We are pleased to invite you to the talk at the Max Planck Institute for Human Development on February 25 at 11:00 am CET. Prof. Dr. Florian Artinger - Head of the B.A. in Digital Business & Management at Berlin International and Perke Jacobs, doctoral candidate at the Max Planck Institute for Human Development, will talk about „How do taxi drivers plan their shifts when earnings are hard to predict?“.
About the talk
A fundamental assumption of expected utility models is that agents make predictions by formulating rational expectations. Building on this assumption, the literature has addressed to what extent neoclassical or behaviorally informed utility models best describe intertemporal substitution of labor and leisure, focusing on the taxi market. Using data from 10 million taxi trips, we find that hourly earnings are barely predictable. Under such uncertainty, satisficing models predict behavior of drivers better than utility models. These models do not require calculating expected earnings and terminate shifts when reaching an aspiration level on shift duration or earnings.
Join the event and get inspired!
The talk is open to everyone and will be held online.
Click here to attend the talk on Thursday, February, 25th at 11:00 am CET.
Please send an email to Izabela Ahmad at firstname.lastname@example.org to receive password for the event.
About Prof. Dr. Florian Artinger
Prof. Dr. Florian Artinger is a professor at Berlin International University of Applied Sciences, where he heads the Digital Business & Management B.A. program, co-founder and managing partner of Simply Rational - The Decision Institute, and associated scientist at the Max Planck Institute for Human Development. His work combines research, teaching, and consulting on human behavior and machine learning.
About Perke Jacobs
Perke Jacobs is a doctoral candidate at the Max Planck Institute for Human Development. Moreover, he is an economist at the German Federal Chancellery. Previously, he studied statistics, economics, and psychology at Maastricht University, UCSD, and Tilburg University, and worked as a data scientist. His research interests include ecological rationality, machine learning, public policy and labor economics.