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ELECTRICITY PRICING Delivering social justice and environmental equity

Author Gavin Dufty Manager of Policy and Research St Vincent de Paul Society Victoria Inc. August 2007

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Table of Contents Abstract

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Recent policy directions

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1 Household energy use in a social context

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1.1 Household consumption and income

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1.2 The value households place upon electricity access and usage

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1.3 Electricity consumption as a proportion of income

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1.4 Substitutability of electricity and appliance holdings

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2 Price and its impact on demand

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2.1 Demand elasticity estimates

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2.2 Time of Use pricing and customer response

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3 Pricing structures and government concessions

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3.1 Tariff design

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3.2 Government concessions

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4 A proposal for managing the impacts of electricity pricing

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4.1 Pricing principles – achieving public policy objectives

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4.2 The key principle - A “lifeline� price cap

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4.3 Fixed charges

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4.4 Pricing principles and other environmental levies

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4.5 The advantages of pricing principles

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Acknowledgments

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Appendix I

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Abstract

Due to numerous factors there is significant potential for domestic energy prices to increase substantially. These factors include the impact of a carbon trading scheme, the cost of the interval meter roll out, and price deregulation to name a few. It is a common perception that an increase in energy charges will lead to reduced consumer demand for energy which subsequently results in a reduced need for investment in infrastructure, and a reduction in greenhouse gas emissions. This paper will discuss the financial implications for domestic households when price is regarded as the panacea to achieve these public policy objectives. The first section of this paper outlines energy consumption patterns and expenditure levels as well as the various factors that may influence household electricity demand elasticitity. It also demonstrates the relationship between household income levels and energy consumption. The second part discusses factors that influence demand elasticity and customers response to price signals. It looks at various empirical demand elasticity estimates and distinguishes between various types of elasticity measures, including long and short run, cross price elasticity and elasticity of substitution. Again the emphasis is on the impact on various household types. This is a key concern as the distributional impact of price changes will disadvantage some classes of consumers, especially those with little or no access to alternative greenhouse friendly energy sources such as natural gas. In the third section the paper goes on to examine a number of electricity tariff structures, including flat, inclining and declining block tariffs as well as dynamic pricing, and assess the impact these have on various classes of consumers. The final part of the paper presents a model for the implementation of pricing principles that allow for the costing of environmental objectives while ensuring that social policy objectives are met in the delivery of essential services. Recent policy directions

The issue of energy pricing, in particular electricity pricing will become increasingly important over the next five years. Much of this is due to major policy developments and market reform as reflected in the following Government policy announcements and commitments: •

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The announcement by the Australian Government to introduce a carbon trading scheme by 2012. It is envisaged that the scheme will cause an increase of $200 to an average annual household electricity bill.1

The report of the joint government-business Task Group on Emissions Trading, 1-06-2007

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The expiration of the current price protections in the Victorian electricity market which are due to be phased out or replaced at the end of 2007. The Victorian Minister for Energy and Resources has been quoted saying that he would be disappointed if these price rises were greater than 10 per cent. 2 The mandated roll out of interval meters (smart meters) in Victoria. The Government’s mandate include an accelerated deployment which means that interval meters will be installed in all Victorian households by 2012. This will not only cost Victorian consumers somewhere between $353 and $954 million in infrastructure costs 3 but it is also believed that the new meters will provide the mechanism for dynamic and more complex tariff design.

These announcements will have a direct impact on how much households will be charged for electricity.

1. Household energy use in a social context 1.1 Household consumption and income

Past research has substantiated some key issues in relation to electricity consumption which ought to be taken into consideration when debating electricity pricing. Electricity is an essential service and that consumers place a high priority on paying their electricity bills has been well documented. A survey initiated by the Victorian Department of Human Services (DHS) revealed that 19 per cent of respondents prioritised electricity bills over all other bills. This places electricity second in importance only to rent/mortgage repayments (40 per cent).4 In order to fully appreciate the nature of electricity as a good, we must bear in mind that a household’s demand is derived from the functionality it provides to many conveniences we associate with a decent standard of living such as lighting, heating, cooking and hot water. As such electricity is only indirectly consumed by households. 5 In terms of energy consumption patterns and energy expenditure levels for lower income groups, research has demonstrated that pensioner groups consume energy at a rate below average household consumption. However conversely, as a proportion of their weekly expenditure, they expend almost double the amount compared to the average household. 6 This highlights the disproportional impact price increases will have on this group. 7 The impact and proportion of utility 8 cost was explored and identified in the 2002 General Social Survey Victoria released in January 2004. 9 Not surprisingly the 2

