Opinion: Maturing China Economy Needs Replacement for Play-As-You-Go Strategy
Mainstream economic theory stumbled badly after the 2007-08 global financial crisis, when economists were at a loss to explain why they failed to see the financial crisis coming and what ideal solution could be applied.
Where mainstream economics failed was the fact that very few economists looked at the system as a whole, in which all the parts were interconnected in a nonlinear and dynamic manner. Instead of reverting back to equilibrium, as mainstream theory assumed would happen, the global financial system threatened meltdown into chaos and panic. In desperation, central bankers invented “unconventional monetary policy” by massive expansion of the central bank balance sheet, which provided liquidity or “quantitative easing” (QE). Much of this was done without any underpinning in theory.
In the interim, economists have been hard at work in search of new tools and frameworks of analysis. As the operating environment became more complex with the emergence of disruptive technology, widening social inequality, pervasive climate change, political and ideological conflicts, and increasingly complicated and costly regulations, there was awareness that mainstream economics should be revamped substantively.
If conventional economics is inadequate, what should replace it? Professor W. Brian Arthur, author of the book Complexity and the Economy, has been working unceasingly to present the case for “complexity economics” as a general framework to replace the special case of mainstream neoclassical models.
At the turn of the 21st century, it became increasingly clear that the context of economic growth has radically changed, driven by severe problems of growing social inequality, disruptive technology that threatens jobs, climate change, increasing pollution, social conflict and war, and toxic politics. Simple models that give simple answers do not work in an increasingly complex world. We should not seek perfection, but what works satisfactorily in a world of radical uncertainty.
China is actually a living example of a complex economy that is adapting to a rapidly changing environment. Because of its scale, China affects the global economy and vice versa in a continuous feedback loop.
Chinese policymakers understand very well that they operate under radical uncertainty, with their operating maxim “crossing the river by feeling the stones.” As most of them are engineers by training, they intuitively have systems thinking, so that they operate under bounded rationality and use the algorithm “act and experiment in order to explore or select paths or options of development.”
China’s economic success arose from the Chinese Communist Party’s willingness to experiment by allowing different levels of local government to actively compete against each other, delegating authority for them to search, seek and experiment with different projects and approaches. This “search, experiment and adapt” policy has served China well in the last three decades, but as China became more successful and complex, the issues of coordination, market-gaming the rules and corruption became more entrenched and complicated.
Nobel Laureate physicist Murray Gell-Mann argues that current specialist sciences fail to see the whole picture, which requires an interdisciplinary view that transcends specialist fields. He argues that one cannot discuss economics by ignoring politics, neither can one discuss politics without considering the military-industrial complex and other institutional aspects of human behavior.
Gell-Mann said that without a “crude look at the whole,” the system is being pulled apart from widely divergent views, resulting in collective action traps. The leader is one of the few who is forced to look at the whole, but he or she may not have the power to force collective action unless there is a “common fate” or common threat that forces collective action. The Chinese call the fundamental dilemma as “top-level architectural design,” without which the different parts of the bureaucracy are acting in contradiction with each other, canceling out each other’s efforts.
Most foreigners incorrectly assume that China is a unitary state and is therefore homogeneous because of a common language. The scale of the country, plus having one-fifth of the world’s population and diverse cultures and stages of regional development with huge legacies of large bureaucracy, make coordination particularly complex and difficult. Reform becomes incremental the more distant the risks of common threats.
Chinese policymakers understand well the self-order of markets, but often underestimate the self-order of complex bureaucracies, particularly where collusion between bureaucracy and market forces create bad incentives that entrench corruption and adopt excessive investment projects that yield low rates of return.
What can complexity economics bring to a better understanding of Chinese economic development? The first is an appreciation that the Chinese search for modernity under uncertainty is “scientific” and that there are no optimal goals or states. While Americans, in the words of Henry Kissinger, instinctively search for the optimal solution to a problem, the Chinese understand that every solution brings multiple problems.
Secondly, given bounded rationality and uncertainty, progress is a continual, inductive search for solutions to emerging problems, which requires an integrative and multidisciplinary approach, drawing on diverse experimentations at adaptation. There is no “one size fits all” solution for all time.
Third, in addition to the search for meta-economics or the thinking-behind development, greater efforts must be made in the area of mesoeconomics — the institutional aspects of social organization. Modern organizations, including jobs, processes, structure and hierarchy, are being challenged by technology, innovation and competition. Using 19th-century ideologies and methods to deal with 21st-century problems is futile. This requires an openness to change and willingness to experiment with new social structures, including social technical platforms that connect very disparate groups.
Fourth, complexity economics has new tools, such as big data and agent-based modeling techniques that enable policymakers to explore the implications of different types of policies. The application of complexity science and cybernetics to social prediction is more likely to be accepted in China because most of the leaders are trained in engineering rather than as lawyers or economists. They are more attuned to thinking of the system as a whole, except that their lack of exposure to international systems and experience in global institutions narrow their decision horizon and spatial thinking.
In sum, I commend Complexity and the Economy as required reading and study in all Chinese universities and research institutions.
Andrew Sheng is a distinguished fellow at the Asia Global Institute at the University of Hong Kong.
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