Penn World Table 11.0

Name: Penn World Table 11.0
Creator: Penn World Table 11.0
License: https://creativecommons.org/licenses/by/4.0/

Open · redistributedCreative Commons Attribution 4.0 (CC BY 4.0)macro

Redistributable. This source is served as canonical Parquet under the license below, with attribution and provenance preserved.

Coverage

Series catalogued

Temporal coverage

1950-12-31 – 2023-12-31

Frequencies

Annual

Distinct geographies

Licensing & provenance

License: Creative Commons Attribution 4.0 (CC BY 4.0)
License URL: https://creativecommons.org/licenses/by/4.0/
Required attribution: Source: Penn World Table 11.0 (CC BY 4.0)
Redistribution: Permitted (served here)
Commercial use: Yes
Modification: Permitted

How to cite

Feenstra, R. C., Inklaar, R., & Timmer, M. P. (2015). The Next Generation of the Penn World Table. American Economic Review. Retrieved from https://www.rug.nl/ggdc/productivity/pwt. Compiled and redistributed by the Elkassabgi Data Library.

Processing: Retrieved from the official source, normalized to a long {series_key, obs_date, value} schema (period-start dates), de-duplicated, and stored as zstd Parquet. Compiled and redistributed by the Elkassabgi Data Library.

Access & mirrors

Download: Select & download penn_world_table series as CSV →
API: Get a free API key, then GET /v1/series/<id>.csv
Canonical landing: https://econdatalibrary.com/penn_world_table.html
Update cadence: annual
Update strategy: overwrite if changed
Storage layout: one parquet per VARIABLE: data/clean_full/penn_world_table/<variable>.parquet (42 files), columns series_key/obs_date/value, series_key='<variable>|<ISO3>'; annual values dated Dec-31. Raw workbook cached at data/raw/penn_world_table/pwt110.xlsx. Plus _ingest_summary.json.

Full description

FULL-COVERAGE grouped ingest of the ENTIRE Penn World Table 11.0 panel. Source: Penn World Table 11.0 (CC BY 4.0). license_id = cc-by-4.0. Cite: Feenstra, Inklaar & Timmer (2015), "The Next Generation of the Penn World Table", American Economic Review 105(10), 3150-3182. DOI 10.34894/FABVLR. CATALOG / ENUMERATION --------------------- PWT ships as ONE Excel workbook (pwt110.xlsx) on the GGDC Dataverse. There is no incremental API and no per-series endpoint: a release is a single full annual panel. The "catalog" is therefore the cross product of every economy x every variable in the workbook's `Data` sheet. PWT 11.0 = 185 economies x 1950-2023 x 42 numeric variables. We download the workbook (polite UA, retry/backoff), then parse EVERY (countrycode, variable) pair -- no sampling, no curated subset. VARIABLES --------- The `Data` sheet has 51 columns. We publish the 42 NUMERIC variables (real GDP / employment / population levels; current-price GDP, capital & TFP; national- accounts variables; exchange rates & GDP price levels; expenditure shares in CGDPo; price levels of expenditure categories & capital; plus cor_exp). The 5 `i_*` "Data information variables" (i_cig, i_xm, i_xr, i_outlier, i_irr) are CATEGORICAL TEXT labels (Benchmark / Extrapolated / Interpolated / Outlier ...), not numeric series, so they are not emitted as float observations; their meaning is recorded in metadata instead. currency_unit is an identifier, not data. GROUPED STORAGE (anti-bloat) ---------------------------- ONE Parquet per VARIABLE -> data/clean_full/penn_world_table/<variable>.parquet with columns series_key (string), obs_date (date32), value (float64) where series_key = "<variable>|<ISO3>". All 185 economies of a variable live inside that ONE file. 42 variables => 42 files for the whole source -- NOT one- file-per-series (which would be ~7,770 tiny files). Annual values are dated Dec-31 of the year, matching the eurostat / owid / faostat annual convention. A per-source JSON summary (_ingest_summary.json) records coverage. catalog.db is NOT touched here; data/clean/ is NOT touched here. Usage: python jobs/ingest_penn_world_table.py --dry # parse + report, no writes python jobs/ingest_penn_world_table.py # FULL run (download if needed, write all) python jobs/ingest_penn_world_table.py --force-download # re-download the workbook

Structured metadata

schema.org/Dataset (Google Dataset Search)

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  "repeatFrequency": "P1Y",
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  "distribution": [
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Croissant (ML-ready, schema.org JSON-LD)

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Part of the Econ Data Library catalog · metadata generated 2026-07-14 from the central registry · browse all datasets