Khatam University, Building No2.
Address: Mollasadra Blvd., North Shirazi St., East Daneshvar St., No.17.
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Dr. Nima Haghpanah
Assistant professor of Economics at Pennsylvania State University
Overview
Information design studies information disclosure policies and their effects on the payoffs of senders and receivers of information. In this short course, we provide an overview of information design, with an eye towards more applied work.We start with Bayesian Persuasion, which presented a framework for studying information design (Kamenica and Gentzkow, 2011). We then study two applications to markets. First, we study how a seller’s ability to price discriminate based on observable characteristics of consumers affects producer and consumer surplus (Bergemann, Brooks, and Morris, 2015). Second, we discuss whether or not consumers benefit from knowing their own preferences (Roesler and Szentes, 2017).
Biography
Nima Haghpanah is an assistant professor of Economics at Pennsylvania State University. Prior to that, he was a postdoctoral associate at MIT CSAIL and Sloan School of Management. He obtained his PhD in 2014 from Northwestern University. His dissertation was on optimal multi-parameter auctions, and his research interests are mechanism design, auction design, and game theory. Nima has received a best dissertation award from Northwestern University, and a graduate fellowship from the Simons Foundation.
Schedule
09:30 – 10:00 Opening
10:00 – 10:30 Introduction to the School
10:30 – 10:45 Coffee / Tea Break
10:45 – 12:00 Introduction to Statistics – Session 1
12:00 – 13:15 Lunch Break
13:15 – 14:15 Python Programming – Basics – Session 1
14:15 – 14:30 Coffee / Tea Break
14:30 – 15:30 Introduction to Statistics – Session 2
15:30 – 15:45 Coffee / Tea Break
15:45 – 16:30 Introduction to Statistics – Session 3
16:30 – 16:45 Coffee / Tea Break
16:45 – 17:45 Data Science in Practice Panel
09:30 – 10:00 Opening
10:00 – 10:30 Introduction to the School
10:30 – 10:45 Coffee / Tea Break
10:45 – 12:00 Introduction to Statistics – Session 1
12:00 – 13:15 Lunch Break
13:15 – 14:15 Python Programming – Basics – Session 1
14:15 – 14:30 Coffee / Tea Break
14:30 – 15:30 Introduction to Statistics – Session 2
15:30 – 15:45 Coffee / Tea Break
15:45 – 16:30 Introduction to Statistics – Session 3
16:30 – 16:45 Coffee / Tea Break
16:45 – 17:45 Data Science in Practice Panel
09:30 – 10:00 Opening
10:00 – 10:30 Introduction to the School
10:30 – 10:45 Coffee / Tea Break
10:45 – 12:00 Introduction to Statistics – Session 1
12:00 – 13:15 Lunch Break
13:15 – 14:15 Python Programming – Basics – Session 1
14:15 – 14:30 Coffee / Tea Break
14:30 – 15:30 Introduction to Statistics – Session 2
15:30 – 15:45 Coffee / Tea Break
15:45 – 16:30 Introduction to Statistics – Session 3
16:30 – 16:45 Coffee / Tea Break
16:45 – 17:45 Data Science in Practice Panel