Creditism

Explore

Creditism: an economic evolution

Avi's Price equation brainstorming.

⁠

BasePrice = ResourcesCost + LaborCosts + CouncilMarkUp

MarketPrice = (BasePrice + CoopMarkup) * Demand/Supply

Note on above: the ResourcesCost itself contains items bought from the market at MarketPrice which means the ResourcesCost is the sum total of pre-purchased ResourcesCost + Labor + MarkUps, so a real total Price of any Resource or Good can be shown in a pie chart so buyer knows how much of each ‘cost’ is actually embedded within the price, if that makes sense? 2 Bike Coops will have different costs and this is how we show them and compare them for purposes of either Bonus PC for workers and possibly CC for their Coop if that industry or product sells for more than BasePrice, that means they are deleting more Cs from the market than Price Councils intended, so that extra C deletion can be given to the winning industries/coops as CC?

⁠

@Avi Volah⁠

I pulled this quote from this article that seems relevent here:

https://medium.com/@macurdy/the-fundamentals-of-growth-8b0ecafd7525⁠

“Cosmologist Eric Chaisson found interesting results when mapping energy metrics across various scales of matter throughout time. He identified the structures that have the highest levels of efficiency, specifically the highest concentration of energy flow per unit mass and time.

The metric is called free energy rate density. According to Chaisson, other scientific disciplines use similar measurements; physicists call it the power-density ratio, engineers call it power-to-mass ratio, biologists call it metabolic rate, geologists, radiant flux, and astronomers say light-to-mass ratio. These terms have been used for decades, but their focus has been too narrow.”

Goods: products and services

Assets: Resources and Goods.

A_unit: Stands for Asset unit. In the case of resources - Liter\Kg\Km.. ; In the case of good - laptop\Data (Gb, Mb..)\bike\time.

rejuvenation_rate: (amount of A_unit replenishment) per amount of time (example: oak_trees_r_rate = 100_kg of oak_tree born per 1yr)

mortality_rate: (amount of A_unit mortality) per amount of time (maybe - “/ total_supply”) (example: oak_trees_m_rate = 50_kg of oak_tree die per 1yr)

extraction_rate: (amount of A_unit extraction) per amount of time (example: oak_trees_ex_rate = 1000_kg of oak_tree per 1yr)

Asset_Processing_rate: the name for both Resource extraction_rate and Good production_rate

Externality: the caused damage to the ecosystem, by extracting resources or other human related activity. There also maybe should be an Externality score/rating to decide which ones are acceptable and which ones arent.

Externality_score: How bad/dangerous it would be to extract the resource or produce the good (on some scale: 0-1; or 0-10; or maybe something that takes inspiration from the kardashev scale - only here its magnitude of impact and not of energy control\harnessing; or, maybe in “levels” like 1, 10, 100... or Fibonacci), it would be probably at least loosely based on the rejuvenation_rate, mortality_rate and total_supply, as well as other side effects of extracting it. Would be assigned by the council (maybe not calculated, but just assigned based on what kind/type of externality it is). Would either be a limit to what score is allowed to extract (like in scale 0-1, anything above 0.5 is not legal), or maybe its better to just be regulated through the market since there would be a higher price on it. GPT4 and me: Purpose: The Externality Score measures how detrimental or impactful the extraction\production of a particular Asset would be to the environment and local communities. This score is derived by considering multiple factors, for example: environmental degradation Oxygen release detriment, soil nutrient/support detriment and etc.

Method: Each of these factors is assigned a weight that reflects its relative importance in the overall assessment of externality for each asset. The factors are scored, and then these scores are multiplied by their respective weights.

Calculation: The results are summed up to produce a single composite score - the Externality Score. This score is essentially a weighted average of the factors considered, where:

Each factor’s score (EF_i) is multiplied by its weight (w_i).

The weighted scores are summed up.

The total may or may not need to be divided by the sum of the weights, depending on whether the weights sum to 1. the sum of the weight indeed should be 1 so no division required. Externality Score = (W1 * EF1 + W2 * EF2 + ... + Wn * EFn) / (W1 + W2 + ... + Wn)

factor: one type of impact (good or bad) from an asset processing (extraction\production) to the ecosystem. EFi: factor number i. EF_score calculation description: how much the Asset_Processing influences the factor (the measured thing’s detriment). EF_parameters: resource factor per A_unit, factor_optimal_state, factor_current_state

Description: resource - Tree Factor1 - oxygen production detriment unit - kg oxygen production externality is calculated by knowing how much the tree produces the oxygen compared to the total oxygen production (from all the sources of oxygen production) in reference of the optimal oxygen production amount.

