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Further Details on The Economic Inequality Rating App (EIRA) and How It Will Benefit Nature and Humankind With a Special Emphasis on its Algorithm.
By Dr. Robert “Rocky” Lipkowitz
ABSTRACT:
An Economic Inequality Rating App (EIRA) in a laptop or handheld device such as that found in a cell phone will allow the consumer to make economic choices that support the 99% simply and conveniently. Consumers can choose a company’s product or service in favor of distributing the purchase revenue to benefit the 99% instead of only favoring the 1%. Just by purchasing the product or service recommended by the EIRA, lower levels of economic inequality will ensue with each transaction.
The EIRA is a proposed tool that will provide clear guidelines as to which consumer products or services when purchased—economically benefit the 99% in contrast to those that benefit the 1%. Its algorithm will accomplish this by analyzing how fairly the revenue from a purchase is distributed across populations, and then rating the levels of economic inequality produced.
Any product or service sold by a company creates revenue. When revenue generated from the purchase is distributed such that only a small group of individuals receive most of that revenue, an economic disparity is created that benefits only those few—the 1%. However, when revenue generated from the sale is distributed more equally, this vastly reduces economic disparity and more evenly benefits the members of the 99%. The role of the EIRA is to evaluate which companies create more economic inequality than other companies and to convey this information to the 99% so they can avoid purchasing products and services form these high producers of economic inequality.
MATERIALS & METHODS:
Due to the fact there are so many companies, and each company can have many products or services, the EIRA project will score each company and hence determine a score for all of that company’s various products or services.
There are approximately thirty-five million different companies in the USA. Each will be evaluated through an algorithm to create their own ERIA score ranging from 0 to 99. From this we know any product or service sold by a company will have the same EIRA score as that of the company. In other words the company and product or services are all scored the same.
There are many factors that will comprise the formulation of the EIRA’s algorithm. These factors, and their significance within the overall equation, will be determined by a large collaborative team comprised of economists, psychologists, sociologists, social psychologists, business researchers, university researchers, statisticians, and a host of others deemed necessary to determine the needed factors and their significance. Once these factors are identified, the collaborative team will structure and synthesized the multifaceted factors into an equation to produce the EIRA’s scores.
The basics behind the EIRA’s operation are simple. The ERIA’s scores will have a range of 0 to 99 that rate the level of economic inequality produced by a company’s selling of a product or service. A score of 0 will indicate that no economic inequality is produced, and a score of 99 will indicate that the highest level of economic inequality is produced. A score of 100 will be reserved for a special situation and will be described later towards the end of this paper. How these scores are arrived at will be based upon the algorithm loaded into the EIRA.
As an example, when the barcode or other appropriate information for a product or service is entered into the EIRA generating a score of 87, this means the product or service produces a relatively high level of economic inequality. When a comparable product is entered into the EIRA and registers a score of 27, this means the item produces relatively a much lower amount of economic inequality. In all cases, the lower-scored product should be purchased over the higher-scored item to reduce economic inequality. For ease of use it should be noted that company names as well as products and services will be entered into the ERIA via barcode or by typing.
A consumer who desires to purchase a product or service will in many cases eventually narrow down their selection until two different options remain. Before making a final decision, the consumer typically has consulted a variety of informational sources—such as Consumer Reports, specific trade magazines, or rating websites—or by comparison shopping on on-line retail outlets or at brick-and-mortar stores.
For example, assume the consumer is looking to purchase a high end product such as a computer and has narrowed down their selection to two different products of similar quality, styling, durability, and price, but the products are produced by different companies. Without the use of the EIRA, the consumer’s decision might be based on meeting their personal desires and ignorant of how much economic inequality their purchase is producing. Little, if any, information is currently available to assess whether the purchase revenue generated will benefit the members of the 1% or the 99%. The EIRA provides consumers with the necessary score to answer this question and then they make their purchase accordingly.
