Arbeitspapier
Choosing the optimal set of instruments from large instrument sets
It 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.
- Language
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Englisch
- Bibliographic citation
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Series: Working Paper ; No. 534
- Classification
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Wirtschaft
Hypothesis Testing: General
Statistical Simulation Methods: General
Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models
- Subject
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Instrumental Variables, MSE, Simulated Annealing, Genetic Algorithms
Instrumentalvariablen-Schätzmethode
- Event
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Geistige Schöpfung
- (who)
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Kapetanios, George
- Event
-
Veröffentlichung
- (who)
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Queen Mary University of London, Department of Economics
- (where)
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London
- (when)
-
2005
- Handle
- Last update
-
10.03.2025, 11:44 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Kapetanios, George
- Queen Mary University of London, Department of Economics
Time of origin
- 2005
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