William Ryan

I'm a PhD Candidate in Marketing at the Haas School of Business, UC Berkeley

I graduated Harvard with a BA in 2014. After graduation I worked at TGG Group, a behavioral economics consulting firm founded by Daniel Kahneman, Steve Levitt, and other academics and business leaders. While there I ran field experiments and did econometric analysis for businesses, governments, and non-profits. After leaving TGG, I completed a Post-Baccalaureate program in Psychology at UC Berkeley, working in  Anne Collin's Computational Cognitive Neuroscience Lab, before entering my PhD in Marketing, focused on Consumer Behavior, in 2019.

My research centers on how consumers make judgments and decisions in the marketplace. In particular, how they might err or fall prey to biases, and how these biases can be corrected. One of my primary research streams has been how consumers manage risky situations once they have entered into them. In my job market paper, I examine how people hedge to make a bad outcome less bad if it does occur (e.g., purchasing insurance/warranties, making backup plans in case plans fall through).  In another paper, I investigate how people spend time, money, or effort to increase their chances of a good outcome (e.g., investing more money into an ad campaign for a project launch, studying more for an upcoming test). 

You can get in touch at wryan@berkeley.edu or williamhryan@gmail.com 

My Google Scholar | My Open Science Foundation Page


Publications

(click the titles to see full text of papers)

People Behave as if they Anticipate Regret Conditional on Experiencing a Bad Outcome

Psychological Science (2024)

William H. Ryan*, Stephen M. Baum* (*co-first author) and Ellen R.K. Evers

Data, materials, preregistrations


Once and Again: Repeated viewing affects judgments of spontaneity and preparation

Psychological Science (2024)

Kristin Donnelly, William H. Ryan, and Leif Nelson

Data, materials, preregistrations


Poisson Regressions: A Little Fishy

Collabra: Psychology (2021)

William H. Ryan, Ellen R.K. Evers, and Don A. Moore

Data, materials, preregistrations


Graphs with Logarithmic Axes Distort Lay Judgments 

Behavioral Science & Policy (2020)

William H. Ryan and Ellen R.K. Evers

Data, materials, preregistrations


Crowdsourcing hypothesis tests: Making transparent how design choices shape research results

Psychological Bulletin (2020)

Justin Landy, ... , William H. Ryan & other members of the Crowdsourcing Hypothesis Tests Collaboration

Data, materials, preregistrations


Working Papers

People are (Shockingly) Bad at Valuing Hedges

William H. Ryan, Stephen M. Baum, and Ellen R.K. Evers

Data, materials, preregistrations


A Big Data and Experimental Investigation of Naturalistic Moral Dilemmas

William H. Ryan, Philipp Hadjimina, Clayton R. Critcher

(Email for draft)


There is a Collector in Every Consumer

Ellen R.K. Evers, William H. Ryan, and Siegwart Lindenberg 

(Email for draft)


No Evidence of Bias When Using Inappropriate Test for Bias: Comment on Cesario, Johnson, & Terrill 2018

William H. Ryan and Ellen R.K. Evers

A comment on this paper. For other critiques of this paper, as well as the authors' responses, see Joseph Cesario's website.




Media Coverage of Research

For People Behave as if they Anticipate Regret Conditional on a Bad Outcome

Berkeley Haas Newsroom; Berkeley Haas Magazine; APS Under the Cortex podcast interview


For Once and Again: Repeated viewing affects judgments of spontaneity and preparation

APS Observer

Utilities and Tools

This section is for small scripts which I made for myself and found useful, and thought might be helpful for others. 

Qualtrics Backup Script

I wrote a short script to make a backup of your Qualtrics account which downloads all the data and .qsf files for all of your surveys using the Qualtrics API.  Helpful to have in case you are, for example, switching institutions and are worried your data will not migrate over successfully. 

Illustrated Research Projects

Below are some images an AI generated when I gave it a sentence describing the key finding of one of the above projects. The description I used is below each image.  If you want to try this as well, I made a post on it. This section of the website was, it should be noted, created well before DALL-E and Midjourney released.

"Using Poisson regressions on count data results in a lot of false positives" 

"When anticipating regret people ask themselves, 'If I get a bad outcome, how often is it my fault?'" 

"When people view something multiple times they make judgments about it as though it actually happened multiple times"

"Collecting is very common, and collectors are mostly just normal people even though research on extreme collectors suggested otherwise" 

"Logarithmic axis graphs make COVID-19 data look less scary" 

"A bunch of researchers predicted the results of many experiments testing the same hypothesis, and were pretty good at it"