Minister Hon Peter Batchelor , Herald Sun, May 26, 2007 CRA International & Impaq Consulting, Advanced interval meter communication Study – Draft report, prepared for the Department of Infrastructure – Energy and Security division, page 3, 23 December 2005 4 Roy Morgan Research, Victorian Utility Consumption Survey 2001, Final Report, June 2002, p. xvi The survey comprised of approximately 2000 interviews of concession card and non-concession card holders in Melbourne and regional Victoria. 5 Sayers, C and Shield, D. Electricity Prices and Cost Factors, Staff Research Paper, Productivity Commission, Canberra, 2001, p. 17 6 ABS Household Expenditure Survey, retailed expenditure items, 2003 -2004 7 Shane Wright and Andrew Probin, The West Australian, Carbon System will cost $400, 6th June 2007 8 The figures combine electricity, gas and telephone as the survey did not distinguish between the different types of utilities. 3

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survey found that consumers in the lowest income (equivalised gross income) quintile had the most incidents of being unable to pay utility bills on time (table 1). Furthermore the survey found that in relation to household composition, single parent households are by far the group facing the greatest affordability problems measured in terms of inability to pay (table 2). Table 1.

Percent of total Total number

Lowest quintile 18.4%

Second quintile 13.5%

Third quintile 16.4%

Top quintiles 8.8%

119,048

82,620

107,912

123,640

two

All person 12.5% 457,875a

Table 2 Couple only

Percent of total Total number

One parent family(dependent child/ren) 36.9%

Lone person households

All person

5.0%

Couple family (dependent child/ren) 13.9%

11.1%

12.5%

47,050

158,599

63720

51504

457,875a

(a) Persons where household income was not know or was not adequately reported are excluded from all columns in both tables.

1.2 The value households place upon electricity access and usage

Access to electricity for all households is essential and much of each household’s consumption is non-discretionary. The non-discretionary load will constrain the ability of households to reduce demand in response to price rises. Yet differences in consumption levels and patterns across income strata suggest that significant discretionary loads are being consumed by some households. Perceptions as to what constitutes necessary or non-discretionary consumption is likely to be determined by a number of factors. Demographic or lifecycle related variables may play a role in the sense that the number, age and income of household members affect electricity needs and demand. Lifestyle factors relating to employment status, leisure time and household activities undertaken by members of a household also impact on their load and demand for electricity. Finally, other variables affecting both discretionary and non-discretionary demand that are fixed in the short run include the size and thermal efficiency of dwellings and appliance holdings (which in turn affect demand through their use and efficiency). 10 As such household demand for both discretionary and non-discretionary load is clearly heterogeneous and subsequently any strict definitions would be futile.

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Australian Bureau of Statistics, 2002 General Social Survey, Victoria, cat number 4159.2.55.001, 21/01/2004. Additional information on this matter can be obtained through the Victorian Government Expert Committee Enquiry into Energy Hardship and the Committee for Melbourne Utility Debt Spiral project. 10 Essential Services Commission, Review of Effectiveness of Retail Competition in Gas and Electricity – Public Draft Report, 2004, p. 106

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1.3 Electricity consumption as a proportion of income

