Dataset Viewer
Auto-converted to Parquet Duplicate
countrycode
stringclasses
169 values
country
stringclasses
169 values
region
stringclasses
8 values
year
int32
1
2.02k
gdppc
float64
295
160k
⌀
pop
float64
2
1.4M
⌀
AFG
Afghanistan
South and South East Asia
1
null
null
AFG
Afghanistan
South and South East Asia
730
null
null
AFG
Afghanistan
South and South East Asia
1,000
null
null
AFG
Afghanistan
South and South East Asia
1,090
null
null
AFG
Afghanistan
South and South East Asia
1,150
null
null
AFG
Afghanistan
South and South East Asia
1,252
null
null
AFG
Afghanistan
South and South East Asia
1,253
null
null
AFG
Afghanistan
South and South East Asia
1,254
null
null
AFG
Afghanistan
South and South East Asia
1,255
null
null
AFG
Afghanistan
South and South East Asia
1,256
null
null
AFG
Afghanistan
South and South East Asia
1,257
null
null
AFG
Afghanistan
South and South East Asia
1,258
null
null
AFG
Afghanistan
South and South East Asia
1,259
null
null
AFG
Afghanistan
South and South East Asia
1,260
null
null
AFG
Afghanistan
South and South East Asia
1,261
null
null
AFG
Afghanistan
South and South East Asia
1,262
null
null
AFG
Afghanistan
South and South East Asia
1,263
null
null
AFG
Afghanistan
South and South East Asia
1,264
null
null
AFG
Afghanistan
South and South East Asia
1,265
null
null
AFG
Afghanistan
South and South East Asia
1,266
null
null
AFG
Afghanistan
South and South East Asia
1,267
null
null
AFG
Afghanistan
South and South East Asia
1,268
null
null
AFG
Afghanistan
South and South East Asia
1,269
null
null
AFG
Afghanistan
South and South East Asia
1,270
null
null
AFG
Afghanistan
South and South East Asia
1,271
null
null
AFG
Afghanistan
South and South East Asia
1,272
null
null
AFG
Afghanistan
South and South East Asia
1,273
null
null
AFG
Afghanistan
South and South East Asia
1,274
null
null
AFG
Afghanistan
South and South East Asia
1,275
null
null
AFG
Afghanistan
South and South East Asia
1,276
null
null
AFG
Afghanistan
South and South East Asia
1,277
null
null
AFG
Afghanistan
South and South East Asia
1,278
null
null
AFG
Afghanistan
South and South East Asia
1,279
null
null
AFG
Afghanistan
South and South East Asia
1,280
null
null
AFG
Afghanistan
South and South East Asia
1,281
null
null
AFG
Afghanistan
South and South East Asia
1,282
null
null
AFG
Afghanistan
South and South East Asia
1,283
null
null
AFG
Afghanistan
South and South East Asia
1,284
null
null
AFG
Afghanistan
South and South East Asia
1,285
null
null
AFG
Afghanistan
South and South East Asia
1,286
null
null
AFG
Afghanistan
South and South East Asia
1,287
null
null
AFG
Afghanistan
South and South East Asia
1,288
null
null
AFG
Afghanistan
South and South East Asia
1,289
null
null
AFG
Afghanistan
South and South East Asia
1,290
null
null
AFG
Afghanistan
South and South East Asia
1,291
null
null
AFG
Afghanistan
South and South East Asia
1,292
null
null
AFG
Afghanistan
South and South East Asia
1,293
null
null
AFG
Afghanistan
South and South East Asia
1,294
null
null
AFG
Afghanistan
South and South East Asia
1,295
null
null
AFG
Afghanistan
South and South East Asia
1,296
null
null
AFG
Afghanistan
South and South East Asia
1,297
null
null
AFG
Afghanistan
South and South East Asia
1,298
null
null
AFG
Afghanistan
South and South East Asia
1,299
null
null
AFG
Afghanistan
South and South East Asia
1,300
null
null
AFG
Afghanistan
South and South East Asia
1,301
null
null
AFG
Afghanistan
South and South East Asia
1,302
null
null
AFG
Afghanistan
South and South East Asia
1,303
null
null
AFG
Afghanistan
South and South East Asia
1,304
null
null
AFG
Afghanistan
South and South East Asia
1,305
null
null
AFG
Afghanistan
South and South East Asia
1,306
null
null
AFG
Afghanistan
South and South East Asia
1,307
null
null
AFG
Afghanistan
South and South East Asia
1,308
null
null
AFG
Afghanistan
South and South East Asia
1,309
null
null
AFG
Afghanistan
South and South East Asia
1,310
null
null
AFG
Afghanistan
South and South East Asia
1,311
null
null
AFG
Afghanistan
South and South East Asia
1,312
null
null
AFG
Afghanistan
South and South East Asia
1,313
null
null
AFG
Afghanistan
South and South East Asia
1,314
null
null
AFG
Afghanistan
South and South East Asia
1,315
null
null
AFG
Afghanistan
South and South East Asia
1,316
null
null
AFG
Afghanistan
South and South East Asia
1,317
null
null
AFG
Afghanistan
South and South East Asia
1,318
null
null
AFG
Afghanistan
South and South East Asia
1,319
null
null
AFG
Afghanistan
South and South East Asia
1,320
null
null
AFG
Afghanistan
South and South East Asia
1,321
null
null
AFG
Afghanistan
South and South East Asia
1,322
null
null
AFG
Afghanistan
South and South East Asia
1,323
null
null
AFG
Afghanistan
South and South East Asia
1,324
null
null
AFG
Afghanistan
South and South East Asia
1,325
null
null
AFG
Afghanistan
South and South East Asia
1,326
null
null
AFG
Afghanistan
South and South East Asia
1,327
null
null
AFG
Afghanistan
South and South East Asia
1,328
null
null
AFG
Afghanistan
South and South East Asia
1,329
null
null
AFG
Afghanistan
South and South East Asia
1,330
null
null
AFG
Afghanistan
South and South East Asia
1,331
null
null
AFG
Afghanistan
South and South East Asia
1,332
null
null
AFG
Afghanistan
South and South East Asia
1,333
null
null
AFG
Afghanistan
South and South East Asia
1,334
null
null
AFG
Afghanistan
South and South East Asia
1,335
null
null
AFG
Afghanistan
South and South East Asia
1,336
null
null
AFG
Afghanistan
South and South East Asia
1,337
null
null
AFG
Afghanistan
South and South East Asia
1,338
null
null
AFG
Afghanistan
South and South East Asia
1,339
null
null
AFG
Afghanistan
South and South East Asia
1,340
null
null
AFG
Afghanistan
South and South East Asia
1,341
null
null
AFG
Afghanistan
South and South East Asia
1,342
null
null
AFG
Afghanistan
South and South East Asia
1,343
null
null
AFG
Afghanistan
South and South East Asia
1,344
null
null
AFG
Afghanistan
South and South East Asia
1,345
null
null
AFG
Afghanistan
South and South East Asia
1,346
null
null
End of preview. Expand in Data Studio

