Least Squares Dummy Variable in Determination of Dynamic Panel Model Parameters

Joseph Uchenna Okeke and Evelyn Nkiruka Okeke
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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.

European Journal of Engineering and Technology Research, 2018, vol. 1, issue 6, 77-81

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.

Keywords: Autoregressive term; dynamic panel model; consistent; least squares dummy variable. (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:epw:ejeng0:v:1:y:2018:i:6:id:60197

DOI: 10.24018/ejeng.2016.1.6.197

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