ISSN No. 2193-7214
On the evidence of rebound effects in the lighting
sector: Implications for promoting LED lighting *
Bianca Blum a; Julian Hübner b; Adrian Milde c;
Bernhard Neumärker d
* Developed first as a Thesis at the Department of Economic Policy &
Constitutional Economic Theory.
a, b, d Department of Economic Policy & Constitutional Economic Theory,
University of Freiburg, Germany.
c Student in Economics, University of Freiburg, Germany.
E-Mail: email@example.com; firstname.lastname@example.org;
10th, May, 2018
University of Freiburg
Institute for Economic Research
Department of Economic Policy and Constitutional Economic Theory
Platz der Alten Synagoge / KG II D-79085 Freiburg
Developed as part of the collaboration project between the University of Freiburg and the
Leistungszentrum Nachhaltigkeit, as well as the partners of the project “Sustainable LED Lighting
- Technologische Herausforderungen, Marktzugangshürden und politische Akzeptanz (SusLight)“.
Table of Content
1. Introduction ............................................................................................................................. 1
2. Germany and the energy consumption for lighting ................................................................ 2
3. On the rebound effect of efficiency improvements in lighting ............................................... 3
3.1. Definition of the Rebound effect......................................................................................... 3
3.2. Empirical evidence on rebound effects in the lighting sector ............................................. 4
4. Implications for the promotion of LED lighting ....................................................................... 8
5. References ............................................................................................................................. 10
With EU Regulation 244/2009, the EU was planning to switch from classic incandescent and
halogen lamps to more efficient lighting technologies, such as compact fluorescent lamps and LEDs
(see Verordnung (EG) Nr. 244/2009). The aim was to reduce energy consumption for lighting. After
all, a light bulb consumes about six times as much power as a comparable LED holding the intensity
of the light constant (see Mills and Schleich 2014). The EU promised about europe-wide electricity
savings of up to 40 billion kWh. Savings in the order of 7.5 billion kWh were forecast for Germany,
which corresponds to about 1.4% of total electricity consumption in Germany (539 billion kWh) in
2009 (see Frondel 2010). In addition, the EU Commission promised to avoid up to 15 million tonnes
of carbon dioxide annually (see Frondel 2010).
The fact that consumers reacted to the prohibition of incandescent lamps with so-called
"Hamsterkäufen” of light bulbs and that halogen lamps have gained a lot of market share since
the prohibition of trade weaken the expected success of the Regulation (see Danish Energy Agency
2015). In addition, the purchase prices of LED fell faster than expected and their development was
faster than predicted, which means that the market shares of LED are also higher than had been
forecast (see Danish Energy Agency 2015). It is estimated that LEDs will account for 71% of global
residential lighting by 2020 (De Almeida et. al.., 2014).
The English economist and philosopher William Stanley Jevons states in his 1865 book that the
more efficient provision of a raw material leads to an increase in the consumption of this raw
material (see Jevons 1865, cited from Clark and Foster 2001). Even today's economists, such as
Borenstein (2013), draw attention to the fact that more energy-efficient goods are used more
frequently than the less efficient predecessor models. This phenomenon is known as the Jevons
Paradox or rebound effect. The concept of Jevons was revived by economists Khazzoom and
Brookes in the 1980s. Hertwich (2005) summarizes Brooke's approach in such a way that
increasing energy efficiency triggers economic growth, which subsequently leads to a net increase
in energy demand (see Hertwich 2005). Brookes sees the rebound effect as a macroeconomic
phenomenon. If gross production increases due to more efficient use of fuel and fuel consumption
increases because its effective prices are falling, then this is a sign of a rebound effect (Brookes
1978, cited from Greening, Green and Difiglio 2000). Khazzoom (1980) takes only one energy
service into account and explores how the demand for it changes when real prices decrease due
to an increase in efficiency (see Khazzoom 1980, cited from Hertwich 2005). Saunders (1992) then
summarizes the two approaches in his paper "Khazzoom-Brookes Postulate" (see Saunders 1992,
cited from Sorrell 2009). Today, "rebound" is understood when only a part of the energy saving
potential is achieved due to rising demand (see Santarius 2015, p.42). This means that an
improvement in efficiency of 1% results in a reduction in energy consumption that is less than 1%
(see Binswanger 2001). How large the rebound effect is, is still controversial today. Some studies
show that the rebound effect exists and can be of great relevance (see Binswanger 2001, Greening,
Green and Difiglio 2000, Sorrell and Dimitropouls 2008). While others find that the rebound effect
is of lesser importance for most energy services (see Schipper and Grubb 2000). It is crucial how
the term is understood and defined.
