The World Bank’s top 10 biggest debtors – fDi Intelligence

Post date June 3, 2025
Post categories In Illustrated
Tags Data Visualization, Debt, fDi Intelligence, World Bank

Allow me to share a very nice interactive map of World Bank’s top 10 biggest debtors: https://www.fdiintelligence.com/content/686944bf-3818-5791-9f76-b97856fb8607

Post date June 3, 2025
Post categories In Illustrated
Tags Data Visualization, Debt, fDi Intelligence, World Bank

Panel VAR with StataNow 18.5 (Natural Disasters)

In a previous blog, I have shown how to estimate Panel VAR with the new command xtvar introduced in StataNow. This time, I will use the EM-DAT database…

Post date April 7, 2025
Post categories In Codes and Datasets, Illustrated
Tags Bond Yields, Climate Risk, Data Visualization, EM-DAT Database, Fiscal Space, Natural Disaster, STATA Code, StataNow 18.5, xtvar

Using one-minute data to understand exchange rate behavior around the US presidential election

In a recent NBER WP, Joshua Aizenman and I examine the behavior of exchange rates around the 2024 US presidential election. In a previous post, I present this…

Post date March 1, 2025
Post categories In Codes and Datasets, Illustrated
Tags Data Visualization, Exchange Rate Adjustment, Exchange Rate Intervention, Institutional Score, Jupyter Notebook, Political News, Python, STATA Code

Panelview with Stata

A good way to visualize panel data with Stata is to rely on the package panelview created and maintained by Yiqing Xu: Other possibilities include Ben Jann’s heatplot:…

Post date June 2, 2024
Post categories In Codes and Datasets, Illustrated, Pedagogical Note
Tags Data Visualization, Heatplot, STATA Code

Treemap with Subgroup using Jupyter Notebook

I am still exploring how to draw a Voronoi treemap. Besides, I found a very handy way to plot treemaps with subgroups using a Jupyter notebook. By using…

Post date April 21, 2025
Post categories In Codes and Datasets, Illustrated
Tags Commodity, Data Visualization, Hierachical Treemaps, Jupyter Notebook

Drawing Maps for the Largest Cities in the World with Geoplot

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Using DBnomics with Stata and Python (Freedom House Data)

Using DBnomics with Stata and Python (World Bank Data)

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Related Posts

Drawing Maps for the Largest Cities in the World with Geoplot

Analyzing your own research output with the SJR website and ChatGPT 5

Drawing Maps for the Chinese Regions with Stata [Second Update with Geoplot – Orthographic Projection (Azimuthal)]

Using DBnomics with Stata and Python (Freedom House Data)

Using DBnomics with Stata and Python (World Bank Data)