Leading Economies GDP Signal Panel
2000–2023
$0.5
Fixed price
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Source, license and coverage
Supplier documentation. These claims are separate from the automated sample score. A listing edit date is not a data freshness date.
- License
- Not documented — confirm reuse terms with the seller
- Source / creator
- Supplier-cited: World Bank Open Data
- Collection method
- Supplier description: Paid 24-feature macro signal panel derived from World Bank WDI GDP data (via datasets/gdp, CC BY 4.0). Extends the public/free panels with multi-horizon rank/share momentum, 10y CAGR, 5y growth volatility, peak drawdown, within-cohort growth percentile, and other agent-ready features for screening and trend detection. 240 country-year rows.
- Coverage / snapshot
- 2000–2023
- Data last updated
- Not documented
- Update schedule
- Not documented
Source attribution is supplier-reported. The source link identifies publisher documentation; it does not independently verify this uploaded extract.
Sample structure score: 98.1 / 100
This automated check describes the inspected sample, not factual accuracy, legal rights, representativeness, or the quality of the entire dataset. It is not a customer rating.
Assessed 10 sample records (CSV) on 2026-10-09. All records in the provided sample were checked.
| Check | Points | Evidence |
|---|---|---|
| Populated cells | 48.1 / 50 | 231 of 240 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated. |
| Consistent value types | 30 / 30 | 231 of 231 populated cells match their column's most common observed type. Types are inferred, not checked against real-world truth. |
| Consistent record shape | 20 / 20 | 10 of 10 records have the expected fields. CSV/TSV use the header width; JSON uses the union of observed keys. |
Field-level findings and improvements
Check missing cells and mixed types below. Document intentional missing values or mixed types in your field descriptions. Do not fill legitimate unknowns with invented values just to increase this score.
| Field | Missing cells | Most common type | Other populated types |
|---|---|---|---|
| country | 0 / 10 | string | 0 / 10 |
| year | 0 / 10 | number | 0 / 10 |
| gdp_usd_trillion | 0 / 10 | number | 0 / 10 |
| rank_within_top10 | 0 / 10 | number | 0 / 10 |
| share_of_top10_pct | 0 / 10 | number | 0 / 10 |
| yoy_nominal_usd_growth_pct | 0 / 10 | number | 0 / 10 |
| index_2000_100 | 0 / 10 | number | 0 / 10 |
| previous_year_rank | 0 / 10 | number | 0 / 10 |
| rank_change_yoy | 0 / 10 | number | 0 / 10 |
| share_change_yoy_pp | 0 / 10 | number | 0 / 10 |
| growth_acceleration_yoy_pp | 0 / 10 | number | 0 / 10 |
| cagr_3y_pct | 1 / 10 | number | 0 / 9 |
| cagr_5y_pct | 1 / 10 | number | 0 / 9 |
| gap_to_year_leader_pct | 0 / 10 | number | 0 / 10 |
| relative_to_year_median_pct | 0 / 10 | number | 0 / 10 |
| top10_total_gdp_usd_trillion | 0 / 10 | number | 0 / 10 |
| rank_change_3y | 1 / 10 | number | 0 / 9 |
| share_change_3y_pp | 1 / 10 | number | 0 / 9 |
| cagr_10y_pct | 5 / 10 | number | 0 / 5 |
| yoy_growth_volatility_5y_pp | 0 / 10 | number | 0 / 10 |
| peak_gdp_to_date_usd_trillion | 0 / 10 | number | 0 / 10 |
| drawdown_from_peak_pct | 0 / 10 | number | 0 / 10 |
| growth_vs_top10_median_pp | 0 / 10 | number | 0 / 10 |
| growth_percentile_within_top10 | 0 / 10 | number | 0 / 10 |
About this data
Macro signal panel for the top 10 economies derived from World Bank WDI GDP data, with 24 features including momentum, 10-year CAGR, growth volatility, drawdown, and percentile rankings across country-year records.
Retrieve with your agent or Python
Create an account and configure DATABAZAAR_API_KEY. This example retrieves free or already purchased data; it never makes a purchase. For a multi-file dataset, choose a file index from the manifest.
Download the Python examplepython3 retrieve-dataset.py 06d05697-f31a-4050-b24a-e4deabbbe940 --output dataset.bin
Full supplier documentation
Schema
| Name | Type | Description |
|---|---|---|
| country | string | |
| year | string | |
| gdp_usd_trillion | string | |
| rank_within_top10 | string | |
| share_of_top10_pct | string | |
| yoy_nominal_usd_growth_pct | string | |
| index_2000_100 | string | |
| previous_year_rank | string | |
| rank_change_yoy | string | |
| share_change_yoy_pp | string | |
| growth_acceleration_yoy_pp | string | |
| cagr_3y_pct | string | |
| cagr_5y_pct | string | |
| gap_to_year_leader_pct | string | |
| relative_to_year_median_pct | string | |
| top10_total_gdp_usd_trillion | string | |
| rank_change_3y | string | |
| share_change_3y_pp | string | |
| cagr_10y_pct | string | |
| yoy_growth_volatility_5y_pp | string | |
| peak_gdp_to_date_usd_trillion | string | |
| drawdown_from_peak_pct | string | |
| growth_vs_top10_median_pp | string | |
| growth_percentile_within_top10 | string |
Sample Data
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For AI Agents
# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
"mcpServers": {
"databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
}
}
# 2. Your agent can then call:
search_datasets({ query: "Leading Economies GDP Signal P" })
// Found: 06d05697-f31a-4050-b24a-e4deabbbe940
buy_now({ dataset_id: "06d05697-f31a-4050-b24a-e4deabbbe940" }) // uses your saved card# Authenticate with your API key:
curl https://api.databazaar.io/datasets/06d05697-f31a-4050-b24a-e4deabbbe940 \
-H "Authorization: Bearer YOUR_API_KEY"
# Purchase:
curl -X POST https://api.databazaar.io/datasets/06d05697-f31a-4050-b24a-e4deabbbe940/buy \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"dataset_id": "06d05697-f31a-4050-b24a-e4deabbbe940"}'