A big part of economics is data analysis, which starts with data visualization: “seeing like an economist” means looking for patterns across many observations, recognizing that the data we see result from peoples’ choices. In class we practice this through weekly exercises and a course project that start with analytical diagrams (such as supply and demand curves) to show the logic by which we explain each observation, and then download data from authoritative sources to make our own charts and tables that summarize what’s been observed.
This blog post pulls together a few suggestions and links about data visualization for convenient reference. The dataverse of available information is expanding rapidly, with increasingly sophisticated expectations about data visualization. That complexity can be daunting, making it hard to get started. My vote for best quick advice about data is to keep it simple, as explained in great posts about how to clear off the table and remove to improve. Those start with bad examples and show how to clean things up and avoid numbo-jumbo.
Successful data visualizations help you tell a story, by making comparisons that highlight both similarities and differences. Charts and tables offer a kind of language designed to help us communicate clearly. The grammar of this language is nicely explained here: http://abacus.bates.edu/~ganderso/biology/resources/writing/HTWtablefigs.html. Change over time is usually best shown with line graphs like Figure 1 of that page, while differences among categories is usually best shown with bar charts that are sorted by magnitude, and a cloud of individual observations is best shown by a scatter plot. It’s useful and fun just to browse through the different charts presented here: http://www.ers.usda.gov/data-products/chart-gallery.aspx, and also click through https://www.ers.usda.gov/data-products/data-visualizations. Other thoughtful guides to making scientific charts and tables include: http://guides.library.duke.edu/datavis/topten and https://www.statisticsauthority.gov.uk/gsspolicy/effective-graphs-and-tables-in-official-statistics.
Your final reports and presentations weave together a sequence of charts and tables. To keep things straight, all figures (whether an analytical diagram or a chart of data) should be numbered consecutively as Figure 1, 2, 3…, and all tables should be numbered separately as Table 1, 2, 3… Each should have a clear title and note describing the nature and source of all data shown in the chart or table, so that a future reader could replicate or update your visualization in the future. Different fields use different conventions about table or figure titles and footnotes, and have preferred visual styles for how things are presented. In general, economics and other social sciences use brief titles above the chart and detailed notes below it, while many health science readers expect a single long figure caption that combines both kinds of information. Examples from my own recent papers include one in health economics style (title and footnote), and one in health-science style (a long caption)
For oral presentation, your charts and tables should appear in ways that help you tell the story. There are many good guides to using PowerPoint effectively, of which one of my favorites is from a prominent biologist named Susan McConnell: https://www.ibiology.org/professional-development/designing-effective-scientific-presentations.
And finally, if you’re interested in guides to writing in general, my favorite is Steven Pinker’s Sense of Style — especially for his brilliant description of how all communication requires effort to overcome the curse of knowledge, in part by chunking information into digestible units which you can then bundle up into increasingly powerful stories. I look forward to seeing how you put your pieces together!
- Politico – US food & ag policy
- Ag2nut – international nutrition
- Chicago Council – global food & ag
- Keith Good – US farm policy
- New Food Economy – US focused
- Food Safety News
- Danielle Nierenberg’s Food Tank
- Gro Intel – deep dives into data
- FERN’s ag insider news
- Boston Network for Intl. Dev.
- Econofact – US economic policy
- Rudd Center – obesity policy
- David Allison – obesity research
- Parke Wilde – food policy
- Jess Fanzo – food systems
- Marc Bellemare – ag & food econ
- Chris Blattman – dev econ
- Jayson Lusk – ag & food econ
- Diane Coyle – economics books
- Marion Nestle – food politics
- Tamar Haspel – food & ag
- World Bank – impact evaluation
- BITSS – research methods
- Econofact – US econ policy
- Susan Dynarski – education policy
- USDA Economic Research Service (ERS) data
- NCCOR – all US food-health data
- World Bank data
- FAO Statistics (FAOSTAT)
- UNICEF statistics
- WHO – child heights and weights
- UN system data
- Famine Early Warning (FEWSNET)
- The dataverse
- IHSN – household surveys
- IPUMS – accessible data (incl. IDHS)
- Euromonitor – branded foods (library subscription)
- Gro Intelligence data