Income and wealth inequality is not a new phenomenon. On the contrary, it seems that it is a permanent feature in human history, and over the years, its causes and consequences have become more numerous and more interconnected. The same is true for many social phenomena, and even though the world looks more complicated today, it is not. What is different is the increased number of domains where public policy is expected to play a role. Regarding inequalities of income and wealth, governments have to make decisions on several interlinked areas such as taxes, education or health.
Unfortunately, the tools at the disposal of policymakers have not always been updated fast enough to cope with these challenges and with their inter-linkages. Moreover, policies are often designed within the narrow confines of one issue, without taking into account their consequences elsewhere.
Economists have tried to simplify and abstract from reality with limiting assumptions like the representative agent and general equilibrium. They have also given primacy to the goal of effectiveness, in detriment to other important considerations such as fairness. Yet, the use of aggregate data obscures the distributional consequences of policies: an economy as a whole may be doing well, but – as we have seen in recent years – there are severe consequences for social cohesion, and ultimately growth itself, if large groups are excluded from the benefits of economic prosperity. In defining growth policies that aimed only at increasing GDP per capita, inadequate attention was paid to institutions, human behaviour, and culture. These approaches failed to adequately account for the realities of markets, consumer decisions, and the interconnectedness of economic, communications and societal networks.
In stark contrast to the assumptions of neo-classical economics, socio-economic systems are not stable, but in constant flux. Complexity science generates new insights and furnishes us with the analytical tools and instruments to help us, as individuals and societies, to navigate this new understanding of the economy. It addresses some of the limitations which constrain conventional economics and ultimately it is helping us to do a better job in advising governments and public institutions.
For example, taking a complexity-based approach we can begin to recognise that the causes and consequences of inequalities and major economic and societal problems are intertwined. Besides contributing substantially to the increase of wealth inequality, the financialisation of the economy also led to increased systemic risks where a problem in the subprime markets led to a major economic crisis that has set additional hurdles in the way of the most vulnerable groups all over the world.
Just like the financial system and its major risks, our social systems are complex and vulnerable. Considering the increased fragmentation and divisions in our societies (and adding the challenge of integration of migrants and marginalized groups) more attention should be paid to social stability. In this vein, policies to address societal problems, should not only rely on traditional economic tools and measures, but broaden them to bring insights of useful disciplines.
This more realistic approach to how people and the economy actually work is needed – an integrated inclusive growth agenda which also considers unintended consequences, trade-offs and complementarities between policy objectives.
Indeed, I believe that economists – and the policy makers they advise – can do better by listening to and learning from others. It’s not easy for an organisation that has “Economic” in it is name, but we need to break the monopoly of economics over policy – looking to other disciplines such as physics, biology, psychology, sociology, philosophy and history. Societies and economies are not static features that can be predicted, but evolutionary systems with breakpoints and changes that need to be better characterized.
At the OECD, we recognise the potential of new economic thinking, drawing on complexity theory, and evolutionary and behavioural economics. Technological and analytical innovations are driving a revolution in the physical sciences, biological sciences, and social sciences, breaking down the barriers between disciplines and stimulating new, integrated approaches to pressing and complex challenges. Advances in computing power are opening up new possibilities for integrating systems models, agent-based modelling and network analysis. It is only by properly utilising these new approaches that we can strive to create social and economic models that provide a more accurate representation of the world around us. These tools also allow us to get away from average representations, or to look at stocks and not only at flows in the economy (income vs wealth inequality).
And indeed, economics is starting to incorporate insights from other disciplines. For example, expectations may be admirably rational in traditional models, but by combining psychology and economics we are designing policies based on how real people actually behave, not on limited assumptions about how some fictional average person should behave. Taking a problem-based approach, we can design policies to influence people and nudge them in the right direction in areas such as consumer policy, regulation, and environmental protection.
The OECD is part of this revolution and we are already transforming our policy thinking and acting. With the New Approaches to Economic Challenges (NAEC) initiative, we are taking a hard look at our analytical methods, our data and policy advice.
Many articles in this series have argued that the economy is a complex adaptive system. Society is a complex system too. It is formed by the interaction and mutual dependence of individuals, and is pursuant to their spontaneous, natural behaviour. Since the emergence of hunter-gather societies inequalities have threatened to undermine and weaken the fabric of the social system. If we are to overcome the pernicious effects of these inequalities, we need to think about the interactions between our social and economic systems – which follow their own logics – and design policies which help our economies to grow. But growth isn’t an end in itself. It has to be inclusive to ensure that all segments of our societies prosper.
Systems thinking can lend us a hand to fight inequalities and develop an agenda for inclusive growth. As we draw out the inter-linkages between different policy areas, we begin to understand how the economic system interacts with other systems, as well as with the history, politics, and ambitions of countries. Our task now is to put this growing comprehension to good use, in order to make the economy work better for all people.
The OECD is organised a Workshop on Complexity and Policy, 29-30 September, OECD HQ, Paris, along with the European Commission and INET. Watch the webcast: 29/09 morning; 29/09 afternoon; 30/09 morning