Final published version, 540 KB, PDF document
Research output: Working paper
Research output: Working paper
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TY - UNPB
T1 - Higher Order Approximation of IV Estimators with Invalid Instruments
AU - Kang, Byunghoon
PY - 2018/12
Y1 - 2018/12
N2 - This paper considers the instrument selection problem in instrumentalvariable (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.
AB - This paper considers the instrument selection problem in instrumentalvariable (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.
KW - Instrument selection
KW - Invalid instruments
KW - Many instruments
KW - 2SLS
KW - LIML
KW - Fuller estimator
KW - Bias-adjusted 2SLS
M3 - Working paper
T3 - Economics Working Papers Series
BT - Higher Order Approximation of IV Estimators with Invalid Instruments
PB - Lancaster University, Department of Economics
CY - Lancaster
ER -