Overview
People's Economy Hub bridges the gap between headline economic indicators and lived household experience. GDP and stock indices dominate the news cycle, but they rarely answer the question families actually ask: “Am I better off than last year?” PEH answers that question with three clear metrics sourced directly from government data.
- Three household metrics: Purchasing power, essentials cost pressure, and financial cushion — each grounded in federal survey data
- Plain-language explainers: Educational articles on GDP vs. wellbeing, mean vs. median, inflation baskets, and more
- Transparent methodology: Every metric links to its source data, calculation formula, update frequency, and known limitations
- Zero-cost operation: Static export on GitHub Pages with free CI/CD and free government APIs
Problem
Mainstream economic reporting focuses on metrics that don't reflect household reality. The disconnect — highlighted by economists like Joseph Stiglitz — erodes public trust and leaves families without actionable information.
Wrong metrics
- GDP measures total output, not distribution
- Stock indices reflect investor wealth, not wages
- Headline inflation hides essential-goods spikes
Inaccessible data
- BLS and Fed data buried in dense reports
- Economic jargon excludes non-specialists
- No single source for household-level picture
Partisan framing
- Economic data weaponized for political narratives
- Cherry-picked timeframes distort the picture
- No neutral, methodology-transparent alternative
Solution
Build a single-page dashboard that distills federal data into three metrics a non-economist can grasp in 90 seconds — non-partisan, transparent, mobile-first, and free to operate at any scale.
Design principles
- Household-centered: Every metric answers “how does this affect my family?”
- Non-partisan: Data-driven, no editorial spin; neutral color palette avoids good/bad implications
- Transparent: Source data, formulas, update schedules, and limitations are all public
- Accessible: WCAG AA compliance, plain language, 90-second comprehension target
- Zero cost: Static export + free APIs + free hosting = sustainable indefinitely
The three metrics
Each metric is chosen to reflect a different dimension of household economic health — income, costs, and resilience — using federal data that updates on a known schedule.
Purchasing power of the median paycheck
Year-over-year change in real (inflation-adjusted) median wages for prime-age workers. Uses BLS Current Population Survey data (quarterly). Focuses on the median — not the mean — so high earners don't skew the picture.
Essentials cost pressure
Year-over-year inflation on housing, food, energy, transportation, and healthcare — weighted by typical household spending. Uses CPI sub-indexes (monthly). Reveals the gap between headline CPI and what families actually feel at checkout.
Household financial cushion
Share of U.S. households that can cover a $400 emergency expense without borrowing. Uses the Federal Reserve SHED survey (annual). A widely-cited resilience indicator that captures financial fragility beyond income alone.
Data pipeline
An automated pipeline fetches, validates, and publishes federal economic data — with fallback values, schema enforcement, and failure notifications baked in.
| Pipeline step | Details |
|---|---|
| 1. Scheduled fetch | GitHub Actions cron triggers BLS and Federal Reserve API calls on monthly/quarterly cadence |
| 2. Schema validation | Zod schemas enforce data types, ranges, and required fields; malformed responses are rejected |
| 3. Transformation | Raw API data is normalized into metric JSON files with historical time series and metadata |
| 4. Fallback handling | If an API is delayed or returns errors, manually curated fallback values are used with a visible freshness warning |
| 5. Auto-commit & deploy | Changed data files are committed to main, triggering a rebuild and deploy to GitHub Pages |
| 6. Failure notification | On error, a GitHub Issue is created automatically with diagnostic details for triage |
Data sources
- BLS: Current Population Survey (wages), CPI sub-indexes (inflation)
- Federal Reserve: SHED survey (financial cushion)
- FRED: Supplemental economic indicators and time series
Data integrity
- Git-versioned: Every data change is committed with full audit trail
- Zod validated: Runtime schema enforcement catches type and range errors
- Freshness tracking: Dashboard shows last-updated timestamps per metric
Infrastructure
Designed to cost nothing to operate at scale — static export on GitHub Pages with Terraform-managed repository configuration and GitHub Actions CI/CD.
Stack
- GitHub Pages: Free static hosting for public repositories
- GitHub Actions: CI (lint, typecheck, test, build, Lighthouse) + CD (deploy) + scheduled data updates
- Terraform: Repository config, branch protection, status checks, secrets, and Pages environment — all in code
- Next.js static export: No server runtime; pure HTML/CSS/JS output
CI/CD workflows
- CI: Lint, type check, test, build, accessibility audit, Lighthouse
- Deploy: Build and push to GitHub Pages on merge to main
- Data update: Scheduled cron + manual trigger for API fetches
- Terraform: Plan/apply on infrastructure changes
- Lighthouse: Performance and accessibility gates (90+ targets)
Accessibility
A public-good platform must be usable by everyone. Accessibility is not an afterthought — it's a first-class design constraint enforced by automated testing in CI.
WCAG AA compliance
- 4.5:1 minimum contrast ratios throughout
- ARIA labels on all interactive and chart elements
- Full keyboard navigation with visible focus indicators
- Skip-to-content links and semantic landmarks
- Screen reader-friendly chart descriptions
Inclusive design choices
- Neutral blue chart palette avoids red/green color-blind issues
- Plain language throughout — no economic jargon without explanation
- Mobile-first responsive layout (320px–1440px)
- Axe-core accessibility testing in CI pipeline
- Lighthouse accessibility score target: 90+
Outcomes
Delivered capabilities
- Three core metrics with interactive Chart.js visualizations
- Automated data pipeline with Zod validation and fallbacks
- Transparent methodology page with sources, formulas, and limitations
- Five educational articles explaining economic concepts in plain language
- Terraform-managed GitHub repository and Pages deployment
- Full CI/CD with lint, typecheck, test, build, and Lighthouse gates
- WCAG AA accessibility with axe-core testing in CI
- Curated resources page with external calculators and data sources
Building data-driven public tools?
People's Economy Hub demonstrates automated data pipelines, zero-cost infrastructure, accessibility-first design, and the ability to make complex data approachable. If you're tackling similar challenges — or need someone who can ship the full stack — let's talk.