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The Difference, System and ‘Double-D’ GMM Panel Estimators in the Presence of Structural Breaks

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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, 2012. "The Difference, System and ‘Double-D’ GMM Panel Estimators in the Presence of Structural Breaks," Dundee Discussion Papers in Economics 268, Economic Studies, University of Dundee.
    • Handle: RePEc:dun:dpaper:268
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    1. Josep Lluis Carrion Silvestre & Tomas del Barrio Castro & Enrique Lopez Bazo, 2002. "Level shifts in a panel data based unit root test. An application to the rate of unemployment," Working Papers in Economics 79, Universitat de Barcelona. Espai de Recerca en Economia.
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    6. De Wachter, Stefan & Tzavalis, Elias, 2012. "Detection of structural breaks in linear dynamic panel data models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3020-3034.
    7. Jeremy C. Stein & Anil K. Kashyap, 2000. "What Do a Million Observations on Banks Say about the Transmission of Monetary Policy?," American Economic Review, American Economic Association, vol. 90(3), pages 407-428, June.
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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).

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    More about this item

    Keywords

    Dynamic panel estimators; mean shifts/structural breaks; Monte Carlo Simulation;
    All these keywords.

    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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