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Data mining and the selection of instruments

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  • Alastair Hall
  • Fernanda Peixe

Abstract

Instrumental variables estimation is widely applied in econometrics. To implement the method, it is necessary to specify a vector of instruments. In this paper, it is argued that there are compelling reasons to use the data for instrument selection, but that it is desirable to ensure the resulting estimator still behaves in the way predicted by standard textbook theory. These arguments lead one to propose three criteria for data based instrument selection. The remainder of the paper assesses the extent to which these criteria are met by two algorithms for data based instrument selection. The first algorithm is the method of structurally ordered instrumental variables proposed in the context of economy-wide linear simultaneous equation models. The second algorithm is proposed in the context of the method of generalized instrumental variables, which is commonly used to estimate the parameters of Euler equation models.

Suggested Citation

  • Alastair Hall & Fernanda Peixe, 2001. "Data mining and the selection of instruments," Journal of Economic Methodology, Taylor & Francis Journals, vol. 7(2), pages 265-277.
    • Handle: RePEc:taf:jecmet:v:7:y:2001:i:2:p:265-277
    DOI: 10.1080/13501780050045128
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    References listed on IDEAS

    as
    1. Alastair R. Hall & Fernanda P. M. Peixe, 2003. "A Consistent Method for the Selection of Relevant Instruments," Econometric Reviews, Taylor & Francis Journals, vol. 22(3), pages 269-287, January.
    2. Fernanda Peixe & Alastair Hall & Kostas Kyriakoulis, 2006. "The Mean Squared Error of the Instrumental Variables Estimator When the Disturbance Has an Elliptical Distribution," Econometric Reviews, Taylor & Francis Journals, vol. 25(1), pages 117-138.
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