As an example of not knowing what products benefit the 99%, many people in the USA are aware of or have used Brawny paper towels due to Brawny’s frequent advertisements. What most people do not know is that Koch Industries owns Brawny paper towels, and Koch Industries is known for creating large amounts of economic inequality. Even though Koch Industries is private, it is a prime example of a company fostering significant economic inequality. Because of this, Brawny paper towels, as well as all products produced by Koch Industries, would theoretically have an EIRA score of 99. As is the case with Koch Industries, the number of products produced by any company can range from just a few to thousands. Even if Brawny paper towels were to come in three different sizes—small, medium, and large—each size would have an EIRA score of 99 matching the company’s EIRA algorithm score.
Let us also assume that Koch Industries has tax shelters in one form or another. Regardless of Koch’s tax shelters, if Brawny paper towels are purchased less often due to a very high score on the EIRA, then less revenue will go into Koch’s tax shelter, and less revenue would weaken Koch’s financial standing. In addition, the revenue that was originally going to Koch Industries would now be going to a company that produces less economic inequality because they have a lower score on the EIRA.
However, not all products when purchased are seen as equal for changing the magnitude of the economic inequality equation. For example, high priced computers, cars, televisions, etc., will have more of an impact on a given population than a low-priced item such paperclips or shoelaces. The high-priced products will be loaded into the EIRA’s database first, and then the less expensive items will follow. This way the greatest economic impact can be seen as companies and associated products are successively loaded and rolled out into the database.
So some of the size variables involved can be mitigated by looking at the impact groups of products will have on economic inequality. By looking at these impacts, different groupings of products will be rolled out onto the EIRA sooner than others.
Having enough consumers in the 99% who are committed to using the EIRA will be facilitated with large-scale advertising and an educational campaign. Of course, a substantial number of companies, products, and services will need to be loaded into the EIRA to bring about significant changes. Clearly, the number of people in the 99% greatly outnumbers those in the 1%. Each individual user of the EIRA will create only a small movement of revenue from the 1% back to those members in the 99%. However, the total number of individuals who use the EIRA will, in aggregate, transfer a massive amount of revenue to the 99%. This will boost and equalize the levels of economic status throughout the country and, no doubt, a change of this magnitude will be revolutionary.
DISCUSSION:
Abundant research indicates that the creation of new technology—such as computers—is a fundamental driver of economic inequality. With rapidly advancing new technology, most CEOs want to generate high profits from each sale so they can create even newer technology and even more sales that will further increase their revenue at the expense and wellbeing of the general population. Therefore, most of these companies’ CEOs do not want to self-regulate to reduce the economic inequality they produce. It is clear that the top 1% places a higher value on profit motive than on economic wellbeing for all.
Unless the 1% self-regulates their new-technology profit distribution margins, economic inequality will continue unabated in order to maintain a high-profit for those few at the top. Consequentially, this quest for profits will increase economic inequality to a point that it creates a dystopian future of inequality-based suffering with resultant class warfare as well as an abject failure to reverse climate change with its increasing toll on nature and wildlife, and ultimately, possibly, cause human extinction. To prevent these dire events, we must first stop runaway economic inequality. The EIRA can serve toward stopping the destruction of our planet and of humankind.
A preliminary explanation of how the EIRA’s mathematical algorithm will be developed follows.
Exorbitant CEO pay is one of a multitude of causes creating economic inequality. Public companies within the U.S. are now required by the Securities and Exchange Commission (SEC) to report the ratio of their CEO pay to their median employee pay. It is clear that a CEO pay ratio of 300 to 1 creates much more economic inequality than a ratio of 30 to 1. This ratio information is readily available and will be used as one of many elements in developing the EIRA algorithm.
Other factors—in addition to the CEO pay ratio—impacting economic inequality can be gleaned from public companies, including employees’ salaries; stock compensation; vacation pay; medical benefits; education programs; community outreach and charitable contributions; lobbying to promote economic inequality; and ever-increasing demands for unpaid overtime. These and other factors will be added to the algorithm as they are analyzed for their contribution to creating economic inequality.
Aside from public companies, there are a multitude of other types of companies in the U.S. used to market products and services, including sole proprietorships, partnerships, corporations, limited liability companies (LLCs), and worker cooperatives. Within these companies are a variety of structures and functional aspects attributed to meeting the needs of the company to sell its products and services. Accordingly, there are factors from these other forms of companies that can be synthesized and incorporated into an algorithm pertaining to those corporate structures and functions, then analyzed for their ability to contribute to economic inequality.