E - E contribution per A_unit’s amount / (factor_optimal_state - factor_current_state) - NOT

E - Asset factor per A_unit * (1 - factor_current_state / factor_optimal_state) - NOT

(Asset factor per A_unit / factor_optimal_state) - 100% (Asset factor per A_unit / factor_current_state) - ?

E - ((Asset factor per A_unit / factor_current_state) * 100) / (Asset factor per A_unit / factor_optimal_state)

((10 liters of O2 / 1,000,000 liters) * 100%) / (10 liters of O2 / 3,000,000 liters) (0.00001 * 100) / 0.00003 - 33% - 0.33

((10 liters of O2 / 4,000,000 liters) * 100%) / (10 liters of O2 / 3,000,000 liters) (0.00004 * 100) / 0.00003 - 133% - 1.33

Not good - it should be the better the situation, the lower the score (we cant use 1 - result, because it can cause negative values)

(Asset factor per A_unit / factor_optimal_state) ; optimal_ratio of the asset’s factor (Lower is better) (Asset factor per A_unit / factor_current_state) ; current_ratio of the asset’s factor (Lower is better)

E - (current_ratio / optimal_ratio) / 10

Bad situation (current state < optimal state): (10 liters of O2 / 1,000,000 liters) / (10 liters of O2 / 3,000,000 liters) 0.00001 / 0.00003 = 0.33; 0.33 / 10 = 0.033

Good situation (current state > optimal state): (10 liters of O2 / 4,000,000 liters) / (10 liters of O2 / 3,000,000 liters) 0.00004 / 0.00003 = 1.33; 1.33 / 10 = 0.133

E - (optimal_ratio / current_ratio) / 10

Bad situation (optimal state > current state): (10 liters of O2 / 3,000,000 liters) / (10 liters of O2 / 1,000,000 liters) 0.00003 / 0.00001 = 3; 3 / 10 = 0.3

Good situation (optimal state < current state): (10 liters of O2 / 3,000,000 liters) / (10 liters of O2 / 4,000,000 liters) 0.00003 / 0.00004 = 0.75; 0.75 / 10 = 0.075

Test Example: we have a total of 100 people population (represents the ecosystem [1 person is just 1% of the ecosystem]), each needing 1 apple (represents some resource [like if 1 tree would be enough to produce 1% of O2 for the planet]), to get 100 vitamins (represents the factor [the O2 in case of trees]), to live_a_day (represents the benefit the factor gives to the ecosystem). factor optimal state is 10,000 vitamins. factor current state is 10,000 vitamins. ITS THE BEGINNING OF THE DAY. so what is the externality of causing death of people in a day by taking 1 apple? by taking 1 apple we would cause 100 vitamins out of 10,000 vitamins to be missing, so the equivalent of 1 person to die (or all 100 people to be at a lesser “health score”). which means it should be 1% externality on that factor. which is 0.01 . so the externality factor of causing death in people_population in a day, by taking 1 apple should be 1% which is 0.01 . But what if its: factor optimal state is 10,000 vitamins. factor current state is 4,000 vitamins. it would seem that the externality by taking 1 apple and therefor 100 vitamins from the current state of 4,000 vitamins would be 2.5%, but thats not true cause we need to account for the factor optimal state. if we would take 1 apple (100 vits’) it would leave 3,900 vits’ out of the needed 10,000 vits’. so the externality would be 61%. which is 0.61 .

factor optimal state is 10,000 vitamins. factor current state is 15,000 vitamins. it would seem that the externality by taking 1 apple and therefor 100 vitamins from the current state of 15,000 vitamins would be 2%, but thats not true cause we need to account for the factor optimal state. if we would take 1 apple (100 vits’) it would leave 14,900 vits’ out of the needed 10,000 vits’. so the externality would be -0.49.

So now writing it as an expression: factor_optimal_state - 10,000 vits’ resource factor contribution per A_unit - 100 vits’ per 1 apple factor_current_state - 4,000 vits’ (factor_optimal_state - (factor_current_state - resource factor per A_unit)) / factor_optimal_state or (factor_optimal_state - factor_current_state + resource factor per A_unit) / factor_optimal_state

And now cleaner:

maybe instead of “factor” it would be “subject_impact” Resource’s EFi = 1 - ((factor_current_state - resource’s factor per A_unit) / factor_optimal_state) - correct! - this is only when calculating the factor for resources - almost correct..