A common perception is that electricity is cheap and as such price increases will have little effect on consumption. However, the distributional impact on households paints a different picture and it is clear that for many Victorians electricity bills are far from negligible. Research has found that Victorian households that experience utility stress spend 9 per cent more on electricity than other customers. 11 Electricity is a normal good in the sense that as income increases, so does consumption. The DHS Survey data effectively demonstrated the effect income levels have on electricity consumption. Concession card households used 15 per cent less than non-concession households (4056kwh and 4766kw per annum respectively). 12 While usage increases with household size, concession card holders consistently consumed less than non-concession card holders across all household sizes. 13 As income increases, however, electricity consumption assumes a lower proportion of total household expenditure. Income elasticity of demand estimates (which measure the percentage change in demand divided by the percentage change in income) show that in the majority of cases, demand increases less than proportionally to the income change. Hunt and Manning (1989), for example, estimated the average income elasticity of demand in Britain as 0.49. 14 Lower income households demonstrate a greater price responsiveness with respect to their marginal consumption than households with higher incomes because electricity makes up a greater proportion of their household expenses. 15 1.4 Substitutability of electricity and appliance holdings

Households’ responsiveness to increases in electricity prices are likely to be larger if they are able to substitute their consumption with other fuels such as gas or wood. The DHS Survey found that 94 per cent of respondents used gas with usage for cooking, hot water and heating totaling 76 per cent, 78 per cent and 88 per cent respectively. 16 This suggests a possibility of high degree of substitutability of electricity for certain activities 17 yet for other purposes such as lighting or electrical appliance usage there will be little or no substitutability. Consumers seem to be conscious of the effect appliance use has on their energy consumption. Almost half of the respondents in the DHS Survey claimed that there were no particular appliances in their household that caused high energy usage (43 per

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Committee for Melbourne, Utility Debt Spiral Study, 2004, p. 7 and 73 Roy Morgan Research, Victorian Utility Consumption Survey 2001, Final Report, June 2002, p. 4 13 Department of Human Services, Response to the Review of Effectiveness of Retail Competition and the Consumer Safety net for Electricity and Gas Issues Paper, 2003, p.4 14 Hunt, L. & Manning, N., “Energy price – and income-elasticities of demand: some estimates for the UK using the cointegration approach”, Scottish Journal of Political Economy, 36(2), 1989, p.183 15 Reiss, P. and White, M., Household Electricity Demand, Revisited, unpublished manuscript, Graduate School of Business, Stanford University, October 12th 2001, p.26 http://www.stanford.edu/-mwwhite/demand.pdf 16 Roy Morgan Research, op. cit., p.iii. Note that the survey generally excluded areas not serviced by mains gas. 17 The actual penetration of gas is affected by availability (reticulation), marketing and government or utility policy 12

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cent) with aged/service pensioners being far more likely to say this. 18 Turning appliances off was also the second most frequently nominated energy conservation measure (40 per cent) after switching off lights (63 per cent). 19 Yet growth in energy demand, particularly the summer load, has been attributed to increased ownership and utilisation of air conditioners. While the use of other high energy consuming appliances such as clothes driers and dishwashers has remained stable or even decreased slightly, ownership and use of air conditioners has increased substantially. A comparison of the 2001 DHS Survey to a similar survey conducted in 1996 clearly demonstrates this. In 2001 just under 60 per cent of households owned air conditioners, up from 40 per cent in 1996. Over the same period utilisation of air conditioners increased on average by fifty-four hours a month. 20 This figure is estimated to have risen to 85 per cent of Victorian households in March 2005. 21 The effect of appliance utilisation and the responsiveness of households to price increases will be discussed in more detail when considering time of use pricing.

2. Price and its impact on demand 2.1 Demand elasticity estimates

Household electricity demand derives from the flow of services provided by household appliances, as such consumption levels are dependent upon both the quantity and efficiency of appliances used. 22 This characteristic of electricity use warrants the distinction between short run and long run demand elasticity. Short run elasticity is based on immediate behavioural changes such as turning lights off or reducing air conditioner usage. 23 Long run elasticity, on the other hand, is a more important measure since it takes into account utilisation changes and appliance replacement decisions. 24 The full extent of household demand response is not revealed until it is possible to see whether households change their energy consuming appliances for more efficient versions. 25 Interestingly, Reiss and White found that higher incomes correlated with substitution toward more price-inelastic electricity use, that is investing in appliances that gave them less opportunity to reduce demand. 26 In addition the income effects of electricity consumption were found to be a result of household appliance choices, rather than usage. 27 The majority of empirical studies suggest that demand for electricity is inelastic both in the short and long run. This means that the percentage change in the quantity of electricity demanded alters less than proportionately to the percentage change in price. 18

