skills/41-sticerd-eee-sewage-econometrics-check/skills/identify/SKILL.md
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".
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research identifyInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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.
log(price) ~ spill_metrics + controls | lsoa + year_quarter. Assumption: spill exposure is conditionally exogenous given LSOA FE.Δlog(price) ~ Δspill_metrics | house_id. Eliminates time-invariant unobservables.docs/overleaf/ for how strategies are currently describedscripts/R/09_analysis/scripts/R/utils/spill_aggregation_utils.R for treatment constructiondocs/overleaf/refs.bib for methodological referencesFor a new or revised strategy, produce:
If reviewing an existing strategy:
# 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.
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Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with "auto review loop minimax" or "minimax review".
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Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".
tools
Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with "auto review loop minimax" or "minimax review".
tools
Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".