OECD Energy Demand: Modelling Underlying Energy Demand Trends using the Structural Time Series Model

Aggregate energy demand functions for 17 OECD countries are estimated with data for 1960-2003 using the Structural Time Series Model (STSM) thus allowing for a stochastic Underlying Energy Demand Trend (UEDT). It is found that the estimated long-run income and price elasticities range from 0.5 to 1.5 and -0.1 to -0.4 respectively. Furthermore the stochastic form for the UEDT is preferred for all countries suggesting a wide variation in the exogenous effects of energy saving technical progress in addition to other pertinent exogenous factors such as economic structure, consumer preferences, and socio-economic influences.OECD Energy Demand, Modelling, Underlying Stochastic Trends

Underlying trends in employment-output equation: the case of Jordan

The underlying employment trend (UET) is investigated in Jordanian economy over the period 1989- 2004 using structural time series model (STSM). This approach allows to modelling the trend in its stochastic form introduced by Harvey (1989). The results show that a stochastic trend is preferred to deterministic trend. In addition, the inclusion or exclusion of the conventional deterministic trend leads to overestimated output elasticity. Furthermore, the UET is found to be non-linear, down downward sloping.Employment, stochastic trend, structural time series modelling, Research and Development/Tech Change/Emerging Technologies, J20,

Modelling the demand for energy in the OECD countries using three econometric approaches

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Underlying trends in employment-output equation: the case of Jordan

The underlying employment trend (UET) is investigated in Jordanian economy over the period 1989- 2004 using structural time series model (STSM). This approach allows to modelling the trend in its stochastic form introduced by Harvey (1989). The results show that a stochastic trend is preferred to deterministic trend. In addition, the inclusion or exclusion of the conventional deterministic trend leads to overestimated output elasticity. Furthermore, the UET is found to be non-linear, down downward sloping

Do Government Expenditures in G7 Countries Target Socioeconomics or Physical Output?

The issue of valuable government policy interventions has not been fully addressed. Therefore, this paper analyzes the impact of government capital expenditure on production efficiency in the G7 countries. Two models are estimated with different dependent variables: the Human Development Index (HDI) as a dependent variable to capture the socio-economic impact and the gross domestic product (GDP) as a dependent variable to capture the physical impact. The paper uses a set of panel data for the G7 countries spanning the years 2000–2018, which were obtained from the World Development Indicators (WDI) database. The paper applies stochastic production frontier analysis (SFA) to estimate each country’s yearly efficiency and to estimate the impact of government expenditure on the overall technical inefficiency for both models. The results demonstrate that increasing government expenditure boosts the inefficiency in the G7 countries in the HDI model, but it depresses inefficiency in the GDP model. This may suggest that government capital expenditure in the G7 countries was directed toward increasing physical output—not toward socio-economic outputs such as health and educational output—during the study period. Furthermore, the results show that the estimated average technical efficiency over the study period was 93.4% for the HDI model and 81.2% for the GDP model. Finally, the results show that the G7 countries’ objectives were not similar in this area, with some countries using socioeconomic-oriented policies and others using physical-capital-oriented policies

Do Government Expenditures in G7 Countries Target Socioeconomics or Physical Output?

The issue of valuable government policy interventions has not been fully addressed. Therefore, this paper analyzes the impact of government capital expenditure on production efficiency in the G7 countries. Two models are estimated with different dependent variables: the Human Development Index (HDI) as a dependent variable to capture the socio-economic impact and the gross domestic product (GDP) as a dependent variable to capture the physical impact. The paper uses a set of panel data for the G7 countries spanning the years 2000–2018, which were obtained from the World Development Indicators (WDI) database. The paper applies stochastic production frontier analysis (SFA) to estimate each country’s yearly efficiency and to estimate the impact of government expenditure on the overall technical inefficiency for both models. The results demonstrate that increasing government expenditure boosts the inefficiency in the G7 countries in the HDI model, but it depresses inefficiency in the GDP model. This may suggest that government capital expenditure in the G7 countries was directed toward increasing physical output—not toward socio-economic outputs such as health and educational output—during the study period. Furthermore, the results show that the estimated average technical efficiency over the study period was 93.4% for the HDI model and 81.2% for the GDP model. Finally, the results show that the G7 countries’ objectives were not similar in this area, with some countries using socioeconomic-oriented policies and others using physical-capital-oriented policies