The orthodoxy in economics is not as clear-cut as in the natural sciences, and thus multiple perspectives are simultaneously present and pursued. Consequently, the underlying economic narrative has frequently changed. In the last century, there have been two dominant schools of thought. The 1929 stock market crash and the Great Depression gave rise to the Keynesian school of economics as the ruling paradigm. Keynesian economics set full employment as its major goal and established the welfare state. This also gave rise to a wider spectrum of government intervention in the market and in the creation of the welfare state. However, during the 1970s the economy experienced stagflation, which is the simultaneous occurrence of economic stagnation and high inflation. Keynesian economics was unable to provide solutions for this problem, nor was it able to provide explanations for the oil crisis and other shocks. The Chicago School proposed the alternative and new paradigm of neoclassical economics.
Under the auspices of the free-market economic theory led by the Chicago School, much focus has been on the idea of market efficiency and how this can be achieved. One approach, that appears widely implemented, is the deregulation of business and the reduction of taxation. This, so the argument goes, reduces frictions to competition, and the more “perfect” competition is, the better. However, this has neglected to fully consider the environmental or social implications of such policy. As evidenced in the period from the 1970s until today, inequality has not improved, and in many cases, has become more extreme. Furthermore, the effects of human-created emissions on the planet are having severely negative consequences. In effect, the linkages between systems were not thought about deeply in the pursuit of productivity growth. Systems thinking fully considers such interconnections by treating these individual systems as intra- and inter-connected. Such an approach, that could be implemented through the development of agent-based modelling, network analysis, and machine learning, has the potential to generate a more holistic picture of these varied cross-effects. A concrete example would be the ability of agent-based models to endogenously reproduce the characteristics of the business cycle without external effects such as supply or demand shocks.
The current state of global affairs presents the opportunity for another paradigm change in economic thinking. A paradigm change centred on the idea of the economy as a complex adaptive system. Such a new approach requires not only a theoretical framework but also an expanded set of tools that can reflect the paths and outcomes of the current world, and allow for research and policy into how to improve it. The predominant experts in systems analysis, IIASA, have already developed a plethora of models that can guide and aid the development of further tools and policy.
Recent work conducted by IIASA scientists concentrates on understanding how economic outcomes are affected by modelling societies that are populated by heterogeneous agents. The effort carried out at the Institute to reconstruct and project populations by age, gender, and educational attainment (see Lutz et al., 2014) has led to a deeper understanding of new stylised facts concerning the interaction of human capital formation, economic growth, and inequality in heterogeneous societies. Such results give us empirical knowledge about how the educational attainment of the different cohorts which coexist at a given time affect economic development trends (Lutz et al., 2008), inequality (Rao et al., 2018), or political outcomes such as democratisation processes (Lutz et al., 2010).
Pure theoretical modelling frameworks aimed at embodying the complexity of the interactions among economic agents in economic growth models have also been developed in interdisciplinary initiatives within IIASA. The degree of interconnectedness of the global economy implies that understanding the systemic characteristics of the existing trade and financial linkages, as well as recognising the importance of their system-level network properties, is central to assess economic growth and the disruptive power of crises in a globalised world. IIASA uses network analysis to provide evidence on the degree of resilience of global commodity trade (Kharrazi et al., 2017) and to provide a general theoretical structure to study the international mobility of labour and capital (Wildemeersch et al., 2019). By using multi-layer networks and combining control theory and system dynamics, the complex interdependencies between labour and capital flows, as well as their contribution to economic growth and well-being, can be captured, and the welfare implications of different policy options can be evaluated.
To position economic growth in a wider systems perspective requires both innovation of the tools, methodology, and policy within the field of economics, and the repositioning of the field of economics in relation to other critical fields such as the environment, social affairs, and political affairs - not only at the analytical and rhetorical levels but through the difficult integration of policies in practice. In the worldwide ferment of new economic thinking, there is an important opportunity for OECD to concert the expertise of its substantive Directorates and policy committees with the scientific capabilities of IIASA and its Member institutions to take a lead in developing the integrated systems-based approaches for sustainable progress so urgently required.
A number of things are clear already. We are faced with a system that is increasingly complex and interdependent. In such a system, the aggregate phenomena that emerge do so as a reflection of the interaction between all the participants in the system. The system is constantly evolving and is neither in, nor converging towards, a steady state. Thus, forecasting cannot be based on extrapolations from the past nor on the analysis of the behaviour of an isolated, “representative” individual or firm.
Perhaps the most important lesson from the crisis is that our socio-economic system is evolving fast and becoming more and more distant from our old basic economic model. Making efforts to “reform” the economy so that it resembles the model more closely through increasing flexibility and deregulation, may not be helpful. We need to develop better analysis of the system as it is and not as we might have liked it to be.
References
Arthur, W. B. (1989) ‘Competing technologies, increasing returns and lock-in by historical events’, Economic Journal, 99: 116–31
Bowles S and H Gintis (2011) A Cooperative Species, Human Reciprocity and Its Evolution Princeton University Press, Princeton N.J
Chavalarias David (2018), « Au-delà des “ fake news ” : à l’ère numérique, nos démocraties doivent évoluer pour ne pas mourir ». https://hal.archives-ouvertes.fr/hal-01924436
Corning P, (2005) Holistic Darwinism: Synergy, Cybernetics and the Bioeconomics of Evolution Chicago, University of Chicago Press
Glaeser E, (2019) “Thoughts On How To Talk Capitalism to Millennials”, Los Angeles Times May 2 2019.
Kharazzi et al. (2017) “Network structure impacts global commodity trade growth and resilience”. PLoS ONE. Vol. 12/2, https://doi.org/10.1371/journal.pone.0171184
Lazer David M. J., Matthew A. Baum, Yochai Benkler, Adam J. Berinsky, Kelly M. Greenhill, Filippo Menczer, Miriam J. Metzger, Brendan Ny, (2018), “The science of fake news” Science 09 Mar:Vol. 359, Issue 6380, pp. 1094-1096
Lutz, W., W. Sanderson, S. Scherbov (2008), “The coming acceleration of global population ageing”, Nature, Vol. 451, pp. 716-719
Lutz, W., J. Crespo Cuaresma, and M.J. Abbasi-Shavazi (2010), “Demography, education, and democracy: Global trends and the case of Iran”, Population and Development Review Vol. 36/2, pp. 253–281
Lutz, W., W.P. Butz, and S. KC (eds.) (2014), “World Population and Human Capital in the Twenty-First Century”, Oxford, UK: Oxford University Press
Mazzucato, Mariana.( 2013). The Entrepreneurial State: Debunking Public vs. Private Sector Myths. New York: Anthem Press
Rao, N., Sauer, P., Gidden, M., and Riahi K. (2018) Income inequality projections for the Shared Socioeconomic Pathways (SSPs). Futures, forthcoming
Seabright P, (2004), The Company of Strangers, Oxford University Press, Oxford.
Sloan-Wilson, David and Alan Kirman, (2016) Complexity and Evolution: Towards a New Synthesis for Economics MIT press Cambridge Mass
Wildemeersch, M., E. Rovenskaya & L. Ilmola. (2017) “A collaborative expert system for group decision making in public policy” IIASA working paper WP-17-01