Roy Morgan Research, op. cit., p. x Roy Morgan Research, op. cit., p.x 20 Roy Morgan Research, op. cit., p.vii 21 Australian Bureau of Statistic, Environmental issues peoples view and practices, March 2005 page 56 cat 4602.0 22 Reiss, P. and White, M., op. cit., p.10 23 Wade, S., Price Responsiveness in the AEO2003 NEMS Residential and Commercial Buildings Sector Models, 2003, p.1 http://eia.doe.gov/oiaf/analysispaper/elasticity 24 Wade, S., Ibid, p.1 25 Reiss and White, op. cit., p. 10 26 Reiss and White, op. cit., p. 26 27 Reiss and White, op. cit., p. 24 19

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Presented in this section is a summary of short and long run elasticity estimates that have been produced by Australian and overseas studies. Research by Langmore and Dufty into household demand responses to electricity price increases found that: Data from 1980-1995 and estimated that the long run price elasticity of demand for the Australian residential sector was -0.25. 28 This means a 10% rise in price results in a 2.5% fall in demand for electricity, an inelastic response. The Victorian PED (price elasticity of demand) was estimated to lie between -0.23 and -0.53 with a mean value of -0.38. 29 Since elasticity estimates are contingent upon the magnitude of price rises, NIEIR reported that these could rise to -0.4 if prices changed by 30-40%. 30 In other words, to elicit a 4% drop in demand for electricity, price changes in the order of 30-40% would be required - thus highlighting how extraordinarily small consumer responses are relative to price changes. 31

That is, a 10 per cent price increase will result in a 2.5 per cent reduction in energy consumption, over the long term. Subsequently, if there was a policy objective to reduce consumption by 4 per cent it is estimated that price increases in the order of 30-40 per cent would be required if relying on price alone. The following example contextualises this in terms of the impact proposed price changes will have on households. It is estimated that the introduction of a carbon trading scheme will result in an electricity price increase in the order of $200 per annum for the average household. Furthermore, as this is the average, some will experience higher than this while others will experience lower cost increases. Using the average, with an estimated price increase of $200 per annum due to a carbon trading scheme, this will only lead to an electricity demand reduction of $50. This effectively means that the average household will be $150 per annum worse off with minor reductions in consumption. On the face of it this price increase may not appear to be a substantial amount however for lower income households, in particular pension and benefit recipients, this is equivalent to a week’s income. 32 Numerous studies have been undertaken in Australia and overseas to estimate demand elasticity. Appendix 1 provides detailed information on various studies but a summary of these studies shows that the lowest estimate for short run residential elasticity of demand is -0.03 while the highest estimate is -0.7. For long run estimates, the lowest residential elasticity of demand is set at -0.27 and the highest is 1.17. 33

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National Institute of Economic and Industry Research, The Price Elasticity of Demand for Electricity in NEM regions, prepared for National Electricity Market Management Company, June 2002 29 National Institute of Economic and Industry Research, op. cit., p. 3 30 National Institute of Economic and Industry Research, op. cit., p. 4 31 Langmore M & Dufty G, Domestic electricity Demand Elasticitites, Issues for the Victorian energy market, June 2004, page 11 32 Australian Government, Centerlink, A Guide to Government Payments, 1 July – 19 September 2007 33 Note that the high elasticities were recorded by studies undertaken during the oil crisis in the US in the 1970’s which we can expect had a positive influence on demand response.

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2.2 Time of Use pricing and customer response

The majority of literature on household response to time varying pricing comes from the United States, where a series of experiments were undertaken by the US Federal Energy Administration in the mid-1970s. Five experiments with mandatory participation and multiple rime of use (TOU) rates were of sufficiently high quality to yield unbiased price elasticity of demand estimates.34 These five studies showed a high degree of consistency of response across customers when differences in rates, peak length, appliance holdings and demographic factors were taken into account. 35 The elasticity of demand estimates have been reviewed already as part of a survey of empirical studies conducted by Charles River Associates on behalf of the Victorian regulator’s report into the costs and benefits of interval metering. The responsiveness of demand for electricity to changes in price by time of use was reported to be inelastic in the short run with most values for peak period usage falling between -0.1 to -0.3. 36 In other words, a 10 per cent price rise will cause consumers to reduce demand by between 1 and 3 per cent. The own price elasticity of demand for on-peak usage is typically larger than own price elasticity of demand for off-peak usage, 37 although in the case of peak load, the estimates had a larger range. These experiments also provided estimates for cross price elasticity of demand. Cross price elasticity of demand gives the percentage change in demand for electricity in one period divided by the percentage change in price in the other. Positive cross price elasticity of demand values are a sign the goods are substitutable while negative values indicate they are not. Cross price elasticity of demand for electricity for peak and off-peak periods yielded both positive and negative estimates. 38 This suggests that peak period electricity is both a substitute and complement to off peak consumption. At best, on the basis of cross price elasticity estimates obtained from the Californian experiments, a price rise of 10 per cent in the peak period would cause load shifting in the form of increased demand by 2 per cent in the off peak period. The table below summarises the price and cross-price elasticity of demand estimates reported by Charles River Associates using the available literature on the US experiments described above. 39 Table 3 Study

Location for experiment

Peak Period Price elasticity of demand

Off -Peak Price elasticity of demand

Cross price elasticity of demand

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ESC, Installing Interval Meters, Position Paper p.62. These were conducted by the following utilities: Carolina Power and Light, Connecticut Light and Power, Los Angeles Department of Water and Power (LADWP), Southern California Edison (SCE) and the Wisconsin Public Service. 35 Schlumberger Electricity Inc, DSM and Metering, Case for Advanced Metering, October 30, 2003, p.5 www.oeb.gov.on.ca/documents 36 ESC, Installing Interval Meters, Position Paper, p.65 37 ESC, Installing Interval Meters, Position Paper, p.66 38 ESC, Installing Interval Meters, Position Paper, p.62 39 ESC, Installing Interval Meters, Position Paper, p.61

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Miedema et al (1981)

California

0 to -0.4

-0.25 to 0.2

Hendrick and Koenker (1978)

California

0 to -0.42

-0.01 to -0.31

0

Mitchell and Acton (1980)

California

0.05 to -0.32

-0.12 to 0.17

-0.13 to 0.20

Lifson (1981)

California

Lifson (1981)

North Carolina, Oklahoma and Wisconsin

-0.08 to -0.27

Insignificant for North Carolina and Oklahoma. -0.08 to -0.27 for Wiconsin

Price elasticity of substitution has also been measured for these experiments and demonstrates as such how a rise in price at any time of day affects the use at other times. Price elasticity of substitution is the percentage change in the quantity ratio of two related goods or services divided by the percentage change in the corresponding price ratio. Parks and Weitzel’s study of price elasticity of substitution found that a rise in the price of electricity for any time period results in a significant increase in usage at other times. 40 The greatest substitution occurs between the morning peak and other morning periods or between the daytime peak and daytime/evening shoulder periods (shoulders being the time periods next to the peak). 41 In the case of both cross price elasticity of demand and elasticity of substitution measures, the level of substitutability or load shifting that is undertaken by households is likely to be dependent on a number of factors. Since electricity is not demanded in itself but rather is derived from the flow of services provided by energy using appliances, many features of the household and its members are likely to affect demand levels and patterns. These may be demographic or lifecycle related in the sense that the number, age and income of household members may affect demand. Lifestyle factors such as employment status, leisure time and household activities undertaken by household members will also affect demand. Finally, other variables affecting demand and fixed in the short run include dwelling size and appliance holdings. In summary the various household characteristics and factors influencing demand include income , household size, appliance holdings, household demographic, life cycles and life styles.

