One of their most recent publications is Residential demand for electricity: The case of Greece. Which was published in journal Energy Economics.

More information about George S. Donatos research including statistics on their citations can be found on their Copernicus Academic profile page.

George S. Donatos's Articles: (2)

Residential demand for electricity: The case of Greece

AbstractThis paper examines the determinants of residential electricity consumption in Greece over the period 1961-86. The paper presents first a brief description of the evolution of residential electricity consumption. Then, it proceeds in the estimation of elasticities of residential demand for electricity using a single equation model with the ridge regression method. The paper concludes that (i) the residential demand for electricity is price inelastic and income elastic; (ii) there is high substitutability between electricity and LPG; (iii) during the examined period the number of consumers played a very important role in the expansion of electricity consumption in Greece; and (iv) there is no regional variation in residential electricity demand.

A Monte Carlo study of some limited and full information simultaneous equation estimators with normal and nonnormal autocorrelated disturbances

AbstractThe purpose of this paper is to examine the small sample properties of various limited and full information estimators of the structural coefficients of a system of two equations. Specifically, we consider a first-order autoregressive error structure under normal and nonnormal disturbances — for four different covariance structures — and report on a Monte Carlo study of the small sample behavior of limited and full information estimators according to the criteria of bias and dispersion. The results show that the differences in performance of the estimators for the alternative forms of the disturbance distributions are large. Moreover, none of the examined estimators is superior relative to the others, in the sense that its bias and dispersion are the smallest for at least one form of the disturbance distribution. Finally, no combination of highly or lowly autocorrelated disturbances favors some specific limited or full information estimator.

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