The USC MPP equips analysts to translate p-values into public good. Learners build Difference-in-Differences (DiD) estimators in Stata, run Causal Forests (CF) on SNAP uptake, and prototype civic apps in Figma before A/B (or A|B) trials. A Policy Communication (Pol-Comms) bootcamp condenses 40-page BCA (Benefit-Cost Analysis) into TikTok explainers, while a Brussels immersion dissects GDPR/AI Act compliance. Graduates leave fluent in both PDFs and Python notebooks.
Sequential-analysis tool for pilot cash-transfer RCTs
Dashboard visualizing eviction-moratorium impacts by zip code
Shiny app estimating VSL (Value of Statistical Life) sensitivity
Sentiment scraping of public comments on EPA rules
NLP topic model of state climate bills 2000-2025
Open-data portal scoring broadband-equity gaps
Ethical AI checklist for predictive policing models
Dynamic microsimulation of child-care tax credits
VR negotiation sim on trans-boundary water treaties
Carbon tax incidence heat-map across income quintiles
Synthetic control tool for stadium subsidy evaluation
Policy brief on CBAM (Carbon Border Adjustment Mechanism)
Crowdsourcing platform rating privacy statements
Adaptive trial design for traffic-calming interventions
Equity lens dashboard benchmarking 311 response time
Design, test and tell policies that outperform the status quo.
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