This paper empirically examines per capita residential natural gas demand using annual data for 29 Organization for Economic Co-operation and Development (OECD) countries from 2005 to 2016. Earlier studies have focused on the effect of price and income to estimate natural gas demand elasticities, but most of them have neglected the demographic variables such as elderly population, population density and urbanization rate. The aim of this work is to include these attributes for modeling the demand function of natural gas. To address the problem of endogeneity, we use a dynamic panel system called Generalized Method of Moments estimator. Our study presents the following main results; First, the increase of the urbanization rate leads to more per capita consumption of natural gas in the residential sector. Second, the ageing of the population decreases the use of per capita residential natural gas in OECD countries. Third, as population density increases, per capita residential natural gas consumption decreases.

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The most common residual viscosity correlation used in the petroleum models is JOSSI et al [1] where the residual viscosity is represented by a polynomial function of 4th degree involving the reduced density ρr ([(η-η*)ξ+10-4]1/4=Σ41=0(aiρri)). Based on this formula, it is possible to predict various uncertainties that can be accumulated and thus alter the performance of viscosity restitution which depends on several factors:The quality of the initial adjustment of the coefficients ai;The precision on the density;The accuracy with which are known the characteristics of the constituents of bases;The validity of the rule of the mixtures selected for the determination of the pseudo-critical coordinates Tcm and Pcm and the equivalent molar mass of the mixture.As far as the results are concerned, we reveal that with the new set of coefficients it is possible to obtain a more preciserepresentation compared to that of JOSSI. The method of JOSSI seems to be especially interesting for the viscosities restitution of systems containing light and close paraffins. However, for some pure substances, the opposite situation could be true. Among the four equations-of-state used, it has been found that the cubic equation-of-stateof PENG and ROBINSON should not be used since we would like to generate the density. Finally, we are not expecting a perfect systematic representation. As demonstrated in our model, if for light alkanes one can expect an average deviation ofless than 10%, for certain pure substances the deviation exceeds 20%.

This analysis uses annual data on residential gas use for 29 Organization for Economic Cooperation and Development nations from 2005 to 2016 to look at per capita energy demand. The effect of price and income on natural gas demand elasticities has been studied in the past, but most research have ignored demographic aspects. The goal of this study is to incorporate these characteristics into natural gas demand modeling. A dynamic panel system dubbed the Generalized Method of Moments (GMM) estimator was used to address the endogeneity issue. The following are the study’s main findings: First, the residential sector consumes more natural gas per capita as the population grows. Second, the consumption of per capita residential natural gas in Organization for Economic Cooperation and Development countries is decreasing as the population ages. Finally, as the population density rises, so does per capita gas consumption.