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(Showing results 1 to 9 of 9)



Gas or Electricity, which is Cheaper? An Econometric Approach with Application to Australian Expenditure Data

Robert Bartels, Denzil G. Fiebig and Michael H. Plumb

Year: 1996
Volume: Volume17
Number: Number 4
DOI: 10.5547/ISSN0195-6574-EJ-Vol17-No4-2
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Abstract:
The question of whether it is cheaper for households to use electricity or gas for space heating, water heating and cooking, generates much debate in Australia. Generally, gas appliances are technically less efficient than electrical appliances, but on a per MJ basis, gas is cheaper than electricity. The trade-off between these two factors has typically been assessed using an engineering approach which ignores the fact that gas and electric appliances might be used in different ways in the home and that there may be price effects. This paper utilises an alternative perspective based on econometric methods. We analyse the actual energy expenditures of a large sample of Australian households and estimate the expenditure on the main end-uses for households using different fuel types. We find that households using electricity for main heating spend considerably less than households using gas. For cooking, households using gas generally spend less, while for water heating the results are mixed. We discuss several possible interpretations of these results in terms of consumer preferences and running costs.



Micro Econometric Modelling of Household Energy Use: Testing for Dependence between Demand for Electricity and Natural Gas

Soren Leth-Petersen

Year: 2002
Volume: Volume23
Number: Number 4
DOI: 10.5547/ISSN0195-6574-EJ-Vol23-No4-3
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Abstract:
This paper contains a micro econometric analysis of household electricity and natural gas demand for a cross section of 2,885 Danish households observed in 1996. The sample includes fulltime employed couples in single family houses. The specification of the model is guided by an explorative nonparametric data analysis. The analysis reveals, among other things, the fairly surprising result that demand for heating is unaffected by the number of children in the household. The dependence between demand for gas and demand for electricity is examined in the paper. This is done by testing for separability of demand for gas from demand for electricity, and vice versa. Separability of electricity (gas) from gas (electricity) is tested by estimating demand for electricity (gas) conditional on demand for gas (electricity). The model allows for endogeneity of the conditional variable. Building regulations and individual time variation, that is panel data, identify the test. The test indicates that demand for electricity is separable from demand for natural gas, and that demand for natural gas is separable from demand for electricity. The result of the test is evidence in favour of single equation modelling of household energy demand in this context.



Efforts and Efficiency in Oil Exploration: A Vector Error-Correction Approach

Klaus Mohn

Year: 2008
Volume: Volume 29
Number: Number 4
DOI: 10.5547/ISSN0195-6574-EJ-Vol29-No4-3
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Abstract:
High oil prices and gradual resource depletion have raised global concerns for security of energy supply. Successful exploration activity is a critical factor for future oil production. Based on standard neoclassical producer behavior and modern time series econometrics, this study reveals new insights into the process of oil and gas exploration. I find that reserve additions are enhanced by an increase in the oil price, due to responses both in effort and efficiency of exploration. Moreover, oil companies accept higher exploration risk in response to an oil price increase, implying lower success rates and higher expected discovery size.



Spatial Dependence in State Renewable Policy: Effects of Renewable Portfolio Standards on Renewable Generation within NERC Regions

Eric Bowen and Donald J. Lacombe

Year: 2017
Volume: Volume 38
Number: Number 3
DOI: 10.5547/01956574.38.3.ebow
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Abstract:
While several studies have examined the effect of renewable portfolio standard laws on renewable generation in states, previous literature has not assessed the potential for spatial dependence in these policies. Using recent spatial panel methods, this paper estimates a number of econometric models to examine the impact of RPS policies when spatial autocorrelation is taken into account. Consistent with previous literature, we find that RPS laws do not have a significant impact on renewable generation within a state. However, we find evidence that state RPS laws have a significant positive impact on the share of renewable generation in the NERC region as a whole. These findings provide evidence that electricity markets are efficiently finding the lowest-cost locations to serve renewable load in states with more stringent RPS laws. In addition, our results suggest that RPS laws may be more effective tools for environmental policy than for economic development.



Forecasting China’s Carbon Intensity -- Is China on Track to Comply with Its Copenhagen Commitment?

Yuan Yang, Junjie Zhang, and Can Wang

Year: 2018
Volume: Volume 39
Number: Number 2
DOI: 10.5547/01956574.39.2.yyan
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Abstract:
In the 2009 Copenhagen Accord, China agreed to slash its carbon intensity (carbon dioxide emissions/GDP) by 40% to 45% from the 2005 level by 2020. We assess whether China can achieve the target under the business-as-usual scenario by forecasting its emissions from energy consumption. Our preferred model shows that China's carbon intensity is projected to decline by only 33%. The results imply that China needs additional mitigation effort to comply with the Copenhagen commitment. The emission growth is more than triple the emission reductions that the European Union and the United States have committed to in the same period.



