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Identification Robust Inference For Moments-Based Analysis Of Linear Dynamic Panel Data Models

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  • Bun, Maurice J.G.
  • Kleibergen, Frank

Abstract

We use identification robust tests to show that difference (Dif), level (Lev), and nonlinear (NL) moment conditions, as proposed by Arellano and Bond (1991, Review of Economic Studies 58, 277–297), Ahn and Schmidt (1995, Journal of Econometrics 68, 5–27), Arellano and Bover (1995, Journal of Econometrics 68, 29–51), and Blundell and Bond (1998, Journal of Econometrics 87, 115–143) for the linear dynamic panel data model, do not separately identify the autoregressive parameter when its true value is close to one and the variance of the initial observations is large. We prove that combinations of these moment conditions, however, do so when there are more than three time series observations. This identification then solely results from a set of, so-called, robust moment conditions. These robust moments are spanned by the combined Dif, Lev, and NL moment conditions and only depend on differenced data. We show that, when only the robust moments contain identifying information on the autoregressive parameter, the discriminatory power of the Kleibergen (2005, Econometrica 73, 1103–1124) Lagrange multiplier (KLM) test using the combined moments is identical to the largest rejection frequencies that can be obtained from solely using the robust moments. This shows that the KLM test implicitly uses the robust moments when only they contain information on the autoregressive parameter.

Suggested Citation

  • Bun, Maurice J.G. & Kleibergen, Frank, 2022. "Identification Robust Inference For Moments-Based Analysis Of Linear Dynamic Panel Data Models," Econometric Theory, Cambridge University Press, vol. 38(4), pages 689-751, August.
    • Handle: RePEc:cup:etheor:v:38:y:2022:i:4:p:689-751_2
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    Cited by:

    1. Hugo Kruiniger, 2025. "Uniform Quasi ML based inference for the panel AR(1) model," Papers 2508.20855, arXiv.org, revised Dec 2025.
    2. Sentana, Enrique, 2024. "Finite underidentification," Journal of Econometrics, Elsevier, vol. 240(1).
    3. Hugo Kruiniger, 2025. "A further look at Modified ML estimation of the panel AR(1) model with fixed effects and arbitrary initial conditions," Papers 2508.20753, arXiv.org, revised Jan 2026.
    4. Sentana, Enrique, 2025. "Reprint of: Finite underidentification," Journal of Econometrics, Elsevier, vol. 248(C).

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