In this category I write and learn about statistical methods and apply them to subjects I find interesting.
The Beveridge curve is a valuable tool for analysing labour markets. In this post, I use it to identify trends in the German job market from 2010 to 2023. By utilising the D3.js visualisation library, we can explore how Germany's Beveridge curve evolved over time, providing an intriguing perspective on the country's labour market dynamics.
I have always been an avid user of official statistics. Eurostat, the OECD, the World Bank, other international organisations and national statistics agencies such as the French INSEE are valuable sources of data. In this post, I present a simple and efficient way of interacting with data from these official providers via the SDMX standard using the pandaSDMX Python library.
This is the second part of a project that illustrates the use of quantitative methods for developing a typology of aid donors. We'll use agglomerative, hierarchical clustering and spectral clustering to identify groups of aid donors.
This is the first post in a two-part series about using quantitative methods to develop typologies. The first part deals with Principal Components Analysis; the second will be about Clustering. I use the topic of development cooperation as a practical example.