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Instrumental Variables Estimation in Large Heterogeneous Panels with Multifactor Structure

Author

Listed:
  • Forchini Giovanni

    (Department of Economics, Umeå University, Umea, Sweden)

  • Jiang Bin

    (Department of Econometrics and Business Statistics, Monash University, Australia)

  • Peng Bin

    (Department of Economics, University of Bath, UK)

Abstract

The paper proposes new instrumental variables estimators for the slope parameters of a panel data model with classical endogeneity in which all the observables – including the instruments – may have a common factors structure. These estimators are shown to be consistent and asymptotically normal under weak regularity conditions. A small Monte Carlo simulation shows that these estimators compare favourably to existing estimators.

Suggested Citation

  • Forchini Giovanni & Jiang Bin & Peng Bin, 2020. "Instrumental Variables Estimation in Large Heterogeneous Panels with Multifactor Structure," Journal of Econometric Methods, De Gruyter, vol. 9(1), pages 1-22, January.
    • Handle: RePEc:bpj:jecome:v:9:y:2020:i:1:p:22:n:3
    DOI: 10.1515/jem-2018-0003
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    References listed on IDEAS

    as
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