Global Macro Database

Access GMD via Packages

You can access the Global Macro Database directly through our packages for Stata, Python, and R.

Access via PythonNew

Install via pip:

pip install global_macro_data

Example usage:

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"])

Parameter guide:

version (str): Dataset version in format 'YYYY_MM'. Defaults to latest.
country (str or list): ISO3 code(s), e.g., "SGP" or ["SGP", "MRT"].
variables (list): Variable codes like ["rGDP", "unemp"].
show_preview (bool): If True with no filters, shows sample data.

More info: Please see package code on our GMD Python Package GitHub Page.

Access via RNew

Install via devtools:

# Install devtools if not already installed
      install.packages("devtools")

      # Install the package from GitHub
      devtools::install_github("KMueller-Lab/Global-Macro-Database-R")

Example usage:

# 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"))

Parameter guide:

version (character): Dataset version in format "YYYY_MM". Defaults to latest.
country (character or vector): ISO3 code(s), e.g., "SGP" or c("MRT", "SGP").
variables (character or vector): Variable codes like c("rGDP", "unemp").
show_preview (logical): If TRUE with no filters, shows preview data.

More info: Please see package code on our GMD R Package GitHub Page.

Release Schedule

Release Date	Details
2025-01-31	Initial release: 2025_01
2025-03-31	Current Version: 2025_03
2025-06-30	Version: 2025_06
2025-09-30	Version: 2025_09
2025-12-31	Version: 2025_12
2026-03-31	Version: 2026_03

Release Notes

📦 Version 2025_03 – March 31, 2025New

📅 Released: March 31, 2025

Overview

This 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.

Data Updates

All datasets have been updated to include the most recently published annual values as of the release date.

Expanded Historical Coverage

New long-run series have been added for Argentina, Ireland, and Taiwan, enriching the database's historical scope.

IMF WEO Treatment Refined

We now treat the IMF World Economic Outlook (WEO) as two distinct sources: one for historical values and one for forecasts. This allows for clearer documentation and improved management of discontinuities between past data and forward-looking projections.

World Bank Data Prioritization

We have adjusted our source hierarchy to prioritize data from the World Development Indicators (WDI) over both editions of the IMF WEO. This change has resulted in some level adjustments, while maintaining stable trends. Correlation with previous versions remains high across variables—for example, nominal GDP retains a minimum correlation of 0.97 between the old and new series.

Exchange Rate Coverage

Monaco has been added to the EUR_fx irrevocable exchange rate list with a fixed rate of 6.55, aligned with the French Franc, which served as the country’s de facto currency prior to euro adoption.

Bug Fixes

Corrected inaccuracies in Australia’s long-run historical real GDP in USD figures.

New Access Tools

Python and R packages: We are excited to announce that our data can now also be easily accessed using our newly-released Python and R packages. See the Data page for setup instructions.
Official Stata package: Now available through the SSC Archive. New function updated for downloading underlying raw data via the "raw" option when using a specific variable.

Data

Download GMD Data