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Local influence analysis for GMM estimation

Author

Listed:
  • Jun Lu

    (Yunnan University of Finance and Economics)

  • Wen Gan

    (Yunnan University of Finance and Economics)

  • Lei Shi

    (Yunnan University of Finance and Economics
    Shanghai Lixin University of Accounting and Finance)

Abstract

The generalized method of moments (GMM) is an important estimation procedure in many areas of economics and finance, and it is well known that this estimation is highly sensitive to the presence of outliers and influential observations. Case-deletion diagnostic has been studied in GMM estimation; however, it is surprised that local influence analysis is under explored. To this end, a local influence method is proposed to assess the effect of minor perturbation on GMM estimation. The local diagnostic measures of GMM estimators under the perturbations of empirical distribution and moment condition are derived to study the joint influence of observations. The obtained results are applied to efficient instrumental variable estimation and dynamic panel data model. Two real data sets are used for illustration, and a simulation study is conducted to examine the effectiveness of the proposed methodology. The advantage of local influence method is analyzed in detail through comparison with the case-deletion method.

Suggested Citation

  • Jun Lu & Wen Gan & Lei Shi, 2022. "Local influence analysis for GMM estimation," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(1), pages 1-23, March.
    • Handle: RePEc:spr:alstar:v:106:y:2022:i:1:d:10.1007_s10182-021-00398-5
    DOI: 10.1007/s10182-021-00398-5
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    References listed on IDEAS

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