Resource’s EFi = (factor’s positive_optimal_state - factor’s positive_current_state + resource factor’s positive per A_unit * allotted_extraction_rate) / factor’s positive_optimal_state - correct but needs re-formatting - (this is only when calculating the factor for resources).

if Resource’s EFi < 0: Resource’s EFi = 0

else: Resource’s EFi

Good’s EFi is different cause a good isnt taken from the earth, its produced, so the damage to the env is not from extracting but from production. And also there is no sense for optimal state here since it would always just be 0 or even negative.

Good’s EFi = negative impact per A_unit / rejuvenation_rate from the impact. - ? So lets say that 1 factor of the laptop produced is Co2 pollution, and there is 2000 liters* of Co2 pollution per 1 laptop. And lets say the rej rate from that is 10000 liters of Co2 are absorbed each year But we need to factor in that some of that absorption is already being “used up” by existing production. So we need factor current state again? what would it represent? factor is in this case stands for Co2 emission, so then factor current state would be current total Co2 emission, is that correct? what does it give us? What we want is for the rej rate to be >= to the factor_current_state + Good’s factor negative impact. And we want to check by how much the production of the Good, will impact the factor_current_state Good’s EFi = negative impact per A_unit / (factor_current_state / rejuvenation_rate from the impact) ? Lets check that with an example to see if it tracks: 1 bike - polluting 1000 liters of Co2. factor_current_state - 50,000 liters Co2 rejuvenation_rate - 60,000 liters Co2 absorbed Bike’s EF1 = 1000 / (50,000 / 60,000) = 1200 - seems wrong, also what would this number represent? is it liters? Good’s EFi = negative impact per A_unit / (rejuvenation_rate - factor_current_state) ? Bike’s EF1 = 1000 / ( 60,000 - 50,000) = 0.1 (lower is better)

or:

Good’s EFi = (rejuvenation_rate - factor_current_state) / negative impact per A_unit

Bike’s EF1 = ( 60,000 - 50,000 ) / 1000 = 10

Bike’s EF2 = ( 30,000 - 25,000 ) / 1000 = 5

Bike’s EF3 = ( 5,000 - 2500 ) / 1000 = 2.5 ~ 2 - Not good, because its making the externality score into just the maximum capacity of 1 factor that is the minimum out of them all.

Then again: Externality Score = W1 * EF1 + W2 * EF2 + ... + Wn * EFn

We need to break it down for it to be calculatable later for the allotted_extraction_rate:

First lets calculate the Weighted Sum of Differences (WSD): WSD = W1 * (1 - (factor_current_state / factor_optimal_state)) + W2 * (1 - (factor_current_state / factor_optimal_state)) + ... + Wn * (1 - (factor_current_state / factor_optimal_state))

Externality fee: the cost of [compensating]\[maintaining or correcting] towards centropy (not a typo). (labor and resources costs of people planting trees for example).

extraction_rate: : ([allowed\approved ?] AllottedSupply_p_yr): should maybe (maybe because there is also the total supply of it) always be BELOW the rejuvenation_rate! (Since “extracting resources often involves disrupting the ecosystem in ways that go beyond the mere removal of the material.”) It is based on: Externality_score, rejuvenation_rate, mortality_rate and total_supply (because there are resources that arent rejuvenating [or takes millions of yr to rejuvenate]). - (this step happens after a resource is known\discovered researched.)

Mine (not finished): extraction_rate = rejuvenation_rate/Externality_score, (total_supply - mortality_rate)

GPT4: extraction_rate = rejuvenation_rate * (1 - Externality_score) * (total_supply / (1 + mortality_rate)) - maybe wrong

500 * (1 - 0.4) * (100,000/(1 + 400)) The equation I provided aims to calculate the extraction rate of a resource based on several ecological and environmental factors. Here's the reasoning behind each component of the equation:

1. **rejuvenation_rate**: This represents the natural rate at which the resource replenishes itself. It serves as the baseline for how much can potentially be sustainably extracted without depleting the resource.

2. **(1 - Externality_score)**: The Externality_score reflects the negative impact of extracting the resource on the environment, scored between 0 and 1 (with 1 being the most harmful). Subtracting this score from 1 inversely adjusts the extraction rate; the more harmful the extraction, the lower the proportion of the resource that should be extracted. This term effectively reduces the extraction rate as the environmental impact increases.

3. **total_supply**: This is the current available amount of the resource. Including total supply in the equation allows the extraction rate to scale with the actual quantity of the resource available.

