Khatam University, Building No2.
Address: Mollasadra Blvd., North Shirazi St., East Daneshvar St., No.17.
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Dr. Kaveh Majlesi
Associate Professor at the Department of Economics and Knut Wicksell Centre for Financial Studies at Lund University
Overview
This course offers a graduate level introduction to the field of Household Finance. In addition to providing an overview on the reasons behind the emergence of the field and important stylized facts, the course focuses in depth on selected topics, in particular, the determinants of households’ allocation of wealth in general and risky assets in particular and the consequences of debt and asset holding.
Biography
Kaveh Majlesi is an Associate Professor at the Department of Economics and Knut Wicksell Centre for Financial Studies at Lund University in Sweden. He has a PhD in Economics from the University of Texas at Austin and a Master’s degree in Public Administration from Harvard University. Kaveh’s research interests are in the areas of Household finance, Labor economics, and Labor and finance. His current research focuses on the effect of labor market shocks on different decisions made at the firm, household and individual levels as well as the determinants and consequences of asset holding and portfolio choice.
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