Regression modelQuasi-experimental / causal inference

Dynamic Instrumental Variables (Dynamic Panel IV / Arellano-Bond)

Dynamic Instrumental Variables estimation addresses endogeneity in panel models where the outcome depends on its own past values. By first-differencing to remove unit fixed effects and then using lagged levels as instruments for the differenced lagged outcome, it produces consistent causal estimates even when standard OLS or fixed-effects are biased by dynamic feedback.

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Sources

  1. Arellano, M., & Bond, S. (1991). Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations. Review of Economic Studies, 58(2), 277-297. DOI: 10.2307/2297968
  2. Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115-143. DOI: 10.1016/S0304-4076(98)00009-8

Related methods

ScholarGateDynamic Instrumental Variables (Dynamic Panel Instrumental Variables Estimation). Retrieved 2026-06-04 from https://scholargate.app/en/causal-inference/dynamic-instrumental-variables