Template-Type: ReDIF-Paper 1.0
Author-Name: Byunghoon Kang
Author-Name-First: Byunghoon
Author-Name-Last: Kang
Title: Higher Order Approximation of IV Estimators with Invalid Instruments
Abstract: This paper considers the instrument selection problem in instrumental<br/>variable (IV) regression model when there is a large set of instruments with potential invalidity. I derive higher-order mean square error (MSE) approximation of two-stage least squares (2SLS), limited information maximum likelihood (LIML), Fuller (FULL) and bias-adjusted 2SLS (B2SLS) estimators with allowing for local violation of the instrument-exogeneity conditions. Based on the approximation to the higher-order MSE, I propose instrument selection criteria that are robust to potential invalidity of instruments. Furthermore, I also show the optimality results of instrument selection criteria in Donald and Newey (2001, Econometrica) under faster than N^(-1/2) locally invalid instruments specication.
Creation-Date: 2018
File-URL: http://www.lancaster.ac.uk/media/lancaster-university/content-assets/documents/lums/economics/working-papers/LancasterWP2019_001.pdf
File-Format: application/pdf
Number: 257105320
Classification-JEL: 
Keywords: Instrument selection, Invalid instruments, Many instruments, 2SLS, LIML, Fuller estimator, Bias-adjusted 2SLS
Handle: RePEc:lan:wpaper:257105320