A Spatial Stochastic Frontier Model with Omitted Variables: Electricity Distribution in Norway

Luis Orea, Inmaculada C. Álvarez, and Tooraj Jamasb

Year: 2018
Volume: Volume 39
Number: Number 3
DOI: 10.5547/01956574.39.3.lore
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Abstract:
An important methodological issue in efficiency analysis for incentive regulation of utilities is how to account for the effect of unobserved cost drivers such as environmental factors. We combine a spatial econometric approach with stochastic frontier analysis to control for unobserved environmental conditions when measuring efficiency of electricity distribution utilities. Our empirical strategy relies on the geographic location of firms as a source of information that has previously not been explored in the literature. The underlying idea is to utilise data from neighbouring firms that can be spatially correlated as proxies for unobserved cost drivers. We illustrate this approach using a dataset of Norwegian distribution utilities for the 2004-2011 period. We show that the lack of information on weather and geographic conditions can be compensated with data from surrounding firms. The methodology can be used in efficiency analysis and regulation of other utilities sectors where unobservable cost drivers are important, e.g. gas, water, agriculture, fishing.



The Impact of a Carbon Tax on the CO2 Emissions Reduction of Wind

Chi Kong Chyong, Bowei Guo, and David Newbery

Year: 2020
Volume: Volume 41
Number: Number 1
DOI: 10.5547/01956574.41.1.cchy
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Abstract:
Energy policy aims to reduce emissions at least long-run cost while ensuring reliability. Its effecacy depends on the cost of emissions reduced. Britain introduced an additional carbon tax (the Carbon Price Support, CPS) for fuels used to generate electricity that by 2015 added £18/t CO2, dramatically reducing the coal share from 41% in 2013 to 6% in 2018. Policies have both short and long-run impacts. Both need to be estimated to measure carbon savings. The paper shows how to measure the Marginal Displacement Factor (MDF, tonnes CO2 /MWh) for wind. The short-run (SR) MDF is estimated econometrically while the long-run (LR) MDF is calculated from a unit commitment model of the GB system in 2015. We examine counter-factual fuel and carbon price scenarios. The CPS lowered the SR-MDF by 7% in 2015 but raised the LR-MDF (for a 25% increase in wind capacity) by 18%. We discuss reasons for the modest differences in the SR- and LR-MDFs.



Spatial Effects of Wind Generation and Its Implication for Wind Farm Investment Decisions in New Zealand

Le Wen, Basil Sharp, and Erwann Sbai

Year: 2020
Volume: Volume 41
Number: Number 2
DOI: 10.5547/01956574.41.2.lwen
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Abstract:
Spill-over effects on electricity nodal prices associated with increased wind generation have not been examined in the literature. To examine these effects, we use spatial econometric models to estimate the direct and indirect effects of wind generation on nodal wholesale electricity prices. Spatial econometric models allow us to provide quantitative estimates of spill-over magnitudes and statistical tests for significance. Results show negative and significant effects are associated with increases in wind penetration, and the effect is stronger during peak hours and weaker during off-peak hours. Simulation results demonstrate net savings of NZ$8 million per MW of additional wind capacity installed at the CNI2 wind site. The findings provide valuable information on the evaluation of wind farm development in terms of site location, wholesale prices, and financial feasibility. Our approach also contributes to forecasting location specific wholesale electricity prices, and provides a better understanding of the implications of locating wind sites.



Locational (In)Efficiency of Renewable Energy Feed-In Into the Electricity Grid: A Spatial Regression Analysis

Tim Höfer and Reinhard Madlener

Year: 2021
Volume: Volume 42
Number: Number 1
DOI: 10.5547/01956574.42.1.thof
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Abstract:
This paper presents an econometric analysis of curtailment costs of renewable energy sources (RES) in Germany. The study aims at explaining and quantifying the regional variability of RES curtailment, which is a measure to relieve grid overstress by temporarily disconnecting RES from the electricity grid. We apply a Heckit sample selection model, which corrects bias from non-randomly selected samples. The selection equation estimates the probability of occurrence of RES curtailment in a region. The outcome equation corrects for cross-sectional dependence and quantifies the effect of RES on curtailment costs. The results show that wind energy systems connected to the distribution grid increase RES curtailment costs by 0.7% per MW (or 0.2% per GWh) in subregions that have experienced RES curtailment over the period 2015�2017. The implication of this finding is that policymakers should set price signals for renewables that consider the regional grid overstress, in order to mitigate the cost burden on consumers due to excess generation from RES.





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