4. **(1 + mortality_rate)**: Mortality rate here is used to factor in the loss of the resource that isn't directly related to human extraction but due to natural causes (death rate in biological contexts or decay rate in non-biological contexts). The division by (1 + mortality_rate) adjusts the extraction rate downward to account for natural losses, ensuring that the calculated extraction rate does not assume more resource availability than what might realistically be sustainable considering natural attrition.

By combining these factors, the equation provides a more ecologically and environmentally sensitive approach to determining how much of a resource can be extracted annually, considering both its natural ability to replenish and the broader impacts of its extraction.

GPT4 ver2

extraction_rate = Rejuvenation Rate − (Mortality Rate × Total Supply) - not

Test Example: We have a total supply of 100 apples, - doesnt matter in the case of resources and also is taken into account in the externality calculation. but does mater in the case of goods. mortality rate is 300 apple per hour, rejuvenation rate is 500 apples per hour, Externality score is 0.1 (low) So it would mean we can extract almost as much as the difference of rejuvenation and mortality rates.

Another one: We have a total supply of 40,000 unit trees mortality rate is 3000 unit trees per year, rejuvenation rate is 5000 unit trees per year, Externality score is 0.61 (high) So it would mean we can extract much less from the difference of rejuvenation and mortality rates.

survival_rate = rejuvenation_rate - mortality_rate

allotted_extraction_rate = survival_rate * (1 - Externality_score) - correct (180 apples)

E = 1 - (F/S)

E=0.1+0.01F

F = 0.9/(0.01+(1/S))

but maybe we can somehow include the total_supply in there as well. we need to see how much the total supply is compared to rejuvenation_rate and mortality_rate survival_ratio = mortality_rate / rejuvenation_rate - (0.6, 6/10, for each 6 that “dies” there are 10 that are “born”)

optional_extraction_rate = (survival_rate + (total_supply interacting with something)) * (1 - Externality_score) - Not

finite_resource: A resource that doesnt really have a rejuvenation_rate

R_total_age: the amount of years since the pre-extraction resource amount was first created on the planet.

finite_resource_extraction_rate = (total_supply_R_unit / R_total_age)

optional_extraction_rate = (survival_rate + finite_resources_extraction_rate) * (1 - Externality_score) - Not

production_capability: the product’s production capability based on the allotted_extraction_rate of all the required resources and etc.

Test Example: We want to make a bicycle thats made out of 3 resources, steel, rubber and plastic, we check the allotted_extraction_rate for each resource; steel - 50,000kg per year rubber - 60,000kg per year plastic - 30,000kg per year, and check how much of each we need to make 1 bicycle; steel - 5kg rubber - 2kg plastic - 1kg and then calculate how much bicycles we can make with that amount, 50,000 / 5 is 10,000 60,000 / 2 is 30,000 30000/ 1 is 30,000 now we take the lowest figure - 10,000 is the number of bicycles its possible to produce with the allotted_extraction_rate of the required resources.

production_capability = min(R1_allotted_extraction_rate/R1_requirement_per_A_unit, R2_allotted_extraction_rate/R2_requirement_per_A_unit, Rn_allotted_extraction_rate/Rn_requirement_per_A_unit)

alloted_production_rate parameters: demand, Externality_score, total_supply (incase of an existing product), production_capability

Example test: we are trying to find the healthy production rate of a laptop lets say that in the process of producing and\or having a laptop there is 10%, 0.1 externality score. we should take into account the

allotted_production_rate = production_capability * (1 - Externality_score)

actual_production_rate, actual_extraction_rate:

if demand > allotted_Asset_Processing_rate: actual_Asset_Processing_rate = allotted_Asset_Processing_rate

if demand <= allotted_Asset_Processing_rate: actual_Asset_Processing_rate = demand

Asset_Processing_rate = rejuvenation_rate * (1 - Externality_score) (and maybe more)

Random thoughts: 1) In the beginning the council does for each resource: a) survey of the resource demand, b) survey of the resource amount, c) calculation of the extraction_rate, .......... 2.2) when a new coop wants to make a new Laptop in a new way for example, they a) check the initial interest from the market through a survey, b) they apply to the council with their detailed plan including the resources they would require, the production process and etc. c) the council is setting the allotted_production_rate, d) check the demand from the market through a CC crowdfunding and product pre-orders, e) arrive to the actual_production_rate. 3) The coop is opening the option to submit orders for the product to gauge the demand and sets the price based on the equation below. the earlier the consumer oders the cheaper it is because the demand is lower compared to the Asset_Processing_rate? The coop would be responsible for recycling its products - maybe. The externality_fee maybe should be determined by the E_score times a credit amount which is relative in some way to the monthly UBI amount, to represent how the people are supposed to pay from their “total” the same percentage of as the externality happening because of their activity.

