20
Jun
2019
Trainings
Projection Bias, Beliefs and Learning
with Assistant Professor Marc Kaufmann (Dep. of Economic and Business, Central European University)
Maison des Sciences Humaines
11, Porte des Sciences
L-4366 Esch-sur-Alzette/Belval
LISER- MSH 1st floor conference room
09:00 am
11:30 am
For inquiries:
trainings@liser.lu

20th June Thursday 9-11.30h 

Projection Bias (2-3 hours)

In this workshop, projection bias will be defined and its evidence highlighted. The model of Loewenstein, O'Donoghue, and Rabin (2003) will be formalized and it will be shown how to employ it in two specific use cases: decisions over work and rest, as well as migrants' decisions of returning to their home country. Finally, some implications of projection bias in these two cases will be illustrated and, time permitting, it will be discussed how projection bias can be identified empirically.

24th June Monday 14 - 16.30h

Present Bias, Beliefs, and Learning (2-3 hours)

This workshop consists of two halves. In the first half, the naive and sophisticated model of present bias is introduced and an overview of economically important situations given where this matters. Some recent work on present bias and related topics will be highlighted. In the second half, recent literature on how to measure subjective beliefs and expectations will be discussed. Beliefs measurement has been neglected, given that it constitutes one of the three main features of individual decision making, along with preferences and constraints. A conclusion will be drawn on how to use beliefs measurements to help identify projection bias and present bias.

Marc Kaufman is an Assistant Professor at the Department of Economics and Business at Central European University.He graduated from Harvard University with a PhD in Economics in 2017, and specializes in applied theory in what will soon be what was used to be known as behavioral economics. His current research projects center around projection bias and narrow bracketing, including experimentally measuring these biases, as well as exploring how they affect work and study decisions, with a focus on implications for education and personnel management.