Evaluation and the causal revolution

Content for Thursday, January 12, 2023

Readings

• The syllabus, content, examples, and assignments pages for this class
• Chapter 1 in Impact Evaluation in Practice (Gertler et al. 2016)
• Chapters 1 and 2 in The Effect (Huntington-Klein 2021)
• DJ Patil, “What Makes a Radical and Revolutionary Technology?”
  • (DJ Patil is the former Chief Data Scientist of the United States under President Obama. He gave this forum address at Brigham Young University on February 13, 2018.)
• Stephen Goldsmith, “Next Generation of Public Employees Must Understand Data and Policy”
• Hadley Wickham, “Data Science: How is it Different To Statistics?”

Slides

Warning

Important!!: In the “Class details” video, I say that there are three books for the class: the World Bank evaluation book, ’Metrics Matter, and Causal Inference: The Mixtape. That’s not the case this semester, since we’re using the new The Effect book, which replaces both ’Metrics Matter and the Mixtape. So ignore that part of the video. The slides are updated with the correct books, though: see here.

The slides for today’s lesson are available online as an HTML file. Use the buttons below to open the slides either as an interactive website or as a static PDF (for printing or storing for later). You can also click in the slides below and navigate through them with your left and right arrow keys.

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Introduction

Data science and public service

Evidence, evaluation, and causation (1)

Evidence, evaluation, and causation (2)

Class details

Tip

Fun fact: If you type ? (or shift + /) while going through the slides, you can see a list of special slide-specific commands.

Videos

Warning

Important!!: In the “Class details” video, I say that there are three books for the class: the World Bank evaluation book, ’Metrics Matter, and Causal Inference: The Mixtape. That’s not the case this semester, since we’re using the new The Effect book, which replaces both ’Metrics Matter and the Mixtape. So ignore that part of the video. The slides are updated with the correct books, though: see here.

Videos for each section of the lecture are available at this YouTube playlist.

• Introduction
• Data science and public service
• Evidence, evaluation, and causation (1)
• Evidence, evaluation, and causation (2)
• Class details

You can also watch the playlist (and skip around to different sections) here:

In-class stuff

Here are all the materials we’ll use in class:

• Session 1 in-person slides (PDF)

RStudio labs:

• RStudio.cloud project
• Project .zip file
• Lab slides 1: Markdown and universal writing (PDF)
• Lab slides 2: Getting started with R and RStudio (PDF)
• Lab slides 3: Data basics (PDF)
• Lab slides 4: Visualize data with ggplot2 (PDF)
• Lab slides 5: Transform data with dplyr (PDF)

References

Gertler, Paul J., Sebastian Martinez, Patrick Premand, Laura B. Rawlings, and Christel M. J. Vermeersch. 2016. Impact Evaluation in Practice. 2nd ed. Inter-American Development Bank; World Bank. https://openknowledge.worldbank.org/handle/10986/25030.

Huntington-Klein, Nick. 2021. The Effect: An Introduction to Research Design and Causality. Boca Raton, Florida: Chapman and Hall / CRC. https://theeffectbook.net/.