(A_unit_Demand_p_yr/A_unit_Asset_Processing_rate): what is it?? ; - (this is happening at the stage after the survey of the demand.) Examples: If Avi has 20 apples, and Eli wants 5 apples, by dividing the amount of apples that Eli wants by how much apples Avi has, we get 0.25 what?..

Eli wants 5 of Avi’s 20 apples is the same as saying he wants 25% (.25) of Avi’s apples so this is redundant. how is this related to the total qty of apples available? that might be useful info? If the allotted supply of oil for a city is 2086 liters, and the demand for the oil in the city is 1506 liters, by using demand divide supply we get 0.722 of what?..

This too is a redundant statement. How is this relevant? what data are you wanting to show with these ‘equations’? Perhaps the question to be asked is how much oil of a region or globe was used, which is relevant as it informs future prices. The optimal outcome for the demand/supply equation, should be between 0 and 1. option1 - the willingness of the entity that requires the thing, to acquire it. - maybe option2 - the percentage of A_unit needed to supply relative to the demand. - not option3 - its the percentage of what we determined we could extract, given the actual demand for the thing - thats just a paraphrase option4 - what we determined we could extract relative to what we consumed is the outcome in percentage. - not option5 - the capability to answer the demand in percentage. - not correct option6 - the rating for how easily we can supply the demand of the resource. - no option7 - The “danger-rating” of breaking the allowance! - Correct! option8 - The capacity-rating - maybe option9 - How far are we from breaking the set allowance for resource extraction. - better!

There is no ‘allowance’ or allotment as you are eluding to in a strict sense. It is an open market of freely cooperating people and groups. That’s the purpose of the currency, as an expression of limited preferences. You and/or your region might consume more than the average ‘allotment’ of oil for a period but that just means you have less credit with which to buy up the rest of other things, and that’s ok, it all balances out, and where there is more demand, well then, again, that’s the purpose of the Credit, it is a resource REGULATOR.

R_unit_Demand_p_yr/R_unit_allotted_extraction_rate: How far are we from breaking the set allowance for resource extraction.

R_Allowance_Rating = R_unit_Demand_p_yr/R_unit_allotted_extraction_rate (lower is better)

External Resources: Resources used indirectly for the sake of the good (F.e: The oil to transport a bicycle from the factory to the “shop” or the customer, or to transport a not in-house made part to the factory, etc.)

Labor should be part of the equation because its a credit measure for time and energy taken to achieve this thing.

But not sure about External resources - Remzi said its

⁠

(maybe the price should be just determined through bidding? since in reality different people and coops will have different priorities and amount of desire for each resource or good..)

⁠

- (this step is happening at the stage after the resource is extracted, since then we will have the data for “Extraction Labor cost” and “External Resources cost”.)

10000credits/100kg*1.1 = 110 per kg of wood

(Will we set a cost on air?! if not, what is the framework\conditions of deciding why not, and when other resources reach that status of not priced? Maybe - get a sense of the supply\demand of air, and based on that get a sense what order of magnitude of the Asset_Ext_Danger_Rating is considered abundance)

G: A specific Good (as in product or service).

G_unit_Demand_p_yr/G_unit_allotted_production_rate: The “something-rating” of something.

G_something_Rating = G_unit_Demand_p_yr/G_unit_allotted_production_rate (Lower is better)

⁠

the reason the Externality Fee is here again, is that there might be a new externality happening when producing the product or service. (f.e: the factory pollutes while making the bicycle)

⁠

(Efficiency_rating = G_Price / G_Labor_Costs) - this can be used as a metric to the consumer and councils, to know which coops are doing better and etc..

Story:

The council [conduct a survey]/[receive orders] for a quantity for the following 3 materials: steel, rubber and plastic (demand). [Example] steel - 4000kg pyr rubber - 2000kg pyr plastic - 1500kg pyr

They check the Rejuvenation_Rate and/or Total_Supply of resources of those materials

They arrived at an Extraction_Rate (allotted supply) of: [Example] steel - 5000kg per year, rubber - 2000kg per year, plastic - 1000kg per year.

They determine the A_E_Danger_Rating for each: steel - 0.8 rubber - 1 plastic - 1.5

They determine the price for each: steel - RCost = Extraction Labor Cost + External Resources Cost + Externality_fee

Want to print your doc?
This is not the way.

Try clicking the ⋯ next to your doc name or using a keyboard shortcut (

CtrlP

) instead.