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Quantum Modelling the Macro-Economic Particle

Quantum Modelling the Macro-Economic Particle

By Akshay Kumar

One of the most prominent misconceptions of economics can best be understood by an analogical comparison to ‘Quantum Mechanics’. Quantum mechanics is a branch of physics which deals with physical phenomena at microscopic scales, where the action is on the order of exotic elementary particles such as electron and nucleons and even smaller. Central Board of Secondary Education class 12th Physics textbook elucidates and wraps up the Quantum theory, arguably the most complex and vital theory of 20th century, in just one very simple Schrodinger equation involving a fashionable ‘operator’. However, when one analyses the equation further the first thing critical variable that one witnesses is ‘psi’, ψ, wave function of particle. The variable persists in the study of quantum mechanics from this critical point to the understanding of virtually anything in the miniscule or majuscule study of a microscopic particle. In the study of macro-economics, if one has to pin-point the ψ of macroeconomics (let’s call it ψm), it has to be the GDP (Growth Domestic Product). The story of macroeconomics or at least the cult of macroeconomics has also been like the CBSE’s elucidation of one-line Schrodinger equation. In dealing with performance, structure, behaviour, and decision- making of an economy, macro-economists have not been able to go beyond such indicators of state as GDP, unemployment rate, and price indices and ironically not all parameters are independent. Essentially, macro-economic state can truly be mirrored by one simple indicator, GDP (ψm); other parameters could be mirrored or factored in terms of GDP. What macroeconomists need to learn and replicate from a quantum ψ (let’s call it ψq from hereon) is that ψq has no physical significance. ψq2 (square of ψq) has physical significance as it measures the probability of finding a particle at a given point in space at a specific point in time. Similarly, GDP (ψm) should not be categorized and hailed by economists as having physical relevance as they have till now. There has to be another more specific and true indicator that responds to and reflects the complex state of an economy at a specific point in time. For instance, let’s say a company named ‘Booster’ manufacturers luxury cars. During the process of manufacturing one unit of luxury car many metals and plastics are used. These materials and plastics are initially refined, moulded and casted in specific shapes and components through various industrial processes. During these processes, invariably, a lot of pollutants are released in the environment and the raw metals are consumed from the current stock-pool of nature. The outcomes of the entire process can be summarized as-
1. A luxury car model valued the market price set by ‘Booster’ (let’s say equivalent to worth $A)
2. The creation of services during the configuration of vehicle and prior to that in processes such as metal refinement, casting, and moulding etc. (let’s say equivalent to worth $B)
3. Exhaustion of 100+ Kgs of metal and other raw materials ( a very moderate number) from the earth’s stock-pool of resources in nature (let’s say equivalent to worth $C)
4. Creation of huge volumes of pollutants during material extraction, refinement, casting and finally vehicle manufacturing and assembling (let’s say equivalent to worth $D)
5. Expense of other sources of energy indirectly during the entire chain such as x units of electricity power consumption and y units of fuel consumption in order to sustain the fixed assets of a company or a refinery (let’s say equivalent to worth $Es)
Now, the GDP is the gross domestic value of all the goods and services that are produced in an economy in a given year. As per the calculations of macroeconomists the GDP of a country has increased by $ (A+B) after this entire chain. It totally ignores the impact of (C+D+E), which is obviously negative, that is the value of goods or services destroyed. Hence, ψm2 should be a function of (A+B-C-D-E), which can be negative like ψq2, instead of the current outcome which always has a positive value, dependent solely on (A+B). Not only this, another flaw in the GDP macroeconomic model lies in measuring its rate of growth or fall. The current system measures it in terms rate of change of A+B over time rather than A+B-C-D-E over time. Hence, the actual state of an economy, as represented by GDP, is an inflated figure both in terms of absolute value and rate of growth of that absolute value. The same measurement ignores the future negative value (operational value) of the same luxury product once it is sold. During it’s lifetime the vehicle emits several pollutants, equating to several carbon credits, thereby further inflexioning the value of C+D+E, while the GDP measurement takes into account only the positive values of oil and services consumed (in its reapirs) by the vehicle, inflexioning the value A+B. Hence, the true measure of the state of economy is usually overstated with the current measurement of indicators in macro-economics. In another case, take for example, the case of regulation of CDOs (Collateralized debt obligation, financial derivatives at the core of 2007 financial crash). Whether regulated or de-regulated the current macroeconomic measurement measures the value generated by 1 unit of CDO equally. The current indicators do not differentiate between the risk-adjusted and risk performance. Macroeconomics needs to be analysed, developed and invented substantially as it has mostly and utterly failed to capture the true state of any economy. Some Schrodinger will have to work his skin out to develop the true wave function of ‘macroeconomic particle’, which squared yields some substantial physical significance.

The author is an undergraduate in Civil Engineering from IIT Delhi and, currently, working at Ernst & Young in strategy consulting. He has been engaged in debating for the past 11 years at various levels. Since past 4 years, he has primarily focused on policy and economics debates and research papers and has been engaged at premier global debating platforms such as G8-G20 Group, Harvard debates, EUDC. Recently, he has developed debating models and tested them at national debating conferences.

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