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The Economic Framework of the CEIS
The Economic Framework of The Cybernetic Economic Intelligence System
1.1. Triptonomics: Economics for a Technological Era
1.2. Challenges in the Current Economic Landscape
2.1. Decoupling of Human Labor and Commercial Productivity
2.2. Incongruity between Inflation-Targeted Monetary System and Technological Efficiencies
2.3. Widening Wealth Gap and Socioeconomic Divide
2.4. Limited Economic Opportunities and Declining Aggregate Demand
3.1. The Triptonomics Approach
3.2. Measuring Efficient Wealth Distribution
3.3. Key Control Policies of Triptonomics
3.3.2. Control #1: Data Ownership and Monetization
3.3.3. Control #2: Shifting Retail Pricing Control to Manufacturers/Suppliers with Manufacturer's Listing Retail Price (MLRP)
3.3.4. Control #3: UIPF Distribution Policy for Effective Income and Wealth Distribution
4.1. Effect #1: Perpetual Growth of Aggregate Demand Proportionate to the Marginal Propensity to Invest, Leading to the Increase of GcW, GcI, and GpP
4.2. Effect #2: Market Equilibrium and Stabilization of Prices
4.3. Effect #3: Implicit Regulation of the Growth Rate of Gross Consumer Wealth (GcW) Relative to the Growth of Gross Product Productivity (GpP) to Sustain Market Equilibrium and Viability
Figures 1: The Phillips Curve Models
Figures 2: The CEIS’ Economic Policy
Figures 3: CEIS’ distributive policy
Figures 4: Distribution of wealth within the network
Figures 5: Classical sequence to market equilibrium
Figures 6: The CEIS' method to market equilibrium
Figures 7: CEIS market equilibrium
Table 1: MPI case study
The following document “The Economic Framework of the Cybernetic Economic Intelligence System” describes a collection of models, and assumptions that help explain how different components of the CEIS economy interact and influence each other. These frameworks guide the analysis of economic issues and guide decision-making in various areas, such as macroeconomic policy, microeconomic behavior, market dynamics, and resource allocation.
The current economic landscape faces unprecedented challenges due to technological advancements and the limitations of traditional economic strategies like inflation targeting. To address these challenges, the Cybernetic Economic Intelligence System (CEIS), otherwise referred to as Triptonomics, offers an innovative framework that recognizes the disruptive impact of technology on the current economic paradigm, and aims to decentralize and distribute productive technologies to create a sustainable and inclusive online marketplace.
Technological advancements have led to a disconnect between human labor and productivity, concentrating economic resources toward major corporations. This concentration of wealth, if unchecked, can widen socioeconomic divides and hinder economic mobility. The existing monetary system based on inflation, is ill-suited for the deflationary effects of technological efficiencies, resulting in depressed wages, limited job opportunities, reduced purchasing power, and barriers to asset acquisition for low to mid-income households.
Triptonomics seeks to address these challenges by integrating economic principles with technology, and establishing autonomous organizations or Smart e-businesses to share in the economic profitability of production technologies. By embracing technological integration, Triptonomics ensures that the advantages of technology are shared among all participants, creating an open and inclusive marketplace ecosystem. The primary goal is to combat the widening wealth gap, wage depression, unemployment, and declining long-term aggregate demand.
Triptonomics acknowledges the need to adapt to the technological era and develop new approaches to supply and distribute economic opportunities. By adopting this alternative economic framework, the CEIS aims to create a more sustainable and efficient system that caters to the demands of the technological age.
In the following sections, we will explore the control policies, effects, and measurement frameworks employed by Triptonomics to achieve its objectives. By understanding these components, we can grasp the principles and mechanisms driving Triptonomics' transformative potential in shaping the e-commerce landscape.
The current economic landscape presents challenges stemming from technological advancements, shifting labor dynamics, and limitations of the inflation-based monetary system. These challenges necessitate a reevaluation of traditional economic management strategies, with the Phillips Curve providing a conceptual framework.
Technological innovations have decoupled human labor from commercial productivity, posing challenges to the labor market. While automation, AI, and disruptive technologies enhance efficiency, the traditional labor-intensive model struggles to adapt. This leads to resource concentration and a widening wealth disparity within major corporations.
