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Data

Gross domestic product (GDP)

About this data

Source
Fouquin and Hugot (2016) – processed by Our World in Data
Last updated
March 19, 2018
Date range
1827–2014
Unit
current GBP

Sources and processing

This data is based on the following sources

Fouquin and Hugot – Two Centuries of Bilateral Trade and Gravity Data: 1827-2014

Due to the long-run nature of Fouquin and Hugot (CEPII 2016) time series, GDP estimates are compiled using a variety of sources. The top five sources, which together make up more than a third of the dataset (approx 11,864 observations out of 31,541) are from the following sources: World Bank (2015) (8513 obs); Mitchell (2017a,b,c) (1714); Barbieri and Keshik (2012) (1037 obs); Smits et al (2014) (335 obs); and Dincecco and Prado (2013) (265 obs).

A comprehensive list of GDP sources and full references can be found here: http://www.cepii.fr/PDF_PUB/wp/2016/wp2016-14.pdf, Table 7, page 19.

Similarly, CEPII's exchange rate variable is set to the British pound value of one local currency unit. Again, it draws on a range of sources of which the top five are reported here: International Monetary Fund (2012) (4394 obs); extracted from Wikipedia (2448 obs); Barbieri and Keshk (2012) (2005 obs); Officer (2014) (1752 obs); and Denzel (2010) (1750 obs).

A comprehensive list of exchange rate sources and full references can be found here: http://www.cepii.fr/PDF_PUB/wp/2016/wp2016-14.pdf, Table 8, page 21.

Russia time series is comprised of Russia from 1992-2014 and the USSR from 1827-1991.

Retrieved on
March 19, 2018
Retrieved from
http://www.cepii.fr/cepii/en/bdd_modele/presentation.asp?id=32
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Fouquin, M. and Hugot, J. (2016). Two Centuries of Bilateral Trade and Gravity Data: 1827-2014. CEPII Working Paper 2016-14, May 2016, CEPII.

Due to the long-run nature of Fouquin and Hugot (CEPII 2016) time series, GDP estimates are compiled using a variety of sources. The top five sources, which together make up more than a third of the dataset (approx 11,864 observations out of 31,541) are from the following sources: World Bank (2015) (8513 obs); Mitchell (2017a,b,c) (1714); Barbieri and Keshik (2012) (1037 obs); Smits et al (2014) (335 obs); and Dincecco and Prado (2013) (265 obs).

A comprehensive list of GDP sources and full references can be found here: http://www.cepii.fr/PDF_PUB/wp/2016/wp2016-14.pdf, Table 7, page 19.

Similarly, CEPII's exchange rate variable is set to the British pound value of one local currency unit. Again, it draws on a range of sources of which the top five are reported here: International Monetary Fund (2012) (4394 obs); extracted from Wikipedia (2448 obs); Barbieri and Keshk (2012) (2005 obs); Officer (2014) (1752 obs); and Denzel (2010) (1750 obs).

A comprehensive list of exchange rate sources and full references can be found here: http://www.cepii.fr/PDF_PUB/wp/2016/wp2016-14.pdf, Table 8, page 21.

Russia time series is comprised of Russia from 1992-2014 and the USSR from 1827-1991.

Retrieved on
March 19, 2018
Retrieved from
http://www.cepii.fr/cepii/en/bdd_modele/presentation.asp?id=32
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Fouquin, M. and Hugot, J. (2016). Two Centuries of Bilateral Trade and Gravity Data: 1827-2014. CEPII Working Paper 2016-14, May 2016, CEPII.

How we process data at Our World in Data

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline

Reuse this work

  • All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately (see below). This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.
  • All data, visualizations, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

Citations

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Gross domestic product (GDP)”. Our World in Data (2026). Data adapted from Fouquin and Hugot. Retrieved from https://archive.ourworldindata.org/20260511-092124/grapher/national-gdp-fouquin-current-gbp.html [online resource] (archived on May 11, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

Fouquin and Hugot (2016) – processed by Our World in Data

Full citation

Fouquin and Hugot (2016) – processed by Our World in Data. “Gross domestic product (GDP)” [dataset]. Fouquin and Hugot, “Two Centuries of Bilateral Trade and Gravity Data: 1827-2014” [original data]. Retrieved May 16, 2026 from https://archive.ourworldindata.org/20260511-092124/grapher/national-gdp-fouquin-current-gbp.html (archived on May 11, 2026).

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Download the data shown in this chart as a ZIP file containing a CSV file, metadata in JSON format, and a README. The CSV file can be opened in Excel, Google Sheets, and other data analysis tools.

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Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Data URL (CSV format)
https://ourworldindata.org/grapher/national-gdp-fouquin-current-gbp.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/national-gdp-fouquin-current-gbp.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/national-gdp-fouquin-current-gbp.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/national-gdp-fouquin-current-gbp.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/national-gdp-fouquin-current-gbp.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/national-gdp-fouquin-current-gbp.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/national-gdp-fouquin-current-gbp.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/national-gdp-fouquin-current-gbp.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear