forecasting-economic-growth

Structures GDP growth forecasting with component analysis, nowcasting techniques, and revision tracking. Use when forecasting GDP, analyzing growth components, or building economic projections.

11 stars

Best use case

forecasting-economic-growth is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Structures GDP growth forecasting with component analysis, nowcasting techniques, and revision tracking. Use when forecasting GDP, analyzing growth components, or building economic projections.

Teams using forecasting-economic-growth 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/forecasting-economic-growth/SKILL.md --create-dirs "https://raw.githubusercontent.com/CaseMark/skills/main/skills/finance/forecasting-economic-growth/SKILL.md"

Manual Installation

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

How forecasting-economic-growth Compares

Feature / Agentforecasting-economic-growthStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Structures GDP growth forecasting with component analysis, nowcasting techniques, and revision tracking. Use when forecasting GDP, analyzing growth components, or building economic projections.

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

# Forecasting Economic Growth

Structures GDP growth forecasting with component analysis, nowcasting techniques, and revision tracking.

## When To Use

- Building quarterly or annual GDP growth projections for a specific economy
- Decomposing GDP into expenditure components (C + I + G + NX) to identify growth drivers
- Producing nowcasts using high-frequency indicators ahead of official releases
- Assessing the impact of policy changes (fiscal stimulus, rate decisions, trade policy) on growth trajectories
- Tracking and interpreting GDP revisions across advance, second, and third estimates
- Constructing scenario-based growth outlooks for investment committees or policy briefings

## Inputs To Gather

- **Target economy and horizon**: Country/region, forecast start quarter, and projection length (e.g., US, Q3 2026 through Q4 2027)
- **National accounts data**: Latest GDP release (level and growth rates, seasonally adjusted annualized rate vs. quarter-on-quarter), at least 8 quarters of history
- **Expenditure components**: Personal consumption, gross private domestic investment (fixed + inventories), government spending, exports, imports — with sub-component detail where available
- **High-frequency indicators**: PMI/ISM surveys, industrial production, retail sales, payrolls, initial claims, consumer confidence, housing starts, vehicle sales
- **Financial conditions**: Policy rate path (actual + market-implied), yield curve shape, credit spreads, equity market levels, USD trade-weighted index
- **Fiscal and trade policy inputs**: Enacted or proposed legislation, tariff schedules, government budget outlays [VERIFY against latest legislative status]
- **Consensus benchmarks**: Bloomberg/Reuters survey medians, IMF WEO, OECD Economic Outlook, Fed SEP, Blue Chip consensus
- **Special factors**: Weather disruptions, strikes, inventory cycles, one-off statistical reclassifications

## Workflow

1. **Establish the base picture**
   - Record latest official GDP print: headline growth rate, component contributions, and statistical discrepancy
   - Note the release vintage (advance/second/third) and the typical revision pattern for that statistical agency [VERIFY revision norms for non-US economies]
   - Chart the recent trajectory — identify whether growth is accelerating, decelerating, or at trend

2. **Decompose by expenditure component**
   - For each component (consumption, investment, government, net exports), assess:
     - Recent trend and momentum (3-quarter moving average of contributions)
     - Leading indicators specific to that component (e.g., real disposable income and saving rate for consumption; durable goods orders and capacity utilization for capex)
     - Known structural shifts (fiscal cliff, capex super-cycle, inventory restocking)
   - Assign a point estimate and reasonable range for each component's contribution to headline growth

3. **Apply nowcasting for the current/next quarter**
   - Map high-frequency data releases to GDP components using bridge equations or factor models
   - Weight indicators by publication timeliness and historical tracking accuracy
   - Update the nowcast as each new data point arrives; log the incremental revision and its source
   - Cross-check against GDPNow-style tracker models where available [VERIFY availability for non-US economies]

4. **Build the medium-term projection**
   - Extend component forecasts beyond the nowcast quarter using:
     - Estimated potential growth rate (trend labor force growth + productivity trend)
     - Output gap trajectory — is the economy above/below potential, and how fast is it closing?
     - Policy impulse: compute fiscal impulse (change in cyclically adjusted primary balance) and monetary stance (real policy rate vs. neutral rate estimate) [VERIFY neutral rate assumptions]
   - Layer in scenario analysis:
     - **Base case**: Most probable policy and macro path
     - **Upside**: Stronger consumption momentum, faster capex recovery, or positive trade shock
     - **Downside**: Financial conditions tightening, trade disruption, fiscal drag
   - Assign subjective probabilities to each scenario

5. **Validate and stress-test**
   - Compare headline forecast to consensus — identify and explain any meaningful divergence
   - Check internal consistency: does the implied saving rate, import elasticity, or inventory-to-sales ratio remain plausible?
   - Run sensitivity analysis on the two or three assumptions with the highest forecast leverage
   - Flag any component where the projection falls outside the historical interquartile range

6. **Track revisions and update cycle**
   - Maintain a revision log: date, data release, prior forecast, revised forecast, and magnitude of change
   - After each official GDP release, compute forecast error and decompose by component contribution
   - Identify systematic bias (persistent over/under-estimation of a component) and adjust methodology

## Output

The forecast report should contain:

- **Executive summary**: Headline GDP growth forecast (point estimate with confidence interval) for each quarter in the projection horizon, plus annual average
- **Component contribution table**: Percentage-point contributions from consumption, investment, government, and net exports — base, upside, and downside scenarios
- **Nowcast detail**: Current-quarter tracking estimate with data-release waterfall showing incremental updates
- **Scenario matrix**: Growth path under each scenario with assigned probabilities and key trigger events
- **Risk register**: Top 3–5 risks to the forecast, directional impact, and the indicator that would signal materialization
- **Revision history**: Log of prior forecasts, actuals, and error decomposition
- **Methodology note**: Model type (structural, reduced-form, judgmental overlay), data sources, seasonal adjustment conventions, and vintage dates

## Quality Checks

- Component contributions sum to headline growth (within rounding tolerance)
- Nowcast uses only data available as of the stated knowledge cutoff — no look-ahead bias
- Confidence intervals widen appropriately as the forecast horizon extends
- Scenarios are internally consistent (e.g., a recession scenario should show rising unemployment and falling imports, not just lower consumption)
- All external data sources are cited with publication date and vintage
- Statistical agency release calendars are referenced so the next update trigger is clear [VERIFY release schedule for the target economy]
- Forecast is compared to at least two independent consensus sources
- Any assumption about policy rates, fiscal policy, or exchange rates is explicitly stated and tagged [VERIFY] where jurisdiction-dependent

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