Gabriela Ramos, OECD Chief of Staff and Sherpa to the G20
When the subprime crisis started, most economists, and the policymakers they advised, thought it would only affect people who had bought homes they couldn’t afford. They didn’t expect that national problem to trigger a cascade of events that almost caused the collapse of the world financial system. Nor did they foresee how the financial crisis would lead to the Great Recession. Global interconnectedness and the complexity it brings were not really understood, nor were the contagion mechanisms that they can trigger and that would impact other regions of the world.
Today, we’re trying to understand how the Great Recession and the other important trends that it aggravated such as growing income and wealth inequality, gave birth to the backlash against globalisation, and to the political crisis we are confronting in many countries, with divided societies and a lack of common purpose. At the OECD, we set up our New Approaches to Economic Challenges (NAEC) initiative to examine these failures and establish the basis of a better way of analysing economic challenges and producing policy advice based on that analysis.
The slogan of this year’s OECD Forum was “You talk, we’ll listen”, and that is what NAEC has been doing. Over the past few years, we’ve asked a wide range of people what was wrong with the way we were doing things. And they haven’t been shy about telling us!
At the Forum, we presented the views of a sample of around 20 world experts across a variety of fields – financiers managing billions of dollars, Nobel prize-winning economists, political scientists, social scientists… compiling the ideas they have shared all through the NAEC initiative.
As you’d expect from such a strong-minded group, they don’t always agree with us or each other, and we do not claim to buy all that they say. More importantly, to avoid the “herd thinking” prevailing before the crisis, and that prevented a better understanding of the imbalances that were accumulating to a tipping point, it is important to listen to those that think differently from us, and to remain open to criticism and honest exchanges.
But a number of common views do emerge from reading the draft report. Growing integration and connectedness is helping to improve living standards across the globe, but the traditional models we use to study today’s economy make too many assumptions that are at odds with the facts. The very name of these models, general equilibrium, shows that they assume that the economy is basically in balance until an outside shock upsets it. They assume that you can understand the economy by studying a representative agent whose expectations and decisions are rational.
This view is essentially linear, and the policy advice it generates is tailored to a linear system where an action produces a fairly predictable reaction. It looks at aggregate outcomes and at average results. It concentrates on flows and does not consider stocks. Real life is not like that.
Economic models that rely only on inputs such as GDP, income per capita, trade flows, resource allocation, productivity, representative agents, and so on can tell a part of the story, but they fail to capture the distributional consequences of the policies we make, and do not address the fact that the growth process has only benefited a few. They do not capture natural depletion, or incorporate environmental damage as liabilities. On the contrary, they assume that, by growing the pie, inequality of income and opportunities will diminish (the trickle-down effect), or that you can always clean after you grow. So we need a full re-vamp of our analytical frameworks and the assumptions that we make, to better capture the reality. At the OECD we have done so by proving that income inequality harms growth.
To start with, we need different more granular information, data and analysis, and definitely, better metrics. We have to be able to check how policies will impact different income groups, communities, regions and firms. We need to get away from growth first and distribute later, or clean later. The unintended consequences of policies should be considered beforehand, and so should equity.
Traditional models do not integrate important dimensions such as justice, trust or social cohesion that are not easily measurable. In fact these models are based on an ideology or narrative that claims that people are rational, take the best decisions according to the information they have to maximize utility, and that the accumulation of rational decisions will deliver the best outcome.
Real people are not like that. Their lives are shaped by their hopes, aspirations, history, culture, tradition, family, friends, language, identity, the media, community and other influences. As these other elements are not the core of macroeconomic models, they are neglected, and the social and human sciences (psychology, history, sociology…) that can explain these variables have been put aside in the modelling work to develop economic policy options. As the economic profession became highly quantitative, the non-measurable features of the economy were just ignored, such as people’s fears, expectations or sense of unfairness.
The world we live in is a system of systems, physical or not, that is complex. That means you have to take a systemic approach that can deal with tipping points, phase changes, emergent properties, and – very important for us – the fact that shocks do not come from outside. The system itself produces the shocks that destabilise it.
We need a new approach to economics that isn’t just about quantitative economics. An approach that integrates behavioural economics and complex systems theory, as well as economic history.
We also need a new narrative to integrate all these different, often conflicting influences. So what might such a new narrative look like? The report concludes that it should be based on the best facts and science available, and contain four stories: a new story of growth; a new story of inclusion; a new social contract; a new idealism.
