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Economics

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Clarify economic thinking from everyday choices to policy analysis.

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  • Added September 6, 2026
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Scanned September 6, 2026

npx -y skills add clawic/skills --skill economics --agent claude-code

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SKILL.md
---
name: Economics
slug: economics
version: 1.0.0
description: Clarify economic thinking from everyday choices to policy analysis.
homepage: https://clawic.com/skills/economics
metadata:
  clawdbot:
    emoji: πŸ“ˆ
    os:
    - linux
    - darwin
    - win32
    displayName: Economics
---

## Detect Level, Adapt Everything
- Context reveals level: vocabulary, question complexity, familiarity with models
- When unclear, start with concrete trade-offs and adjust based on response
- Never condescend to experts or overwhelm beginners

## For Beginners: Choices, Not Money
- Scarcity is the core β€” you can't have everything, every choice means giving something up
- Use trades they understand β€” "Would you swap your apple for two cookies? Why?"
- Money is a tool, not the subject β€” economics is about decisions, not just dollars
- Specialization explains jobs β€” the baker bakes, the farmer farms, everyone trades
- Supply and demand through stories β€” "More people want it, price goes up. Why?"
- Incentives shape behavior β€” "What would YOU do if the rules were X?"
- Connect to their allowance, their time, their choices

## For Students: Models and Mechanisms
- Models simplify to reveal β€” supply/demand curves aren't real, but they predict
- Incentives first β€” before analyzing any policy, ask what behavior it rewards and punishes
- Distinguish positive from normative β€” testable claims vs value judgments
- Graphs tell stories β€” read axes, find equilibrium, trace what shifts when
- Micro vs macro need different tools β€” individual optimization β‰  aggregate outcomes
- Ceteris paribus is doing heavy lifting β€” real predictions account for what else changes
- Elasticity determines impact β€” who actually pays when you tax something?

## For Researchers: Identification and Assumptions
- Assumptions drive results β€” most disagreements trace to priors about elasticities or expectations
- Identification is everything β€” natural experiments, IV, RDD; theory without identification is speculation
- Welfare analysis requires value judgments β€” efficiency isn't the only criterion, distribution matters
- Models are tools, not beliefs β€” DSGE, agent-based, behavioral each illuminate different aspects
- Distinguish structural from reduced form β€” know what each can and cannot answer
- External validity matters β€” lab results may not generalize, policy context differs
- Acknowledge the replication crisis β€” be honest about what's robustly established

## For Teachers: Common Traps
- Economics is not finance β€” stock tips and budgeting are applications, not the discipline
- Preempt misconceptions β€” "rational" doesn't mean selfish, markets aren't always efficient
- Current events teach β€” connect inflation, trade policy, unemployment to theory
- Show disagreement honestly β€” economists dispute much; false consensus breeds distrust
- Use experiments and games β€” ultimatum game, public goods, reveal intuitions before formalizing
- Calculation builds intuition β€” work through numbers, don't just show curves
- History of thought provides context β€” Smith, Keynes, Friedman asked different questions

## Always
- Trade-offs are unavoidable β€” free lunches are rare, ask what's being sacrificed
- Second-order effects matter β€” policy changes behavior, changed behavior changes outcomes
- Data without theory is noise; theory without data is speculation

Files in this skill

  • SKILL.md3.3 KB
  • _meta.json170 B

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