The Demand for Energy of Italian Households

1

The Demand for Energyof Italian Households

Ivan Faiella

2

Italian Households Energy Demand

Questions

1. What is the consumption of energy of ItalianHouseholds?

2. What have been the main drivers of energy demand inthe past?

3. Is heterogeneity relevant in explaining energy demand?

4. How changes in demographic structure will affectenergy demand in the next decades?

5. How changes in energy prices and surfacetemperatures will affect energy demand in the nextdecades?

3


4


0

5

10

15

20

25

30

35

40

45

50

55

19711972197319741975197619771978197919801981198219831984198519861987198819891990199119921993199419951996199719981999200020012002200320042005200620072008

Mto

e

Petroleum products (HH transport)ElectricitySolid Fuels&RenewablesGasPetroleum Products (heating) estimates

5

Households Energy Prices

80

90

100

110

120

130

140

150

160

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Pric

e in

dex

(200

2=10

0)

Petrol

Gasoil (motor fuel)

Gasoil (heating)

Natural gas

Electricity

Price level (excluding energy)

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Households Energy Intensity

0

10

20

30

40

50

60

70

80

90

100

19711972197319741975197619771978197919801981198219831984198519861987198819891990199119921993199419951996199719981999200020012002200320042005200620072008

Toe

per

M€

(200

0)

Petroleum products (HH transport)ElectricitySolid Fuels&RenewablesGasPetroleum Products

7

The drivers of Households Energy Demand

25

30

35

40

45

50

55

1971

1972

1973

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

50

60

70

80

90

100

110

HHs energy intensity (toe per M€ 2000)

HHs energy demand (Mtoe)

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The drivers of Households Energy Demand

-4%

-3%

-2%

-1%

0%

1%

2%

3%

4%

1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

Change in E/CChange in C/HHChange in HH

High crude oil prices High crude oil pricesLow crude oil prices

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Households Energy Efficiency

0.60

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1990 1995 2000 2002 2003 2004 2005 2006 2007

toe

/ca

r

Italy

EU27

Energy consumption of road transport per equivalent car

In Italy, cars are energy-efficient …

1.50

1.55

1.60

1.65

1.70

1.75

1990 1995 2000 2002 2003 2004 2005 2006 2007

toe/dw

ellin

g

Italy

EU27

Consumption per dwelling scaled to EU average climate

… but buildings are not!

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Italian Households Energy Expenditures

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Households Energy Expenditures: trends

Ratio of energy expenditures to total expenditures (1997-2008)

private transport

heating

electricity

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%

11%

12%

13%

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

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Households Energy Expenditures: distribution

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Households Energy Expenditures: stylised fact 1

0%

1%

2%

3%

4%

5%

6%

7%

8%

0 20 40 60 80 100age class of the RP

heating private transport electricity

Ratio of energy expenditures to total expenditures (2008)

14

0%

1%

2%

3%

4%

5%

6%

7%

8%

1 2 3 4+household size


Households Energy Expenditures: stylised facts 2


15

0%

1%

2%

3%

4%

5%

6%

7%

1 2 3 4 5 6 7 8 9 10tenth of equivalent expenditure




16

4,4% 3,6% 2,9%

5,2%5,6%

6,1%

1,9% 2,2% 3,2%

0%

2%

4%

6%

8%

10%

12%

14%

North Center South

geographical area




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A model for households Energy Expenditures

1.Prices (P): in the short term, energy demand is rather inelastic, because of the lowdegree of substitution, while in the medium term, the rise of energy prices inducehouseholds to invest in energy-efficient appliances (or switch to less expensive fuels).The efficiency gain might be crowded-out by an increase in energy demand aphenomenon known in the literature as rebound effect.

2.Demographics (Zi): energy demand increases with the number of householdmembers and with the presence of pre-school children and elderly people that spendmore time at home. Households where members commute using privatetransportation demand more energy and those living in small towns have less optionsto use public transportation.