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Parks, R.W. and Weitzel, “Measuring the customer welfare effects of time-differentiated electricity prices,� Journal of Econometrics, 3(26), p. 50 41 Parks, R.W. and Weitzel, Ibid, p. 51

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3. Pricing structures and government concessions 3.1 Tariff design

There are severe equity implications associated with certain pricing structures. The tariff design will also have implications for the impact prices have on various classes of consumers or household types. The following examples look at the impact associated with some common tariff components and designs: •

• • •

Standing charges, irrespective of the pricing structure applied, will make up a larger proportion of the bill for small consumers than large consumers. Low income consumers (who on average use less) are also more likely to find these charges onerous. Flat tariff structures result in large users paying a larger share of costs by virtue of their larger consumption. However low volume customers may disadvantaged due the impact of the standing charge. Inclining block tariffs increase the cost for high volume users. Since lowincome consumers on average use less, they may benefit. Declining block tariffs increase the cost of use for low volume consumers and are thus more likely to disadvantage low-income households. Time of Use pricing is likely to disadvantage those who are unable to shift peak consumption. For low-income earners with little discretionary load, time of use pricing may result in higher bills. These losses may be offset however if cost savings achieved by the net reductions across the customer base are passed through to consumers. Those who use intensively during peak periods, such as consumers using air conditioners, will face the highest costs. This may affect those in warmer regions disproportionately. Dynamic pricing minimises cross subsidisation of peak period consumption. These tariffs provide the greatest cost reflectivity but can potentially penalise those without much discretionary load. Furthermore, low-income consumers may find the cost of monitoring prices onerous, especially if relying on the installation of devices to automate demand response. As with time of use pricing, consumer using air conditioners are likely to be disadvantaged.

These responses can in part be explained by the nature of electricity as a non-storable, largely non-substitutable, essential service. Furthermore, it highlights the inability of many households to change consumption in response to price signals, and hence the bluntness of pricing as a tool to drive behavioral change. 3.2 Government concessions

To ensure that all households have access to energy the service must remain affordable. The Victorian Government directly intervenes in ameliorating the impact of electricity tariffs on households through the provision of concessions. The Victorian Government increases affordability by providing various concessions and rebates, including: The Winter Energy Concession which provides a 17.5 per cent discount on winter bills for eligible households. This concession is designed to reduce the cost of heating for Victorian Health care card holders.

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The Network Tariff Rebate which acts as a cross subsidy to reduce the higher costs for supplying energy in non-metropolitan Victoria. The Supply Charge Concession which offsets the impact of the supply charge on lowconsumption households. The Off-peak Concession which is designed to ameliorate costs from significant increases in off-peak pricing during early 2000. All these concessions seek to reduce the impact of price on particular groups within the community, highlighting the social and economic impact of energy pricing.

4. A proposal for managing the impacts of electricity pricing 4.1 Pricing principles – achieving public policy objectives

Given the likelihood of increased electricity prices and price volatility, this proposal demonstrates how the Government can ameliorate much of the detrimental social impacts through implementing electricity pricing principles. These principles can complement and achieve several public policy objectives. Firstly, the pricing principles would not only serve to protect low consumption households (which include many low-income consumers) but also support and reward those that have or will implement energy conservation strategies. Secondly, the proposal does deny retail competition as the model allows industry to price according to what the market can accept. Thirdly, the model provides a structure for government to implement additional charges and levies, as may be required, for example by a carbon trading scheme. 4.2 The key principle - A “lifeline” price cap

The pricing principle proposal includes the introduction of a ‘household’ cap on daily electricity consumption at a fixed price per kWh. This “lifeline” cap should be set at a level of consumption that would equate to a minimum household usage to provide hot water, space heating, refrigeration and minimum lighting. As such, all energy consumed within the “lifeline” cap is protected from the pass through of costs associated with carbon trading and excessive profiteering by the electricity retailers. Price setting for consumption above the “lifeline” price cap, however, would be for each individual retailer to determine. Thus allowing the industry to price according to marginal cost or what the market will bear. 4.3 Fixed charges

In conjunction with a regulated price with minimum “headroom” for companies in the “lifeline” cap of energy usage, the fixed charge should be capped as proportion of the regulated electricity consumption component, say at a ratio of 80 per cent consumption and 20 per cent fixed charges. For example, if the regulated energy consumption component was set at 14 cents for a total of 1020 kWh per quarter (a total quarterly energy cost of $142.80) then the fixed cost could not be more than $28.56.

