Token Econometrics: An Approach to Designing Tokens
In crypto-economics, it is nearly impossible to have a token without a protocol, a protocol without an ecosystem, an ecosystem without an economy, and an economy without governance. The approach to token econometrics review the relationships between the value accrued to a token and it's entire sector, be it a protocol, an ecosystem, an economy, and it's government. To analyze token econometrics, there is need for understanding Crypto-economics and token economics.
Crypto-economics is an attempt to create models that allow the analysis of interrelationship in increasingly complex frameworks of human interaction in distributed system. Simply put, it examine how individuals and groups respond to incentives. Studying crypto-economics explore protocols that govern the production, distribution, and consumption of goods and services in a decentralized digital economy.
Token Economics focuses on token application, token supply, and token validation. It explains token usage and it's behavior, not only while conducting transactions but after it's accomplishment. It is divided into Microtokenomics and Macrotokenomics. Refer to my previous article for a broader view. Token economy is defined as a reward system used in a behavioral modification for positive behaviors. Thus, token economics explores the incentive models and token distribution, creating a demand for the token and adding effect to it's market price value.
In crypto-economics, as related to token economics, there are various policies to be reviewed. These policies contribute to the analysis of incentive designs in decentralized systems. They are listed below:
- Economic Experimentation.
- Challenging Theory of the Firm.
- Macro and Microeconomic Policy
- Monetary Policy.
- Fiscal policy.
Economic Experimentation:
The 21st Century is headed towards a world of simulation, where everything changes but nothing changes. As blockchain air-based technologies mature and evolve, incentive designs in decentralized emerging system provide unparalleled opportunities for experimentation with economic models, stability mechanisms, and policy tools. More importantly, the emulation of existing designs and policy tools in an entirely new economic structure could allow for examining the interaction and feedback effects of otherwise completely separate subject of economics.
Particularly, with incentive design systems, the study of economics on human behavior and token prices are enabled. Thus, crypto-economics enable the analysis of an effect of macro on microeconomics and vice versa. The economic experimentation is given access by the creation of new economic ecosystems and entirely new economies. Each of these new economy are created with the design of a token and can have unique monetary and fiscal policy and regulation. All of which are computational in a smart contract.
Challenging Theory of The Firm:
In the traditional world, it is assumed that firms exist to reduce transaction cost. That is, they are a response to the high cost of using markets. Employees within are necessitated with a fixed salary while they follow changing instructions. Digitalization incited decentralization, creating a solution for human interaction that challenges the basic theory of a firm. This indicates that, the role of a firm may change if decentralized solutions help lower the cost of using markets exponentially.
More particularly, Decentralized Autonomous Organisations are established for the replacement of the functions of a firm in the traditional world. It acts as the coordinator and monitor of a team. A DAO can effectively measure the contribution of each of it's members to the finished work product and allocate respective rewards accordingly. Explicitly, an effective system is built with lower transaction costs.
Micro and Macro:
Crypto-economics necessitate micro and macroeconomic policies and measures. In traditional economics, macroeconomics deal with the overall structure that defines the economy, such as inflation, employment, aggregate demand, Gross Domestic Product (GDP), among others. Microeconomics on the other hand deal with the individual sentiments towards the market, reviewing demand and supply mechanisms.
In crypto-economics, macroeconomic questions are raised to determine the basis of token design in the context of supply and timing, as well as the allocation mechanism of tokens. It generally addresses and examines the overall economy for tokens in terms of GDP, inflation, economic events, employment, among others. Approaching decentralization, it reviews the timing, quantity of token creation, as well as token allocation. Thus, creating an avenue for democratization of monetary policies for the respective token economy.
Microeconomics in a Crypto-economic sector raises the necessity for token value generation in designing tokens. Tokens enable economic interactions, and design of incentive mechanisms for it's holders that are individually rational and Incentive compatible.
