I’m at the New Zealand Association of Economists annual conference in Auckland. The opening keynote speech was from James K. Galbraith on a global view of inequality. He showed a variety of results from the University of Texas Inequality Project’s Estimated Household Income Inequality dataset, which I hadn’t realised existed before. It’s the result of a patient and painstaking effort to make the most internationally comparable estimate possible of household inequality, and involves modelling when needed to create predicted inequality based on the best indicators available.
First, download the data, bring it into R, and tidy it up from its wide format into a more analysis-friendly tidy or normalised form:
Let’s take a first look
OK, lots of lovely data, not a terribly attractive plot. Not informative either, having chopped off the legend. We should be able to do better than that.
One thing of interest might be which countries have seen the biggest changes over time. Restricting ourselves to just countries with data in 1963 (to make comparison valid), let’s have a go:
Here’s the code that constructed that plot:
This is obviously just the beginning. The countries have their ISO 3 character codes, which will make it easy to join them with other data for analysis. Maps are an obvious presentation step too, and Galbraith’s team look to make extensive use of the data for this purpose. Looking forward to a closer look when I’ve got more time.