As a starting point for the collaborative team to begin their work, worker cooperatives will serve as an example to explain salient points about the algorithm.
There are approximately 40,000 cooperatives of all types within the U.S., many of them being worker cooperatives. In general, these cooperatives promote less economic inequality within their business structure than do other business structures. Once functional, the EIRA will eventually cause other business structures to act more in line with the metrics of their algorithm. The EIRA algorithm will be based upon the factors and their associated weights the collaborative team identifies first in worker cooperatives, and then in other business structures that actually reduce economic inequality.
One way to Influence other companies to come more into line with our algorithm metrics is through a system of rewards. The closer these other businesses can match the operational metrics of our algorithm, the more they will be rewarded with a more favorable score on the EIRA. This will concomitantly increased sales of their products and services by the 99% adding to their bottom line.
No business entities will need to change their core structures, but the EIRA score-incentive will prompt them to operate in a way that is beneficial to their bottom line while creating less economic inequality in the world.
A major challenge for the collaborative team is to have access to information based upon the multitude of other core business structures. For example, public companies have a requirement to report their CEO pay ratio but worker cooperatives have no such requirements. However, many of the cooperatives could be coaxed into giving up this data once they see that by doing so they could significantly increase their standing on the algorithm compared to say a traditional privately held stock company. Here again, having their products or a service ranked more favorably on the EIRA is a good incentive for them to participate by supplying their proprietary information to the collaborative team.
Although there is abundant literature indicating worker cooperatives can significantly reduce economic inequality when compared to most other types of businesses, there are probably other company structures or just aspects of structures capable of reducing economic inequality even more than worker cooperatives. They too will need to be considered by the collaborative team in developing an all-encompassing model.
Worker cooperatives generally have a significantly reduced CEO pay ratios compared to other businesses. This obviously lowers economic inequality, but there may also be other less obvious interactions between factors involved within these worker cooperatives that synergistically lower economic inequality. It will be the function of the collaborative team to analyze these interrelated functions and once identified add them to the algorithm if warranted.
The idea is to create a standard, a data-set by which to compare everything else to. Every company of a certain type can be compared to this one standard. For example, sole proprietorships can currently be more easily compared to other sole proprietorships but without the EIRA cannot be compared accurately to worker cooperatives—it would be like comparing apples to oranges.
To pinpoint some salient advantages to using worker cooperatives as a model upon which to start to formulate the EIRA algorithm, we can look at data concerning worker cooperatives that is cited in Wikipedia (https://en.wikipedia.org/wiki/Worker_cooperative):
- Several factors regarding worker cooperatives are more favorable to distributing revenue to the 99%. This is because a worker cooperative is a cooperative that is owned and self-managed by its workers. This control may mean a firm where every worker-owner participates in decision-making in a democratic fashion, or it may refer to one in which management is elected by every worker-owner who each have one vote.
- According to Virginie Perotin’s research, which looked at two decades worth of international data, worker cooperatives are more productive than conventional businesses. Another study by The Democracy Collaborative found that in the US, worker cooperatives can increase worker incomes by 70-80%. One 1987 study of worker cooperatives in Italy, the UK, and France found “positive” relationships with productivity. It also found that worker cooperatives do not become less productive as they get larger.
- In Mondragon Corporation, the world’s largest worker cooperatives, the pay ratio between the lowest and the highest earner was 1:9 in 2018. The ratio is decided by a democratic vote by the worker-members. By comparison, the ratio between CEO pay to average earner in top 350 US companies was 1:321 in 2018.
- According to an analysis, worker cooperatives in British Columbia, Alberta, and Quebec in the 2000s were almost half as likely as conventional businesses to fail in ten years.]According to an analysis of all businesses in Uruguay between 1997 – 2009, worker cooperatives have a 29% smaller chance of closure than other firms. In Italy, worker owned worker cooperatives that have been created by workers buying a business when it’s facing a closure or put up to sale have a three-year survival rate of 87%, compared to 48% of all Italian businesses. Similar statistics are found globally.
