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Least Squares Dummy Variable in Determination of Dynamic Panel Model Parameters

Author

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  • Joseph Uchenna Okeke

    (Department of Mathematics and Statistics, Federal University Wukari, Taraba Stateş)

  • Evelyn Nkiruka Okeke

    (Department of Mathematics and Statistics, Federal University Wukari, Taraba State.)

Abstract

This paper investigates the small sample performance of the Least Squares Dummy Variable (LSDV) estimator of the dynamic panel data models for period, T, greater than the cross sections, N and its large sample performance in the direction of T as N remains finite, and compares it with the performance of the instrumental variable- generalize method of moments (IV-GMM) estimators using the properties of root mean squares error(RMSE) of the model , root mean squares error of the autoregressive term ? (RMSE?), the bias of ? (bias?) and the Akaike Information Criterion (AIC) with the motive of ascertaining the usefulness of the LSDV estimator in determining the parameters of a dynamic panel model as T? and finite N, for which it is regarded as consistent.

Suggested Citation

  • Joseph Uchenna Okeke & Evelyn Nkiruka Okeke, 2018. "Least Squares Dummy Variable in Determination of Dynamic Panel Model Parameters," European Journal of Engineering and Technology Research, European Open Science, vol. 1(6), pages 77-81, July.
    • Handle: RePEc:epw:ejeng0:v:1:y:2018:i:6:id:60197
    DOI: 10.24018/ejeng.2016.1.6.197
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