خلاصة:
Energy intensity is a measure of the energy efficiency of a nation’s economy. Many factors
influence a country’s energy intensity. In this paper, however, we note the effective factors of
energy intensity and decompose it by applying Logistic Smooth Transition Regression (LSTR) in
Iran during the period 1980- 2013. The main factors are the ratio of the added value of services
to GDP (explaining both linear and nonlinear part of the energy intensity), the percentage of
internet users, income per capita and Human Development Index (explaining nonlinear part of
the energy intensity). The results indicated that the lifestyle and structural changes had a
significant and considerable effect on decreasing energy intensity and that the ratio of services
value-added to GDP as a transition variable caused an asymmetric behavior of energy intensity
affected from explanatory variables. The most effective factor on energy intensity was Human
Development Index.
ملخص الجهاز:
In this paper, however, we note the effective factors of energy intensity and decompose it by applying Logistic Smooth Transition Regression (LSTR) in Iran during the period 1980- 2013.
The main factors are the ratio of the added value of services to GDP (explaining both linear and nonlinear part of the energy intensity), the percentage of internet users, income per capita and Human Development Index (explaining nonlinear part of the energy intensity).
The results indicated that the lifestyle and structural changes had a significant and considerable effect on decreasing energy intensity and that the ratio of services value-added to GDP as a transition variable caused an asymmetric behavior of energy intensity affected from explanatory variables.
In this paper, we estimate the following model, in which energy intensity of GDP (EI) is the dependent variable, and SER, IT, HDI and YP are independent variables: t t ) 2 t , 2 t , 2 t , (6) EI F q Z EI SER IT 2 0 HDIt i , 0YPt i )t ii LSTR F (qt ) 1 xp (qt k) (7) In (6) and (7), F(qt) is the transition function and qt can be each of the variables in vector Z, their lags, or time trend.
In other words, nonlinear transition of energy intensity ,which is under the effect of lifestyle and structural changes, depends on the estimated threshold value of the ratio of services value-added to GDP (c = 52.