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This would serve to protect the intrinsic nature of the “lifeline” cap and minimise the overall potential for price distortions for low consumption households that could occur through the increase of fixed charges. 4.4 Pricing principles and other environmental levies

If governments believe that additional charges need to be levied, for example to raise revenue for demand management or energy conservation programs, these should be applied on top of the price set by retailers. The overall effect of establishing a “lifeline” tariff with no room for excessive profiteering, while completely deregulating prices above, effectively results in the industry implementing an inclining block tariff. 4.5 The advantages of pricing principles

These principles would serve a number of policy objectives that are consistent with social justice and environmental equity: First, they would provide a “lifeline” price cap. This price cap would serve to partially protect many low-income energy consumers from the cost of carbon pricing being incorporated into the first block or the fixed charge of electricity consumption. This is a potential risk as most carbon is produced from base load generation and as such costs associated with carbon trading could be passed through in the first block of consumption or in the fixed charge, rather than energy consumption at moderate or higher levels. Second, such pricing principles would not only provide a reward for those households with low electricity usage it would also serve as an incentive for all households to reduce consumption to a particular level, thus supporting and rewarding those households that have sound environmental practices. Third, such a proposal would be consistent with, and complement, calls for households to be issued with a carbon emissions budget. Furthermore, it would align a household based scheme with the proposed arrangement for stationary energy production. 42 Fourth, although such a proposal would increase electricity costs for households with large consumption (costs they would be exposed to without the introduction of pricing principles), it would also make retrofitting and other alternative energy sources, such as solar photo voltaic technologies, more cost competitive. Fifth, the pricing principles structure complements the current energy concessions framework. The concessions framework could be exposed to significant cost increases if industry introduced declining block tariffs or raised fixed charges. The proposed model provides an incentive to reduce consumption and therefore reduces this exposure to potential growth in the cost of concession delivery.

42

The proposed arrangement means that generators will be allowed to exempt production to a certain level from additional cost. This cost structure should be applied directly to households.

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Six, it would allow the Government to deliver on its commitment to deregulation of electricity pricing. Finally, it would complement the planned interval meter (smart meter) roll out allowing these principles to be implemented as the smart meters are installed in households providing a real and practical use for this technology that every consumer ultimately pays for. I believe these pricing principles, if introduced in conjunction with targeted audit and retrofit programs, possible adjustments to the broader energy concessions and rebate program, and the introduction of education strategies that assist households with practical behavioral change, would go a long way towards counter-balancing the social impacts of carbon trading while assisting with meaningful greenhouse emission reductions. Acknowledgements The author would like to acknowledge the valuable assistance in preparing this paper by May Johnston and the support of the Consumer Utility Advocacy Center.

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Appendix 1 Numerous efforts have been made in Australia and overseas to calculate demand elasticity. The Independent Pricing and Regulatory Tribunal of New South Wales’ (IPART) investigation into inclining block tariffs cited the following studies and estimates of residential price elasticity. 43 • • •

• •

Filippini and Pachauri (2002) estimated a short run residential demand elasticity of between -0.16 and -0.39 for Indian households. 44 Fatai, Oxley and Scrimgeour (2003) estimated short run price elasticity of demand for New Zealand to lie between -0.18 and -0.24 and long run estimates in the range of -0.44 and -0.59. Miller (2001) estimated a long run residential demand elasticity for the United States of -0.37. 45 Miller’s report also documented the long run residential price elasticity of demand estimates obtained from U.S. data in 14 other studies conducted from the 1960s to the mid-1990s. Estimates lay within a large range, with the majority between -0.5 and -1.5. 46 Wade (1999) estimated U.S. price elasticity of demand in the short and long run yielding -0.23 and -0.31 respectively. 47 Furthermore, cross price elasticities 48 range from 0.0 to 0.86. 49 Studies reviewed by Sayers and Shield (2001) and Fatai, Oxley and Scrimgeour (2003) estimated short run price elasticity of demand of between 0.17 and 0.7 and for the long run between -.27 and 1.1795. 50