The inflation-based monetary system clashes with deflationary effects resulting from technological efficiencies. Improved production technology reduces costs and creates deflationary pressures. However, the monetary system fails to account for these forces, causing wage depression, limited job opportunities, reduced purchasing power, and obstacles for low to mid-income households.
The decoupling of labor and productivity, along with the incongruity of the monetary system, exacerbates income inequality and widens the wealth gap. Technological advancements and resource concentration further hinder economic mobility, impede social progress, and pose long-term stability risks.
The current economic landscape poses challenges such as limited economic opportunities and declining aggregate demand. The Phillips Curve predicts depressed wages, unemployment, and reduced purchasing power. These challenges hinder economic growth, impede innovation, and perpetuate a cycle of decreased economic activity. It’s important to note that the Phillip’s curve remains a foundational framework that informs and guides monetary policy.
Addressing these challenges requires a reassessment of our economic paradigm. A comprehensive approach like Triptonomics aims to adapt to the changing landscape, foster inclusivity, and promote sustainability. By integrating technology and implementing effective control policies, Triptonomics strives to achieve efficient wealth distribution, increased economic opportunities, and enhanced purchasing power.
The CEIS platform serves as the foundation of Triptonomics, providing the necessary infrastructure for its effective management. Its ultimate goal of Triptonomics is to inverse the Phillips Curve by focusing on income and wealth growth through decentralized ownership of data and productive technologies, instead of relying solely on job growth through inflation. By integrating productive technologies, Triptonomics aims to incrementally decouple human labor from commercial productivity, while ensuring efficient distribution of benefits among all participants in the economy.
Triptonomics implements control policies to promote inclusivity and sustainability. These policies include the monetization of data ownership through retail margin redistribution (Control #1), shifting retail pricing control to manufacturers/suppliers (Control #2), and implementing a distribution policy for effective income and wealth distribution (Control #3). These measures optimize economic opportunities and maintain market equilibrium.
Figure 1. The Phillips Curve Models Figure 2. The CEIS’ Economic Policy
Recent evidence suggests that the traditional measure of economic prosperity, GDP, is becoming less aligned with human labor due to technological advancements. To address this, we propose a new metric called "Cumulative Wealth Efficiency" (CWE) that takes into account both productivity and the actual effectiveness of wealth generation on a network.
CWE encompasses several key measurements:
- Gross Consumer Wealth (GcW): GcW represents the total capital invested in Community- Sourced Funds within the network. It is calculated by combining the liquidity available for consumption or investment (Lq) and the total amount of funds invested (I). GcW = Lq + I
- Gross Consumer Income (GcI): GcI captures the total income generated from commercial activities on the network. It considers the yield generated from investments (Y) and the time period (t) over which the yield was generated. GcI = Y / t
- Purchasing Power (pp): pp reflects the change in consumers' ability to make purchases based on the performance of their individual Autonomous Organization and the network's CWE.
- Gross Product Productivity (GpP): GpP measures the distribution and variety of products available on the platform. It takes into account factors such as consumption (cp), total investment inventory (tIN), supplier variation (sVR), and product variation (pVR). GpP = (tIN/ (cp x sVR x pVR)
- Coefficient of Variation (CV): CV indicates the variation of each unit of wealth created in relation to the total number of consumers within the platform.
- Token Value (Tv): Tv represents the fluctuation in value of the native token.
Triptonomics implements several key control policies to ensure the effective functioning of its economic framework and achieve its goals of effective wealth distribution, market stability, and sustainable growth.
Control #1 is foundational to the purpose of the CEIS. Data ownership is inherent to the mission of inversing the Phillip Curve. It suggests that the definition of human productivity needs to be expanded beyond labor (physical or intellectual) to include the contribution of data. Even as technology improves and becomes more capable and self-reliant, it will still continuously require fresh inputs of data in order to remain relevant. Herein lies society’s opportunity to quantify that data and use it to sustain continuous income streams from a resource inalienable to itself.
