global-macro-data 0.3.1
Global Macro Database by Karsten Müller, Chenzi Xu, Mohamed Lehbib and Ziliang Chen (2025)
Requires Python: >=3.6

# The Global Macro Database (Python Package)
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[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE)

[Link to paper 📄](https://www.globalmacrodata.com/research-paper.html)

This repository complements paper, **Müller, Xu, Lehbib, and Chen (2025)**, which introduces a panel dataset of **46 macroeconomic variables across 243 countries** from historical records beginning in the year **1086** until **2024**, including projections through the year **2030**.

## Features

- **Unparalleled Coverage**: Combines data from **32 contemporary sources** (e.g., IMF, World Bank, OECD) with **78 historical datasets**.
- **Extensive Variables**: GDP, inflation, government finance, trade, employment, interest rates, and more.
- **Harmonized Data**: Resolves inconsistencies and splices all available data together.
- **Scheduled Updates**: Regular releases ensure data reliability.
- **Full Transparency**: All code is open source and available in this repository.
- **Accessible Formats**: Provided in `.dta`, `.csv` and as **<a href="https://github.com/KMueller-Lab/Global-Macro-Database" target="_blank" rel="noopener noreferrer">Stata</a>
/<a href="https://github.com/KMueller-Lab/Global-Macro-Database-Python" target="_blank" rel="noopener noreferrer">Python</a>/<a href="https://github.com/KMueller-Lab/Global-Macro-Database-R" target="_blank" rel="noopener noreferrer">R</a> package**.

## Data access

<a href="https://www.globalmacrodata.com/data.html" target="_blank" rel="noopener noreferrer">Download via website</a>

**Python package:**
```
pip install global_macro_data
```

**How to use (examples)**
```python
from global_macro_data import gmd

# Get preview data (Singapore 2000-2020)
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=["USA", "CHN", "DEU"])

# Get specific variables
df = gmd(variables=["rGDP", "infl", "unemp"])

# Combine parameters
df = gmd(version="2025_01", country=["USA", "CHN"], variables=["rGDP", "unemp", "CPI"])
```

## Parameters
- **version (str)**: Dataset version in format 'YYYY_MM' (e.g., '2025_01'). If None, the latest dataset is used.
- **country (str or list)**: ISO3 country code(s) (e.g., "SGP" or ["MRT", "SGP"]). If None, returns all countries.
- **variables (list)**: List of variable codes to include (e.g., ["rGDP", "unemp"]). If None, all variables are included.
- **show_preview (bool)**: If True and no other parameters are provided, shows a preview.

## Release schedule 
| Release Date | Details         |
|--------------|-----------------|
| 2025-01-30   | Initial release: 2025_01 |
| 2025-04-01   | 2025_03         |
| 2025-07-01   | 2025_06         |
| 2025-10-01   | 2025_09         |
| 2026-01-01   | 2025_12         |

## Citation

To cite this dataset, please use the following reference:

```bibtex
@techreport{mueller2025global, 
    title = {The Global Macro Database: A New International Macroeconomic Dataset}, 
    author = {Müller, Karsten and Xu, Chenzi and Lehbib, Mohamed and Chen, Ziliang}, 
    year = {2025}, 
    type = {Working Paper}
}
```

## Acknowledgments

The development of the Global Macro Database would not have been possible without the generous funding provided by the Singapore Ministry of Education (MOE) through the PYP grants (WBS A-0003319-01-00 and A-0003319-02-00), a Tier 1 grant (A-8001749- 00-00), and the NUS Risk Management Institute (A-8002360-00-00). This financial support laid the foundation for the successful completion of this extensive project.