Download the full dataset or access it via our packages.
You can access the Global Macro Database directly through our packages for Stata, Python, and R.
Access
via Stata
Install Stata Package:
Our package is available on the Stata SSC Archive. You can install it using:
ssc install gmd
The gmd command's syntax is straightforward:
gmd variable_abbreviation, option
gmd
gmd rGDP, raw
gmd rGDP, country(FRA)
Additional resources:
For detailed syntax, type help gmd in the Stata terminal.
Also see our dedicated article describing the gmd package.
Access
via Python
from global_macro_data import gmd
# Get preview data
df = gmd()
# Get latest version
df = gmd(show_preview=False)
# Specific version
df = gmd(version="2025_01")
# Specific country
df = gmd(country="USA")
# Multiple countries
df = gmd(country=["USA", "CHN", "DEU"])
# Specific variables
df = gmd(variables=["rGDP", "infl", "unemp"])
# Combine filters
df = gmd(version="2025_01", country=["USA", "CHN"], variables=["rGDP", "unemp", "CPI"])
'YYYY_MM'. Defaults to
latest."SGP" or
["SGP", "MRT"].
["rGDP", "unemp"].True with no filters, shows sample data.
Access via R
# Install devtools if not already installed
install.packages("devtools")
# Install the package from GitHub
devtools::install_github("KMueller-Lab/Global-Macro-Database-R")
# Load the Package
library(globalmacrodata)
# Get preview data
df <- gmd()
# Get data from latest available version
df <- gmd(show_preview = FALSE)
# Get data from a specific version
df <- gmd(version = "2025_01")
# Get data for a specific country
df <- gmd(country = "USA")
# Get data for multiple countries
df <- gmd(country = c("USA", "CHN", "DEU"))
# Get specific variables
df <- gmd(variables = c("rGDP", "infl", "unemp"))
# Combine parameters
df <- gmd(version = "2025_01", country = c("USA", "CHN"), variables = c("rGDP", "unemp", "CPI"))
"YYYY_MM". Defaults to
latest."SGP" or
c("MRT", "SGP").
c("rGDP", "unemp").
TRUE with no filters, shows preview data.
| Release Date | Version | Details |
|---|---|---|
| 2025-01-31 | 2025_01 | Initial release |
| 2025-03-31 | 2025_03 | Update |
| 2025-06-30 | 2025_06 | Update |
| 2025-08-23 | 2025_08 | Patch |
| 2025-09-30 | 2025_09 | Update |
| 2025-12-31 | 2025_12 | Update |
| 2026-01-25 | 2026_01 | Current version |
| 2026-03-31 | 2026_03 | Upcoming |
| 2026-06-30 | 2026_06 | Upcoming |
This release introduces significant enhancements to data accuracy and infrastructure. Key updates include a comprehensive revision of the real GDP series and the deployment of a fully automated, cloud-based data processing pipeline to ensure timely future updates.
We have conducted a major review of the real GDP series. The data has been rigorously corrected and is now consistently rebased to the year 2015, ensuring greater comparability and accuracy across the dataset.
We have implemented a new automated pipeline. This system autonomously handles downloading, processing, and merging data from all sources in the cloud, ensuring the maintenance process and allowing for more frequent and reliable database updates.
We have launched a dedicated repository for the official Stata package, now available on GitHub.
Additionally, we have released a comprehensive companion paper, which serves as a detailed guide to using the package effectively.
This update introduces improved government finance statistics, an extended technical appendix, a major overhaul to the Stata package, bug fixes, and the inclusion of World Bank income groups.
This quarterly update introduces improved government finance statistics, streamlined source handling, a new outlier detection process, and numerous fixes and small improvements.
RR_infl, Clio,
UN_trade, BEL_1, CAN_2, and KOR_2.
nGDP, cons, inv,
finv, imports, and exports
govdebt, govdef, govexp, govrev,
and govtaxThis release includes updated annual data, expanded historical coverage for key countries, resolved inconsistencies in past series, and introduces new ways to access the database through our Python, R, and Stata packages.
All datasets have been updated to include the most recently published annual values as of the release date.
New long-run series have been added for Argentina, Ireland, and Taiwan, enriching the database's historical scope.
We now treat the IMF World Economic Outlook (WEO) as two distinct sources: one for historical values and one for forecasts.
We have adjusted our source hierarchy to prioritize data from the World Development Indicators (WDI) over both editions of the IMF WEO.
Monaco has been added to the EUR_fx irrevocable exchange rate list with
a fixed rate of 6.55.
Corrected inaccuracies in Australiaβs long-run historical real GDP in USD figures.
The Global Macro Database is an open-source project, and we welcome all contributions.
Submit issues or feedback on our GitHub repository, or email us at kmueller@globalmacrodata.com.