In this guest post, Wang Zhenying, director-general of the research and statistics department at the PBoC’s Shanghai head office and vice chairman of the Shanghai Financial Studies Association, summarises the arguments in his new Chinese-language textbook on economics.
Crises destroy, but crises also create.
The outbreak of each crisis gives rise to new economic theories. Marx’s theory of Surplus Value was created amidst frequent economic crises in the late 19th century and Keynes’s revolutionary theory was put forward during the Great Depression in the 1930s. Today, with a worldwide financial tsunami only now receding, people are expecting a new economic theory in response to the failure of the pre-crisis mainstream.
“Trading economics” is one new theory emerging against this backdrop. Mainstream economics deduces the macro whole by extrapolating from the behavior of individual “representative agents”. Trading economics replaces this with a systematic and comprehensive analysis approach. It stresses that in an interconnected world, the interaction between trading subjects is the fundamental driving force behind the operation, development, and evolution of economic systems.
Trading economics first analyses the actions of trading subjects, then builds a dynamic trading network among trading subjects through trading relations, and finally reveals the operational rules of the economic system. The rules could be examined from two perspectives: short-term and long-term. The business cycle and price changes are examined in the short-term perspective. The long-term perspective would focus on the rules of economic evolution as well as changes in technology, knowledge, system, and network.
Throughout the history of economics, trading economics is the first and foremost theory to incorporate all economic phenomena into an all-encompassing logical system. It changes the long-standing scenario in the economics field, that is, the macro was separated from the micro, and the short-term from the long-term. Trading economics is a revolution of mainstream economic theories and is bound to exert a great and profound impact on all areas, including economic theoretical research and practical application.
The economic landscape of trading economics is picturesque
The world is full of variety. In mainstream economic theories, however, all people are presumed to be “economic persons”, who are fully rational and informed and highly intelligent and knowledgeable; all enterprises are presumed to be machines seeking maximized profits. Their positions are decided: people demand goods and enterprises supply them. In the constantly-changing world, they only respond to prices — when the price goes up, the demand goes down, and the supply goes up, while price declines encourage the reverse.
In this way, a huge and complex system is reduced to a world where everyone is driven by one single motivation: price. This is a dull and mechanical picture that mainstream economics conjures up, out of tune with the colorful world we live in and failing to tell the stories of the true world.
Trading economics chooses a different path. Everyone participating in economic activities is put in a specific organisational structure. As a result, their behaviour becomes affected by culture, morality, property, and system. There is no “economic person” like Robinson Crusoe in trading economics. Trading economics only has organizations with specific internal structures: households and enterprises. This is the first step to bring economic theory back to the reality.
Behavioural economics experiments have demonstrated that choices are characterised by variety — there is no single answer to all situations. To implement this principle in economic theories, trading economics describes how people make decisions instead of depicting the decision itself. Expected earnings are at the core of the decisionmaking model. Expected earnings are not an indicator, but a function containing a series of indicators. This allows for differences in the internal structure of trading subjects under a unified objective. As a result, trading economics not only reflects the variety of the world, but also achieves the uniformity of trading decisions, which could lay a foundation for technological convenience in theoretical analysis.
In trading economics, trading subjects overcome their limited rationality by learning and adapting. This is embodied in each link of the expected earnings function. Trading subjects constantly adjust their decisionmaking methods based on experience. People also start with different information sets. Information determines how each subject makes decisions. Under this structure, each subject is defined by its own information set, hence creating a situation of unified forms and various behaviors of trading subjects — exactly the reverse of mainstream theories characterised by various forms and unified behaviors.
Besides differences in information, trading participants have different approximation degrees and different time elasticities when pursuing maximum profits. Some people are less exact than others, and will therefore maximise earnings less than those who are more precise even if both individuals otherwise have the same goals and outlook. Time elasticity reflects that people make decisions within a certain period of time against a certain background. It is in sharp contrast with the neoclassical economics, which assumes subjects make decisions instantly using ultra-long-term forecasts.
Trading economics’ depiction of economic activities is more realistic
In mainstream economic theories, consumers and manufacturers have no distinct identities. The problem of aggregating micro individuals into macro models remains unsolved. The existing approach is to assume that trading subjects are homogeneous, which makes the models simpler at the cost of being unrealistic.
Trading economics gives up this assumption. Each entity has its own constraint set and information set, which are its own characteristics. They also have distinct assets and liabilities — not just the total assets and liabilities of each trading subject, but also the asset structure, liquidity structure, etc. There are corresponding accounting matrices for enterprises and households. These accounting matrices not only reflect the economic status of the trading subjects, but also link subjects together into a single financial network.
The matrices provide trading subjects with a basis for decisionmaking. People and businesses will not think solely of “utility” or “margin”, but will optimise the accounting matrix from a number of dimensions, which greatly broaden the decision horizon. This framework is also more in line with reality.
