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

Bivariate Maps for Chinese Regional Data

Asjad Naqvi released a new version of the bimap package, let me show a small example of how this package works with some regional data for China. I…

Post date May 4, 2024
Post categories In Codes and Datasets, Illustrated
Tags Bimap, China, Data Visualization, Economic Growth, Inflation, Maps, STATA Code
2 Comments on Bivariate Maps for Chinese Regional Data

Brent-WTI spread

The Brent-WTI spread has known important evolutions after 2010. While it is well known by practitioners, market participants and academics, it may be useful to recall this point.…

Post date February 11, 2025
Post categories In Illustrated
Tags Brent-WTI spread, Data Visualization, Oil market, Oil Price

Panel Data with DBnomics

What if I told you that you can build a panel dataset of 3 variables for almost 200 countries and around 60 years in less than four minutes?…

Post date February 11, 2024
Post categories In Codes and Datasets, Illustrated, Pedagogical Note, Video
Tags Data Management, DBnomics, Panel Data, STATA Code, World Bank, World Development Indicators

Guest Contribution: “Global shocks, institutional development, and trade restrictions: What can we learn from crises and recoveries between 1990 and 2022?”

Quantile LP with Stata

Using coefplot to visualize the results of several models with Stata

3D plots using Stata and Python

25 percent of my research project with an available replication archive

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Related Posts

Guest Contribution: “Global shocks, institutional development, and trade restrictions: What can we learn from crises and recoveries between 1990 and 2022?”

Quantile LP with Stata

Using coefplot to visualize the results of several models with Stata

3D plots using Stata and Python

25 percent of my research project with an available replication archive