Simply analysed, Crypto-economics in a micro sector evaluate metrics for the value proposition of tokens. It also examines the interaction enabled by the tokens as well as the incentive allocation to agents/holders who participate in the respective token economy in an effort to ensure fairness and promote economic behavior.
Monetary Policy:
Monetary Policy in a decentralized economy emulates the central monetary mechanisms while instilling new elements. The centralized monetary mechanisms are orchestrated by the Federal Reserve Bank (FED) of the United States. It's monetary policy mechanisms include Discount Rates, Reserve Requirements, Open-Market-Operations (OMO), and interest on reserves.
Monetary Policy in Crypto-economics refer to the interactions of token supply, token release, and the minimum issuance of tokens in a given token issuance.
A project's ICO issuance strategy can predefine monetary policy by predetermining the fixed number of tokens created and issued during the ICO. A maximum token issuance for example, in combination with controlled token supply release can result in small increase in the demand for the token, which in turn drive the price upward. The mechanism for token emission helps to manage the supply of tokens in circulation. Thus, to avoid, token price crash, it is necessary for a succulent monetary policy that would determine the respective features of the token thereby creating a sustainable economy.
Fiscal Policy:
Fiscal policy tools in centralized economies typically revolve around government spending and tax policies. To increase business activity in an economy, the government can increase the amount of money it spends, often referred to as stimulus spending, as opposed to deficit spending. Government tax policies may stimulate centralized economies by lowering taxes. By increasing taxes, governments can remove money out of the economy and slow business activity. Fiscal policy in decentralized economic incentive designs emulates centralized fiscal policy and adds additional factors. The economic benefits token holders receive from holding tokens are a key concept associated with quasi-fiscal crypto policy. Two central questions help illustrate this point:
- What is the underlying value of the issued tokens? And;
- What factor contribute to the value appreciation or depreciation of issued tokens?
For instance, linking commercial benefits with token usage can incentivise token holders to use all various services associated with a given token.
Several benefits are associated with the quasi-fiscal tool of adjusting commercial benefits of tokens in decentralized economic incentive designs;
First, the increase in commercial benefits associated with a token heightens the aggregate demand of the given token supply.
Second, commercial benefits associated with a token issuance can help offset depreciated supply scarcity, e.g. the effects of a large issuance / supply of a given token in circulation.
Third, commercial benefits associated with tokens can be adjusted as a form of quasi-fiscal policy to control the flow of tokens in a given issuance through indirect economic incentives. Adjustments in commercial benefits can help manage operational cost changes for the issuer and the external competition with other token issuers experienced by the issuer, among other factors.
Fourth, adjusting the commercial benefits associated with a given token issuance avoids more drastic monetary policy intervention by way of emergency sales, building token reserves, or a decrease or increase of token supply in circulation.
To create a more significant effect, the quasi-fiscal policy tool can be combined with monetary policy. If the aggregate demand for a given token issuance increases through better commercial benefits associated with the tokens, the issuer can simultaneously increase the total supply in circulation. Options for increasing the total supply of tokens in circulation include issuing escrowed tokens or even secondary issuances. The combined effect of quasi-fiscal policy (increasing benefits associated with the tokens) and monetary policy (increasing the token supply in circulation) may or may not have an effect on the market price of the respective tokens. The balance of commercial benefits of a token offering and associated use cases of the token in combination with supply scarcity is critical in the issuance of a token offering.