The aim of this paper is to assess the evidence of rebound effects in the lighting sector through
empirical studies and derive policy implications for promoting LED lighting. In the first section
energy consumption for lighting in Germany is considered to estimate the relevance of possible
rebound effects. Following on from a brief definition of the term rebound, empirical studies on
rebound effects in the lighting sector will be considered and analyzed. This will provide insight into
the potential relevance of rebound effects in the sector under consideration and provide the
opportunity to derive policy implications for promoting energy efficient LED.
2. Germany and the energy consumption for lighting
Germany is pursuing ambitious targets for the energy turnaround; in 2020, for example, it intends
to reduce gross electricity consumption by 10% compared to 2008, and by 2040 gross electricity
consumption should even be 25% lower (see Destatis 2015, p.11).
In its report "Daten zur Umwelt", Destatis (2015) compares energy consumption by application in
2005 and 2015 (see Destatis 2015, p.34). It is found that the share of lighting in total energy
consumption has increased over the years studied from 1.7% in 2005 to 1.9% in 2013. Electricity
consumption for lighting also increased by 4.8%, from 12.4 billion kWh in 2005 to 13 billion kWh
in 2013 (see Destatis 2015, p.40).
In a large-scale meta-study on energy efficiency in Germany, Bauernhansl and Sauer (2016) also
conclude, that the energy requirements for lighting increased from 2003 to 2014. This increase in
energy demand takes place despite the possibility of saving large amounts of energy through more
energy-efficient lighting (see Bauernhansl and Sauer 2016, p.203). The reasons for the insufficient
decrease in power requirements for lighting are various. In their study, the authors suspect that
this might be due to the rebound effect.
Along with the increased consumption of light, the number of applications for lighting is steadily
increasing. For example, data from the Federal Statistical Office show that the trend is currently
towards more living space and an increase in single- and two-person households (see Destatis
2015 p.11). Thus, not only effectively more area is created, which is to be illuminated, but it also
use fewer people the illuminated area. Another reason that seemed to prevent the expected
savings from the light bulb ban was the relatively small switch to LED lighting. While the sales of
halogen lamps in Europe increased by 477% between 2007 and 2013 (see Danish Energy Agency
2015), LEDs consumed comparatively slightly more. The main reasons for this seemed to be the
high purchase price (see Leuser, Weiß and Britschke 2016).
There is obviously considerable potential in Germany to save energy in the lighting sector by using
energy-efficient light sources such as LED. However, the relevance of rebound effects should be
considered here. In the following, after a short definition of the term, empirical studies on the
rebound effect in the lighting sector will be presented and discussed.
3. On the rebound effect of efficiency improvements in lighting
3.1.Definition of the Rebound effect
First of all, a short definition of the term rebound effect investigated in the context of this paper
is to be made. It is also important to distinguish between energy efficiency, energy and energy
services. Energy efficiency is defined as the relationship between output and input, in the case of
lighting that would be the ratio of generated lumens (output) and wattage (input) required (see
Sorrell and Dimitropoulos 2008). Energy is the input factor here, measured in wattage, as the
required amount of electricity to provide an energy service. Following Sorrell and Dimitropoulos
(2008), output is defined as an energy service. This can result in a rebound effect if the lighting
intensity has increased, while the energy consumption remains constant.
Moreover, rebound does not necessarily mean that the same energy service has an increasing
demand. It may also be possible, that the energy efficiency improvement of one good leads to an
increase in the demand for another different energy service. It may happen that savings in the
automotive sector are re-invested in an air travel. In this case, we speak of an indirect rebound
effect (see Madlener and Alcott 2009). This paper is based on a definition of the direct rebound
effect, which requires that energy efficiency improvement causes the increase in demand for
energy services (see Santarius 2015, p.48).
Furthermore, when considering the rebound effect, the approaches examined here are
predominantly addressed only to the consumer side, but not to the producer side, as is the case
in other publications (see Berkhout, Muskens and Velthuijsen 2000, see Sorrell 2010).
Sorrel and Dimitropoulos (2008) explore in their study the different, microeconomic definitions of
the rebound effect, as well as their weaknesses and strengths. The rebound effect is usually
determined by elasticities, such as price, income, or substitution elasticities. In addition, it is
assumed that the efficiency improvement is exogenous and therefore costless (see Gillingham,
Rapsony and Wagner 2016). All relationships between an increase in efficiency and demand can
therefore be described as elasticities (see Madlener and Alcott 2011, pp. 19f.). Madlener and
Alcott (2011) write in their report “Wachstum, Wohlstand, Lebensqualität " of the German
Bundestag that science cannot even agree on a rough estimate for the rebound effect, which
shows how perse the definition and measurement of the rebound effects exit. It should be
therefore remarked, that calculations of rebound effects have not necessarily been compiled using
the same methodology. A comparison of different studies of rebound effects in the lighting sector
should give better insights of the relevance of the effect for the lighting sector.
