Fuel consumption of European Fuel consumption of European cars: The effect of standards, cars: The effect of standards,

taxation and safetytaxation and safety

Theodoros Zachariadis

Economics Research Centre, University of Cyprus

COST 355 meeting, Madrid, May 2007

Contents

• The effect of standards on fuel economy (Clerides and Zachariadis, “Are standards effective in improving automobile fuel economy?”, July 2006)

• Some recent results, trying also to explain the share of diesel cars in each country

• Do vehicle safety requirements compromise fuel economy?

Rationale of the study on fuel economy standards

• Share of transportation in energy use and GHG emissions steadily rising

• It will take time for biofuels and new technologies (hybrids, fuel cells etc.) to be effective

Improve fuel economy of conventional engines/fuels

FE improvements may be attained through:

• Higher fuel prices

• FE standards / industry voluntary commitments

• CO2-based vehicle taxation

• Autonomous technical progress

How much improvement from which measure?

Previous similar work

• Espey (Energy Economics, 1996); Johansson & Schipper (J. Transp. Econ. Policy, 1997)

• Greene (Energy Journal, 1990)

• Gately (Energy Journal, 1992)

• Small & Van Dender (UC Irvine, 2005)

What is new in our study:

• 18 countries, 20 cross-sections, period: 1975-2004

• Period with & without FE standards, with high & low fuel prices

• FE standard is explicitly addressed as a variable

New-car fuel consumption and standardsin the US and EU, 1975-2004

4

8

12

16

20

1975 1980 1985 1990 1995 2000 2005 2010

Model Year

Fue

l Con

sum

ptio

n (li

ters

per

100

km

)

0

10

20

30

40

50

60

70

80

90

Con

stan

t Bre

nt p

rice

(US

$'20

04)

US CarsUS CAFE Car StandardEU CarsEU voluntary targetBrent price

Data (sample size: 384)

Country Vehicle category Sample period Type of standards Enforcement typeFirst decision for the adoption of

standards/targets

First year of implementation or

first target year

Australia Cars 1978-2002 FE Voluntary 1978 1978Austria Cars 1980-2003 CO2 Voluntary 1998 2008Belgium Cars 1980-2003 CO2 Voluntary 1998 2008Canada Cars 1980-2003 FE Voluntary 1976 1980Canada Light duty trucks 1980-2003 FE Voluntary 1982 1990

Denmark Cars 1995-2003 CO2 Voluntary 1998 2008France Cars 1980-2003 CO2 Voluntary 1998 2008

Germany Cars 1980-2003 CO2 Voluntary 1998 2008Ireland Cars 1995-2003 CO2 Voluntary 1998 2008

Italy Cars 1980-2003 CO2 Voluntary 1998 2008Japan Cars 1980-2000 FE Mandatory 1995 2010

Luxembourg Cars 1995-2003 CO2 Voluntary 1998 2008Netherlands Cars 1995-2003 CO2 Voluntary 1998 2008

Portugal Cars 1995-2003 CO2 Voluntary 1998 2008Spain Cars 1995-2003 CO2 Voluntary 1998 2008

Sweden Cars 1981-2003 CO2 Voluntary 1998 2008Switzerland Cars 1996-2004 FE Voluntary 2002 2008

United Kingdom Cars 1980-2003 CO2 Voluntary 1998 2008United States Cars 1975-2004 FE Mandatory 1975 1978United States Light duty trucks 1975-2004 FE Mandatory 1975 1982

Regression results

Notes: Estimation carried out with the Arellano-Bond GMM procedure. Robust t-statistics in brackets. *, ** and *** denote significance at 10%, 5% and 1% level. Last column reports the probability of the Arellano-Bond test for second order serial correlation of residuals.

CountriesCross-

sectionsSample

sizeλ

Time trend

Price STD Income Autocorrel.

All 20 339 0.709 *** -0.001 -0.080 *** 0.135 *** -0.004 0.636[20.270] -[1.350] -[6.580] [2.490] -[0.130]

N. America 4 98 0.653 *** 0.000 -0.094 *** 0.236 * -0.009 0.649[9.180] [0.160] -[3.180] [1.770] -[0.170]

EU 13 193 0.780 *** -0.001 -0.043 *** 0.219 *** 0.015 0.426[26.760] -[1.000] -[4.190] [3.760] [0.320]

Policy implications – 1

1. Are FE standards significant for reducing automobile

fuel consumption?

