Data Visualization

Data visualization is a crutial tool in applied economics, to explore, diagnosize and communicate.

Date

October 8, 2025

Objective

This session aims to help you develop essential skills for effective data visualization and a better understanding of its usefulness when it comes to applied econometrics analyses.

Summary

A significant portion of communicating economic research results-whether in presentations or written papers—relies on graphs and visuals. This field is largely studied outside of economics and builds on key principles that we explore and discuss in this session. Overall, being aware of these principles, of general hurdles, of best practices and of do’s and don’ts allow to build effective visualizations and can serve and improve applied economics analyses. Similarly, being aware of the different types of existing graphs and their relative strengths and weaknesses allow to pick the type of graph that enables making the specific point one wants across. Data viz are also instrumental to econometrics studies and this session discusses how we can harness its power to improve our applied economic analyses. Overall, data viz help you understand your data, test your identifying and modelling assumptions, communicate results.

Session Outline

Introduction: data viz can be instructive, deceptive, memorable
Why is data viz important?
- Usefulness: when and why use it?
  - Understand your data
  - Test your identifying and modelling assumptions
  - Communicate results
- But need to be careful because can also be deceptive
Key data viz principles
- Perception principles
- Avoid clutter
- Why make nice looking visuals?
Building a graph
- Choosing the right type of graph
- Concrete tips and recommendations
- Inspiration through examples of nice data viz
Data viz for research in economics
- Data viz in the various steps of analyses:
  - Rhetoric
  - Explore
  - Check assumptions (identifying and on model form)
  - Diagnostics
  - Communicate
- Specifics
Main take-away points

Materials

Open slides in html

Open slides in PDF

Specific resources for this lecture

Handbooks

Here is a short list of useful applied data visualization handbooks:

Fundamentals of Data Visualization provides a great code-free introduction to data viz.¹
Modern Data Visualization with R and Data Visualization - A practical introduction both discuss key data viz concepts and teaches you how to apply them in R and ggplot.
R for Data Science provides a nice introduction to ggplot, THE package to build plots in R. To go further you can read this book.

Additional resources

There are massive amount of resources on data viz. Here is a subset, based on the lecture outline:

Introduction
Usefulness and importance
- Explore and explain
  - Why looking at data?
  - Existing tools for exploratory data analysis in R
- Deceptive visualizations
  - Defense against dishonest charts
Key data viz principles
- Perception and color
  - More on Gestalt principles (plus a research article)
  - How to find and create good color palettes on
- Data-to-ink ratio
  - A critique of the data-to-ink ratio
- Aesthetics
Building a graph
- Graph galeries
- What questions to ask when creating charts
- Decision trees for a graph type
- Concrete recommendations
  - For color
  - For text
- Specific do’s and don’ts
Data viz for research in economics
- When do we use graphs in econ?
- Specificities of viz in econ
Main take-away messages

Footnotes

Although R code can be found on the book’s GitHub if needed.↩︎