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Access dataset files directly from scripts, code, or AI agents.
Each file has a stable URL (r-link) that you can use directly in scripts, apps, or AI agents. These URLs are permanent and safe to hardcode.
Start with these files — they give you everything you need to understand and access the dataset.
- 1. Fetch datapackage.json to inspect schema and resources
- 2. Download data resources listed in datapackage.json
- 3. Read README.md for full context
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annual
Schema
| name | type | description |
|---|---|---|
| year | integer | Calendar year |
| variable_id | string | Machine-readable variable slug (e.g. 'real-uk-gdp-at-market-prices') |
| variable | string | Full variable description from the original dataset |
| section | string | Thematic section (e.g. 'National Accounts', 'Financial markets', 'Trade') |
| unit | string | Unit of measurement (e.g. '£mn, Chained Volume measure, 2013 prices') |
| value | number | Observed value in the stated unit |
quarterly
Schema
| name | type | description |
|---|---|---|
| period | string | Quarter identifier in YYYY-QN format (e.g. '1920-Q1') |
| year | integer | Calendar year |
| quarter | integer | Quarter number (1–4) |
| variable_id | string | Machine-readable variable slug |
| variable | string | Full variable description from the original dataset |
| section | string | Thematic section |
| unit | string | Unit of measurement |
| value | number | Observed value in the stated unit |
monthly
Schema
| name | type | description |
|---|---|---|
| period | string | Month identifier in YYYY-MM format (e.g. '1920-01') |
| year | integer | Calendar year |
| month | integer | Month number (1–12) |
| variable_id | string | Machine-readable variable slug |
| variable | string | Full variable description from the original dataset |
| section | string | Thematic section |
| unit | string | Unit of measurement |
| value | number | Observed value in the stated unit |
Data Files
| File | Description | Size | Last modified | Download |
|---|---|---|---|---|
annual | Annual headline series (A1) covering 65 macroeconomic variables from 1086 to 2016. Long-format with one row per year-variable pair. Sections: National Accounts, Labour/Capital/Productivity, Wages and Prices, Financial Markets, Money and Credit, Fiscal, Trade. | 2.86 MB | about 1 month ago | annual |
quarterly | Quarterly headline series (Q1) covering 48 macroeconomic variables. Long-format with one row per period-variable pair. Period format: YYYY-Q1 through YYYY-Q4. | 2.81 MB | about 1 month ago | quarterly |
monthly | Monthly headline series (M1) covering 26 macroeconomic variables. Long-format with one row per period-variable pair. Period format: YYYY-MM. | 6.3 MB | about 1 month ago | monthly |
| Files | Size | Format | Created | Updated | License | Source |
|---|---|---|---|---|---|---|
| 3 | 12 MB | csv | about 1 month ago | Open Government Licence v3.0 | A Millennium of Macroeconomic Data for the UK, Version 3.1 (Bank of England, updated 2025) |
A Millennium of Macroeconomic Data for the UK
Bank of England dataset covering UK macroeconomic history from the 13th century (with benchmark estimates from 1086, the year of the Domesday Book) through 2016. Version 3.1.
Background
Compiled by Ryland Thomas and Nicholas Dimsdale at the Bank of England, this dataset brings together over 130 macroeconomic variables for the United Kingdom spanning nine centuries. It covers national accounts, labour, capital and productivity, wages and prices, financial markets, money and credit, fiscal accounts, and trade.
The dataset is notable for its historical depth: GDP estimates reach back to 1086, prices to 1209, and interest rates to 1694 — making it one of the longest continuous macroeconomic records for any country.
Data
Three CSV files in data/, all in long format (one row per period-variable pair):
data/annual.csv
65 variables at annual frequency, 1086–2016.
| Column | Description |
|---|---|
year | Calendar year |
variable_id | Machine-readable variable slug |
variable | Full variable description |
section | Thematic section (e.g. National Accounts, Wages and Prices) |
unit | Unit of measurement |
value | Observed value |
data/quarterly.csv
48 variables at quarterly frequency. period format: YYYY-Q1 through YYYY-Q4.
data/monthly.csv
26 variables at monthly frequency. period format: YYYY-MM.
Sources
- Thomas, R. and Dimsdale, N. (2017). A Millennium of Macroeconomic Data for the UK. Bank of England OBRA dataset, Version 3.1.
Reproduce
python3 process.py
Downloads the Bank of England xlsx and extracts the three headline sheets (A1 annual, Q1 quarterly, M1 monthly) into long-format CSVs. The original source file is archived at archive/millennium-of-macroeconomic-data.xlsx.