While there is a variety of methods by which data can and is valued, for the purposes of a peer-to-peer marketplace, where profits are decentralized, we found it most reasonable to relate the value of a user’s data directly to the economic productivity it generated. This is determined by converging upon the point of purchase and assigning data credits proportional to the margin value of the consumer’s purchase order. The credits are then applied to an algorithm that determines the real-time value of the consumer’s data and redistributes that amount in the form of the platform’s native currency, Tripto. This process describes the monetization of data, which is likely to be the primary source of funds from which consumers will invest in their Autonomous Organizations.
Control #2 grants suppliers the authority to determine the retail pricing of their products within the e-marketplace. The CEIS framework empowers manufacturers/suppliers by allowing them to submit the Manufacturer's Listing Retail Price (MLRP), which is often derived from the Manufacturer's Suggested Retail Price (MSRP). This transfer of retail pricing control to manufacturers enables them to assess their pricing strategy in relation to the distribution and retail margins offered to their stakeholders, namely the consumers who invest in and purchase their products.
As mentioned in Control #1, the CEIS captures the retail margin from consumer product purchases and utilizes it to assign value to and monetize consumer data contributions. These funds are directed to an internal reserve, generating credits based on the margin value. These credits are then processed within an algorithm that determines the real-time value of consumer data and redistributes it in the form of Tripto Coins. This data monetization process serves as the primary funding source for consumers to invest in their e-businesses.
Therefore, when establishing prices, manufacturers and suppliers are compelled to consider not only the prices set by their competitors but also the monetary impact it has on their stakeholders, such as distributors and retailers. This control mechanism ensures that pricing decisions are made in a competitive context, taking into account the interests of all involved parties within the CEIS framework.
The CEIS employs the Gaussian distribution curve as a metric to categorize a user's financial requirements in relation to the rest of the network. Through a range of techniques based on Modern Portfolio Theory (MPT), commercial opportunities are spread across user accounts, leveraging their diverse income ranges to achieve risk diversification and increase the potential for returns. Triptonomics, as the implementation of these objectives, aligns with the CEIS' mission to inverse the Phillips curve.
Maintaining symmetrical wealth distribution through a mathematical framework holds significant importance for the long-term fiscal growth and viability of the CEIS economy. As an inclusive system, it must accommodate the financial circumstances of all users. By identifying and categorizing each user's unique profile, the Gaussian distribution allows these profiles to leverage each other's positions and synchronize their commercial interests. This framework enables each profile, regardless of its position, to pursue its financial objectives.
Figure 3. CEIS’ distributive policy
The Gaussian distribution naturally accounts for outliers within any population distribution. In the case of the CEIS, one end of the distribution represents individuals with a significantly lower ratio of wealth compared to the mean, which may be attributed to inexperienced users joining the network. On the other end of the distribution are outliers with an exceptionally higher ratio of wealth, reflecting the user's time and experience on the platform.
Given these considerations, our strategy involves understanding each user's unique financial circumstance to develop an inter-temporal profile that aligns with their personal needs for optimal investments in their e-business. This is done in relation to the overall distribution of users. Users will invest for themselves and with each other, harmonizing their potential, limitations, interests, and objectives within the network.
To achieve this, the CEIS implements the Monee Tree Protocol (MTP), which combines the principles of the Keynesian Consumption Function and Modern Portfolio Theory (MPT) to generate a User Investment Profile Fit (UIPF). The MTP considers the user's consumption requirements and investment propensities in relation to the network. It establishes homeostasis between users with high consumption requirements and a low propensity to invest on one end, and those with low consumption requirements and a high propensity to invest on the other.
For instance, the MTP may match one user with exceptionally low consumption requirements relative to their investment propensity (+4th standard deviation) with a pool of ten users who have exceedingly high consumption requirements relative to their investment propensity (-4th standard deviation). By doing so, the system distributes risk proportionally across each UIPF while increasing the probability of a return on investment.
The system's objective for each user account is to continually increase their economic status by at least one Monee Station relative to their current position within the distribution. Each Monee Station represents a standard deviation within their respective distribution. For example, if a user's current economic station is -3 standard deviations within the distribution, their robot's goal will be to elevate them to -2 standard deviations. The number of stations is theoretically limitless, as the system divides the total population into wealth ranges, accumulating more ranges as wealth increases on the platform.
By implementing the UIPF distribution policy, the CEIS ensures an effective distribution of income and wealth, allowing users to benefit from diversified investment opportunities, achieve their financial objectives, and continuously improve their economic status within the network.
