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Technological Innovation and a Changing Energy Mix - A Parametric and Flexible Approach to Modeling Ontario Manufacturing

Dean C. Mountain, Bill P. Stipdonk and Cathy J. Warren

Year: 1989
Volume: Volume 10
Number: Number 4
DOI: 10.5547/ISSN0195-6574-EJ-Vol10-No4-9
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Abstract:
For the purposes of explaining historical trends in relative fuel usage and energy efficiency, an encompassing framework must incorporate both the influence of changing fuel prices and technological change. Schurr (1982), Rosenberg (1983), Jorgenson (1984, 1986) and Berndt (1986) have provided recent documentation of the importance of these two factors in explaining productivity growth. Moreover, these studies indicate that a key to understanding such trends is analysis at the individual industrial sector level.In ignoring the influence of technological change on interfuel substitution, modern studies (e.g., Gopalakrishnan, 1987; Moghimzadeh and Kymm, 1986) have left unaltered the approach taken in the pioneering studies of Berndt and Wood (1975), Fuss (1977), Griffin and Gregory (1976) and Halvorsen (1977).



Perspectives on nonparametric and Semiparametric Modeling

Adonis Yatchew

Year: 2008
Volume: Volume 29
Number: Special Issue
DOI: 10.5547/ISSN0195-6574-EJ-Vol29-NoSI-2
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Abstract:
Nonparametric regression techniques hold out the promise of more flexible modeling of data in many areas of physical, biological and social sciences. However, their use is hampered by the "curse of dimensionality" which imposes enormous data requirements as the number of explanatory variables increases. After summarizing two of the most commonly used methods for mitigating the �curse�, this paper outlines a new approach which exploits data on derivatives. In economics, such circumstances arise in the joint estimation of cost and factor demand functions, or when production function data are combined with data on factor prices. The ideas are illustrated using empirical examples from energy economics.



Is Productivity Growth in Electricity Distribution Negative? An Empirical Analysis Using Ontario Data

Dimitri Dimitropoulos and Adonis Yatchew

Year: 2017
Volume: Volume 38
Number: Number 2
DOI: 10.5547/01956574.38.2.ddim
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Abstract:
Electricity industries are experiencing upward cost pressures in many parts of the world. This paper focuses on productivity trends in electricity distribution. We apply two methodologies for estimating productivity growth - an index based approach, and an econometric cost based approach - to data on 73 Ontario distributors for the period 2002 to 2012. The resulting productivity growth estimates are approximately -1% per year, suggesting a reversal of the positive estimates that have generally been reported in previous periods. We implement flexible semi-parametric specifications to assess the robustness of these conclusions and discuss the use of such statistical analyses for calibrating productivity and relative efficiency within a price-cap framework.



Decomposing aggregate CO2 emission changes with heterogeneity: An extended production-theoretical approach

H. Wang, B.W. Ang, and P. Zhou

Year: 2018
Volume: Volume 39
Number: Number 1
DOI: 10.5547/01956574.39.1.hwan
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Abstract:
Quantifying the driving forces behind changes in aggregate CO2 emissions provides valuable information for supporting policy making in addressing climate change. We study this issue using the production-theoretical decomposition analysis (PDA) technique. Within a production theory framework, PDA examines CO2 emission changes from the perspective of productive efficiency. Although regional and sectoral heterogeneities in energy consumption and emission patterns prevail, they have not been taken into account in the PDA literature. By incorporating relevant decomposition methods, this study proposes an extended PDA approach to resolving the heterogeneity issue. The approach is applied to examine China's aggregate CO2 emission changes in its 11th five-year plan period (2005- 2010). By accounting for the heterogeneities, detailed results at the regional and sectoral levels are generated and further discussions presented.



Heterogeneous Returns to Scale of Wind Farms in Northern Europe

Giacomo Benini, Maria Carvalho, Ludovic Gaudard, Patrick Jochem, and Kaveh Madani

Year: 2019
Volume: Volume 40
Number: The New Era of Energy Transition
DOI: 10.5547/01956574.40.SI1.gben
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Abstract:
The present paper tries to identify the optimal size of a wind farm using North European data. An empirical analysis of 61 sites constructed between 2004 and 2014 suggests that economies-of-scale are highly heterogeneous across on-shore and off-shore projects. A Varying Coefficient Model captures such diversity by making the impact of the farm site on the amount of its potential capacity a non-linear function of the number of installed turbines. The resulting scale elasticities suggest that small on-shore farms have a bigger per-turbines output than off-shore ones, while the opposite is true for big projects.



Modelling Required Energy Consumption with Equivalence Scales

Yuxiang Ye, Steven F. Koch, and Jiangfeng Zhang

Year: 2022
Volume: Volume 43
Number: Number 6
DOI: 10.5547/01956574.43.6.yuye
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Abstract:
Due to difficulties in accessing detailed energy modelling and usage data that are required to estimate energy needs that are responsive to local circumstances, we propose an equivalence scale approach to the determination of required energy consumption. Our method requires the estimation of energy equivalence scales that are used to rescale reference household energy consumption and, thus, yield household-specific energy requirements. We apply the method using readily available income and expenditure data, finding that estimated required energy is well above actual energy expenditure for low- and middle-income households, which is consistent with an expectation that basic energy needs for poor households may not be met. The proposed approach is general enough to incorporate other features that might be deemed relevant and available in other settings, and, therefore, can be used to examine the affordability component of SDG 7, undertake energy poverty analysis or design appropriate policies.





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