maddison-project

The Maddison Project Database (MPD): long-run estimates of real GDP per capita and population by country, from year 1 to the present, kept by the Groningen Growth and Development Centre (GGDC), University of Groningen, continuing the work of Angus Maddison. Three releases, 2018, 2020 and 2023, each as published, with a typed Parquet of each table beside the original files.

CC BY 4.0, with the citations each release asks for (see Licence).

Releases

subset rows countries years values from
2023.full_data 131,144 169 1 to 2022 gdppc 21,366, pop 17,875 raw/2023/mpd2023_web.xlsx, sheet Full data
2020.full_data 21,682 169 1 to 2018 gdppc 19,706, pop 17,199 raw/2020/mpd2020.xlsx, sheet Full data
2018.full_data 19,873 169 1 to 2016 cgdppc 17,441, rgdpnapc 17,712, pop 16,859 raw/2018/mpd2018.xlsx, sheet Full data
2018.regional_data 1,039 7 regions and the World 1870 to 2016 761 each raw/2018/mpd2018_region_data.xlsx, sheet Long data
2018.region_composition 147 147 raw/2018/mpd2018_region_data.xlsx, sheet Composition
2018.benchmark_1990 17,872 169 1 to 2016 gdppc 17,872 raw/2018/mpd2018_1990bm.xlsx, sheet LongForm

"values" counts the rows where the column is not empty. The 2023 table has a row for every country and every year that any country has (776 years), so most of its rows are empty; the 2018 and 2020 tables have rows only where there is a value.