- According to a study drawing on a questionnaire from the population of the Italian province of Trento, worker cooperatives are the only form of enterprise that fosters social trust between employees. A survey conducted in Seoul suggests that in conventional firms, employees become less committed to their job as their work becomes more demanding; however, this was not the case in worker cooperatives. In the US, home health aides in worker cooperatives were significantly more satisfied with their jobs than in other agencies. One 1995 study from the US also indicates that “employees who embrace an increased influence and participation in workplace decisions also reported greater job satisfaction”] Once more, we see that globally worker cooperatives provide both a more humane, productive and universally advantageous environment that benefits the good of the whole.
- In addition, at worker cooperatives there is better mental and physical health, and longer lives, with fewer strokes and heart attacks. Plus, children are less likely to skip school, there is less crime, including less domestic violence, and greater feelings of safety. Higher rates of social participation such as joining clubs and charities, giving blood, and voting were found among those working in worker cooperatives. On a larger scale, perception of a more positive society, having more supportive personal networks, and more trust in the government was found to go hand-in-hand with those employed at worker cooperatives.
In looking at the overall revenue of a company we want to compare how equally this revenue is distributed to its employees and then to how this revenue is distributed in a model algorithm similar to that of worker cooperatives. Each factor comprising the revenue distribution would be assigned a certain weight in the algorithm’s formulation depending upon how much economic inequality it creates. The more economic inequality an individual element creates, the greater that weight will be in the algorithm and the higher the score will be on the EIRA.
Economic inequality is an extremely powerful bio-psycho-social force and has been developed evolutionarily over the course of millions of years at a subconscious level. Our analysis shows changing it requires getting in touch with its root causes which do not involve tangential social value systems. For this reason, only economic inequality parameters are evaluated by the EIRA. This differentiates us substantially from other initiatives and is a main reason the EIRA will be successful once implemented.
Other factors related to social value systems—such as whether or not a company is “green,” or uses slave labor in the manufacturing of their products, or performs animal testing—will not be considered in the algorithm. This differentiates the EIRA significantly from other attempted models which to date have not been successful in changing economic inequality. Clearly economic inequality continues to rise regardless of the use of these social value system concepts being incorporated into a multitude of initiatives.
It is only the distribution of the revenue within a company from the sale of its products or services, and how this distribution impacts its employees that will be considered. The distribution may include the following twenty two factors to be evaluated by the collaborative team regarding worker cooperatives, and how these factors impact the degree of economic inequality within a company:
1) The CEO pay ratio
2) Salaries of individuals within the company and how evenly pay is distributed once the CEO pay is factored out
3) Stock compensation allowed between certain tiers of employees but not others
4) Vacation pay if granted to one tier of employees and not others
5) Medical insurance, if available
6) Bonus pay if granted to one tier of employees and not others
7) Education benefits, if granted to one tier of employees and not others
8) Community outreach and charitable contributions reflecting how the revenue of a company is distributed
9) Promotion of economic inequality outside the company’s boundaries—for example, the percentage of total wealth a company is used to lobby congress or local municipalities that increases economic inequality elsewhere
10) Child care provisions
11) Employee access to discounts for products or services
12) Promotion opportunities for higher pay
13) 401k or similar financial matching plans
14) Social Security benefits
15) Gratuities and tip sharing
16) Full time vs. part time hour availability
17) Financial assistance and loans to employees
18) Personal legal assistance for employees
19) Housing assistance directly or with a stipend
20) Debt relief for company vs. employee benefits
21) Work at home opportunities
22) Company’s total revenue to employee benefit ratio
What weight would each of these factors—and additional factors not mentioned here—have upon the algorithm and, hence, the EIRA scores? There are dynamic relationships between all of these factors that come into play and impact economic inequality. Overtime, the influence of all these factors on the ERIA’s algorithm will change as new information is gathered and either added or deleted to the equations.
