From 3f92c9d67a178869397fb3f36d8d0a0729956c2c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Karsten=20M=C3=BCller?= <52325194+karstenm1987@users.noreply.github.com> Date: Wed, 30 Sep 2026 20:44:17 +0200 Subject: [PATCH] docs: update dataset numbers for release 2026_09 46 variables (77 series), 239 countries and territories, 167 sources, data 1086-2025 with forecasts through 2031. Examples now use the latest version by default and 2026_09 where a specific version is shown. Co-Authored-By: Claude Opus 5.5 --- +globalmacrodata/gmd.m | 4 ++-- README.md | 11 +++++------ 2 files changed, 7 insertions(+), 8 deletions(-) diff --git a/+globalmacrodata/gmd.m b/+globalmacrodata/gmd.m index cbb5263..b133ba0 100644 --- a/+globalmacrodata/gmd.m +++ b/+globalmacrodata/gmd.m @@ -26,8 +26,8 @@ % the print-only modes. % % Example: -% df = globalmacrodata.gmd('version','2025_12', ... -% 'country',{'USA','CHN'}, 'variables',{'rGDP','infl'}); +% df = globalmacrodata.gmd('country',{'USA','CHN'}, ... +% 'variables',{'rGDP','infl'}); arguments opts.variables = [] diff --git a/README.md b/README.md index 4510ba2..5fec102 100644 --- a/README.md +++ b/README.md @@ -17,16 +17,16 @@

Link to paper

-This repository complements the paper, **Müller, Xu, Lehbib, and Chen (2025)**, which introduces a panel dataset of **79 macroeconomic variables across 243 countries** from historical records beginning in the year **1086** until **2025**, including projections through the year **2030**. +This repository complements the paper, **Müller, Xu, Lehbib, and Chen (2025)**, which introduces a panel dataset of **46 core macroeconomic variables (provided as 77 harmonized series) across 239 countries and territories** from historical records beginning in the year **1086** until **2025**, including projections through the year **2031**. ## Features -- **Unparalleled Coverage**: Combines data from more than **121 contemporary and historical sources** (e.g., IMF, World Bank, OECD). +- **Unparalleled Coverage**: Combines data from **35 contemporary sources** (e.g., IMF, World Bank, OECD) and **132 historical datasets**, totaling **167 sources**. - **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. - **No Dependencies**: Pure MATLAB, including a built-in reader for the Stata `.dta` files the project publishes. -- **Accessible Formats**: Provided in `.dta`, `.csv` and as **Stata/Python/R/MATLAB package**. +- **Accessible Formats**: Provided in `.dta`, `.csv` and as **Stata/Python/R/MATLAB/Julia package**. ## Installation @@ -68,7 +68,7 @@ outFile = package_toolbox(); df = globalmacrodata.gmd(); % Get data from a specific version -df = globalmacrodata.gmd('version', '2025_12'); +df = globalmacrodata.gmd('version', '2026_09'); % List all available versions globalmacrodata.gmd('version', 'list'); @@ -117,7 +117,6 @@ bibTable = globalmacrodata.gmd('cite', 'load'); % Combine parameters df = globalmacrodata.gmd( ... - 'version', '2025_12', ... 'country', {'USA', 'CHN'}, ... 'variables', {'rGDP', 'unemp', 'CPI'}); ``` @@ -128,7 +127,7 @@ df = globalmacrodata.gmd( ... |-----------|------|-------------| | **variables** | char or cellstr | Variable code(s) to include (e.g., `'rGDP'` or `{'rGDP', 'unemp'}`) | | **country** | char or cellstr | ISO3 country code(s) (e.g., `'SGP'` or `{'MRT', 'SGP'}`). Use `'list'` to print or `'load'` to return the country table | -| **version** | char | Dataset version in format `'YYYY_MM'` (e.g., `'2025_12'`). Use `'current'` for the latest version, `'list'` to see all available versions | +| **version** | char | Dataset version in format `'YYYY_MM'` (e.g., `'2026_09'`). Use `'current'` for the latest version, `'list'` to see all available versions | | **start_year** | numeric | Keep only rows with `year >= start_year` | | **end_year** | numeric | Keep only rows with `year <= end_year` | | **raw** | logical | If `true`, download raw source-level data for a single variable |