Figure 4. Distribution of wealth within the network
The distributive policy of the CEIS aims to ensure that every user's economic objective is to increase their financial position by one Monee Station while also shifting the portion of the population on the extreme negative side of each distribution towards their middle sections. This approach minimizes friction and aligns with the economic goals of each account, regardless of their Monee Station.
- Extreme users on the extremely negative side of the distribution have their investment opportunities catalyzed as they are in high demand and perceived as less risky. They benefit from the participation of users on the extremely positive side of the distribution and enjoy a larger population of users who can pool investments together.
- Users closest to the mean of the distribution experience investment opportunities catalyzed by the greatest portion of wealth on the platform. They also have a larger pool of users to match investment interests with, maximizing their investment potential.
- Users on the extremely positive side of the distribution also have their investment opportunities catalyzed. They can absorb the largest share of a given investment derivative that carries high demand and the least risk within their respective distribution.
By implementing this distributive policy, the CEIS creates a dynamic environment where investment opportunities are optimized for users across the entire distribution. This approach allows users at different positions within the distribution to pursue their economic objectives effectively, ensuring a balanced and beneficial economic ecosystem within the network.
In the CEIS method, we replace the consumer's propensity to save with the consumer's propensity to invest, based on the Keynesian consumption function. This adjustment acknowledges two main implications of saving:
- When consumers have surplus income beyond their consumption needs, they seek investment opportunities that can outpace inflation or deflation.
- If a consumer's present income is insufficient to meet their consumption demands, saving becomes necessary to ensure future consumption.
By offering investment opportunities to consumers, the CEIS method caters to both scenarios, making the accumulation of liquid assets a justifiable alternative to traditional saving.
To quantify the impact of Control Policies #1-3, we consider the perpetual increase in aggregate demand and the marginal propensity to invest. As consumers earn more income from their e-businesses and investments, their demand for products also increases. This higher demand stimulates greater investment propensity, resulting in an increase in Gross Consumer Wealth (GcW), Gross Consumer Income (GcI), and Gross Product Productivity (GpP).
The marginal propensity to invest (MPI) is calculated as the change in investment divided by the change in income: ∆Investment / ∆Income. For example, if we have the following data:
Table 1: MPI case study
The change in investment is ($1,000 - $500) = $500, and the change in income is ($3,000 - $2,000) = $1,000.
Therefore, MPI = $500 / $1,000 = 0.5.
This implies that for each additional unit of income, savings increase by 0.5. Thus, the change in GpP has a multiplied impact on the system, generating increased income from Returns on Investment (ROI). Moreover, higher GcW and GcI lead to increased consumption, which, in turn, stimulates further production. This virtuous cycle perpetually increases GcW, GcI, and GpP over time.
The spending multiplier can be expressed as the magnified change in production (product variation) due to a $1 change in an autonomous variable. It can be calculated as 1 / MPI, where MPI is the marginal propensity to invest. The larger the output of 1 / MPI, the greater the increase in product variation over time, reflecting a growing virtuous cycle of economic expansion.
Through the implementation of Control Policies #1-3 in the Triptonomics framework, market equilibrium is achieved, and prices in the distribution and retail sectors stabilize. This occurs due to the interplay between consumer behavior and competition among manufacturers and suppliers.
When consumers earn additional income from their e-businesses and investments, each unit of margin they generate becomes a multiplier of their income. This creates a natural constraint in the market that influences pricing decisions. If a supplier sets their product price too high (Manufacturer's Listing Retail Price or MLRP), consumers are less likely to purchase it because it would reduce their potential future income. Conversely, if the price is set too low, suppliers risk diminishing their profit margins.
To stay competitive and attract investment, manufacturers are inclined to lower their prices (manufacturer's price) when selling their products to Autonomous Organizations for distribution. This reduction is driven by the desire to gain a competitive edge and the decreasing production costs resulting from technological efficiencies.
To further illustrate, let's consider the following scenario:
- To remain competitive, Product x must be priced at (x + x(sqd)), where x(sqd) represents the cost of the product and x represents the product's margin. Any price above (x + x(sqd)) is considered $1 or more above the market rate.
