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npx versuz@latest install brycewang-stanford-awesome-agent-skills-for-empirical-research-skills-41-sticerd-eee-sewage-econometrics-check-skills-research-git clone https://github.com/brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research.gitcp Awesome-Agent-Skills-for-Empirical-Research/SKILL.MD ~/.claude/skills/brycewang-stanford-awesome-agent-skills-for-empirical-research-skills-41-sticerd-eee-sewage-econometrics-check-skills-research-/SKILL.md--- name: research-ideation description: Generate structured research questions, hypotheses, and empirical strategies from a topic or dataset within the sewage/environmental economics space. This skill should be used when asked to "brainstorm research questions", "what else can we do with this data", "research ideas", or "ideation". argument-hint: "[topic, phenomenon, dataset, or 'extensions']" allowed-tools: ["Read", "Grep", "Glob", "Write"] --- # Research Ideation Generate structured research questions, testable hypotheses, and empirical strategies from a topic, phenomenon, or dataset. **Input:** `$ARGUMENTS` — a topic, phenomenon, dataset description, or `extensions` to brainstorm extensions of the current paper. --- ## Project-Specific Context ### Available Data - **EDM data (2021-2024+):** Event-level sewage spill records for all overflow sites in England - **Land Registry:** Universe of property transactions (prices, dates, postcodes) - **Zoopla:** Rental listings with prices and characteristics - **Met Office:** Daily rainfall at LSOA level - **River networks:** PostGIS topology of English waterways - **Annual returns:** Water company infrastructure data (sewer capacity, population served) - **Geographic boundaries:** LSOAs, MSOAs, constituencies, water company areas ### Existing Identification Strategies Hedonic, repeat sales, long difference, DiD with media coverage, upstream/downstream, dry spills, hydraulic capacity IV ### Related Literature Areas Environmental disamenity capitalisation, water quality and property values, UK water industry regulation, infrastructure and house prices, information and price discovery --- ## Workflow ### Step 1: Understand the Input Read `$ARGUMENTS` and any referenced files. - If `extensions`: read current manuscript sections and analysis scripts to understand what's been done - If a topic: ground it in the available data and methods ### Step 2: Generate 3-5 Research Questions Order from descriptive to causal: - **Descriptive:** What are the patterns? (e.g. "How do spill frequencies vary across water companies?") - **Correlational:** What factors are associated? (e.g. "Is sewer age correlated with spill frequency after controlling for rainfall?") - **Causal:** What is the effect? (e.g. "What is the causal effect of media coverage of sewage spills on house prices?") - **Mechanism:** Why does the effect exist? (e.g. "Do dry spills affect prices through stigma or physical damage?") - **Policy:** What are the implications? (e.g. "Would mandated real-time spill disclosure affect property markets?") ### Step 3: Develop Each Question For each: - **Hypothesis:** Testable prediction with expected sign/magnitude - **Identification strategy:** How to establish causality - **Data requirements:** What data is needed — is it available in the project? - **Key assumptions:** What must hold - **Potential pitfalls:** Threats to identification - **Related literature:** 2-3 papers using similar approaches ### Step 4: Rank by Feasibility and Contribution | RQ | Feasibility | Contribution | Priority | |----|-------------|-------------|----------| | 1 | High/Med/Low | High/Med/Low | ... | ### Step 5: Save Output ```markdown # Research Ideation: [Topic] **Date:** YYYY-MM-DD ## Overview [1-2 paragraphs situating the topic] ## Research Questions ### RQ1: [Question] (Feasibility: High/Medium/Low) **Type:** Descriptive / Correlational / Causal / Mechanism / Policy **Hypothesis:** [Prediction] **Identification:** [Method + key assumption] **Data:** [What's needed and what's available] **Pitfalls:** [Top 2 threats] **Related work:** [2-3 papers] ## Ranking [Table] ## Suggested Next Steps 1. [Most promising direction] 2. [Data to obtain or analysis to run] 3. [Literature to review] ``` Save to `output/log/research_ideation_[topic].md`. --- ## Principles - **Be creative but grounded.** Every suggestion must be empirically feasible with available or obtainable data. - **Think like a referee.** For each causal question, immediately identify the identification challenge. - **Leverage existing infrastructure.** The project already has spatial matching, spill aggregation, and river network tools — build on them. - **Consider data availability.** Flag when data is already available vs needs to be obtained. - **Extensions are valuable.** For `extensions`, focus on questions that use the same data infrastructure but ask different questions.