The state can help empower the shift. An empowering state is one that focuses on strategic investments to allow people, firms and regions to fulfil their potential. That means putting people at the centre of our policy efforts, and broadening the objectives of policies to include not only material well-being but many other options that are important such as health, quality jobs, a sense of belonging, social cohesion, and environmental outcomes.
At the OECD we have made progress with NAEC and with the Inclusive Growth Initiative, inviting policy makers and stakeholders to consider different alternatives to the traditional framing of economic issues. We conclude that by being inclusive, economies can be more productive, and that fostering productivity growth in an inclusive manner makes growth sustainable. We call this the “nexus” or the need to foster “inclusive productivity”. We are making the call to turn this analysis into action, but this will require a re-engineering of the institutional settings in OECD economies, getting rid of silos and having a holistic approach for the well-being of people, that is multidimensional.
The lively and informative debate with the public at the OECD Forum suggests to me that the draft report touched on a number of subjects people care deeply about. But it is still a draft and we need to continue the conversation, so please send your comments, criticisms and suggestions to us at [email protected], and we’ll keep you informed on how the discussion progresses over the coming months.
A new role for science in policy formation in the age of complexity?
Vladimir Šucha, Director General, European Commission, Joint Research Centre
The recent financial crisis was a wakeup call for both scientists and policy makers. It exposed new and unknown links between economic magnitudes but also between various parts of our modern, globalised world. It further helped to reveal the limitations of some approaches in economics as well as social sciences which proved to be unsuitable for this new world.
The crisis, above all, showed that the economy is a highly complex, dynamic and evolving undertaking, with the potential, at times, to produce unpredictable (and often undesired) outcomes. Finally, it showed the need to embrace more appropriately this complexity in the science underlying policy analysis as well as in the policy making process itself.
So, eight years on from the beginning of the crisis, have scientists and policy makers moved out of their comfort zone? Are new ways of thinking being embraced? Are they being applied in practice? What do we have to do to ensure that they result in better policies and, ultimately, fairer and more resilient societies?
As the European Commission’s science and knowledge service, the Joint Research Centre (JRC) is supposed to bridge the gap between science and policy makers, as is the OECD. Based on our experience, we believe that a good deal of progress has been made. However, there is still a lot of work to do if the science dealing with such complexity is to deliver its full potential.
Complexity science, of course, has been around for some decades now. It is the scientific study of complex systems, where many components interact producing a global conduct that could not easily be predicted using simple models only which are based on the ordinary inter-action between the individual constituent elements of such systems. Since such systems can be found in many areas of life, complexity science is used in a number of different fields, including biology, social sciences, computer science, transport, energy and critical infrastructure protection.
It has developed quickly in the last few decades. Concepts such as non-linearity, self-adaptation, emergence, chaotic dynamics and multiple equilibria, are now firmly established. Valuable tools have been developed, such as sensitivity analysis, scenario modelling and foresighting, network science and dynamic systems modelling, which allow these concepts to be applied appropriately.
Economics was relatively late to embrace these concepts and tools. However, following the crisis, there is an increased interest in applying them, particularly to financial markets.
The JRC is moving in this direction. For example, our researchers employ network science to estimate inter-linkages between the banking sector and other institutional investors and how shocks could propagate within the system.
However, our impression is that, in spite of the stronger interest in recent years, complexity economics still needs to spread more widely among economists. It should not be the preserve of a small number of outsiders only.
We also feel that it is still not as useful as it could be for policy making. This is because it remains rather abstract. In many cases, it can help us to understand the theoretical characteristics or basis of a phenomenon but it is still difficult to use it for practical problem solving. This may either be because the related models are not sufficiently detailed or because the data used are not sufficiently adequate for the problem under consideration.
There are, of course, many novel sources of data available. The task is to develop innovative paradigms for their collection, and also new methods for their analysis, since large amounts of data can often obscure rather than clarify an issue if the appropriate techniques for interpreting and making sense of them are not available.
Scientists, therefore, need to develop new approaches for gathering and organizing data, such as how to deal with Big Data or else text and data mining. They also need to explore models and tools for data analysis in a policy context, including indicators, innovative visualisations and impact evaluation methods.
The good news is that policy makers are now opening up, at least to some extent. Most of them now realise that attention to the inter-linkages between policy areas and the related objectives, and improving evidence on the simultaneous movement of various targets and policy levers, is essential.
