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The difference, system and ‘Double‐D’ GMM panel estimators in the presence of structural breaks

Author

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  • Rosen Azad Chowdhury
  • Bill Russell

Abstract

The effects of structural breaks in dynamic panels are more complicated than in time series models as the bias can be either negative or positive. This paper focuses on the effects of mean shifts in otherwise stationary processes within an instrumental variable panel estimation framework. We show the sources of the bias and a Monte Carlo analysis calibrated on United States bank lending data demonstrates the size of the bias for a range of auto‐regressive parameters. We also propose additional moment conditions that can be used to reduce the biases caused by shifts in the mean of the data.

Suggested Citation

  • Rosen Azad Chowdhury & Bill Russell, 2018. "The difference, system and ‘Double‐D’ GMM panel estimators in the presence of structural breaks," Scottish Journal of Political Economy, Scottish Economic Society, vol. 65(3), pages 271-292, July.
    • Handle: RePEc:bla:scotjp:v:65:y:2018:i:3:p:271-292
    DOI: 10.1111/sjpe.12142
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    Cited by:

    1. Fedotenkov, Igor & Idrisov, Georgy, 2021. "A supply-demand model of public sector size," Economic Systems, Elsevier, vol. 45(2).

    More about this item

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation

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