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higher-ed-fred-analysis

使用FRED(联邦储备经济数据)为高等教育利益相关者创建复杂的经济数据分析和可视化。当用户请求以下内容时,请使用此技能:(1) 学生贷款债务、按教育水平划分的失业率或收入数据的分析,(2) 高等教育经济指标的仪表板或视觉展示,(3) 关于高等教育投资回报率或经济价值的叙述性报告,(4) 为机构利益相关者(如理事、招生管理部门、财务援助办公室)提供的数据驱动型沟通材料,或(5) 将FRED API数据集成到交互式可视化中。

person作者: jakexiaohubgithub

Higher Education FRED Analysis

Create data-driven analyses and visualizations of higher education economic indicators using the Federal Reserve Economic Data (FRED) API.

Overview

This skill enables creation of professional, evidence-based economic analyses for higher education institutions. It combines FRED API data access, sophisticated visual design, and stakeholder-focused narrative frameworks to produce compelling dashboards and reports about student debt, employment outcomes, and earnings differentials by educational attainment.

Core Workflow

1. Determine Analysis Type

Interactive Dashboard: Use when stakeholders need real-time, explorable data visualizations Narrative Report: Use when stakeholders need written analysis with supporting data Combined Approach: Most effective for comprehensive stakeholder communications

2. Identify Relevant FRED Series

Read references/fred-series-guide.md for complete catalog. Common series:

  • Student Debt: SLOAS (Student Loans Owned and Securitized)
  • Unemployment by Education: LNS14027662 (Bachelor's+), LNS14027660 (HS), LNS14027659 (No HS)
  • Earnings by Education: LEU0252918500A (Bachelor's+), LEU0252917300A (HS only)

3. Fetch and Process Data

Use scripts/fetch_fred_data.py for consistent data retrieval with error handling:

python scripts/fetch_fred_data.py --series SLOAS LNS14027662 --api-key YOUR_KEY

Or implement in-artifact fetching for interactive dashboards (see template).

4. Create Visualizations

For interactive dashboards:

  • Copy and customize assets/dashboard-template.html
  • Implements React + Chart.js with FRED API integration
  • Includes CORS proxy pattern for client-side POCs

For narrative reports:

  • Follow structure in references/narrative-templates.md
  • Integrate visualizations as needed

Apply consistent design system from references/design-system.md:

  • Dark sophisticated theme (primary: #1a2332, accent: #d4af37)
  • Typography: Playfair Display (headers), IBM Plex Mono (data), Inter (body)
  • Chart styling configurations provided

5. Craft Stakeholder-Appropriate Narratives

Read references/stakeholder-personas.md for audience-specific strategies. Match tone and depth to audience:

  • Trustees/Board: Executive summary focus, strategic implications
  • Financial Aid: Debt contextualization, ROI analysis
  • Enrollment Management: Student recruitment value propositions
  • Faculty/Academic Affairs: Discipline-specific outcomes when possible

Key Principles

Evidence-Based: Ground all claims in FRED data with proper attribution and source citations Context-Rich: Never present debt/cost data without employment/earnings context - the ROI story matters Balanced: Acknowledge limitations (correlation ≠ causation, individual variation, field differences) Actionable: Conclude with strategic implications for institutional decision-making

Common Analysis Patterns

ROI Analysis: Combine debt (SLOAS), unemployment (LNS series), and earnings (LEU series) data to show net value Trend Analysis: Use 5-10 year windows for meaningful trend identification; avoid cherry-picking Comparative Analysis: Always show education level differentials, not absolute values alone Crisis Impact: Layer recession periods (2008, 2020) to highlight higher ed's stabilizing effect

Technical Notes

FRED API Access

  • Requires free registration at research.stlouisfed.org
  • Rate limits: 120 requests per minute
  • Returns JSON observations with dates and values
  • Handle "." values (missing data) gracefully

Implementation Approaches

  • Client-side (POC): Use CORS proxy (corsproxy.io) - note security limitations
  • Production: Backend API calls recommended for key management and caching
  • Hybrid: Client-side with pre-fetched data embedded in artifact

Data Update Frequencies

  • Unemployment: Monthly
  • Earnings: Annual
  • Student Debt: Quarterly
  • Plan analysis refresh cycles accordingly

Important Considerations

  • All monetary values are nominal; consider CPI adjustments for multi-decade comparisons
  • Seasonal adjustments vary by series; check FRED metadata
  • Education categories may not align perfectly across different BLS surveys

Bundled Resources

Scripts

  • scripts/fetch_fred_data.py - Python utility for fetching FRED data with error handling and caching

References

  • references/fred-series-guide.md - Comprehensive catalog of higher ed relevant FRED series
  • references/design-system.md - Visual design specifications and Chart.js configurations
  • references/narrative-templates.md - Report structures and writing guidelines
  • references/stakeholder-personas.md - Audience-specific communication strategies

Assets

  • assets/dashboard-template.html - Complete React dashboard boilerplate with FRED API integration