analyzing-labor-markets

Structures employment data analysis with payroll, wage, and participation rate interpretation. Use when analyzing employment, interpreting jobs data, or assessing labor market conditions.

11 stars

Best use case

analyzing-labor-markets is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Structures employment data analysis with payroll, wage, and participation rate interpretation. Use when analyzing employment, interpreting jobs data, or assessing labor market conditions.

Teams using analyzing-labor-markets should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/analyzing-labor-markets/SKILL.md --create-dirs "https://raw.githubusercontent.com/CaseMark/skills/main/skills/finance/analyzing-labor-markets/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/analyzing-labor-markets/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How analyzing-labor-markets Compares

Feature / Agentanalyzing-labor-marketsStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Structures employment data analysis with payroll, wage, and participation rate interpretation. Use when analyzing employment, interpreting jobs data, or assessing labor market conditions.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Analyzing Labor Markets

Structures employment data analysis with payroll, wage, and participation rate interpretation.

## When To Use

- Interpreting a new BLS Employment Situation report (nonfarm payrolls, unemployment rate, hourly earnings)
- Assessing labor supply tightness for monetary policy or investment positioning
- Comparing regional or sectoral employment trends over time
- Evaluating wage growth dynamics relative to inflation and productivity
- Building a labor market dashboard for macro research or policy briefings

## Inputs To Gather

- **Headline data release**: Nonfarm payrolls change, unemployment rate (U-3), underemployment rate (U-6)
- **Wage data**: Average hourly earnings (month-over-month and year-over-year), Employment Cost Index if available
- **Participation metrics**: Labor force participation rate (LFPR), prime-age (25–54) LFPR, employment-population ratio
- **Supplemental indicators**: JOLTS (openings, quits, hires), initial and continuing jobless claims, ADP private payrolls
- **Scope parameters**: Time horizon, geographic focus (national vs. state/MSA), sector breakdown (goods-producing vs. services)
- **Revision history**: Prior two months' payroll revisions and net revision direction

## Workflow

1. **Anchor the headline numbers**
   - Record nonfarm payrolls change, unemployment rate, and average hourly earnings
   - Note prior-month revisions (net positive or negative) — revisions often matter more than the headline
   - Compare headline payrolls to consensus estimate and the 3-month / 6-month / 12-month moving averages

2. **Decompose the establishment survey**
   - Break payrolls by sector: goods-producing (manufacturing, construction, mining/logging) vs. private services (leisure/hospitality, healthcare, professional/business services, retail) vs. government
   - Identify which sectors drove the majority of the gain or loss
   - Flag any sector showing three or more consecutive months of contraction
   - Note temporary help services trend — a leading indicator of broader hiring momentum [VERIFY: confirm current BLS series ID for temp help]

3. **Analyze the household survey**
   - Compare household employment change to establishment payrolls change; persistent divergence signals measurement issues or structural shifts
   - Assess LFPR and prime-age LFPR — distinguish cyclical recovery from demographic drag (aging population effects)
   - Calculate U-6 minus U-3 spread; a widening spread indicates rising involuntary part-time or marginally attached workers
   - Review duration of unemployment distribution (median and mean weeks) for hysteresis risk

4. **Evaluate wage and cost dynamics**
   - Report average hourly earnings MoM and YoY; compare to core PCE or CPI to gauge real wage growth
   - Note composition effects: if low-wage sectors dominate hiring, aggregate wage growth may be biased downward
   - Where available, cross-reference with ECI (quarterly) for a composition-adjusted wage measure
   - Assess wage-productivity gap: wage growth persistently above productivity growth signals unit labor cost pressure [VERIFY: latest BLS productivity release quarter]

5. **Integrate leading and supplemental indicators**
   - JOLTS: openings-to-unemployed ratio (Beveridge curve position), quits rate as a confidence gauge
   - Initial claims: 4-week moving average trend direction; level relative to pre-recession baseline
   - Conference Board Help Wanted Online Index or Indeed job postings data if available
   - ISM employment sub-indices (manufacturing and services) for forward momentum

6. **Synthesize and frame implications**
   - Classify the labor market regime: overheating, full employment, softening, or contracting
   - Map findings to policy implications: Fed rate path expectations, fiscal policy pressure points
   - Identify two or three key risks (e.g., participation plateau, sector concentration, wage-price spiral risk)
   - State the investment or policy conclusion supported by the data

## Output

Deliver a structured labor market analysis report containing:

- **Executive summary** (3–5 sentences): headline verdict, key surprise vs. consensus, and primary implication
- **Data table**: payrolls (headline + revisions), unemployment rate, LFPR, average hourly earnings MoM/YoY, U-6, JOLTS openings (most recent)
- **Sector breakdown**: top three gaining and losing sectors by payroll change
- **Wage and participation assessment**: real wage trajectory, participation trend, composition caveats
- **Leading indicator dashboard**: claims trend, JOLTS quits rate, ISM employment
- **Regime classification**: current labor market characterization with supporting evidence
- **Implications**: 2–3 bullet points on monetary policy, fiscal, or market positioning takeaways
- **Risks and watch items**: factors that could shift the assessment in the next 1–3 months

## Quality Checks

- Payroll numbers cite the correct reference month and vintage (preliminary vs. revised)
- Revisions to prior months are explicitly stated — never silently use unrevised figures
- Seasonal adjustment noted; flag if analyzing non-seasonally-adjusted data [VERIFY: confirm SA vs. NSA series used]
- Unemployment rate denominator (civilian labor force) is correctly defined; do not conflate with working-age population
- Wage growth comparisons use consistent periodicity (MoM vs. YoY not mixed without labeling)
- Any cross-country or cross-state comparisons use matching definitions and survey methodologies
- Claims about "trend" require at least three data points; single-month moves labeled as such
- Mark all forward-looking statements (Fed expectations, recession probability) as analyst interpretation, not data fact
- [VERIFY] tags applied to any statute, regulation, or BLS methodology detail that may have changed since last confirmed update

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