Credit-to-GDP gap signals (BIS macroprudential credit cycle)
Quarterly macroprudential signals derived from BIS credit-to-GDP gaps: the deviation of private-sector credit from its long-run trend for ~44 economies — the Basel III countercyclical-buffer guide — alongside the underlying credit-to-GDP ratio. Each series carries quarter-on-quarter and year-on-year changes, 30-quarter annualized change volatility, 1-quarter momentum, 3-sigma anomaly flags vs a trailing 12-quarter baseline, naive-drift 1-quarter forecasts, a per-quarter cross-country volatility rank, plus Basel guide flags (gap > 2pp, gap > 10pp) and 10-year z-scores. Country codes are normalized to ISO alpha-3 so rows join cleanly with other country-keyed datasets. Raw series: Bank for International Settlements (WS_CREDIT_GAP).
Quality
Attribution
Bank for International Settlements (derived signals by Frontier Data Hub)
Schema
| Column | Type | Description |
|---|---|---|
| date | string | First day of the reference quarter (BIS SDMX TIME_PERIOD, e.g. 2026-Q1 -> 2026-01-01). |
| country | string | |
| country_code | string | |
| series_id | string | BIS BORROWERS_CTY code plus the gap-data-type suffix: .GAP for the credit-to-GDP gap, .RATIO for the credit-to-GDP ratio (official CL_AREA and CL_CREDT_GAP_DTYPE codelists). |
| series_label | string | BIS CL_AREA English name plus the official CL_CREDT_GAP_DTYPE label: 'Credit-to-GDP gap (actual minus HP-filter trend)' or 'Credit-to-GDP ratio (actual data)', for the private non-financial sector. |
| value | float | Credit-to-GDP gap or ratio in percentage points, as published in the BIS WS_CREDIT_GAP dataflow (private non-financial sector, all lenders). |
| qoq_change_pp | float | |
| yoy_change_pp | float | |
| volatility_30d | float | |
| momentum_3m | float | |
| anomaly_flag | integer | |
| forecast_1m | float | |
| rank | integer | |
| ccyb_guide_flag | float | |
| high_gap_flag | float | |
| gap_z_10y | float | |
| ratio_z_10y | float |
Sample rows
| date | country | country_code | series_id | series_label | value | qoq_change_pp | yoy_change_pp | volatility_30d | momentum_3m | anomaly_flag | forecast_1m | rank | ccyb_guide_flag | high_gap_flag | gap_z_10y | ratio_z_10y |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1947-10-01 | United States | USA | US.RATIO | United States — Credit-to-GDP ratio (actual data) | 47.060190285428 | — | — | — | — | 0 | — | — | — | — | — | — |
| 1948-01-01 | United States | USA | US.RATIO | United States — Credit-to-GDP ratio (actual data) | 47.573557478739 | 0.513367193310998 | — | — | 0.513367193310998 | 0 | — | — | — | — | — | — |
| 1948-04-01 | United States | USA | US.RATIO | United States — Credit-to-GDP ratio (actual data) | 47.87667465787 | 0.3031171791310001 | — | — | 0.3031171791310001 | 0 | — | — | — | — | — | — |
| 1948-07-01 | United States | USA | US.RATIO | United States — Credit-to-GDP ratio (actual data) | 48.046789997951 | 0.17011534008100426 | — | — | 0.17011534008100426 | 0 | — | — | — | — | — | — |
| 1948-10-01 | United States | USA | US.RATIO | United States — Credit-to-GDP ratio (actual data) | 48.59859732216 | 0.5518073242090011 | 1.5384070367320035 | — | 0.5518073242090011 | 0 | — | — | — | — | — | — |
Download sample data
Download the full sample snapshot for this dataset (sample rows, not the complete dataset).
Use with an LLM
Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).
cURL
curl "https://datazimuts.com/v1/datasets/bis_gap_signals/credit_to_gdp_gap_signals" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/bis_gap_signals/credit_to_gdp_gap_signals").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)API endpoint: https://datazimuts.com/v1/datasets/bis_gap_signals/credit_to_gdp_gap_signals
Tip: fetch /llms.txt for the full machine-readable catalog.