<--- Back to Details
First PageDocument Content
Statistics / Estimation theory / Statistical theory / Regression analysis / Statistical inference / Statistical methods / Linear regression / Instrumental variable / Estimator / Asymptotic theory / Shrinkage estimator / M-estimator
Date: 2013-10-06 16:12:54
Statistics
Estimation theory
Statistical theory
Regression analysis
Statistical inference
Statistical methods
Linear regression
Instrumental variable
Estimator
Asymptotic theory
Shrinkage estimator
M-estimator

INSTRUMENTAL VARIABLES ESTIMATION WITH MANY WEAK INSTRUMENTS USING REGULARIZED JIVE CHRISTIAN HANSEN AND DAMIAN KOZBUR Abstract. We consider instrumental variables regression in models where the number of available instr

Add to Reading List

Source URL: www.n.ethz.ch

Download Document from Source Website

File Size: 543,48 KB

Share Document on Facebook

Similar Documents

On Rewriting Terms with Strict Functions and Error Propagation Olaf Owe Department of Informatics University of Oslo September 1990

On Rewriting Terms with Strict Functions and Error Propagation Olaf Owe Department of Informatics University of Oslo September 1990

DocID: 1rjs4 - View Document

Special Sessions Special Session 1: Qualitative Studies of PDEs: Entire Solutions and Asymptotic Behavior Peter Polacik, University of Minnesota, USA Eiji Yanagida, Tokyo Institute of Technology, Japan The aim of this se

Special Sessions Special Session 1: Qualitative Studies of PDEs: Entire Solutions and Asymptotic Behavior Peter Polacik, University of Minnesota, USA Eiji Yanagida, Tokyo Institute of Technology, Japan The aim of this se

DocID: 1riz8 - View Document

INSTRUMENTAL VARIABLES ESTIMATION WITH MANY WEAK INSTRUMENTS USING REGULARIZED JIVE CHRISTIAN HANSEN AND DAMIAN KOZBUR Abstract. We consider instrumental variables regression in models where the number of available instr

INSTRUMENTAL VARIABLES ESTIMATION WITH MANY WEAK INSTRUMENTS USING REGULARIZED JIVE CHRISTIAN HANSEN AND DAMIAN KOZBUR Abstract. We consider instrumental variables regression in models where the number of available instr

DocID: 1rgnG - View Document

Ann Inst Stat Math:469–490 DOIs10463Second-order asymptotic comparison of the MLE and MCLE of a natural parameter for a truncated exponential family of distributions

Ann Inst Stat Math:469–490 DOIs10463Second-order asymptotic comparison of the MLE and MCLE of a natural parameter for a truncated exponential family of distributions

DocID: 1reUL - View Document

An efficient analytical approach for solving fourth order boundary value problems Songxin Liang ∗ , David J. Jeffrey Department of Applied Mathematics, University of Western Ontario, London, Ontario, Canada, N6A 5B7

An efficient analytical approach for solving fourth order boundary value problems Songxin Liang ∗ , David J. Jeffrey Department of Applied Mathematics, University of Western Ontario, London, Ontario, Canada, N6A 5B7

DocID: 1rdZn - View Document