To maintain the integrity of the EIRA, factors involved in the formulation of the algorithm will be made public, but the weight given to each aspect will be strictly confidential. This way an unscrupulous individual or company will not be able to corrupt the system to their advantage.
As mentioned earlier, an EIRA score of 100 will be given to a company and hence its products or services in a certain instance. This score is reserved for companies unwilling to participate with our collaborative team and hence the 99%. Products and services with a score of 100 are to be completely avoided by the user of the EIRA. This is a hard stop. If however a company does eventually decide to make their information available to the collaborative team, then their score will be adjusted to include them accordingly.
For example, the collaborative team may need to know what percentage of a company’s staff is eligible for education benefits. This is the company’s proprietary information, and unless they are a public company, the team may not have access to this information. A score of 100 means the 99% is to boycott them completely and they will not have any sales within our system. This will be used as leverage to coax that company into releasing this information. Once this has been done they will no longer be boycotted and only then will their score will be reevaluated and released.
The levels of economic inequality within the USA are continuing to climb and past initiatives to mitigate them have not been successful. The EIRA’s algorithm addresses this by getting at the very core of the problem which is too much wealth in the hands of too few people. This ability to take corrective action on a personal level can now be put directly into the hands of the 99%. Never before has this level of personal control exist where so many individuals can set their own destiny without political or bureaucratic intervention. This empowerment is extremely motivational and will in turn drive the success of the overall project.
Based upon the research literature first presented towards the top of this document, with negative and positive directional changes, it is easy to understand the very bleak assessment of economic inequality. This listing clearly shows the overwhelming impact economic inequality has upon our society. Economic inequality is not only correlated to these social ills but in most instances is causative. Here we can recognize the real offender causing so many problems in the world is economic inequality. By stopping or even reversing economic inequality with the EIRA we have the newfound freedom to not only reduce these problems but to also create a more beautiful world.
CONCLUSION:
We now have a mechanism whereby when a consumer purchases according to the EIRA’s recommendations, their choice completely bypasses the usual political, tax, and judicial gridlock experienced in today’s world. No one has to vote anybody into office, change any laws, or rewrite any existing tax structures. If a person uses the EIRA to support the 99%, this places the decision power directly into their hands at the time of purchase—it’s as simple as that.
Our current economic system is broken and does not meet the needs of the 99%. We want to repair it by regulating it in a practical and common-sense manner making it more responsive to all our needs; this will reduce the balance of the economic inequality throughout the nation. The EIRA provides a way of creating more favorable economic outcomes aligned with society’s best interests.
Overall, the EIRA will work as a regulator of the amount of economic inequality our current capitalistic system produces. The 99% end users will be arbiters of how much economic inequality is allowed to exist in the marketplace by using the EIRA.
By shifting large amounts of profits from companies favoring the upper 1% back to companies reducing economic adversity of the 99%, the EIRA will provide a tool for the 99% to move the levers of power economically and, in turn, politically in their favor. The EIRA is a catalyst for change, and the shift it can produce will allow us to reclaim economic control of people’s lives, which is where that control rightfully belongs.
Within our country there are many individuals and organizations working in their own unique ways to stop the toxic effects of economic inequality. The ERIA provides the means to free ourselves from the bondage and tyranny of economic inequality. From the climate change activists to those fighting against poverty and homelessness, and to every person railing against injustice, we believe everyone can support the EIRA as the one rallying tool to fight for what we all collectively believe in. The EIRA is the one bright spark sufficient to unite us all and ignite an economic revolution bringing our diverse groups together for what we know is fair and right.
In sum, since the first days of civilization, the 1% has made the 99% subservient to its will through financial might. With proper development and large-scale use, the EIRA may provide our best opportunity to free ourselves from this bondage. Now, with the power to alter the course of inequality, we are at the threshold of an era that favors the equality and will of the 99%.
Help us to build a greater voice in our own future. With the EIRA as the catalyst, we can protect our humanity by placing social good above profits. Our lives and the direction future technology takes depend upon it.
LET US KNOW YOUR THOUGHTS AND FEELINGS ABOUT IMPLEMENTING THIS SPECIAL PROJECT WITH YOUR FORUM POSTS.