The releases cannot be stacked into one series. Each is a full revision made with its own method, so the same country and year has other values in another release. The 2020 release page says it "uses a different methodology compared to the 2018 update", having "to some extent gone back to the original Maddison approach". Of the 19,213 country-years with gdppc in both 2020 and 2023, 6,601 differ. Japan in 1950:

release column value
2018 cgdppc (2011 US$, multiple benchmarks) 2,519
2018 rgdpnapc (2011 US$, 2011 benchmark) 3,023
2018 benchmark_1990.gdppc (1990 US$) 1,921
2020 gdppc (2011 US$) 3,062
2023 gdppc (2011 US$) 3,062

and in 2016: 36,452 and 37,465 (2018), 37,465 (2020), 37,384.56 (2023). Use one release, and say which.

The xlsx and dta files of each release and the documentation papers of 2018 and 2020 are under raw/<release>/, byte for byte as served; each release's MANIFEST.json gives their URLs, sizes, sha256 and Last-Modified, and for 2023 the SHA-1 DataverseNL states. MPD 2013 and the Maddison Database 2010 are not here: their pages state no licence.

Files and columns

The Parquet is made from the xlsx with DuckDB's excel extension. The dta files were not read and are only carried unchanged.

Every cell is read as its text and typed by the column's name, never by inference:

columns type
year INTEGER
gdppc, cgdppc, rgdpnapc, pop DOUBLE
everything else VARCHAR, the text of the cell

The columns of each table, with the definitions in the workbook's Legend or Notes sheet:

table column meaning
all country tables countrycode 3-letter ISO country code; includes former states such as CSK, SUN, YUG
country country name
year year
2023, 2020 full_data gdppc real GDP per capita in 2011 US$
pop population, mid-year (thousands)
2023 full_data region one of 8 regions, as the release groups countries
2018 full_data cgdppc real GDP per capita in 2011 US$, multiple benchmarks (for cross-country income comparisons)
rgdpnapc real GDP per capita in 2011 US$, 2011 benchmark (for cross-country growth comparisons)
pop population, mid-year (thousands)
i_cig whether the observation is extrapolated, a benchmark, or interpolated
i_bm for benchmarks, the kind of benchmark
2018 benchmark_1990 gdppc GDP per capita in 1990 US$, Maddison benchmark, updated time series
2018 regional_data region two-letter code: af, ea, ee, la, wa, we, wo, wd (World)
region_name region name
year, cgdppc, rgdpnapc, pop as in 2018 full_data
2018 region_composition countrycode country
region1870 its region for the years before 1950 (40 countries)
region1950 its region from 1950 (all 147)
-- DuckDB, straight off the Hub: GDP per capita of Japan, release 2023
SELECT year, gdppc, pop
FROM 'hf://datasets/yuiseki/maddison-project/parquet/2023/full_data.parquet'
WHERE countrycode = 'JPN' AND gdppc IS NOT NULL
ORDER BY year;

Note that a chart like this one falls under the project's request to cite the original sources (see Licence).

Things to know

  • In 2018 full_data, the Legend describes i_cig as "0/1/2" and i_bm as codes 1 to 5, but the xlsx holds the labels: i_cig is Extrapolated (10,318 rows), Interpolated (6,032), Benchmark (1,364) or an empty string (2,159); i_bm is ICP PPP estimates (1,144), Multiple of subsistence (122), Historical income benchmarks (68), Real wages and urbanization (21), Braithwaite (1968) PPPs (9) or an empty string (18,509). The empty strings are kept as empty strings, as in the sheet, not turned into NULL.
  • The 2018 sheet Full data has 126 formatted but empty rows at its foot. They are not in the Parquet. No other row was dropped.
  • In 2018, GDP per capita is rounded to the nearest dollar and population to the nearest thousand (the Legend says so). In 2020 and 2023 the values are not rounded; 2023 has 8,841 non-integer gdppc and 9,565 non-integer pop.
  • 2018 regional_data: before 1950 the regions are made of fewer countries (region1870 in region_composition) and linked to the 1950 regions. The Legend: "Data for the World in 1870 do not include Eastern Europe. Data for the World before 1950 do not include Africa and Western Asia." The years are not continuous before 1950; 278 of the 1,039 rows have no values.
  • 2018 region_composition lists 147 countries, not all 169.
  • The 2018 regions (7 two-letter codes and wd for the World, with Africa and Western Asia) are not the 2023 region values (8 names, with Middle East and North Africa, and Sub Saharan Africa).
  • The 2020 and 2023 workbooks also have a Regional data sheet, wide, with two header rows and unlabelled columns, and the country values again in wide form (GDP pc, Population). They are not made into Parquet; they are in the xlsx under raw/. So are the 2018 sheet Partial countries (England from 1252 and Holland, in wide form with two header rows), the 2023 sheet Maddison original sources, and the Sources sheets.
  • The 2018 release has no Sources sheet; its page points to Appendix A of Bolt et al. (2018), the paper in raw/2018/gd174.pdf.
  • The xlsx and the dta of a release were not compared with each other.

