Part II in a series. Read part I.
In my last post, I introduced the slopegraph, a fun ‘new’ kind of chart from 1983. My first attempt didn’t quite live up to my expectations, so I’m trying again today with some more fresh and interesting data from Bill Easterly and Ariell Reshef’s working paper on African export successes. This data is actually so perfect for the slopegraph format (which focuses on both rank order and relative rate of change) that the original paper used a sort of proto-slopegraph to show how rankings of some African countries’ top export goods had been reordered. But it’s not only the characteristics of the data that make slopegraphs interesting in this context — it’s the role of chart-making in the construction of a narrative, which is the aspect I want to focus on today. To keep things simple, I’m going to use only one example, their export data and related chart for Tanzania:
Figure 1: Original ‘Tanzania Top Ten’ chart
No offense to whoever put these together — it is a working paper after all — but the charts in the original contain a lot of what data nerds would call ‘chartjunk,’ or unnecessary graphics and information. The preference for beautiful, minimalist charts is not just aesthetic chauvinism: while nice looking charts are, of course, nice to look at, there is a more important issue here. Chartjunk imposes a real cognitive burden on readers, which actually makes it harder for them to understand the chart’s message. Professional academics and researchers will be able to chew through the gristle and get at the meat, but of all the economic specialties, development economics probably has one of highest proportions of non-technical readers — notably development practitioners, policy makers, and advocacy groups. For this reason, minimizing unnecessary cognitive burden in development papers is especially important. This is equally true of working papers, since practitioners, politicians, and advocates will rarely wait for peer review to disseminate, digest, and discuss a new research finding.
I do think that the ‘throw everything in’ tendency that academics have when making charts arises from a laudable desire to fully disclose all the data on which they are basing their arguments, so that their peers can potentially spot inconsistencies or contradictions. I would say that this data should be included, but as an appendix. Charts form a part of the argument of the paper, and so should be tuned to focus on those aspects that the author considers important or notable.
(Read on to find out how I tried to ‘fix’ this funky-looking chart…)
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