Choosing the Optimal Set of Instruments from Large Instrument Sets
AbstractIt is well known that instrumental variables (IV) estimation is sensitive to the choice of instruments both in small samples and asymptotically. Recently, Donald and Newey (2001) suggested a simple method for choosing the instrument set. The method involves minimising the approximate mean square error (MSE) of a given IV estimator where the MSE is obtained using refined asymptotic theory. An issue with the work of Donald and Newey (2001) is the fact that when considering large sets of valid instruments, it is not clear how to order the instruments in order to choose which ones ought to be included in the estimation. The present paper provides a possible solution to the problem using nonstandard optimisation algorithms. The properties of the algorithms are discussed. A Monte Carlo study illustrates the potential of the new method.
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Bibliographic InfoPaper provided by Queen Mary, University of London, School of Economics and Finance in its series Working Papers with number 534.
Date of creation: May 2005
Date of revision:
Instrumental Variables; MSE; Simulated Annealing; Genetic Algorithms;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-05-23 (All new papers)
- NEP-CMP-2005-05-23 (Computational Economics)
- NEP-ECM-2005-05-23 (Econometrics)
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