• Use data from AT, BE, FR, DE, IT, JP, SE and UK

• Split data in two periods: ‘pre-standard’ (1980-1994) and ‘with standards’ (1995-2004)

• Re-estimate model without STD variable: i) for ‘pre-standard’ period ii) for entire period

• Perform a Wald test and a Chow test to examine stability of estimated coefficients

• Both tests reject the null of coefficient stability

structural break, i.e. FE regulations made a difference

New-car fuel consumption in Europe and Japan, 1980-2003

(liters / 100 km)

4

5

6

7

8

9

10

11

1975 1980 1985 1990 1995 2000 2005

FranceGermanySwedenUKJapan

Policy implications – 2

2. Given a future FE (or CO2) target to be met without

tighter standards, how much should prices increase?

• In the US, tightening current CAFE standard by 10% is equivalent to raising gasoline price by 36 US cents’2004 / gallon (result is similar with those of other studies)

• In Europe, stated policy target of 120 g CO2/km – 25% tighter ‘standard’; retail fuel prices might have to double to induce similar fuel savings

Policy implications – 3

3. How might fuel consumption evolve without further

standards and at today’s fuel prices?

Time trend coefficient: α1 insignificant, near zero

i.e. no ‘autonomous’ improvement per year ?

Changing consumer preferences towards more powerful and comfortable cars have cancelled out any autonomous technical progress

European long-term models, assuming that FE will continue to improve at fast rates even without post-2010 FE regulations, may have to be revisited

Policy implications – 4

4. Are taxes always the most efficient measure?

“To tackle an externality, impose a tax and let the market work”

But: Taxes less effective because of consumer myopia Impact of higher taxes on the whole economy?

(e.g. sectors that use fuel as an intermediate good) Political acceptance of higher taxes Major externalities (accidents, congestion)

associated with miles driven, not with fuel consumed

Conclusions of the study on FE standards

• If there were no standards in force, car fuel economy would not have improved considerably

• Very high fuel price increases required in Europe if fuel economy to be improved without standards

• Absent technological breakthroughs or an economic recession, FE will only improve further with tighter standards

• Raising fuel taxes is not an option for Europe, could be considered in the US together with stricter standards (modified CAFE rules)

Recent extensions

• Focus on European countries only

• Fuel consumption may also depend on: total vehicle taxes (registration, circulation, insurance etc.) urbanisation and population density ratio of retail gasoline/diesel price

• Except for gasoline/diesel ratio, other variables not available as a time series but only as a country-specific figure for a given year (i.e. fixed effect)

• Efficient estimation of dynamic panel models wipes out fixed effects, therefore adding these as explanatory variables is not possible

Feedback requested: are national data on vehicle taxation available for several years?

Effect of gasoline/diesel price ratio

• Price ratio was constructed from retail fuel prices (source: IEA)

• To avoid endogeneity/collinearity:

– Gasoline price is the average of the previous three years

– Gasoline/diesel ratio is the current year’s price ratio

Using both price variables improves estimation

CountriesCross-

sectionsSample

sizeλ

Time trend

gasoline price

price ratio

STD Autocorrel.

EU + CH 14 201 0.704 *** -0.001 *** -0.026 ** -0.024 *** 0.268 *** 0.246[25.520] -[2.580] -[2.050] -[3.290] [4.800]

Is there a safety – fuel economy trade-off?

