An instrumental variable approach to dynamic models
Date: 10/25/2018 (Thu)
Time: 3:30pm- 5:00pm
Location: Seminar will be held on-site: Social Sciences room 113
Organizer: Adam Rosen
Meeting Schedule: Login or email the organizer to schedule a meeting.
All meetings will be held in the same location as the seminar unless otherwise noted.
8:45am - Adam Rosen (pickup from Washington Duke Inn)
9:30am - Andrew Patton @228F
10:00am - Matt Masten
10:30am - Francesca Molinari
11:00am - Yanyou Chen
11:30am - Gaurab Aryal
12:00pm - Lunch: Steven, Matt, Allan, Pat
1:00pm - Allan Collard-Wexler
1:30pm - Tiancheng Chen
2:00pm - Valentin Verdier (UNC, @visitor's office)
2:30pm - Federico Bugni @ 240
3:00pm - Seminar Preparation
3:30pm - Seminar Presentation (3:30pm to 5:00pm)
5:00pm - Jia Li @ 228G
5:30pm - Matthias Kehrig
6:15pm - Dinner at Mateo. Steven, Adam, Jimmy, Francesca.
Additional Comments: with Giovanni Compiani (Berkeley, Haas School of Business). Abstract: We present a new class of methods for the identification and estimation of dynamic models with serially correlated unobservables, which typically imply that state variables are econometrically endogenous. In the context of Industrial Organization, these state variables often reflect econometrically endogenous market structure. We propose the use of Generalized Instrumental Variables methods to identify those dynamic policy functions that are consistent with instrumental variable restrictions on unobserved states. Extending popular ``two-step'' methods, these policy functions then identify the structural parameters of the dynamic model. We provide simulated examples as well as an illustrative empirical analysis.