They know that the impact of regulation cannot be judged only on the basis of its specific achievements inside a given context but that it may also produce unintended (and undesired) consequences in other areas outside the context under consideration. There is therefore a potential demand for the greater use of complexity science to understand such wider linkages in complex systems.
However, it can be difficult to explain counter-intuitive results to politicians and policy makers.
Equally, while scientists must make policy makers aware of the complexity of the systems they are dealing with, it is important not to overburden them. If they feel that these systems are so complex that no one can possibly understand or influence them, the result will be inertia and defeatism.
Moreover, there is little point in using complexity science to understand the linkages in systems, unless policy makers are prepared to strive for integrated solutions working with one another, across silos. All are committed to doing this in theory but it does not always happen in practice. DG JRC sees part of its role as organising forums on complex issues, where policy makers from different fields can meet, along with scientists from different disciplines.
It is also important to involve those stakeholders most affected by the phenomena under review. DG JRC is experimenting with new ways of directly involving stakeholders in the “co-design” of public interventions. This is all part of developing a multi-faceted perspective.
Finally, there is a job to do in helping policy makers and politicians to develop simple messages to persuade the public of the merits of the solutions arrived at using complex science.
These are only some very basic reflections on why DG JRC welcomes this event. We are keen to further extend our cooperation with OECD and the Institute for New Economic Thinking in the area of Complexity and Policy. By cooperating more closely, we believe that we can further improve the role of science in policy formation in our current world of ever increasing complexity.
The OECD is organising 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
Societies and economies are complex systems, but the theories used to inform economic policies predominantly neglect complexity. They assume for example representative agents such as a typical consumers, and they also assume that the future is risky rather than uncertain. This assumption allows for the application of the probability calculus and a whole series of other techniques based on it.
In risk situations, all potential outcomes of a policy can be known. This is not the case in situations of uncertainty, but human beings, policy makers included, cannot escape having to take their decisions and having to act facing an uncertain future. The argument is one of logic. Human beings cannot know now what will be discovered in the future. Future discoveries may however impact and shape the consequences of their current decisions and actions. Therefore, they are unable to come up with an exhaustive list of potential outcomes of a policy decision or action.
Properly taking into account the complexity of the economy and the uncertainty of the future implies a paradigm shift in economics. That paradigm does not need to be developed from scratch. It builds on modern complexity science, neo-Austrian economics (in particular Hayek and von Mises), as well as the work of Keynes and Knight and certain strands of cognitive psychology (for example, Kahneman 2011). There is no room here to elaborate on the theory and the claim that it entails a paradigm shift. Rather, I will discuss the implications for economic policy that follow from this paradigm.
This starts with the recognition that the future cannot be predicted in detail. We should be modest about what can be achieved with economic policy. This is the “modesty principle”. Economic policy cannot deliver specific targets for economic growth, income distribution, inflation, the increase of the average temperature in four decades from now, etc. Economic policy makers would be wise to stop pretending that they can deliver what they cannot. This insight implies that many current policies should be discontinued. To mention just one example: inflation targeting by central banks does not pass the modesty test.
This principle also implies refraining from detailed economic forecasts as a basis for policy making and execution. Policies should not be made on the assumption that we know the value of certain variables which we cannot know. An example here is the income multiplier in relation to changes in fiscal policy. The modesty principle also flashes red for risk-based regulation and supervision.
What economic policy can do is contribute to the formation and evolution of a fit economic order, and avoid doing harm to such an order, what I would call the “do no harm principle”, and be as little as possible a source of uncertainty for private economic agents.
Order is a central concept in the alternative paradigm, replacing the (dis)equilibrium concept in mainstream economics. An order is the set of possible general outcomes (patterns, like growth, inflation, cyclicality, etc.) emerging from purposefully acting and interacting individuals on the basis of a set of rules in a wide sense (laws, ethics, conventions…), together called a regime. Economics can analyse the connection between changes in regime and changes in economic order. Economic policy can influence the economic order through changing the regime.
However, this knowledge is not certain. There is always the potential for surprises (positive and negative; opportunities and threats) and unintended consequences. Policy can therefore not be designed first and then just be executed as designed. Policy making and execution have to evolve in a process of constant monitoring and adaptation. This would also allow for evolutionary change. An economic order that is not allowed to evolve may lose its fitness and may suddenly collapse or enter a crisis (as described by Scheffer for critical transitions in society). This mechanism may have played a role in the Great Moderation leading up to the financial crisis of 2007/2008 and in the crisis of fully funded pension systems. It is also a warning against basing sustainability policies on precise temperature targets decades in the unknowable future.
