خلاصة:
The aggregate model of North America includes residential-commercial and transportation sectors. The residential-commercial sector equation is Constant Elasticity Model (CEM) and in this paper we used it for Almon polynomial distributed lag model. This model gives the long run price elasticity of demand. The price elasticity compete the income elasticity in the sense that moderate increase in energy demand. The real price elasticity of demand is –0.19 while the income elasticity of demand is high considerably estimated as 0.59.Like price elasticity in the transportation sector (with the same method) is -0.1 delineating an inelastic demand to price. Also the income elasticity is rather considerable. Income elasticity in this sector is 0.67 that shows the driving force in energy demand in the North America is the transportation sector. The R&D efforts along with other non-price policies contribute in lower energy demand growth. The coefficient of filter variable to cover the asymmetric response of demand to price changes (as a proxy variable for technology improvement) is estimated as -0.037.Although technology improvements could relax the demand in this sector, but the demand growth still will be considerable.
ملخص الجهاز:
"But by Almon (1965) polynomial distributed lag model can assumes that m0 follows the second- degree polynomial the lags weights and result that: Et = a + bYt + +et Or : Et = a + bYt + + ++ et And then with substitution (Zlt= ,Z2t= ,Z3t= ) may write equation as below : Et = a + bYt + a0 Zlt + a1 Z2t +a3 Z3t + et For energy demand analyses, it is desirable to adopt regression techniques that enable the robust estimation of short- and long-run elasticities.
II- Equations for Aggregate-Energy Demand As mentioned, the following equation is suitable for energy demand: Ei = F (GDP, PE, FILT, T) Where Ei is aggregate energy consumption by sector i (Residential-Commercial and Transportation) in North America.
In this equation aggregate energy consumption has been calculated as below for two sectors: Residential-Commercial: ER=OR+SR+GR+ER Transportation: OT+GT+ET Which O is oil, S is solids fuels (coal), G is gas and E is electricity.
III- Estimating aggregate energy demand For North America (Residential-Commercial and Transportation sectors), in period of 1970-2001 several equations were examined, using different combinations of explanatory variables.
Then it shows long run coefficient or elasticity of energy price (PE) in Residential-Commercial sector, it is equal of -0.
In this paper we used from this method for estimate of relation energy demand and energy price in North America Residential-Commercial and transportation sectors.
The long-run coefficient of filter variable in North America that be used to cover the asymmetric response of demand to price changes, in this sector wasn’t statistically significant and wasn’t entered in model."