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GMM estimation of panel data models with time-varying slope coefficients


  • Yoshihiro Sato
  • Måns Söderbom


A difference/system generalized method of moments (GMM) model that imposes time-constant coefficients is common in empirical studies using panel data. However, a rejection by the Sargan–Hansen test is sometimes a serious concern for researchers. We highlight the fact that the Sargan–Hansen test for GMM estimators applied to panel data is a joint test of valid orthogonality conditions and coefficient stability over time. A possible reason for a rejection is therefore that the slope coefficients vary over time. One solution is to estimate an empirical model in which the coefficients are time specific. We apply this solution to the system GMM estimator of simple nondynamic Cobb–Douglas production functions for a selection of Swedish industries and find that relaxing the assumption of constant slope coefficients results in more satisfactory outcomes of the Sargan–Hansen test.

Suggested Citation

  • Yoshihiro Sato & Måns Söderbom, 2017. "GMM estimation of panel data models with time-varying slope coefficients," Applied Economics Letters, Taylor & Francis Journals, vol. 24(21), pages 1511-1518, December.
  • Handle: RePEc:taf:apeclt:v:24:y:2017:i:21:p:1511-1518
    DOI: 10.1080/13504851.2017.1302053

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    Cited by:

    1. Timo Mitze & Nino Javakhishvili‐Larsen, 2020. "Graduate Migration and Early‐career Labor Market Outcomes: Do Education Programs and Qualification Levels Matter?," LABOUR, CEIS, vol. 34(4), pages 477-503, December.
    2. Sweta Sen & Narayan Chandra Nayak & William Kumar Mohanty, 2023. "Impact of tropical cyclones on sustainable development through loops and cycles: evidence from select developing countries of Asia," Empirical Economics, Springer, vol. 65(5), pages 2467-2498, November.

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