As in mainstream economics, trading economics describes behaviour by having each entity try to maximise income. However, there is an important change. Classical economics assumes everyone has full information and is absolutely rational, which means that maximisation is an objective indicator and is uniform for everyone. This is another manifestation of homogenisation by the mainstream.
Trading economics differs by recognising that different people have different information, in part because they have different experiences. So while each trading subject seeks maximum profits, the “maximum” differs from one subject to another, even when trading and constraints are the same. Therefore, if the behaviour model in neoclassical economics is the absolute maximum, then it is the relative maximum in trading economics. This is where the difference lies.
Trading economics gives up the hypothesis of a perfect reality
The theoretical framework of the neoclassical economics depends on the idea of equilibrium. Absent an external “shock”, the economy grows at a stable rate. After the shock hits, the economy returns to its previous trend path. To achieve equilibrium, changes in price are supposed to effortlessly produce changes in supply and demand. It is through the market that we can enjoy the most efficient allocation of resources and the distribution of wealth associated with the highest social welfare. However, the three-century long history of industrial and economic development shows that the free market does not always produce these results, as neoclassical economic theories assume.
Trading economics defines interaction between subjects on the basis of behaviour rules — the interaction between the subjects is always at the core, from which there comes the nonlinear characteristics and self-reinforcing phenomenon of the system. The process of self-reinforcing behaviour on the trading network is similar to that of chain reaction, which is defined by the economic nature of wave-like operation. Under certain circumstances, there could be explosive growth, or avalanche-like crisis. Along this path, our picture of the economic system is completely different from that in the classical theory, and makes the system more dynamic and diversified.
The basic logic of trading economics is that each trading subject pursues optimal profit transactions according to its goals and mastered information. It is the trading network, the network among subjects via transactions, rather than the market, that plays the intermediate role. In the mainstream theory, the trading subject is separated from the market. When the market is abstracted, the interaction among trading parties is greatly simplified to be passive reaction to price, whose mode is consolidated with all trades occurring at the same exact time.
In the real world, the interaction among trading parties is very complicated. People and businesses respond not only to spot price, but to trading itself, expected prices, expected network change, and information related to the trading. The interaction among subjects spreads, assembles, and diffuses in the network. Once a feedback with self reinforcing mechanism is formed, strong trading momentum will be generated in the corresponding market.
Economic growth is the expansion of the trading network scale parameters, and price is the result of a game between traders in a particular pricing mechanism. Pushed by transactions, the trading network evolves in a self-organising process reflected in the development of system, technology, and knowledge. In turn, the system, technology, and knowledge constitute the driving force for further development of the economic system. This is the picture of the economic system presented by trading economics.
In the view of trading economics, there is no conceptualised “market” because markets are just sets of relationships and interactions. It is like a device whose cover is open, presenting a transparent relationship map. The market is not already in place, but a result of the process joined by each trading participant, and a trading relation that is changing all the time.
Trading economics incorporates time into economics
Time expresses the order of events. Gaps between decisions are made and when actions are taken affect behaviour. Awareness of time and these lags is omnipresent in human activities throughout history. A theory without the function of time fails to reveal the operational rules of complex economic system. Yet there is no trace of time lapse in mainstream economics.
Trading economics incorporates time into economics. It studies how trading networks develop and comes to the conclusion that it evolves in four dimensions: technology, knowledge, system, and network structure. Trading economics starts by studying the behaviour of micro trading subjects and ends with the development of human society. Continuous and innumerable trading activities of subjects are the momentum driving social development while any social development in the four dimensions releases more trading room for trading activities. In trading economics, micro subjects and macro society form a closed loop with mutual feedback, which make society develop in a spiral way.
From the study of the development rules of economic system, it is found that global economic integration is neither the innovation of a single politician, nor a strategy implemented by a certain country to pursue its own interests. Instead, it is the only option following the development rules of social economic system. Today’s world has shifted from an isolated island, through small-world development, to a network without marks.To achieve comprehensive progress and development, the world economy must promote the integration of trading network among countries. We need to listen to the warning of trading economics in a world awash with anti-globalisation thoughts.
Observing the world in a different way
The most common way of thinking is that events have identifiable causes. People try to understand the reasons why things happen in the hope this knowledge will provide the basis for controlling the occurrence and frequency of events. In Great Contraction 1929-1933, a masterpiece by Milton Friedman, the goal was to determine the cause of the great recession. By establishing a logical link of causal relationships among a series of events, he argued that monetary tightening is the basic cause for economic recession.
But many phenomena are the results of many interacting factors. Their exact roles in the causal relationship are impossible to be identified in the process of interaction. It is impossible to find a single factor among various events to explain for example, the great contraction that affected the whole world. Although Friedman wrote a thick book for his argument, trying to prove that monetary contraction under the gold standard monetary system was the root cause of the Great Depression, he did not settle the question.
