A Comparative Study for Estimation Parameters in Panel Data Model
Ahmed H. Youssef and
Mohamed Abonazel ()
MPRA Paper from University Library of Munich, Germany
This paper examines the panel data models when the regression coefficients are fixed, random, and mixed, and proposed the different estimators for this model. We used the Mote Carlo simulation for making comparisons between the behavior of several estimation methods, such as Random Coefficient Regression (RCR), Classical Pooling (CP), and Mean Group (MG) estimators, in the three cases for regression coefficients. The Monte Carlo simulation results suggest that the RCR estimators perform well in small samples if the coefficients are random. While CP estimators perform well in the case of fixed model only. But the MG estimators perform well if the coefficients are random or fixed.
Keywords: Panel Data Model; Random Coefficient Regression Model; Mixed RCR Model; Monte Carlo Simulation; Pooling Cross Section and Time Series Data; Mean Group Estimators; Classical Pooling Estimators. (search for similar items in EconPapers)
JEL-codes: C13 C15 C33 C51 C61 C63 (search for similar items in EconPapers)
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Published in InterStat Journal May, No. 2.2009(2009): pp. 1-17
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:49713
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