Cooling schedules for optimal annealing
Mathematics of Operations Research
On the Convergence and Applications of Generalized Simulated Annealing
SIAM Journal on Control and Optimization
Factor-GMM estimation with large sets of possibly weak instruments
Computational Statistics & Data Analysis
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It is well known that instrumental variables (IV) estimation is sensitive to the choice of instruments both in small samples and asymptotically. Recently, a simple method has been suggested in the literature 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 this method 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. A possible solution to the problem using nonstandard optimisation algorithms is provided. The properties of the algorithms are discussed. A Monte Carlo study illustrates the potential of the new method.