France Housing Loans Growth: Year-on-Year Mortgage Credit Growth Since 2012

This dataset tracks the year-on-year growth rate of the stock of housing loans held by French resident households, as published by the Banque de France in its BSI1 statistics, monthly from September 2012 across 164 observations. It is the rate of change of a stock, which makes it the cleanest single reading of the French mortgage credit cycle. The series ranges from a peak of 8.31% in August 2021 to a trough of -2.87% in November 2024, an 11.2 point swing inside three years, and it has now spent 45 months of its history below zero.

Dataset: France Housing Loans Growth (2012–2026) · Updated 2026-07-01

Data provided as is, with no warranty of accuracy or timeliness. Check any figure against the primary source cited on this page before using it. Terms: legal notice.

Source: Banque de France, Webstat BSI1 · housing loans to resident households, annual growth rate

Macro Takeaway

Dataset Overview

Dataset Variables

The CSV, Excel and JSON files contain the following columns.

Column names match the CSV headers exactly.

Download the Complete Dataset

The full France housing loans growth dataset is available in CSV and Excel formats.

Data provided as is, with no warranty of accuracy or timeliness. Check any figure against the primary source cited on this page before using it. Terms: legal notice.

Direct CSV Access – Eco3min Structured Dataset

https://eco3min.fr/dataset/fr/fr-housing-loans-growth.csv

This URL returns the complete dataset in CSV format. It can be used directly in pandas, R, curl, or any data tool. The upstream series is published by the Banque de France through Webstat, in the BSI1 dataset.

Using the Dataset in Python

import pandas as pd

url = "https://eco3min.fr/dataset/fr/fr-housing-loans-growth.csv"
df = pd.read_csv(url, parse_dates=["date"])

print(df.tail())
print(df[df["housing_loans_growth"] < 0].shape[0], "months below zero")

Using the Dataset in R

library(readr)

url <- "https://eco3min.fr/dataset/fr/fr-housing-loans-growth.csv"
df <- read_csv(url)

tail(df)
sum(df$housing_loans_growth < 0)

Both examples load the dataset directly from the URL, with no download or API key required.

Methodology

The Banque de France publishes this growth rate alongside the outstanding amounts in its BSI1 statistics. It is an annual rate of change computed on the adjusted stock, which means it corrects for reclassifications, revaluations and, where relevant, loan securitisation, so that a change in reporting perimeter does not show up as credit growth. That correction is the reason the growth rate published here cannot always be reproduced exactly by dividing two consecutive readings of the raw outstanding series twelve months apart.

The Eco3min pipeline pulls the series through DBnomics, which mirrors Banque de France Webstat, and writes the CSV, Excel and JSON files, rebuilding the full history on each run.

Data Quality & Provider Notes

This is an adjusted growth rate, not a raw ratio. Deriving a year-on-year change directly from the outstanding series will produce a similar but not identical number. The published rate is the one to cite, because it is the one that strips out non-transaction effects.

Base effects govern the short run. A twelve-month growth rate carries the memory of the month that just dropped out of the window. Sharp moves in a single month often say more about the comparison base a year earlier than about current lending.

Latency and revisions. BSI1 publishes with roughly a two-month lag, and revisions to the underlying stock propagate into the growth rate for every affected month. The pipeline rebuilds the whole file on each run, so revisions replace history rather than accumulating beside it.

Terms. Banque de France data (WEBSTAT portal), reusable including commercially under the Webstat legal notice: data not altered, source and update date cited, WEBSTAT portal named for commercial reuse. Neither the Licence Ouverte nor a Creative Commons licence applies.

Historical Regimes

2012–2013 – Moderate growth. Annual averages of 3.4% and 3.2%, a housing credit market expanding at a pace close to nominal income growth.

2014–2015 – The first contraction. The series goes negative for twelve consecutive months, from May 2014 to April 2015, with a 2014 annual average of -0.15%. This episode is easy to overlook and useful as a reference point: it shows the growth rate can cross zero without a broader credit crisis.

2016–2021 – Six years of acceleration. Annual averages climb 3.5%, 5.5%, 5.6%, 6.1%, 6.5%, 7.3%. The peak reading of 8.31% comes in August 2021. Nothing in the file matches this run for either length or level.

2022–2023 – The turn. Growth halves to a 5.9% average in 2022 and then falls to 1.2% in 2023. The series crosses zero in July 2023, beginning the longest negative stretch in the record.

2024–2026 – Sustained contraction. The 2024 average is -1.98%, with the all-time low of -2.87% in November. Twenty-nine consecutive negative months run to November 2025, and after a brief return above zero the series is negative again from January 2026, standing at -0.10% in April, at the 26th percentile of its history.

Related Macroeconomic Datasets

A credit growth rate reads against the stock it derives from, the flow that feeds it, and the price that governs both.

Macroeconomic Dataset Hub

This dataset is part of the Eco3min macro-financial data repository.

Explore the Eco3min Dataset Hub

Sources

• Banque de France – Webstat, BSI1 statistics, housing loans to resident households, annual growth rate, series M.FR.N.A.A22.A.I.U6.2251.Z01.A
• Terms: Banque de France Webstat legal notice (reuse including commercial, data not altered, source and update date cited); neither the Licence Ouverte nor a Creative Commons licence applies
• Eco3min Research – structured dataset compilation

Dataset Reference

Eco3min Research. (2026). France Housing Loans Growth, Monthly Year-on-Year Data (2012–2026).<br> https://eco3min.fr/en/france-housing-loans-growth-dataset/