According to Friedman, the collapse of banks and withdrawal of money by depositors led to a reduction in bank deposits and then money stock, the result of which was a more serious deflation and collapse in industrial output. Opponents believe the reason the banks collapsed is that depositors and other people expected the economy to collapse — the banking panic came from the expectation of the economic situation.
Both of the opinions sound reasonable and convincing, but they are contrary to each other and cannot be coordinated. This is a common phenomenon, especially in the economic field, behind which the key point is the structural conflict between the thinking mode and the interpretation objects concerning causal relationship. In a feedback loop that has many links, selections of slices at different locations will lead to different causal conclusions. Although correct from their own perspectives, these conclusions are in conflict with each other. This is why there are so many conflicting explanations in reality.
Neoclassical economics perceives supply and demand as two opposite forces in the market, and sets the direction of their dynamic interaction as equilibrium, thereby establishing a mechanical analysis framework going towards balance. This is established at the expense of the internal relationship of trading activities and the integrity of the economic system, which will easily lead to the results of seeing only trees, but not the forest. Neoclassical economic theory is therefore limited to partial analyses of market behaviour. We cannot deny the value of this partial analysis method represented by monocausal relationships, because this provides the essential premise and foundation to understand an event as a whole. But once beyond this scope, there will be large deviations from reality.
Trading economics gives up on simple causal relationships. In the face of a complex phenomenon, it looks at interactions among a set of interrelated events, and seeks after the feedback loops that influence the trend. This integrated thinking mode is more extensive in framework because it can accommodate more factors. In analysing economic phenomena, trading economics focusues on the trading feedback loop: the force that promotes the evolution of trading momentum, through which the trading momentum equation, the development rule of trading momentum is formulated. Thereby, knowledge is gained dynamically about the development trend and change intensity of trading.
It is the unique feature of dynamic analysis of trading economics to find and analyse the characteristics and momentum of the trading feedback loop in the trading network. In an economic system, once a powerful feedback loop emerges, it will have a sweeping potential — like a tornado on the land. But in general, if there is no feedback loop, or an insufficiently powerful feedback loop on the trading network, we can conclude that the economy is stable. Analysis in classical theory is like studying fragments of a giant painting, such as consumption, investment, export, credit and consumer confidence, etc. Analysis in trading economics pieces these fragments together to get a complete picture.
A key to the gate of a mysterious world
When analysing specific economic problems, mainstream economics solves equations after inputting independent variables. This method provides only the final result, but not the detailed process how the economic system achieves the results. There is neither time nor an information-processing mechanism.
Trading economics provides a completely different model of economic analysis. The economic system gets a concrete structure through the trading network. Once the rule is specified for how each node reacts to signals from all over the network, the operation of the economic system can be accurately simulated with computer technology. Various possibilities of economic operation can be predicted, including the fluctuation of economic cycles, the probability of crisis, assessment of policy effects, etc.
Disturbances from the outside can be evaluated precisely using the simulation, which also provides detailed information on how the disturbance affects the economy over time. Compared with the mainstream economic analysis framework, trading economics provides much more enriched information of the economic system. The improvement of analytical method will greatly enhance the accuracy of economic analysis and open a new era of macro economic management of human society.
Trading economics also establishes a closer connection between macroeconomics and behavioural economics. The behaviour of each trading subject and the ways in which they react to external disturbances can be informed by the research of behavioural economists and psychologists. The economic operation simulated in this way is better targeted and the analysis has more solid experimental foundation. Trading economics is a great leap in methods of economic theory research because it represents the unity of economic research and natural science in methodology.
Simulation calculations can also be introduced into the field of economic evolution. The feedback of system, knowledge, and technology to economic development can be brought back into the economic system, thereby forming a complete feedback loop, where the economic evolution of human society is realised as an iterative process. By extension, the methods of trading economics will not only launch a revolution in the field of economic analysis, but also have a profound impact in the field of social science research.
Trading economics is bound to become a gold key to the gate of the mysterious economic world.
Related links:
Economics after the crisis: New model army — The Economist
Building a better model — Free exchange
A brief history of macro: how we got here — Free exchange
Wang Zhenying has served in various positions at the People’s Bank of China over the last 23 years. He is currently director-general of the research and statistics department at the PBoC’s Shanghai head office and vice chairman of the Shanghai Financial Studies Association. Mr Wang was previously seconded by the PBoC to the Bank for International Settlements, where he worked on supervision of Asia Pacific emerging economies. He earned his PhD from Renmin University in 1994. A first comprehensive introduction of the theory, The Theory of Trading Economics, written by Mr. Wang Zhenying, was published by China Finance Press in August 2016.
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