High-dimensional instrumental variables regression and confidence sets - v2/2012

12/29/2018
by   Eric Gautier, et al.
0

This was a revision of arXiv:1105.2454v1 from 2012. It considers a variation on the STIV estimator where, instead of one conic constraint, there are as many conic constraints as moments (instruments) allowing to use more directly moderate deviations for self-normalized sums. The idea first appeared in formula (6.5) in arXiv:1105.2454v1 when some instruments can be endogenous. For reference and to avoid confusion with the STIV estimator, this estimator should be called C-STIV.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
07/16/2021

Self-normalized Cramer moderate deviations for a supercritical Galton-Watson process

Let (Z_n)_n≥0 be a supercritical Galton-Watson process. Consider the Lot...
research
11/21/2018

High Dimensional Linear GMM

This paper proposes a desparsified GMM estimator for estimating high-dim...
research
12/21/2022

Partly Linear Instrumental Variables Regressions without Smoothing on the Instruments

We consider a semiparametric partly linear model identified by instrumen...
research
01/13/2022

Binary response model with many weak instruments

This paper considers an endogenous binary response model with many weak ...
research
06/28/2021

A Note on the Topology of the First Stage of 2SLS with Many Instruments

The finite sample properties of estimators are usually understood or app...
research
05/18/2022

Validation of a photogrammetric approach for the study of ancient bowed instruments

Some ancient violins have been reduced throughout their history. We prop...
research
12/07/2020

Mapping Leaf Area Index with a Smartphone and Gaussian Processes

Leaf area index (LAI) is a key biophysical parameter used to determine f...

Please sign up or login with your details

Forgot password? Click here to reset