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I've developed an economic model to resolve the economic crisis automation is creating. It needs funding to strength test and publish. I'm an economist and entrepreneur that became disabled, falling through the cracks of a fractured system. While bed ridden, I looked back across the history of automation, read everything I could. I analyzed all contributing factors along with the pros and cons of every policy decision. I discovered the most optimal way to not only protect against real wage decline, not just a living wage, but to create a social wage. To increase the labor share of income and stabilize it there, without causing price inflation.
The goal of this project is to protect against real wage decline in the age of AI. Paving the way to a post labor economy. I'm researching a model to replace the corporate flat tax with this: Tax Rate = 2×Profit÷Labor Costs
The Structural Problem With the Economy
Accelerating automation and AI have decoupled corporate productivity from worker compensation. Traditional interventions have fallen short because they are static: minimum wages don't rise with productivity, while concepts like the UBI are rapidly captured by firms using algorithmic price theory to absorb consumer surplus. Furthermore, classic "robot taxes" fail because defining what constitutes a "robot" creates an intractable accounting and regulatory infeasibility.
The Mechanism
Instead of taxing technology, this framework replaces the corporate tax rates with a tax rate based on the firm's internal capital-labor distribution. Meaning, when an automated firm generates high net profits relative to its labor expenditures, its tax rate increases proportionally. Businesses will choose to optimize their ratio of profit to labor spending to generate maximum post-tax profits. At a ratio above 1:4 (profit:labor) their post-tax profits would decline. Meaning, highly automated companies will have to choose between raising wages, expanding payroll, reducing work weeks, offering other compensation, or lowering consumer prices to reduce taxable margins.
Milestones to success:
Milestone 1: I'll run econometric simulations against SEC/Compustat data across all industries to evaluate capital-expenditure resilience and revenue neutrality.
Milestone 2: I'll define mathematical guardrails: deciding on the types of eligible compensation (excluding executive bonus gaming) and structuring border-adjustment tariffs based on importer profit-to-labor ratios to neutralize capital flight.
Milestone 3: I'll calibrate the market-driven equilibrium dynamics. Determine how capital-intensive firms will respond with consumer price reductions and B2B labor demand.
Milestone 4: Publish an open-access working paper, release interactive simulation code on GitHub, and host a public calculator for businesses, economists, and fiscal policy analyst.
Total Request: $45,000
$32,000 — Principal Researcher Living Stipend: Covers 12 months of subsistence runway, allowing full-time dedicated research and model construction while accommodating physical disability needs.
$5,500 — Financial Datasets & Analytical Tools: Licenses for historical corporate reporting databases (Compustat/WRDS access) and statistical computing environments.
$4,500 — Quantitative Econometric Peer Review: Compensation for independent economists and tax analysts to critique model assumptions, edge cases, and econometric proofs.
$3,000 — Open-Access Dissemination: Web hosting for interactive modeling calculators, dataset repositories, and open-access paper distribution.
Lead Researcher (Andrew Dundas Laurent) I’m an independent economist and entrepreneur. I've ‘touched grass’ with 15 years in the service industry, hold a B.S. in Economics, founded and operated a restaurant delivery service in the dawn of the Great Recession, helped train Google search results, and faced a crippling disability giving me abundant time to independently study. Across 14 years of disability, I read the historical works of economists like Adam Smith, John Keynes, Marx, Mises, as well as every modern book on the economics of automation. I developed the initial "Labor Floor" mathematical framework in 2015 and recently built an open-access profit-labor optimization calculator. With a depth of life experiences, a foundation in economics, excellent comprehension, and have significantly rebounded from disability, I am prepared to fully develop this project and publicly discuss the concept.
Critics will argue that highly automated or capital-intensive industries (e.g., automated manufacturing, data centers) face disproportionately high tax rates due to low direct headcount.
I've considered this. Rather than creating carve-outs, subsidies, or subjective depreciation exemptions, which invite higher regulatory costs and lobbying loopholes, the formula should apply universally.
Currently, capital-intensive firms reinvest heavily during setup and expansion, naturally recording low or negative net profits, shielding them from high tax liabilities until capital investments mature. When their profits come, they have two pathways to reach their post-tax profit-maximizing equilibrium:
Consumer Price Reductions: Lowering unit margins directly lowers the profit-to-labor ratio, cutting the firm's tax rate while delivering the deflationary gains of automation directly to consumers.
Supply-Chain Labor Demand: Sourcing intermediate goods, logistics, maintenance, and support services from labor-intensive vendors to absorb operational expenses and optimize after-tax returns, circulating capital into the human labor market and giving relief to labor intensive businesses.
Another concern I've considered is highly profitable firms might inflate executive bonuses or c-suite stock compensation to artificially inflate the "Labor" denominator and lower their tax rate without raising frontline wages.
During the policy research phase I will define "Eligible Labor Compensation" using statutory caps—such as tying qualifying payroll strictly to non-exempt workers or capping eligible individual payroll.
My last concern, the only true concern, is that people won't understand the need. Years ago, I faced resistance when discussing it because people assume the economy will always naturally produce more jobs. But we still have the New Deal policies that were designed to address the economic problems automation created in the 1920s, when real wages declined. People today struggle to understand how those policies still help mitigate the negative effects of automation.
I have realized that those policies aren't helping enough anymore. They treated the symptoms rather than the condition. The Social Wage I'm developing takes a more direct and efficient approach. Not to replace those policies, but make them less necessary.
While my project wasn't well received by the average person 10 years ago, the climate around the concern for automation has grown. I'm now getting good feedback from people of a wide range of political preferences. AI companies are expressing concern about the economy because of their technology. With sufficient funding and adoption by more economists, our attempts at public education for this project is likely to gain traction similar to the UBI.
No institutional funding, grants, or active donations have been received for this project to date. I've spent a small amount of saving I had to develope the calculator.