Policymakers need a new theory to manage the dynamics of national and international economies
Governments in developed as well as emerging economies are struggling to define an optimal regulatory structure for the financial sector. With too little regulation, the sector becomes unstable, destabilizing the entire economy. With too much regulation, or the wrong regulation, innovation is stifled. Governments are also confronted with a conceptual challenge regarding industrial policy. Industrial planning in the Soviet Union and in India prior to the 1980s killed entrepreneurship. However, free markets with no industrial policy, the theory the US espoused and which became the dominant paradigm of economic policymaking around the world since the 1990s, except in countries such as China, Korea, and arguably Germany too, has not delivered results either.
Now India needs an industrial policy to grow its manufacturing sector to create jobs and reduce its current account deficit. Even the US is developing an industrial policy for the same reasons, to create more jobs and balance its trade. Within the broader scope of industrial policy also lies the vexatious issue of pharmaceuticals that must be addressed in India and in the US too, viz, how to reduce prices of medicines without bureaucratic controls that will destroy incentives for innovation and investment in the industry.
It is safe to say that neither leave it to the market, nor top-down planning and control are the solutions. Insights into systems’ architecture can provide governments new concepts for managing complex financial and industrial systems. Broadly, complex systems may be divided into three classes. One is engineered systems. These are systems designed by man, following scientific disciplines, to produce desired outcomes. Machines are the most common manifestation of this class of systems. So are top-down planning systems that control inputs and outputs. However, as all students of engineering learn, engineered systems are subject to the second law of thermodynamics. This law says that the entropy within a system (roughly translatable as confusion within) will inevitably increase over time. Therefore, the capability of an engineered system will reduce over time. The operation of the law is evident in our experience. Machines must be periodically repaired and renovated by engineers to maintain their levels of performance. And we also know from experience that while planned economies may start vigorously, they lose their abilities over time. Moreover, physical scientists can explain, with mathematical models, that an increase in entropy is inevitable in engineered systems.
The second class of systems is chaotic systems. These are formed by the interactions of millions of independent particles or free agents. The concept of a universally free market composed of free agents without any governmental regulation, that liberal market extremists espouse, has the structure of a chaotic system. Chaotic systems can produce surprising outcomes. The example of a butterfly flapping its wings in Brazil that causes storms in Hong Kong is often cited to illustrate this characteristic of chaotic systems. The near collapse of the global financial system, stemming from problems in the housing loan market in the US, could be another example. Mathematicians and physical scientists are studying the mechanisms by which the consequences of local events transmit across large system to understand the structures of chaotic systems.
The third class of systems is complex self-adaptive systems. Insights into these have come from a collaborative, interdisciplinary exploration of systems by economists, physical scientists, evolutionary biologists, computer systems experts and others interested in the behaviour of complex systems. These systems display characteristics that neither engineered systems nor chaotic systems have. They increase their capabilities over time unlike engineered systems, and they do this with some underlying logic unlike random chaotic systems.
The most obvious illustrations of such systems are in nature where capabilities of species evolve through competition. Thus, over time, more evolved species develop. Contrary to the second law of thermodynamics, natural systems follow a law of evolutionary biology that says that complex systems will increase their capability over time. The competition in nature does not destroy the whole system. There is some higher order, or some deeper structures—depending on whether one believes in God or is an atheist—that regulates this competition so that the commons on which all depend are maintained. On these commons the competitive game plays out evolving better capabilities in the system over time.
Complex self-adaptive systems sit on the edge between engineered systems and chaotic systems. They neither sink into stasis like engineered systems nor are they an unformed, potentially chaotic mass. They have an underlying architecture that gives them the capability to evolve from lesser order to higher order. Systems’ science is bringing together experts, who generally live within the conceptually gated communities of their own disciplines, to understand the whole system rather than defend their intellectual turfs. They are discovering the architectural principles that give complex, self adaptive systems their unique capabilities. Among these principles are: permeable boundaries, minimal critical rules, requisite variety and sufficient redundancy in the system.
Policymakers need a new theory to manage the dynamics of national and international economies. They shun planning and controls. And they no longer want an unregulated economy. A new paradigm they are adopting is the regulation of competition. To tune up regulatory regimes, they could be well guided by emerging insights into the architecture of complex self-adaptive systems.