Search

Begin New Search
Proceed to Checkout

Search Results for All:
(Showing results 1 to 3 of 3)



Forecasting Nonlinear Crude Oil Futures Prices

Saeed Moshiri and Faezeh Foroutan

Year: 2006
Volume: Volume 27
Number: Number 4
DOI: 10.5547/ISSN0195-6574-EJ-Vol27-No4-4
View Abstract

Abstract:
The movements in oil prices are very complex and, therefore, seem to be unpredictable. However, one of the main challenges facing econometric models is to forecast such seemingly unpredictable economic series. Traditional linear structural models have not been promising when used for oil price forecasting. Although linear and nonlinear time series models have performed much better in forecasting oil prices, there is still room for improvement. If the data generating process is nonlinear, applying linear models could result in large forecast errors. Model specification in nonlinear modeling, however, can be very case dependent and time-consuming.In this paper, we model and forecast daily crude oil futures prices from 1983 to 2003, listed in NYMEX, applying ARIMA and GARCH models. We then test for chaos using embedding dimension, BDS(L), Lyapunov exponent, and neural networks tests. Finally, we set up a nonlinear and flexible ANN model to forecast the series. Since the test results indicate that crude oil futures prices follow a complex nonlinear dynamic process, we expect that the ANN model will improve forecasting accuracy. A comparison of the results of the forecasts among different models confirms that this is indeed the case.



Changes in Energy Intensity in Canada

Saeed Moshiri and Nana Duah

Year: 2016
Volume: Volume 37
Number: Number 4
DOI: 10.5547/01956574.37.4.smos
View Abstract

Abstract:
Canada is one of the top energy users and CO2 emitters among the OECD countries. However, energy intensity has been declining, on average, by about 1.4 percent since 1980. In this paper, we use the Fisher Ideal Index to determine the contribution of changes in the composition of economic activities and efficiency to a decline in energy intensity in Canada at national, provincial, and industry levels. We also apply panel data estimation methods to further investigate the factors driving energy intensity, efficiency and activity indexes for the period 1981-2008. We test for endogeneity as well as cross-section dependency in the provincial data and control for factors such as climate, policy, and energy endowment. The national and provincial decomposition results suggest that most of the reduction in energy intensity has occurred mainly due to improvements in energy efficiency rather than shifts in economic activities. Within the industry, while energy intensity has declined significantly in manufacturing, it has remained stable in transportation, utilities, and construction, and increased significantly in oil extraction and mining industries. The provincial panel regression results indicate that energy intensity is higher in provinces with higher average incomes, faster population growth, colder climate, and a higher capital-labour ratio, and lower in provinces with higher energy prices and higher investment. The industry panel regression results show that investment has contributed to energy efficiency in utilities and mining and to a shift away from energy-intensive activities in manufacturing and transportation industries. Technological advances have been most effective in increasing energy efficiency in construction and utilities and in decreasing energy-intensive activities in manufacturing industries. The results indicate that although efficiency contributes to a reduction in energy intensity in Canada, increasing activity in energy-intensive industries, such as oil and mining, partially offsets the efficiency gains in other industries.



Manufacturing in a Natural Resource Based Economy: Evidence from Canadian Plants

Saeed Moshiri, Gry Ostenstad, and Wessel N. Vermeulen

Year: 2023
Volume: Volume 44
Number: Number 1
DOI: 10.5547/01956574.44.1.smos
View Abstract

Abstract:
This study investigates the effects of an oil boom on manufacturing plants performance. First, we derive several predictions using a model of heterogeneous firms. Second, we test these predictions on a plant level dataset using the Canadian Annual Survey of Manufacturers for 2000–2010. We exploit the time variation of the booming natural resource sector revenue in an oil-producing area in combination with the location of manufacturing plants to create an exogenous treatment variable. The outcome variables include plant level wages, employment, sales, and exports. We find that initial plant level productivity provides an important differentiation in average plants effects. Plants that are more productive become more likely to export in response to the oil boom, while less productive plants become less likely to export. Exporting firms become more likely to increase wages relative to non-exporting firms, but less likely to increase employment. While there is a great variety in the effect by sector, we do not observe that industry linkages with the resource industry drive plant performance.





Begin New Search
Proceed to Checkout

 

© 2025 International Association for Energy Economics | Privacy Policy | Return Policy