Tim Christensen - NYU
Nonparametric value functions and term structures Many contemporary macro/finance models feature agents with recursive preferences or robust preferences. These models present a challenge for conventional semi/nonparametric estimation techniques such as GMM, as the pricing kernel is a function of the continuation value of the future consumption plan, which is unobservable when state dynamics are modeled flexibly. We describe sieve procedures for estimating the value function in models with recursive or robust preferences. The procedures solve a nonparametric fixed-point problem that is different from the usual Bellman equation obtained under time-separable preferences. To improve the finite-sample properties of the estimator, we introduce a new nonparametric regression procedure for estimating the conditional mean of a positive stochastic process. We apply the methodology to analyze the term structure of equity allowing for general nonlinear state dynamics.
Date: 11/10/2016 (Thu)
Time: 3:30pm- 5:00pm
Location: Seminar will be held on-site: Social Sciences room 113
Organizer: Jia Li, Ph.D.
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.
9:00am - Luis Candelaria Pickup, Breakfast
10:00am - Jia Li
10:30am - Adam Rosen @ 221B
11:00am - Tim Bollerslev
11:30am - Andrew Patton
12:00pm - Lunch with Andrew Patton, Federico Bugni
1:30pm - Federico Bugni @ 240
2:00pm - George Tauchen
2:30pm - Red Davies
3:00pm - Seminar Prep
3:30pm - Seminar Presentation (3:30pm to 5:00pm)
6:00pm - Dinner with Jia, Tim Bollerslev at M Sushi