Fitness of an order has five dimensions. The first is an order in which agents are acting as described in the previous paragraph – policymaking involves a process of constant monitoring and adaptation. In addition to that, fitness is determined by alertness of agents (the ability to detect mistakes and opportunities); their resilience (the ability to survive and recover from mistakes and negative surprises); adaptive capacity (the ability to adjust); and creative capacity (the ability to imagine and shape the future). Policies may be directed at facilitating economic agents to improve these capacities, although constrained by the “modesty” and “do no harm” principles. Note that the concept of stability does not appear in the definition of fitness. This marks a difference with current policies which put much emphasis on stability.
In its own actions the government should be transparent and predictable. The best way to do that seems to be to follow simple rules. For example in fiscal policy, balance the budget, perhaps with clearly-defined, limited room for automatic stabilisers to work.
This alternative paradigm places highlights some methods and analytical techniques, including narrative techniques), network analysis), evolutionary logic), qualitative scenario thinking, non-linear dynamics (Scheffer), historical analysis (development of complex systems is path dependent) and (reverse) stress testing.
Economic policies developed along these lines help people to live their lives as they wish. They are good policies for good lives.
The OECD is organising 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
The Importance of a Policy Coherence Lens for Implementing the Sustainable Development Goals
Ebba Dohlman, Senior Advisor, Policy Coherence for Development, OECD
The 2030 Agenda for Sustainable Development and the Addis Ababa Action Agenda call upon all countries to “pursue policy coherence and an enabling environment for sustainable development at all levels”. Sustainable Development Goal 17 – on the means of implementation – includes a Target to “enhance policy coherence for sustainable development” (PCSD). The OECD defines PCSD as an approach and policy tool to integrate the economic, social, environmental, and governance dimensions of sustainable development at all stages of domestic and international policy making. PCSD aims to increase governments’ capacities to foster synergies across economic, social and environmental policy areas; identify trade-offs; reconcile domestic policy objectives with internationally agreed objectives; and address the spillovers of domestic policies.
Policy coherence for sustainable development is fundamental to ensure that progress achieved in one SDG contributes to progress in other SDGs, and to avoid the risk of progress in one goal at the expense of another. PCSD is critical to:
- Consider the economic, social and environmental costs and unintended consequences of policy decisions. For example, the USD 55-90 billion annual support for fossil fuels in OECD countries incentivise further CO2 emitting fossil fuels rather than investment in renewables; contribute to climate change; aggravate pollution and health risks; and waste money that could be reallocated for more targeted spending on the poor while contributing to global climate objectives.
- Identify effective uses of diverse sources of finance other than ODA. While ODA remains crucial for the least developed countries and most vulnerable populations, it now represents only 20% of the developed world’s financial engagement with developing countries. PCSD can help to make best use of existing resources, including more effective fiscal administrations, higher tax income; remittances; trade and investment; more direct access to capital markets; low interest debt; and addressing illicit flows.
- Shed light on critical sectoral interactions to achieve SDGs and Targets. PCSD can help to inform how efforts to attain a goal in one sector would affect (or be affected by) efforts in another sector, for example between water (SDG6), food (SDG2), and energy (SDG7). Agriculture is the largest user of water at the global level; energy is needed to produce and distribute both water and food; and the food production and supply chain accounts for almost one third of total global energy consumption. Policy decisions made in these sectors can have significant impacts on each other and tensions may arise from real or perceived trade-offs between various objectives. Improved water and energy services reduce the burden on women and young girls who often spend several hours each day collecting water and gathering biomass for cooking, thus freeing up time for their participation in education and income generation activities. The provision of cleaner water and energy services is also linked to improvements in the health, micro-enterprise activity, and agricultural productivity of women, thereby spurring overall national economic development.
- Deal with systemic conditions and disablers that hamper sustainable development. Illicit financial flows for example are a major disabler for sustainable development. In many countries of origin, they are a symptom of governance failures, weak institutions, and corruption, but also of other systemic conditions in recipient countries that allow IFFs to thrive, such as tax havens and secrecy jurisdictions. A PCSD lens can inform actions at international level to support a fairer and more transparent global tax system; and curb tax avoidance strategies which in most cases are legal but unfairly take advantage of the interaction between tax rules of different countries. At the national level, success will depend on the quality of domestic regulations, institutions and capabilities to identify, track, and fight tax evasion, money laundering and corruption.
