Identify

Key Data Features

• EDM data: 2021-2024+, high-frequency (event-level)
• Land Registry: universe of transactions
• Zoopla: rental listings
• Met Office: daily rainfall at LSOA level
• River networks: PostGIS topology
• Treatment radii: 250m, 500m, 1000m, 2000m, 5000m, 10000m

Workflow

Step 1: Context Gathering

1. Read existing manuscript sections in docs/overleaf/ for how strategies are currently described
2. Read relevant analysis scripts in scripts/R/09_analysis/
3. Read scripts/R/utils/spill_aggregation_utils.R for treatment construction
4. Check docs/overleaf/refs.bib for methodological references

Step 2: Strategy Development

For a new or revised strategy, produce:

1. Strategy memo — Design choice, estimand (ATT/ATE/LATE), key assumptions, comparison group
2. Estimating equation — LaTeX-formatted with clear variable definitions
3. Pseudo-code — Implementation sketch (what the R code will do)
4. Robustness plan — Ordered list with rationale:
   • Radius sensitivity (250m → 10km)
   • Time period variation (prior period vs full period)
   • Alternative treatment measures (count vs hours vs binary)
   • Subsample analysis (sales vs rentals, urban vs rural)
5. Falsification tests — What SHOULD NOT show effects and why
6. Referee objection anticipation — Top 5 objections with pre-emptive responses

Step 3: Strategy Review

If reviewing an existing strategy:

Phase 1: Claim Identification

• What is the claimed design?
• What is the estimand?
• What is the treatment / comparison?

Phase 2: Core Design Validity

• Are identifying assumptions stated and defensible?
• Are the biggest threats acknowledged?
• Does the specification match the stated design?

Phase 3: Robustness Assessment

• Does the robustness plan address the right concerns?
• Are falsification tests well-chosen?
• Is there radius sensitivity analysis?

Step 4: Present Results

# Identification Strategy: [Approach]
**Date:** YYYY-MM-DD
**Design:** [Hedonic / Repeat Sales / Long Diff / DiD / IV / etc.]
**Estimand:** [ATT / ATE / LATE]

## Strategy Summary
[2-3 sentence description]

## Estimating Equation
$$\log(p_{it}) = \alpha + \beta \cdot \text{SpillMetric}_{it} + \gamma X_{it} + \mu_i + \delta_t + \varepsilon_{it}$$

## Key Assumptions
1. [Assumption 1] — [defense]
2. [Assumption 2] — [defense]

## Assessment: [SOUND / CONCERNS / CRITICAL ISSUES]

## Robustness Plan (ordered)
1. [Most important check]
2. [Second check]
...

## Falsification Tests
1. [Test 1] — [expected null and why]

## Anticipated Referee Objections
1. [Objection] — [Response]

## Next Steps
- [ ] Implement main specification
- [ ] Run falsification tests
- [ ] Generate pre-trend evidence

Save to output/log/strategy_memo_[approach].md.

Principles

• Catch problems before coding. A flawed strategy caught now saves weeks of wasted analysis.
• Multiple strategies are strength. This paper uses 6+ approaches — consistency across them is the key argument.
• Cross-reference approaches. Each strategy should address threats the others cannot.
• The user decides. Present trade-offs, don't make choices unilaterally.
• Strategy memo is the contract. Once approved, analysis scripts implement it faithfully.