Why Econometrics
In traditional economics, econometrics is regarded as the application of quantitative methods to economic relationships. This is also applicable for for Crypto-economies. It evaluates the influence of a variable on another variable in order to forecast and predict resulting outcomes. Crypto-economics focuses on econometric evaluation of a token via regression, autocorrelation, heteroscedasticity among others. It reviews the volatility modelling and forecasting through Generalized Autoregressive Conditional Heteroscedasticity (GARCH). In 2021, Cerbian-Hernandez and Jimenez Rodriguez used the Dynamic Conditional Correlation (DCC) model of Engel (2002) on a mixed portfolio composed of $BTC and other ten assets. In 2020, Shi et al, investigated the dynamic correlation among six tokens using a multivariate factor stochastic volatility model in the Bayasian framework. Seven empirical steps towards econometric analysis are associated with both traditional economics and Crypto-economics:
Theory:
In traditional economics, a theory is clearly defined as related to economic activities. For example, the relationship between consumption and income in a micro sector and the relationship between aggregate demand and it's variables (Consumption, investment, government spending, and export) in a macro view. In crypto-economics, we review the theories associated to the relationship between token issuance and it's policies. For example, Token Policy, a theory that reviews the monetary policy and valuation accrued to a token. For more reading, refer to my previous article. A question of interest is therefore formulated and further analysis is done.
Mathematical Model:
For econometric estimation to be established, there is a necessity for mathematical Model specification. Could be linear, logarithmic, or exponential model. For instance, the price of a token is determined by the effect of demand. A mathematical Model is specified by:
Within the above mathematical model, it is clearly defined that an change in demand simultaneously affects the price outcome. Specification of this model sets the gear for econometric estimation. In the above model;
Y is the dependent variable known as price.
X is the independent variable known as demand.
B1 and B2 are parameters that determines the changes in the variables. They are regarded to as intercept and slope respectively.
Econometric Model:
The econometric Model specification provides a stern outlook to the mathematical Model. Reviewing Crypto-economics in a macro level, we realize that there are other factors that affects the price of a token other than demand. This also defines the relationship between demand and the various factors. In our previous illustration, while evaluating monetary and fiscal policy, we expanded the variables by reviewing the token issuance mechanisms which examine the policy measures. Thus, establishing a token issuance supply cap resulting in a rise in demand and stimulating increase in the price of the token.
To establish a successful econometric model, beyond reviewing other factors, protocols give room for errors. For example, in the same illustration, it was speculated that there is a possibility for token crash given that, factors outside the variables positively affecting the demand for a token and it's effect on the price are introduced unknowingly. Thus, a stochastic variable "u" known as the error term is established to subdue these external variables into one variable. The model is specified by:
Obtaining Data:
To estimate econometric models, data is required. It could be a micro data or a macro data. It could also be a cross sectional data, time series data or a longitudinal data depending on what variables being estimated. For the above equation as related to Crypto-economics in a macro sector, particularly for decentralized systems, data is actualized via testnets and feasibility reports.
Parameters Estimation:
The B1 and B2 parameters are analysed and estimated to determine the level of centralization, decentralization, consistency, value accrued, simulation among many others. These are parameters referred to in a token model to design a perfect incentive token economy. To estimate the parameters, several models are analysed such as regression, t-test, Analysis of Variance, autocorrelation, Heteroscedasticity and many more.
Hypothesis Testing:
Under a conditional statement, an econometrician forecast results through hypothesis. This is established to either nullify presumptions or accredit them. This is similar to the "Objective and Constraint Optimization methodology" in Token Engineering.
Forecasting and Prediction:
The outlying estimation results are used in formulating policies and predicting future outcomes. It helps to drive conclusions based on hypothesis defining the estimated relationship and outlying results.
The econometrics of crypto tokens stern to evaluate the below metrics:
- Price discovery in different exchanges.
- Modelling the volatility of price returns.
- Development of artificial intelligence and machine learning models for price and direction forecasting.
- Study of fractal properties and market efficiency.
- Risk management through symbolic analysis using interval modelling.
- Management and diversification of investment portfolios with crypto tokens.
In conclusion, tokens are created based on several models and estimation. The process of establishing utility and regenerating value stern beyond prices and charts. It is a blessing to have explored the topic and I hope you find it valuable. Thank you!
Name: Abubakr Olawale Qomorudeen
Twitter: https://twitter.com/RubiksWeb3hub.
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Your favorite tokenomics engineer, Rubiks greets you!!!
Good day!!