Other reviews of empirical studies which have yielded price elasticity of demand estimates that were not discussed in the IPART report include: •

Lafferty et al, cite Taylor who incorporated eighteen elasticity studies into two surveys and found that the short run price elasticity for aggregate elasticity demand is -0.2 and the long run elasticity is between -0.7 and -0.9. 51

43

IPART, Inclining Block Tariffs for Electricity Network Services, Secretariat Discussion Paper, June 2003. In the case of Miller and Wade’s study extra information, not included in IPART’s report, has been provided. 44 Filippini, M. and Pachauri, S., “Elasticities of electricity demand in urban Indian households” CEPE Working Paper No. 16, Centre for Energy Policy and Economics, Zurich, Switzerland, 2002 45 Miller, J.I Modeling Residential Demand for Electricity in the U.S.: A Semiparametric Panel Data Approach, Unpublished draft manuscript, Rice University, November 2001, p.1 46 Miller, J.I, Ibid, p.3. Since many studies included data from the crisis period of the 1970s structural change was thought to account for this wide range. Furthermore, the difference in elasticities during periods of falling prices as opposed to periods of rising prices was also thought to be a contributing factor. 47 Wade, S., Price Responsiveness in the NEMS Buildings Sector Model, Report No. EIA/DOE – 0607(99), http://www.eia.doe.gov/oiaf/issues/building_sector.html 48 Cross price elasticity of demand gives the percentage change in demand for electricity in one period divided by the percentage change in price in the other. 49 Wade, Ibid, p. 1 50 Sayers, C. and Shield, D. 2001, Electricity Prices and Cost Factors, Staff Research Paper, Productivitity Commission, Canberra. 51 Lafferty, Huynger, Ballard, Mahrenholz, Mead bandera, Demand Responsiveness in Electricity Markets, Office of Markets, Tariffs and Rates, January 15, 2001, p.8

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• • •

• •

A survey of twenty five studies of residential demand by Bohi demonstrated short run elasticities varying from -0.03 to -0.54 and long run elasticities varying from -0.45 to -2.1. 52 From a survey of 18 studies of residential demand Bohi and Zimmerman conclude that the short run price elasticity for the residential sector is -0.2 and the long run price elasticity is -0.7. 53 A survey of aggregated demand, 21 residential, 7 commercial and 18 industrial studies of price elasticity of demand by Dahl showed wide variances in price elasticity estimates. Long run price elasticity of demand for the residential sector was nonetheless estimated between -0.91 and -0.75. 54 The Western Public Agencies Group similarly cite these studies by Dahl, Bohi & Bohi and Zimmerman yet also use studies by Houthhakker, H. and Taylor, L and Uri, N. D. to find that elasticities are between -0.13 and -0.45. 55 Supawat Rungsuriyawiboon (2000) estimated short run price residential electricity demand as -0.213 while the long run price elasticity is -0.975. 56

52

Bohi, D.R., Analysing Demand Behaviour: A survey of Energy Elasticities, John Hopkins University Press, Baltimore, 1981 54

Dahl, C., “A survey of Energy Demand Elasticities in Support of the Development of the NEMS,” (1993) contract De-APOI-93EI23499, US Department of Energy 55 Houthakker, H. and L. Taylor, Consumer Demand in the United States: Analyses and Projections, Cambridge: Harvard University Press, 197- and Uri, N “The Growth in the Demand for Electrical Energy in the United States” Journal of Energy and Devleopment, 3(1). Autumn 1977, cited in Western Public Advisories Group, Price Elasticity of Demand for Electricity p.2 56 Rungsuriyawiboon, S., “Demand for Residential Electricity in the United States”, Unpublished paper, May 5, 2000, p.,1

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