The multi-sectoral and transformative nature of the 2030 Agenda for Sustainable Development will require institutions to be able to work across policy domains (horizontal coherence) and governance levels from local to global (vertical coherence). It requires policies that systematically consider sectoral inter-linkages (synergies and trade-offs) and effects (here and now, elsewhere, and tomorrow). The OECD’s analytical framework can help inform decision-making and support policy-makers and stakeholders to design policies that systematically consider:
- The roles and responsibilities of different actors as well as the diverse sources of finance – public and private, domestic and international – for achieving sustainable development outcomes.
- The policy inter-linkages across economic, social and environmental areas, including the identification of synergies, contradictions and trade-offs, as well as the interactions between domestic and international policies.
- The non-policy drivers, i.e. the enablers (that contribute to) and disablers (that hamper) sustainable development outcomes at the global, national, local and regional levels.
- The policy effects “here and now”, “elsewhere”, and “later”. This captures ways in which the pursuit of well-being today in one particular country may affect the well-being in other countries or of future generations (the long-term impact of policies at national and global levels).
Analytical Framework for Policy Coherence for Sustainable Development
Against this background, the OECD is developing PCSD Framework, a self-assessment policy toolkit, aimed at providing policy-makers with practical guidance on: (i) setting up institutional mechanisms for coherence, including political commitment and leadership, coordination capacity and monitoring systems; (ii) managing policy interactions at different levels to detect and resolve policy conflicts; (iii) addressing contextual factors that enable or impede coherence for sustainable development; and (iv) anticipating the unintended consequences of policy decisions. It includes thematic modules on Food Security, Illicit Financial Flows and Green Growth.
Policy Coherence from New Data, New Research, New Mindsets
Catherine L. Mann, OECD Chief Economist and Head of the Economics Department
Recent global economic performance – characterized by sluggish growth, widening inequality, environmental precariousness, and market volatility – is a sobering reminder of the myriad challenges facing policymakers. How can understanding and quantifying the interrelationships between and among policies help design policy packages to improve performance?
New analysis at the OECD, undertaken with new data, new methods, and new mindsets reveals the importance of policy coherence. The essence of policy coherence is to ask, How well do policies – directed toward demand management, structure of markets, environmental sustainability, and frontier innovation – work together to enhance the overall wellbeing of the citizens of a country and even broader through spillovers to the world? To what extent could a piece-meal approach, rather than an integrated policy assessment, lead us astray?
The mindset of policy coherence seems obvious. But it is in the nature of governments, academia, think tanks, and international organisations to analyse economic policies in silos – e.g. labour, environment, competition, finance, fiscal – because that simplifies the analysis and contains the domain for policy bargaining. The OECD is not immune to the silo tendency. However, the New Approaches to Economic Challenges (NAEC) ushered in a systematic mindset to see economic problems through a new lens to recognise that coherence in research across the silos is required to produce the evidence that yields “better policies for better lives”.
Productivity research is one example of how new data and mindsets promote policy coherence. The traditional approach to policy making (and its research underpinnings) focused on policies to grow the pie (via productivity-enhancing policies such as R&D spending) in isolation from policies to redistribute the pie (via taxes and transfers or through skills development). This is partly because the research datasets to investigate these topics were distinctly separate, as were the interests of the researchers. But also, policy analysis was separated because the policymakers that would implement the policies had separate mandates. In any case, detailed data on firms and workers were not available, which implied that policy design was founded on the relationships between average firms, average workers, and average economies, and average outcomes.
The NAEC approach to policy research on productivity evaluates policies for growing the pie and for its distribution at the same time. The research shows that it is the same type of policies (such as ease of business entry and exit, flexibility of labour markets, robustness of financial firms) that negatively affect productivity growth, negatively affect the matching of skills to firms, with attendant negative consequences for income distribution and is growth. This work reveals negative feedback loops that were not observed before, opening up new recommendations for policy packages. We are able to make this link now between productivity growth and income distribution because our datasets are granular enough and can be matched across objectives, the interests of the researchers came into alignment, and the importance of policy coherence is better appreciated by policymakers too.
