STICERD Econometrics Seminar Series
Kernel Estimation for Dyadic Data
James Powell (UC Berkeley), joint with Bryan S. Graham and Fengshi Niu
Thursday 23 May 2019 14:15 - 15:45
32L 2.04, 2nd Floor Conference Room, LSE, 32 Lincoln's Inn Fields, London WC2A 3PH
Many of our seminars and public events this year will continue as online seminars or as online and in person. Please check our website listings and Twitter feed @STICERD_LSE for updates.
Unless otherwise specified, current restrictions mean in-person seminars are only open to members of the LSE community (those with a valid LSE ID card).
Those unable to join the seminars in-person are welcome to participate via zoom.
About this event
In this forthcoming working paper we consider nonparametric estimation of density and conditional expectation functions for dyadic random variables, i.e., random variables defined for all pairs of individuals/nodes in a network of size N. These random variables are assumed to satisfy a “local dependence” property, specifically, that any random variables in the network that share one or two indices may be dependent (though random variables which do not have an index in common are assumed to be independent). Estimation of density functions for continuously-distributed random variables or regression functions for continuously-distributed regressors are proposed using straightforward application of the kernel estimation methods proposed by Rosenblatt and Parzen (for densities) or by Nadaraya and Watson (for regression functions). Estimation of their asymptotic variances is also straightforward using existing proposals for dyadic data. More unusual are the rates of convergence and asymptotic (normal) distributions for the estimators, which are shown to converge at the same rate as the (unconditional) sample mean, i.e., the square root of the number N of nodes, under standard assumptions on the kernel method. This differs from the results for nonparametric estimation of densities and regression functions for monadic data, which generally have a slower rate of convergence than the sample mean.
STICERD Econometrics seminars are held on Thursdays in term time at 14.00-15.30, ONLINE, unless specified otherwise.
For further information please contact Lubala Chibwe, either by email: firstname.lastname@example.org.
Please use this link to subscribe or unsubscribe to STICERD Econometrics mailing list (emetrics).
This event will take place in 32L 2.04, 2nd Floor Conference Room, LSE, 32 Lincoln's Inn Fields, London WC2A 3PH. The building is labelled on the map.