3.2.Empirical evidence on rebound effects in the lighting sector
Table 1 gives an overview of the different studies on the rebound effects in the lighting sector,
which were considered in this paper. There are several approaches to approximately determine
or prove the rebound effect for lighting. Borenstein (2013) tries to quantify this by means of the
price elasticity and the substitution effect for lighting. While others use household surveys (see
Mills and Schleich 2013, Schleich, Mills and Dütschke, 2014) or historical data (see Fouquet and
Pearson 2006, Fouquet and Pearson 2011) to investigate the rebound effect.
Fouquet and Pearson (2006) use historical data from the United Kingdom to try to approximate
the rebound effect in the lighting sector. They analyzed the change in demand for lighting in the
United Kingdom (UK) over the past seven centuries, from 1300 to 2000, depending on the different
light sources (candlelight, whale oil lamp, natural gas lamp, light bulb). In addition, they controlled
for wealth and development of the economy.
Table 1: Overview of rebound studies in the lighting sector
Authors Study Kind of
Fouquet und Seven Centuries of Energy Services: The price and the use of empirical
Pearson (2006) light in the United Kingdom (1300-2000)
Fouquet und The Long Run Demand for Lighting: Elasticities and Rebound empirical
Pearson (2011) Effects in Different Phases of Economic Development
Greening, Green Energy efficiency and consumption – the rebound effect – a literatur
und Difiglio survey review
Schleich, Mills, A brighter future? Quantifying the rebound effect in energy empirical
Dütschke (2014) efficient lighting
Mills und Schleich Household transitions to energy efficient lighting empirical
Tsao und Waide The World’s Appetite for Light: Empirical Data and Trends empirical
(2010) Spanning Three Centuries and Six Continents
Tsao et. al. (2010) Solid-state lighting: an energy-economics perspective empirical
Borenstein (2013) A Microeconomic Framework for Evaluating Energy Efficiency theoretical
Rebound And Some Implications framework
Berkhout, Defining the rebound effect literatur
Muskens und review
Reference 1: Own illustration.
The authors examined how the energy price, energy efficiency, the price of lighting, per capita
light consumption, light consumption in general and real GDP per capita have changed. For
example, lighting in 2000 was a thousand times more efficient than in 1800 and light consumption
in 2000 was more than 25,000 times 1800 or light consumption per capita increased by a factor of
6566 compared to 1800 (Fouquet and Pearson 2006). It is also noticeable in the study that per
capita light consumption in the years under review rose much more than the real GDP per capita.
Frondel (2012) attributes this to the dramatic price reduction for lighting during this period. With
GDP 15 times higher in 2000 compared to GDP in 1800, it is also important to look at the rise in
UK living standards and falling real prices for lighting. The living space was also larger and
households could afford more lighting. Fouquet and Pearson (2006) were able to show what
influence decreasing energy prices and increasing efficiency have on lighting.
In a recent study, Fouquet and Pearson (2011) calculated price and income elasticities in demand
for lighting in the UK. The price elasticity allows to estimate the magnitude of the rebound effect.
Fouquet and Pearson (2011) found out that by the mid-19th century, the income elasticity was
about 0.7 and the price elasticity was about -1.2. A price elasticity of less than -1 means that the
rebound effect was over 100%, resulting in a so-called backfire. Backfire is a disproportionate
increase in energy consumption as a result of energy efficiency improvement. From 1840 to 1890,
income and price elasticities rose again dramatically. At that time, a 1% price reduction or an
efficiency improvement led to a 1.7% increase in lighting consumption. An increase in per-capita
income by 10% to 35% also led to an increased demand for lighting. From this it can be deduced
that both the introduction of more efficient lighting and the access to it due to increasing
prosperity in the past must have increased the rebound effect.
In general, these historically considered rebound effects should not be over-interpreted. Unlike
the period around 1900, lighting is no longer considered as a luxury good today (see Fouquet and
Pearson 2011). Fouquet and Pearson (2011) find that income elasticity has fallen below 1.0 since
1960 and between 0.3 and 0.2 over the period 1980-2000. Price elasticity for lighting has been in
the range of -0.7 to -0.4 since 1910 (see Fouquet and Pearson 2011). The authors conclude that
these elasticities are high as long as an economy grows strongly and has not yet reached its
saturation level. However, when a certain level of wealth is reached, the elasticity decreases again.
For this reason, the authors also suggest that the EU ban on incandescent lamps in the UK could
actually lead to low energy savings (see Fouquet and Pearson 2011).