- Deflation occurs semi-annually with a value of x/2.
Figure 5: Classical sequence to market equilibrium
Figures A, B, and C depict the classical sequence of events for Product x to maintain market equilibrium over a 6-month period. Market equilibrium is represented by (x + x2).
- Figure A illustrates the traditional division of prices among the manufacturer, distributor, and retailer, resulting in the final retail price of Product x.
- Figure B demonstrates the impact of deflation on each segment after 6 months. Deflation leads to an additional value of x/2 within each segment, increasing the price of Product x to (x + x(sqd) + x/2).
- Figure C shows how sellers react to deflation by reducing the price of Product x by x/2, bringing it back to market equilibrium (x + x(sqd)). As a result, the revenue generated from each segment decreases proportionally to the deflation value of x/2, reducing the overall size of the chart in Figure C.
Figure 6: The CEIS' method to market equilibrium
Now, let's examine Figures D, E, and F, which illustrate the CEIS' approach of transforming deflation into liquid assets by involving the consumer in the distribution and retail segments of the supply chain.
- Figure D depicts the transition within the distribution and retail segments, where the consumer takes on the roles of both a consumer(distributor) through Autonomous Organizations and a consumer(retailer) through data contribution. The margins from these segments are redirected back to the consumer.
- Figure E, similar to Figure B, shows the effect of deflation after 6 months. The profit margin is redirected to the consumer from the distribution and retail segments, countering the deflationary impact. Meanwhile, the manufacturing/production segment remains susceptible to deflation. As a result, the deflation of manufacturing prices, while distribution and retail prices remain stable, leads to a marginal increase in consumer profits and the value of their data.
- Figure F demonstrates how sellers respond to market deflation, specifically in the manufacturing segment. It also showcases the income multiplier effect resulting from involving the consumer in the distribution and retail processes. Figure F highlights how these factors expand the network's economy, increase consumer wealth and income, and enhance product variety, aggregate demand, and the propensity to consume.
In the Triptonomics framework, Controls #1-3 play a crucial role in achieving Economic Objective #1, which involves implicitly regulating the growth rate of Gross Consumer Wealth (GcW) and Gross Consumer Income (GcI) in relation to the growth of Gross Product Productivity (GpP). This regulation ensures the maintenance of market equilibrium and the long-term viability of the network.
Figure 7: CEIS market equilibrium
Figure 7 illustrates the concept of market equilibrium within the CEIS. GpP serves as a reference signal, indicating the desired direction for the growth of GcW and GcI. To maintain a stable and sustainable economic environment, both GcW and GcI should closely align with the growth rate of GpP. This alignment prevents excessive inflation or deflation that could disrupt the economic balance.
It also provides further insights into the framework's control policy by introducing parameters represented by the slope (m) of GpP over a one-month period. These parameters define the acceptable range for the growth rates of GcW and GcI. It ensures that the growth rate of GcW and GcI does not fall below or exceed the growth rate of GpP over a 30-day timeframe. By adhering to these parameters, the system ensures a controlled and sustainable growth trajectory.
The CEIS implements these controls with the aim of creating an anti-fragile response to the deflationary forces present in the real economy. Factors such as globalization, automation, and data technology can contribute to deflationary pressures. However, in the CEIS, these forces are harnessed to increase the purchasing power of consumers and enhance their investment capacity, thereby fostering economic growth within the network.
By implicitly regulating the growth rates of GcW and GcI relative to GpP, the Triptonomics framework ensures the stability and viability of the network. This approach allows participants to leverage deflationary forces as opportunities for growth, enabling them to thrive in a dynamic economic landscape.
To summarize, the Triptonomics framework's control policies and mechanisms facilitate the implicit regulation of the growth rates of GcW and GcI in relation to GpP. This regulation ensures market equilibrium, promotes the network's viability, and empowers participants to harness deflationary forces for sustainable economic growth within the CEIS.
In conclusion, Triptonomics presents a comprehensive economic framework that embraces technological integration, redistributes economic opportunities, and promotes inclusive growth. By leveraging technological advancements, Triptonomics strives to ensure that the economic advantages of these technologies are efficiently distributed throughout the network while sustaining an open, inclusive, and viable economic paradigm that is conducive to the evolving information-based era.