Posts Tagged ‘cartogram’
A bit of shameless self-promotion! I will be presenting my work on trade cartograms at UseR! 2010. I’ll update this with a link to the abstract when it is listed there.
Earlier this year I posted on the use of cartograms to visualize dyadic trade flows.
useR! 2010, the R user conference, will take place at the Gaithersburg, Maryland, USA campus of the National Institute of Standards and Technology (NIST) from 2010-07-21 to 2010-07-23. Pre-conference tutorials will take place on July 20.
- R as the `lingua franca’ of data analysis and statistical computing,
- providing a platform for R users to discuss and exchange ideas how R can be used to do statistical computations, data analysis, visualization and exciting applications in various fields,
- giving an overview of the new features of the rapidly evolving R project.
As for the predecessor conferences, the program consists of two parts:
- invited lectures discussing new R developments and exciting applications of R,
- user-contributed presentations reflecting the wide range of fields in which R is used to analyze data.
A major goal of the useR! conference is to bring users from various fields together and provide a platform for discussion and exchange of ideas: both in the formal framework of presentations as well as in the informal part of the conference in Gaithersburg.
Prior to the conference, on 2010-07-20, there are tutorials offered at the conference site. Each tutorial has a length of 3 hours and takes place either in the morning or afternoon.
I gave a talk at the Fletcher School today on my work on dyadic trade flows (slides).
In a nutshell, the talk argues that cartograms and dendrograms can give students and practitioners a better understanding of the patterns of trade among partner contries, both for teaching and for research. We have thousands of observations of dyadic relationships in panel datasets. Most often these datasets are presented as aggregates: total annual world trade, top exporters in world trade, top exporters, top exporters in an industry sector, top exporters to a political union (such as the EU), top exporters within a geographic area, etc. What these statistics ignore is the information in the dyadic trade flows: who trades with whom?
What I offer is a way to crunch down the total number of country dyads into manageable graphics that can appear on a single slide. We can look directly at the dyadic patterns of trade using hierarchic clustering (dendrograms). We can compare partner trade flows across countries and time periods using cartograms. The techniques are not new; what is new is the presentation of rich international trade datasets in relatively complete format that can be digested by inspection, rather than with complex and poorly understood statistical techniques. Complete annual sets of cartograms and dendrograms give scholars the power to explore the distribution of dyadic trade and discover hypotheses that are worth testing more carefully, either with quantitative or qualitative methods.
One of the reasons trade courses have focused so much on models, theorems, and policy of international trade is that it is hard to describe trade patterns in any meaningful and comparable terms. My slides suggest how to do exactly that: present changes to global trade patterns in a succinct, visual format that enables rich comparisons across time and space.