From Elite Markets to Equitable Systems: How Gen Z’s Equity Mindset and AI-Native Tools Can Reshape Who Business Serves

Gen Z Intervention Model for Equitable Market Systems (2019–2024) This dataset supports the research note \"Gen Z Intervention Model for Equitable Market Systems,\" providing a time-series analysis (N=6 years) linking indicators of market exclusion with sociographic and technological variables that drive the proposed intervention. Key Research Goal To empirically model the feasibility of Gen Z utilizing deflationary technology (AI) to create equitable market opportunities, specifically in the context of rising socioeconomic inequality and housing affordability crises. Time Period and Scope Time Period: 2019 to 2024 (Latest available data). Geographic Scope: United States (National Aggregate Data). Units of Observation: Yearly aggregate values for key economic, social, and technological indicators. Critical Synthetic Variable Defined A primary feature of this dataset is the **Rent_vs_Income_Gap_Pct**, a synthetic variable used to quantify the financial squeeze on the median renter. It is calculated as the cumulative percentage point difference between the growth in housing costs and the growth in real wages over the period of accelerated decline (Early 2020 to Early 2024). Calculation Components (2020-2024): Cumulative Rent Growth (JCHS): 26.0% Cumulative Real Wage Growth (BLS): 19.5% Resulting Gap (2024): -6.5 (Rents outpaced real wages by 6.5 percentage points) Primary Data Sources The dataset synthesizes data from highly authoritative sources, ensuring maximum credibility: Bureau of Labor Statistics (BLS) Harvard Joint Center for Housing Studies (JCHS) Federal Reserve Bank of Atlanta (ATLHOPI) Federal Reserve Economic Data (FRED) Deloitte Global Gen Z and Millennial Survey (2024) Stanford University AI Index Report (2024)