Estimating elasticities of residential energy demand from panel county data using dynamic random variables models with heteroskedastic and correlated error terms

A dynamic random variables model correcting for heteroskedastic and correlated error terms over time and space and dynamic demand and using panel county data offers consistent and efficient elasticity estimates of residential electricity and natural gas demands. The model developed by Swamy [Swamy, P.A.V.B., 1974. Linear models with random coefficients. In: P. Zarembka (Eds.), Frontiers in Econometrics, Academic Press, London, pp. 143–168.] with a modification suggested by Maddala et al. [Maddala, G.S., Trost, R.P., Li, H., Joutz, F., 1997. Estimation of short-run and long-run elasticities of energy demand from panel data using shrinkage estimators. Journal of Business and Economic Statistics 15, 90–100.] uses a panel of selected California counties for the years 1983–1997 to yield elasticity estimates that differ from those obtained from more standard panel data procedures.