The article argues that the Federal Reserve's recent rate hike decision, while justifiable on inflation grounds, highlights a critical lack of an underlying, transparent policy framework. The core problem is that the Fed's decisions appear discretionary, leading to market uncertainty because the committee's judgment, rather than clear data, dictates policy shifts. The author proposes that the Fed adopt a formal monetary policy rule—an algebraic formula linking the target rate to indicators like inflation and unemployment—to replace subjective guidance. Implementing such a rule would provide market predictability, enhance transparency, and shield the Fed from political attacks by making deviations from the standard easily quantifiable.
How can we improve workforce outcomes for community college students?
English Summary
Community colleges are essential pathways to well-paying jobs for students not pursuing bachelor's degrees, yet most students fail to complete credentials with meaningful labor market value. Research comparing high-performing colleges with underperforming ones identified five key success factors: aligning programs with local labor demands, deepening employer partnerships, offering diverse work-based learning experiences, integrating career readiness skills across curricula, and providing robust student support with low-caseload advising. Policy recommendations include outcomes-based state funding mechanisms, technical assistance for employer engagement, adequately resourced academic advising, and expanded federal workforce funding through initiatives like Workforce Pell grants. As AI reshapes labor markets, community colleges and policymakers must prioritize rigorous evaluation of these practices and emerging models, particularly for noncredit workforce programs and alternative financing like income-share agreements.
中文摘要
社區大學是未攻讀學士學位學生進入高薪工作的重要途徑，然而大多數學生未能完成具有實質勞動市場價值的證書課程。對比高績效與低績效社區大學的研究確認了五項關鍵成功因素：使課程與當地勞動力需求相一致、加深與雇主的夥伴關係、提供多樣化的工作基礎學習體驗、在課程中融入職業準備技能，以及透過低案例負擔顧問提供強有力的學生支持。政策建議包括基於成果的州級資金機制、雇主參與的技術協助、充分配備資源的學術顧問，以及通過《勞動力佩爾助學金》等計畫擴大聯邦勞動力資金。隨著人工智慧重塑勞動力市場，社區大學和政策制定者必須優先對這些實踐和新興模式進行嚴格評估，特別是針對非學分勞動力課程和所得分成協議等替代融資方式。
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