Estimating the evolution of elasticities of natural gas demand: the case of Istanbul, Turkey

Abstract

Much of the existing literature on demand for natural gas assumes constant and single-value elasticities, overlooking the possibility of dynamic responses to the changing conditions. We aim to fill this gap by providing individual time series of short-run elasticity estimates based on maximum entropy resampling in a fixed-width rolling window framework. This approach does not only enable taking the variability of the elasticities into account, but also helps obtain more efficient and robust results in small samples in comparison with conventional inferences based on asymptotic distribution theory. To illustrate the methodology, we employ monthly time-series data between 2004 and 2012 and analyze the dynamics of residential natural gas demand in Istanbul, the largest metropolitan area in Turkey. Our findings reveal that the elasticities of the demand model do not remain constant and they are sensitive to the economic situation as well as weather fluctuations.