Checked before upload

scripts/02_verify.py in the source repository checks:

  • every raw file against its release's MANIFEST.json (size, sha256, and for 2023 the SHA-1 DataverseNL states) and that it opens as its type
  • each sheet is read again with the Python standard library alone (zipfile and xml.etree, not DuckDB), and the Parquet has the same number of rows, equal to the pinned counts above
  • every value of every row equals the cell it came from, typed the same way, in sheet order (sha256 over all values printed for both sides)
  • the columns are the sheet's header, each of the type its name gives
  • (countrycode, year) is unique in the country tables, (region, year) in regional_data, countrycode in region_composition
  • a DuckDB with no extension loaded opens every file
  • no row group has a bloom filter

Licence

Each release page states CC BY 4.0. Read on 2026-10-05:

2023, https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2023 :

Maddison Project Database, version 2023 by Jutta Bolt and Jan Luiten van Zanden is licensed under a Creative Commons Attribution 4.0 International License.

DataverseNL (https://doi.org/10.34894/INZBF2) gives the 2023 dataset the licence CC-BY-4.0.

2020, https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2020 :

Maddison Project Database, version 2020 by Jutta Bolt and Jan Luiten van Zanden is licensed under a Creative Commons Attribution 4.0 International License.

2018, https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2018 :

Maddison Project Database, version 2018 by Jutta Bolt, Robert Inklaar, Herman de Jong and Jan Luiten van Zanden is licensed under a Creative Commons Attribution 4.0 International License.

The 2020 and 2023 pages also ask, under "Attribution requirement":

All original papers must be cited when: the data is shown in any graphical form subsets of the full dataset that include less than a dozen (12) countries are used for statistical analysis or any other purposes A list of original papers can be found in the source sheet of the database. When neither a) or b) apply, then the MPD as a whole should be cited.

(the two conditions are a list on the page). The Sources sheet is in raw/2020/mpd2020.xlsx and raw/2023/mpd2023_web.xlsx. For 2018 the page says: "For the references to the original research on individual countries, see Appendix A of Bolt et al. (2018)."

What was changed: the xlsx, dta and pdf files are unchanged. The Parquet holds six sheets of those xlsx files, typed by column name, with blank rows left out; no value was changed. LICENSE beside this file says the same.

Citation

Release 2023, as its page asks:

Bolt, Jutta and Jan Luiten van Zanden (2024), "Maddison style estimates of the evolution of the world economy: A new 2023 update", Journal of Economic Surveys, 1-41. DOI: 10.1111/joes.12618

Release 2020, as its page asks:

Maddison Project Database, version 2020. Bolt, Jutta and Jan Luiten van Zanden (2020), "Maddison style estimates of the evolution of the world economy. A new 2020 update".

(the paper is raw/2020/wp15.pdf)

Release 2018, including its regional and 1990 benchmark data, as its page and the workbooks' Legend ask:

Maddison Project Database, version 2018. Bolt, Jutta, Robert Inklaar, Herman de Jong and Jan Luiten van Zanden (2018), "Rebasing 'Maddison': new income comparisons and the shape of long-run economic development", Maddison Project Working paper 10

(the paper is raw/2018/gd174.pdf; the 1990 benchmark workbook writes "Maddison Project Database, version 2018; 1990$ benchmark.")

When the data is charted, or fewer than 12 countries are used, also cite the original papers in the release's Sources sheet (2018: Appendix A of Bolt et al. 2018).

Downloads last month
376