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identify

Design or review how a sewage spill study estimates effects on house prices. Produce a strategy memo covering the target effect, assumptions, estimating equation, implementation outline, robustness checks, falsification tests, and anticipated referee objections.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Design or review identification strategy for the sewage-house-prices project. Produces strategy memos with estimand, assumptions, pseudo-code, robustness plan, falsification tests, and referee objection anticipation. This skill should be used when asked to "design the strategy", "identify the effect", "write a strategy memo", or "think through identification".

설치 방법 보기

이럴 때 유용합니다

  • Planning how to estimate sewage spill effects on house prices
  • Reviewing assumptions behind an existing analysis
  • Designing robustness checks and falsification tests
  • Preparing responses to likely referee objections

포함된 파일(1)

  • SKILL.md5.0 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Identification Strategy

Design or review an identification strategy for the sewage-house-prices project.

Input: $ARGUMENTS — a research question, approach name (e.g. "hedonic", "dry spills"), or "review existing" to audit all current strategies.


Project-Specific Context

Existing Strategies

  1. Hedonic — Cross-sectional: log(price) ~ spill_metrics + controls | lsoa + year_quarter. Assumption: spill exposure is conditionally exogenous given LSOA FE.
  2. Repeat sales — Within-property: Δlog(price) ~ Δspill_metrics | house_id. Eliminates time-invariant unobservables.
  3. Long difference — Grid-level: changes in average prices within 250m grids. Eliminates level differences.
  4. News/media DiD — Treatment = post-media-coverage × exposure. Tests whether information matters for capitalisation.
  5. Upstream/downstream — River network topology via PostGIS. Downstream sites receive upstream pollution. Tests directionality.
  6. Dry spills — Spills without rainfall. If dry spills affect prices, suggests awareness/stigma channel over physical damage.
  7. Hydraulic capacity instrument — Planned IV using sewer capacity as instrument for spill frequency.

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.

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