France Mortgage Renegotiation Share: Refinancing as a Share of New Lending Since 2010
This dataset measures how much of French monthly mortgage production is refinancing rather than new borrowing, as published by the Banque de France in its MIR1 statistics, monthly from October 2010 across 154 observations. It is the correction factor for the headline production series: without it, a refinancing wave and a housing boom look identical. The share ranges from 3.7% in January 2012 to 61.8% in January 2017, the month when renegotiation accounted for nearly two euros in every three lent.
Dataset: France Mortgage Renegotiation Share (2010–2026) · Updated 2026-07-01
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Source: Banque de France, Webstat MIR1 · weight of renegotiations in new housing loans to households
Macro Takeaway
Renegotiation is what households do when the rate on offer falls far enough below the rate they are paying to justify the cost of switching. It therefore rises when rates fall fast, and collapses when they rise, with almost no relationship to housing transactions. That makes this series the necessary companion to new housing loan production: gross production counts both, and only the share tells you which one moved.
The 2015 to 2017 wave is the defining episode. Annual averages reach 50.0% in 2015, 42.6% in 2016 and 36.3% in 2017, and fifteen months print above 50%, from February 2015 to March 2017. At the January 2017 peak of 61.8%, applied to a record EUR 38.5 billion of production, roughly EUR 23.8 billion was refinancing and only about EUR 14.7 billion was new lending. Read on its own, that month says France had its biggest mortgage month ever. Read with this series, it says French households repriced their existing debt en masse.
Since 2018 the share has stayed in a narrow band, averaging between 14% and 23% every year, and it sits at 13.6% in April 2026, at the 14th percentile of its own history. That is the arithmetic of a rising-rate world: with the mortgage rate above the rate on most outstanding loans, there is nothing to renegotiate, and gross production once again measures what it appears to measure.
Dataset Overview
| Indicator | France Mortgage Renegotiation Share (2010–2026) |
|---|---|
| Geography | France |
| Frequency | Monthly |
| Period | 2010–2026 |
| Variables | date, renegotiation_share |
| Unit | Percent of new housing loan production |
| Format | CSV, Excel (XLSX), JSON |
| Sources | Banque de France, Webstat MIR1, series M.FR.B.A22PR.A.W.A.2254FR.EUR.N |
| Last updated | — |
Dataset Variables
The CSV, Excel and JSON files contain the following columns.
| Column | Type | Description |
|---|---|---|
date | Date (YYYY-MM-DD) | Observation month, dated to the first day of the month |
renegotiation_share | Float | Weight of renegotiations in total new housing loans to resident households, percent (Banque de France MIR1) |
Column names match the CSV headers exactly.
Download the Complete Dataset
The full France mortgage renegotiation share dataset is available in CSV and Excel formats.
Direct CSV Access – Eco3min Structured Dataset
https://eco3min.fr/dataset/fr/fr-mortgage-renegotiation-share.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 MIR1 dataset.
Using the Dataset in Python
import pandas as pd
share = pd.read_csv("https://eco3min.fr/dataset/fr/fr-mortgage-renegotiation-share.csv", parse_dates=["date"])
flow = pd.read_csv("https://eco3min.fr/dataset/fr/fr-new-housing-loans.csv", parse_dates=["date"])
df = share.merge(flow, on="date")
df["new_money"] = df["new_housing_loans"] * (1 - df["renegotiation_share"] / 100)
print(df.tail())
Using the Dataset in R
library(readr) url <- "https://eco3min.fr/dataset/fr/fr-mortgage-renegotiation-share.csv" df <- read_csv(url) tail(df) summary(df$renegotiation_share)
The Python example shows the operation this dataset exists for: stripping refinancing out of gross production to isolate genuinely new lending.
Methodology
The Banque de France reports, within its MIR1 new-business statistics, the portion of new housing loans to resident households that corresponds to renegotiations of existing contracts. The published figure is a weight, expressed as a percentage of total new housing loan production for the reference month.
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
Renegotiation and external refinancing are not the same thing. This measure covers the renegotiation of a loan with the existing lender. A household that repays its loan and takes a new one at a different bank produces a new loan and an early repayment, which is economically similar but does not necessarily enter this line the same way. The series therefore captures the bulk of refinancing behaviour, not all of it.
The share is not seasonally adjusted, while the production series it corrects is. Multiplying one by the other, as the Python example above does, mixes an adjusted flow with an unadjusted share. The result is a good approximation of new money over quarters and years, and a rough one month by month.
A ratio moves when either side moves. A rising share can mean more refinancing or less purchase lending. In late 2023 and 2024, with production near its lows, a stable share of around 16% to 17% coexisted with a sharply reduced absolute amount of refinancing.
Latency and revisions. MIR1 publishes with roughly a two-month lag, and revisions replace history rather than accumulating beside it, since the pipeline rebuilds the whole file on each run.
Licence. Banque de France Webstat data is published under the Licence Ouverte 2.0 (Etalab), which permits reuse including commercial reuse, subject to attribution of the source.
Historical Regimes
2010–2012 – Low and falling. The series opens near 18% in late 2010, and 2012 averages just 5.85%, the lowest annual figure in the file, with the all-time low of 3.7% in January 2012. With rates high relative to the recent past, there was no gain in switching.
2013–2014 – A first wave. The annual average jumps to 29.1% in 2013 as rates begin their long descent, then settles back to 20.7% in 2014.
2015–2017 – The great renegotiation. Annual averages of 50.0%, 42.6% and 36.3%. Fifteen months print above 50%, from February 2015 to March 2017, and the peak of 61.8% arrives in January 2017. For three years, the majority of French mortgage production in several months was households replacing their own debt.
2018–2022 – Normalisation. The share falls back into a 15% to 23% band and stays there, averaging 17.1%, 21.4%, 22.7%, 17.8% and 15.6%. Even the 2020 and 2021 lows in mortgage rates did not restart a wave, because the stock had already been repriced.
2023–2026 – Structurally low. Annual averages of 16.1%, 17.5%, 14.5% and 14.5%. The April 2026 reading of 13.6% sits at the 14th percentile of the series. With market rates above the rate on most outstanding loans, renegotiation has no economic motive.
Related Macroeconomic Datasets
This share exists to be read against the production series it corrects, and against the rate that drives both.
- France New Housing Loans – the gross flow this share decomposes
- France Mortgage Rate – the variable that creates or removes the motive to renegotiate
- France Housing Loans Outstanding – the stock being repriced
- France Housing Loans Growth – net credit growth, which refinancing does not change
- France Mortgage Spread – the bank margin squeezed by a refinancing wave
- France House Price Index – the transaction side, which refinancing leaves untouched
Macroeconomic Dataset Hub
This dataset is part of the Eco3min macro-financial data repository.
Explore the Eco3min Dataset Hub
Sources
- Banque de France – Webstat, MIR1 statistics, weight of renegotiations in new housing loans to resident households, series M.FR.B.A22PR.A.W.A.2254FR.EUR.N
- Licence Ouverte 2.0 (Etalab), reuse permitted with attribution to the source
- Eco3min Research – structured dataset compilation
Dataset Reference
Last updated — 21 September 2026
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