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R-Codes to Calculate GMM Estimations for Dynamic Panel Data Models

Mohamed Abonazel ()

MPRA Paper from University Library of Munich, Germany

Abstract: These codes presented three functions for calculating three important estimators in dynamic panel data (DPD) models; these estimators are Arellano-Bond (1991), Arellano-Bover (1995), and Blundell-Bond (1998). All functions here need to the following variables: yit_1: dependent variable for DPD model; phi: the value of autoregressive coefficient; D.T_D.T: first-difference operator matrix of Arellano-Bond estimator; HD: instrumental variables of Arellano-Bond estimator; HL: instrumental variables of Arellano-Bover estimator; W: weighting matrix of Blundell-Bond estimator; HS: instrumental variables of Blundell-Bond estimator. Also, they need to the following R libraries: simex; plm; dlm. For more details about the theoretical bases and the developments of that estimators, see, e.g., Youssef et al. (2014a,b) and Youssef and Abonazel (2015). Moreover, these codes have been designed to enable the user to make a simulation study in this topic, such as the simulation study in Youssef et al. (2014b).

Keywords: Dynamic panel data models; Generalized method of moments (GMM); Monte Carlo simulation; Two-step GMM estimations. (search for similar items in EconPapers)
JEL-codes: C1 C4 C5 C87 (search for similar items in EconPapers)
Date: 2015-12
New Economics Papers: this item is included in nep-ore
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