Whereas the same type of policies affect productivity growth and income distribution, each country has its own unique combination of those policies, and therefore its own specific set of challenges. A key understanding under NAEC is to promote policy coherence across structural policies as well as demand management policies. The first generation of analysis of structural policies tended to address the implications for GDP growth of flexibility-enhancing labour market policies in isolation from policies to promote product market competition, and with little reference to overall demand conditions and demand management policies such as fiscal spending or monetary expansion. And, potential structural flaws in financial markets were not considered.
This piece-meal approach to policy assessment can lead to misunderstandings of how policies might impact economic performance. For example, increased flexibility in labour markets alongside product markets that lack competition or in which there is slack demand push the brunt of adjustment onto individuals, raising inequality. On the other hand, robust competition among firms but with rigid labour markets starves competitive firms of resources to grow, hampering productivity. Or, a third example, banking systems that evergreen loans (renew them continuously) to poorly performing firms dampens overall productivity growth and traps labour, thus raising inequality. A new mindset appreciates the complexity of the interactions between policies. Integrated policy assessments that take into account the unique characteristics of each country help quantify how policy reforms might work together to raise productivity growth and improve income distribution. This integrated policy assessment helps policymakers tailor their approach to improve economic performance and respond to shocks.
We have the tools to quantify structural policies and their impact on firms and individuals in a coherent way, including during business cycle upturns and downturns. We have an understanding of how best to deploy different types of fiscal instruments to achieve inclusive growth. Is our understanding of policy coherence complete? No, not in two key dimensions: macroeconomic spillovers and micro-behaviour and attitude toward change.
On understanding and quantifying spillovers, we still lack the trade and financial linkages and the empirical apparatus to fully understand and quantify how spillovers from one country to another may impinge on achieving policy objectives of greater productivity along with inclusive and sustainable growth. But, these data and tools are available and the OECD is in the process of incorporating these into our integrated policy assessment for economies.
On understanding micro-behaviour and attitude toward change, much more needs to be done, and this is essential for understanding the political economy of reform. The key challenge is that enhanced productivity growth comes only with firm and worker reallocation, but fear of this dynamic can constrain policymakers’ actions. A dynamic environment can strip economic rents from sheltered firms and exposes workers and households to job change and income volatility. As the pace of technological change increases, the imperative for a dynamic economy also increases. If people are not empowered to adjust, the backlash is reflected in policy stasis instead of reform, and worse outcomes, rather than better.
Research examining the behaviour of individuals is starting to give insights on which policies can best help them navigate change, but more needs to be done. Faster and more efficient resource reallocation helps economies to recover more quickly from adverse shocks, contributing thereby to reduced inequality, enhanced productivity growth, and higher living standards.
New Approaches to Economic Challenges (NAEC) Seminar Series January-February 2016
7th NAEC Group Meeting, 12 January 2016, “New Year, New Challenges, New Approaches”. Remarks by Angel Gurria, OECD Secretary General
NAEC Seminar: Fostering New Approaches to Sustainable Development, 13 January 2016 [Watch the webcast]
Are policy makers stuck in time? That may explain why incremental issues that cumulate and creep slowly across the temporal dimension pose such huge challenges. Politicians are clearly more comfortable in the here and now. Harder to deal with are slow-moving emergencies such as climate change, growing inequality and state pension reform, to name but a few. Rather than being the wolf at the door, these issues are the termites in the floor. Without action, the floor will collapse—guaranteed.
“Political short-termism”, “policy myopia”, “policy short-sightedness”… these are the terms of present-centric policy thinking, a phenomenon in which policy makers fail to use present opportunities to mitigate future harms. It’s all part of the freaky world of intertemporal policy trade-offs.
So why do we have such underdeveloped intertemporal policy chops? Neuroeconomists suggest that we may be born that way.
Situated in the ventral striatum, within the basal ganglia of the brain, is the nucleus accumbens or NAc, sometimes called the brain’s reward centre. A study published last month shows that interaction of the NAc with the hippocampus is critical in shaping decisions that involve time trade-offs. Compared with controls, rats with a disrupted hippocampal-NAc interaction lost their ability to select delayed food rewards.
Should we start examining the hippocampal-NAc interaction in the brains of policy makers? Probably not. But it does evoke the physiological and evolutionary function of intertemporal trade-offs. The fact we are still here as a species seems to suggest that we get it right at least some of the time.
Policy makers have company. Children, drug addicts and the poor also tend to be bad at intertemporal trade-offs, the latter because they have little choice but to deal with continuous and immediate crises.