3.Climatic conditions (T): the use of energy is also affected by the change in surfacetemperature. The increase in the temperatures reduces heating demand but increasethe request for cooling and this can primarily affect households residing in SouthernItaly. For example in 2006 the peak demand for electricity was registered - for thefirst time in Italy - during summer.

(i= i-th Household. j=1,2,3: heating, transport and electricity)

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A model for households Energy Expenditures

(i= i-th Household. j=1,2,3: heating, transport and electricity)

SURE estimate of a quasi-quadratic Almost Ideal Demand System (QAIDS):

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A model for households Energy Expenditures(95 per cent confidence intervals)

Heating

-15% -10% -5% 0% 5% 10% 15%

Age

Age squared

Employed

Self employed

College degree

More than 2 HH members

Dependants (age<6or age>74)

More than 4 rooms

Houseow ner

Expenditure < 20th perc

Expenditure > 20th perc

North

South

Surface temperature

Surface temperature (South)

log(expenditure)

log(expenditure) squared

Number of durables

log of price for heating (gas)

log (price for electricity)

log (price for liq fuels)

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Electricity

-8,0% -6,0% -4,0% -2,0% 0,0% 2,0%

Age

Age squared

Employed

Self employed

College degree



More than 4 rooms

Houseowner



North

South

Surface temperature


log(expenditure)


Number of durables





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Private transport

-5% 0% 5% 10% 15% 20% 25% 30%

Age

Age squared

Employed

Self employed

College degree



More than 4 rooms

Houseowner



North

South

Surface temperature


log(expenditure)


Number of durables





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Households Energy Expenditures: 2020 and 2030 simulation

Simulation of energy-related shares on households expenditures using thestructural relations estimated.

• Energy prices changes (electricity, gas and liquid fuels) incorporate IEAscenarios for 2020 and 2030.

• Surface temperatures modifications incorporates OECD (2008) projectionsfor 2020 and 2030.

• Demographic structure is modified (raking ratio technique): Age x Sex, according to Istat (2009). Household size using Istat and survey data to estimate the trend in the

reduction of household size (and the increase in households number)

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Households Energy Expenditures: simulation results

• Energy-related shares decrease by 1.8 percentage points (pp) in 2020 and of2.2 pp in 2030. The reduction is largely driven by the effect of climate changeand prices (there is a major reduction in the share of heating).

• The increase in surface temperatures reduces the demand for heating andapparently counterbalances the higher demand for electricity induced by therequest of cooling.

• Unless a major structural shift in households behaviour takes place, the aging ofthe Italian population is going to exercise a downward pressure on energy use(demand for electricity and heating will be more than compensated by thedecrease in the demand for private transportation).

• The distribution of the shares in 2020 and 2030 becomes more unequal (this isdetermined by both demographics, prices dynamics and higher temperatures).

0 0.1 0.2 0.3 0.4 0.5 0.6

2007

2020

2030

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Households Energy Expenditures: main conclusions

1. Italian households use a third of total final energy demand (47 Mtoe, about 2 toeper HH and 0.8 toe per individual): 80 per cent is used for heating/cooking andtransportation.

2. In the past decades the increase in households number almost offset the gains inenergy efficiency.

3. Households Energy bill amounts to about 12 per cent of total expenditures and ismore unequally distributed than other items.

4. Households Energy expenditures show different patterns according to households’characteristics.

5. Changes in demographic structure, in energy prices and surface temperatures willreduce the mean energy demand in the next decades - with the increasing numberof HH contrasting the aging effect. Energy efficiency improvements will probablysustain this reduction.

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Possible improvements of the analysis

1. Temperatures should be modeled at a more disaggregated level (atleast at nuts1 level);

2. some indicator of energy efficiency should be included;

3. the modelling strategy should be modified in order to improve itsrobustness in dealing with the high number of households with zeroexpenditures for private transportation;

4. stochastic simulation.

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The Demand for Energyof Italian Households

Ivan Faiella

Thanks!

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The Demand for Energy of Italian Households