• “Car manufacturers don’t respect their CO2 commitment … legislation to cut CO2 emissions from cars to come soon”

EU Environment Commissioner, 03/11/2006

• “Decrease in CO2 emissions has recently slowed. This is due to strong customer demand for larger and safer vehicles and disappointing consumer acceptance of extremely fuel-efficient cars”

European car industry (ACEA), 05/11/2006

• “Better car safety does not jeopardise emission reduction … the added weight due to safety interventions is negligible”

European Transport Safety Council, 13/11/2006

Safety vs. fuel economy

Two questions:

1. Does safety affect vehicle mass?

2. Does safety affect fuel consumption / CO2 emissions?

US studies analyse relationship between traffic fatalities and attributes of vehicles involved in accidents [see Ahmad and Greene, Transp. Res. Record 1941(2005): 1-7]

Earlier results showed that lower fuel consumption leads to less safety more fatalities

Recent evidence is inconclusive

Safety vs. fuel economy: Empirical analysis

• Car safety data obtained from EuroNCAP website for 193 cars of model years 2000-2007(www.euroncap.com)

• EuroNCAP provides consumers with independent information about a car’s safety

• Ratings for three tests are provided: Adult occupant test, pedestrian test, child protection test

• Score is provided in integer numbers (e.g. 0-30) and then codified in stars (‘excellent’ is 5 stars for adult & children tests, 4 stars for pedestrian test)

• For each model tested, EuroNCAP provides exact model description (e.g. Peugeot 207cc, 1.6 ‘sport 1’), kerb weight and model year

Safety vs. fuel economy: Empirical analysis (2)

• For each one of the 193 EuroNCAP car models, fuel consumption & CO2 data were retrieved from the 2001-2006 databases of the German Federal Motor Transport Authority (KBA) (purchased on CD-ROMs)

• Data for 2007 models were obtained from online databases of the UK Vehicle Certification Agency (VCA) (www.vcacarfueldata.org.uk) & of portal www.carpages.co.uk

• Linear regressions:

massi = f(safetyi, engine_sizei, dsl_dummy, year_dummy)

CO2i = f(safetyi, engine_sizei, dsl_dummy, year_dummy)

Results (1): Safety effect on vehicle mass is very small

Dependent Variable: MASS (kg/100)Method: Least SquaresIncluded observations: 192White Heteroskedasticity-Consistent Standard Errors & Covariance

Variable Coeff. Std. Error t-Stat. Prob.

ENGINE_SIZE 5.610 0.347 16.167 0.000SAFETY (adult rating) 0.043 0.016 2.690 0.008

C 1.714 0.518 3.309 0.001diesel_dummy 1.803 0.329 5.484 0.000

automatic_dummy -3.390 0.892 -3.801 0.000year01 0.549 0.315 1.743 0.083year02 0.221 0.439 0.502 0.616year03 0.557 0.304 1.832 0.069year04 0.111 0.358 0.311 0.756year05 0.309 0.288 1.075 0.284year06 0.761 0.387 1.965 0.051

R-squared 0.864Adjusted R-squared 0.857

Mean dependent var 13.667 S.D. dependent var 3.490

Durbin-Watson stat 1.509

Results (2): Safety effect on CO2 is marginally significant, small and negative!

Dependent Variable: CO2 (g/km)Method: Least SquaresIncluded observations: 190White Heteroskedasticity-Consistent Standard Errors & Covariance

Variable Coeff. Std. Error t-Stat. Prob.

SAFETY (adult rating) -0.493 0.274 -1.802 0.073ENGINE_SIZE 73.892 3.221 22.940 0.000

C 68.931 6.667 10.339 0.000diesel_dummy -27.279 3.615 -7.545 0.000

automatic_dummy -8.555 11.833 -0.723 0.471year01 -0.793 4.209 -0.188 0.851year02 9.540 6.032 1.582 0.116year03 1.548 4.025 0.385 0.701year04 -4.211 4.721 -0.892 0.374year05 -4.544 3.941 -1.153 0.251year06 -7.592 4.860 -1.562 0.120

R-squared 0.848Adjusted R-squared 0.840

Mean dependent var 180.237 S.D. dependent var 40.024

Durbin-Watson stat 1.562

Safety vs. fuel economy: tentative conclusion

• “Better car safety does not jeopardise emission reduction … the added weight due to safety interventions is negligible”

European Transport Safety Council, 13/11/2006

ETSC is probably right !• Results are similar if we observe subsets of the whole

sample (e.g. if we exclude SUVs and/or superminis, observe family cars and/or MPVs only)

• Results are similar if safety variable includes both adult+pedestrian test ratings

• Results are consistent with Ahmad and Greene (2005) who used fatalities as dependent variable

Please comment!