DANL/ECON 399 · Fall 2026
Your semester map
Use Monday research studios to make defensible choices, then turn those choices into reproducible evidence in Wednesday R labs.
Note
The course meets Mondays and Wednesdays, 12:30–1:45 PM, in South 227B (the instructor’s office). The sequence may adapt as the individualized project develops. The official calendar lists Labor Day on September 7, Fall Break on October 10–13, Thanksgiving Break on November 25–28, the last day of classes on December 7, and final examinations on December 9–15. View the official academic calendar.
Week 01 · Aug 24–26Frame the study
Mon · Aug 24 Course launch and environmental-policy question landscape.Wed · Aug 26 Reproducible R workflow and candidate-data inventory.
Available now · Open week →
Week 02 · Aug 31–Sep 2Literature and evidence
Mon · Aug 31 Policy institutions, stakeholders, mechanisms, and debates.Wed · Sep 2 Literature search, evidence matrix, and research notes.
Coming soon
Week 03 · Sep 7–9Research design
Mon · Sep 7 Labor Day — no class.Wed · Sep 9 Outcome, comparison, mechanism, and feasible scope.
Coming soon
Week 04 · Sep 14–16Units and identification
Mon · Sep 14 Unit of analysis; descriptive, predictive, and causal claims.Wed · Sep 16 Data ethics, provenance, documentation, and project structure.
Coming soon
Week 05 · Sep 21–23Acquire environmental data
Mon · Sep 21 Choose one anchor source and only necessary context layers.Wed · Sep 23 Import files and APIs in R; record queries and licenses.
Coming soon
Week 06 · Sep 28–30Transform in R
Mon · Sep 28 Tidy structure, units, temporal alignment, and missingness.Wed · Sep 30 Clean, reshape, join, validate, and build the data audit.
Coming soon
Week 07 · Oct 5–7Visual evidence
Mon · Oct 5 Question → task → encoding; perception, color, and accessibility.Wed · Oct 7 EDA lab: distributions, relationships, time, and uncertainty.
Coming soon
Week 08 · Oct 12–14Break and spatial restart
Mon · Oct 12 Fall Break — no class.Wed · Oct 14 Spatial foundations and Research Kick-off Report studio.
Coming soon
Week 09 · Oct 19–21Kick-off and mapping
Mon · Oct 19 Feasibility clinic and reproducible data freeze.Tue · Oct 20 Research Kick-off Report due.Wed · Oct 21 CRS, spatial joins, normalization, and honest choropleths.
Coming soon
Week 10 · Oct 26–28Spatial analysis
Mon · Oct 26 Scale, distance, aggregation, and spatial dependence.Wed · Oct 28 Interactive maps with
Coming soon
sf; optional Google Maps publishing lab.
Week 11 · Nov 2–4Machine-learning design
Mon · Nov 2 Target, observation, prediction horizon, metric, and baseline.Wed · Nov 4 Preprocessing, leakage checks, and spatial/temporal resampling.
Coming soon
Week 12 · Nov 9–11Fit and compare
Mon · Nov 9 Select a question-appropriate regularized or tree-based extension.Wed · Nov 11 Fit the baseline and extension in one reproducible workflow.
Coming soon
Week 13 · Nov 16–18Validate and interpret
Mon · Nov 16 Performance, calibration, uncertainty, and policy-weighted errors.Wed · Nov 18 Importance, partial dependence, residual maps, and progress studio.
Coming soon
Week 14 · Nov 23–25Policy synthesis
Mon · Nov 23 Institutions, trade-offs, causal limits, and policy relevance.Wed · Nov 25 Thanksgiving Break — no class.
Coming soon
Week 15 · Nov 30–Dec 2Build the integrated argument
Mon · Nov 30 Connect literature, design, results, limitations, and implications.Wed · Dec 2 Figure suite, paper workshop, and final-exam synthesis.
Coming soon
Week 16 · Dec 7Paper and final review
Mon · Dec 7 Last class: paper studio, reproducibility audit, and course synthesis.Wed · Dec 9 Final-examination period begins; no regular class.
Coming soon
Assessment sequence
| Milestone | Purpose | Timing |
|---|---|---|
| Research proposal | Establish the question, policy context, data, and analysis plan | Set with the instructor |
| Research Kick-off Report | Demonstrate feasibility with documented data, a data audit, initial visual evidence, and an analysis/validation plan | Tuesday, October 20 |
| Progress report | Document implementation, early evidence, obstacles, and next steps | Set with the instructor |
| Final comprehensive exam | Synthesize and apply the research and data-science methods developed in the course | During Dec 9–15; date/time TBD |
| Research paper | Integrate research design, analysis, writing, findings, and policy context | Set with the instructor |
There is no midterm exam. Remaining due dates and grade weights will be established with the instructor and communicated through Brightspace.