Each group (along with the rest of us) exhibits what behavioural economics calls “present-biased preference”—the discounting of the future such that an immediate reward is preferred to the detriment of a more desirable future reward or outcome. A common symptom of present-biased preference is procrastination. We are “time inconsistent” the behavioural economists tell us, which means at different points in time we want different things. Economists even slice us into temporally and preferentially distinct selves. Freaky indeed.
But individual wiring may be just one factor in policy myopia.
In his speech to the UN last year, Yoshihiko Noda, the former Prime Minister of Japan, suggested that the very nature of our democratic system “comprised of representatives serving people living now” necessarily skews policy towards a present bias and “invites politics that burden silent future generations and puts problems off.”
Economist William Nordhaus predicted that “A perfect democracy with retrospective evaluation of (the economic performance of) parties will make decisions based against future generations” (Nordhaus, 1975).
But if the system is biased, what can politicians do? The spectre of electoral retribution is never far from the politician’s mind, and he or she will invest only within a zone of electoral safety. The OECD’s Regulatory Outlook (forthcoming) points to the conflict between election cycles and policy cycles, making it hard for politicians to focus on longer-term regulatory projects. The “rush to regulate” is one of the ways regulation stays rooted in the present, as politicians are pressured by current events and catastrophes to find regulatory solutions. But also, the benefits of regulatory policies tend to be dispersed and generally only evident in the medium term, where political signals are weaker, while groups that stand to lose are always brashly vocal in their opposition. Even policy makers who want to promote long-term social, economic or environmental policies (and there is reason to believe they are the majority), regularly face enormous electoral pressure to deliver short-term results.
But present bias is not destiny – necessarily.
In the intertemporal policy sphere, present costs tend to be more salient than future rewards, but not in every case. Perceived direct causal links between present action and future outcomes can overcome present-biased preferences and facilitate the task of the would-be intertemporal policy maker. If I believe that rising sea levels and storm surges will impinge on my family’s future well-being, and that by voting for stricter CO2 reduction objectives I can avoid or mitigate that outcome, then I will be motivated to make certain trade-offs. It may be difficult, however, for some to imagine that adjustments in the way they live today can have an impact on global temperatures tomorrow. Education can go a long way in helping citizens (and perhaps some politicians) understand important causal linkages. In the US, for example, Next Generation Science Standards encompassing global climate change science, are being widely implemented in elementary to high school curricula. Call them the seeds of tomorrow’s intertemporal policies.
But causal links can be blurred, by the length and complexity of causal chains or by deliberate intent. Special interest groups that seek to delegitimize broadly established climate science, attempt, among other things, to blur causal lines while appealing to our present-bias by evoking would-be short-term pain (job losses, high energy bills and business closures, etc.) should we attempt to limit the use of fossil fuels.
Indeed, research suggests that special interests may play a primary role in short-sighted policy decisions (Jacobs, 2011). It’s easy to understand why, with short-term financial objectives dominating business cycles and the prevalence of special interest groups in electoral and policy-making processes. The OECD’s Financing Democracy (forthcoming) points to the enormous challenges that remain in political finance reform.
Emphasis on biased political processes downplays the importance of citizens as agents of change. If short-term thinking is hard-wired into the electoral process, a shift towards long-term thinking in voter attitudes can force representatives out of their bias.
But also, citizens increasingly have an additional role to play, beyond voting, in shaping policy. The Regulatory Outlook reports that a growing number of countries are mandating stakeholder consultation in the creation and assessment of policies. This is based on the principle that policies best serve the public good when input is gathered from those subject to them—citizens, businesses, civil society, NGOs, public sector organisations… Ideally, citizen-consultants can evaluate policy for its impact on, or effectiveness in addressing long-term outcomes.
But can we ourselves be counted on to be reliable custodians of the interests of our future selves and those beyond us? Do we need, as author Jonathan Boston suggested, a High Commissioner for Future Generations or equivalent to give a voice to silent future stakeholders? And how might one go about embedding the interests of future stakeholders in a democratic process?
Whatever the answers may be, now-distant consequences of unmitigated issues will eventually show up on our doorstep and we will be obliged to respond with all of our courage, stamina, resources and intelligence.
Or we can get our intertemporal game on earlier when our options are immensely better.
W.D. Nordhaus, The Political Business Cycle, The Review of Economic Studies, Vol. XLII (2), No. 130, April 1975, pp. 169-190
A. Jacobs, Governing For The Long Term, Cambridge University Press, 2011