Methodology
16 articles
Running Claude Code skills, for applied economists
A setup guide for the TETS Claude Code skills introduced in the tool series (papers-md-generator, replication-package-analytics, attribution-audit-network).
Census API in Python: Pulling ACS Data With Validation Checks
A Python workflow for pulling ACS data from the Census Bureau API, with the validation checks that catch bad data before it reaches the analysis.
How to Validate GTFS Feeds Before Routing Breaks
A Python workflow for catching the transit data problems that structural checks miss. Six validation layers from download fallbacks to multi-agency sanity checks.
How to Build a Classifier When 94% Accuracy Means Nothing
A scikit-learn workflow for imbalanced classification, where 94% accuracy can mean nothing, and the evaluation metrics that actually matter for rare classes.
How to Interpret a Classifier with SHAP Values
A Python workflow using SHAP values to explain what drives a fraud classifier's predictions, and what SHAP importance does and does not actually measure.
Spatial Analysis with GeoPandas: From Joins to Autocorrelation
A spatial analysis workflow that starts with point-to-polygon joins and builds toward spatial weights, autocorrelation testing, and LISA cluster detection…
The Data We Forgot We Had: A Tagging System
Tag datasets by the questions they can answer, not just what they contain. A question-first system makes dormant research data discoverable when new questions…
Measuring Crime Where People Actually Live
Swapping county averages for neighborhood-level data reveals a 22-fold range in crime rates that the coarser geography completely hides.
Claude Charts Not Working? Fix AI Research Graphics
When Claude and ChatGPT get research figures wrong, structured Antigravity prompts produce the publication-quality graphics we need.
Scaling Up: From 7 Counties to Statewide
Expanding from 2,000 to 9,039 census tracts reveals what scales linearly (Census API, KD-trees) and what requires adaptation (transit aggregation, memory…
Building a Better Metric: The Residualized Accessibility Index
Income, density, and car ownership explain 81% of county-level food-security vulnerability; residualization separates the structural signal from the rest.
Why County Rankings Confound Policy with Context
Merced County's vulnerability index is 2.3 times higher than San Francisco's. But before drawing policy conclusions, we need to understand what that number…
Transit Travel Time Matrix in Python (Free, No API Keys)
Compute transit travel-time matrices in Python with r5py, using free GTFS and OpenStreetMap data. No API keys, fully worked example.
The Retail Density Paradox: Why More Stores Mean Worse Data
A verification method for EBT acceptance across the roughly 28,800 California stores in the USDA list, where more retailers means messier, not better, data.
From Methods Paragraph to Working Pipeline with AI
A well-written methodology section is almost executable code, and AI assistants have narrowed the gap between describing a procedure and implementing it.
How Neighborhood Intersections Predict Food Insecurity
A validated neighborhood food-security index showing why single demographic factors miss the mark, and how intersecting conditions predict vulnerability better.'t tell the full story.