Behavioral Economics Schedule

Week 11: Happiness and Utility

Tuesday 9 April



Thursday 4 April

Week 2: Policy and Manipulation

Tuesday 16 April

Thursday 18 April

  • I hope we can do an exercise with the World Values survey here for Lab6, but I may defer that if I think you need more time for your team projects.

Week 1: Introduction

Thursday 24 January

  • What is Economics about? How does it inform policy?
  • What is Behavioral Economics about? How might it inform policy?
  • The results of in-class question about behavioral economics will appear here


  • Behavioral Economics for Kids here
  • Alm, James, 2017, “Presidential Address: Is economics useful for public policy”, Southern Economic Journal, 83 (4), 835–854 (16 pages)
    • Why read this? I want to convince you, first, that economics itself is useful for informing policy decisions and, second, that behavioral economics is at least as useful too in informing policy-makers on how to construct policy too. But, we mustn’t throw out the baby with the bathwater: “economics” and “behavioral economics” must be used appropriately.


  • The Behavioral Economics Guide 2016, available here.
    • The BE Guide is useful for you to get a broad sense of what we do in Behavioral Economics and what kinds of ideas you might want to research in your team project.


Transparency and Integrity in Research


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Week 2: Heuristics & Biases

Tuesday 29 January


  • Cartwright Chapter 2: To the end of section 2.5.
  • Rabin, Matthew, 2002, “A Perspective on Psychology and Economics”, European Economic Review, 46 (4-5): 657-685.
    • This Rabin paper is a lovely and not too technical introduction to many of the important ideas in behavioral economics. Some of the ideas will only become clear later in the course, but don’t worry we shall get there later.


  • BFH Chapter 3: Doing the best you can


  • Rabin, Matthew, 1998, “Psychology and Economics,” Journal of Economic Literature, Vol 36 (1): 11-46.
    • This is a much more technical approach than the Rabin paper above, but potentially useful depending on what you plan to do for your project.


Thursday 31 January

Today we shall do

  1. Go to and log on to ensure that you have access to the RStudio server.
  2. One you have done that, start a new R Notebook file clicking on File -> New -> R Notebook.
  • Go here: Lab1
  • Access the cheat sheets from RStudio Help -> Cheatsheets -> [Select the Cheatsheet you want]

If we have time, we’ll do this set of decisions in an experiment:



  • BH, Chapter 1.

Week 3: Risk

Tuesday 5 February



  • BFH Chapter 13: A Risky and Unequal World.

Thursday 7 February

Homework Once you’re comfortable with the server, do the following. On your laptop, follow these steps to install R and the latest version of RStudio. Make sure to install R and LaTeX first!

  1. Download and install R here:
  2. Download and install LaTeX here:
  3. Download and install R Studio here:

We will use these documents as guides, for some of them you will need to log in to Moodle:

Watch these videos by Nick Horton (Amherst College) as an introduction to R markdown if you want more revision:

Prof Horton also has some videos about starting out with R:

Week 4: Risk

Tuesday 12 February


  • Cartwright Chapter 3, Section 3.6 (don’t read further than 3.6)
  • George Loewenstein et al, 2001., “Risk as Feelings,” Psychological Bulletin, Vol 127 (2): 267-286. (15 pages)
  • Make sure you’ve also read the Kahneman & Tversky paper from last week.
  • We shall spend time finishing up to the end of 3.5, briefly discuss 3.6, then switch to the two papers.

Other Notes

  • Check here for the notes on Bayes’ Rule and understanding expected utility changes: bayes_rule.

Thursday 14 February

  • We shall work on in Lab 3 today after checking in about Lab 2.

Week 5: Time

Tuesday 19 February



  • Cass Sunstein, “Why Ebola Is Scarier Than It Should Be,” Bloomberg, 2014.

Thursday 21 February

ggplot Exercise

We are going to do an exercise where we use ggplot to try to reproduce at least one graphic from a published paper. The paper is:

Working with the data

  • We will follow what to do at Lab4
  • You will notice that the data is not glyph-ready and it also isn’t that tidy.
  • Ideally, we would work with the spreadsheet as is and import it into R. We’re not going to do that, but will create different spreadsheets with different data and then import them into R.

Team Projects

  • The teams are here: project teams Spring 2019
  • I want you to emphasize the following steps:
    • making sure you have data to work with (to bring to later class sessions)
    • deciding on the literature with which your project fits to produce a literature review
    • (later) thinking about the ways in which you can alter/improve on the existing experiments/surveys to improve our overall knowledge

Week 6: Time concluded

Tuesday 26 February



Week 7: Learning & Information

Tuesday 5 March


  • Textbook & Lab notes
  • Cartwright, Chapter 5 up to the end of Section 5.4 (feel free to exclude Section 5.3.4. if you’re struggling to understand it as it may employ game theory you have not done)

Catch-up on groups & on learning articles: - Sundali and Croson, 2006, “Biases in casino betting: The hot hand and the gambler’s fallacy,” Judgment and Decision Making, Vol 1 (1): 1-12 (11 pages)

Thursday 7 March

Week 8: Fairness and Social Preferences

Do people only worry about their own consumption or their own money, or are they concerned (in prosocial or antisocial ways) about what others get? If they do care, what do their preferences look like? Are they altruistic? Are the reciprocal? What experiments do we use to check this and how can we understand the breadth of these preferences?

Tuesday 19 March



  • Kusum Ailawadi and Paul Farris, “How Companies Can Get Smart About Raising Prices,” Wall Street Journal, 2013. See also: Four Barrel.
  • The rise of the sharing economy,” Economist, 2013.



  • BFH Chapter 2

Thursday 21 March

  • Presentations

Week 9: Fairness and Social Preferences (contd.)

Tuesday 26 March

See readings for Week 9. We focused on the slides. I’ll look at readings a bit next week if we have time.

Thursday 28 March

We’re going to spend some time learning about ifelse() today to make sure everyone is comfortable with how it can be used to create new and useful variables.

  • Go to this new lab: lab_extras
  • We will also look at how to do citations in R Markdown at the citations page.

Week 10: Gender and Preferences

Tuesday 2 April

  • Gender – See readings on Moodle

Thursday 4 April

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