A much-cited study on rebound effects comes from Greening, Green and Difiglio (2000). In their
survey study, they summarize a large number of empirical studies to give an overview of the
magnitude of the direct rebound effect in different energy service sectors. In doing so, they deal
with research on the rebound effect of private households, as well as with studies on the rebound
effect of companies, as well as with essays on the macroeconomic rebound effect. They subpide
into different energy services, e.g. Space heating, lighting, etc., in private households and
companies and then give details of their rebound effect and its height (see Greening, Green and
Difiglio 2000). In addition, they point out that there are few empirical studies on lighting,
compared to other energy services sectors. They estimate that household lighting can achieve 80%
-95% of potential savings. As a result, they come to a direct rebound effect for residential lighting
of 5-12% (see Greening, Green and Difiglio 2000).
Schleich, Mills and Dütschke (2014) determined the direct rebound effect by exploring a large
survey in German households. The rebound effect is measured as efficiency elasticity of demand.
In addition, they investigate the proportion of the rebound effect that can be attributed to both
the increased burning time of the lamp and the increased luminosity (see Schleich, Mills and
Dütschke 2014). They find that in 90% of the cases, when changing from an incandescent lamp to
a more efficient luminaire, the illumination duration and / or the brightness has changed in
lumens. If, for example, a light bulb is replaced by a more efficient light, it is 24% brighter than the
light bulb. The burning time increased on average by 8 minutes per day. Schleich, Mills and
Dütschke (2014) calculate a rebound effect of 6%. The higher luminosity in lumens accounted for
almost 60% of the rebound effect.
Tsao and Waide (2010), and Tsao et. al. (2010), investigate medium to long-term rebound effects
in the lighting sector. The study by Tsao and Waide (2010), which analyzes light per capita
consumption relative to GDP per capita and the cost of lighting based on historical data, has
provided insights into the long-term rebound. They asked whether demand for light was
independent of energy efficiency and thus independent of the cost of lighting. This would mean
that technological advances would not lead to an increase in the demand for lighting, but to a
decrease in (input) energy and thus there would be no rebound effect. In contrast to most of the
other studies on the rebound effect in lighting, the authors deal with the question of the medium
to long-term rebound effect. They take into account that it often takes decades before new
application possibilities for useful energy emerge, which can then dramatically impact the
demand. Using other empirical studies, including that of Fouquet and Pearson (2006), they could
gather data from 3 centuries (1700-2000), 6 continents (Africa, Asia, Europe, Australia, North and
South America) and 5 different species each Evaluate fuels and lighting technologies. They
conclude that per capita consumption of light is approximately linearly proportional to the ratio
of per capita income to the cost of light (see Tsao and Waide 2010). Taso and Waide (2010) So
they conclude that both the price and income elasticity of demand for lighting is around 1. They
also find that a similar proportion of global GDP per capita is spent on light, suggesting a relatively
high rebound effect.
Tsao et. al. (2010) forecasts for lighting consumption in 2030, based on the findings from Tsao and
Waide (2010). They assume that LED will be the dominant lighting technology of the future and
that this technology will be even more efficient and cheaper by the year 2030 (see Tsao et. al.,
2010). Assuming that demand for light does not saturate, they expect the share of 0.72% of global
GDP per capita to remain unchanged for lighting. In addition to the global number of many poorly
lit or poorly lit areas, as well as new application possibilities for LED could also drive demand for
LED further (see Tsao et. al., 2010).
Saunders and Tsao (2012) comment on the results of the previous study by Taso et. al. (2010).
They confirm that the introduction and market penetration of more efficient lighting techniques
will not result in any overall energy savings in lighting. Saunders and Tsao (2012) estimate a
rebound effect of just over 100%, concluding that the global energy intensity of lighting, that is,
the energy consumption of lighting relative to global GDP, has not changed over the past 30 years
and will not change in the future (see Saunders and Tsao 2012).
4. Implications for the promotion of LED lighting
To ensure that growth does not come at the cost of more energy use, the energy efficiency
improvement must be stronger than the increase in demand for energy for lighting. According to
recent findings of this paper, the direct and short-term rebound effect in residential lighting seems
to be just above zero to about 10% (see Berkhout, Muskens and Velthuijsen 2000, Greening, Green
and Difiglio 2000). However, the rebound effect in the lighting sector not only entails the danger
that energy savings will not be achieved, but also that there will be more and more lighting overall.
For example, Schleich and Mills (2013) have shown that luminous intensity increases dramatically
when a light bulb is replaced by a more efficient luminaire. Animals and humans are already
suffering from light pollution and this issue could pose an even more serious threat to the health
of living beings in the future (see Borchers and Schomerus 2015). It is therefore necessary to
implement a suitable rebound management in the promotion of energy-efficient light sources,
such as the LED, in order to counteract the negative effects of increasing energy efficiency in the
long term. In addition to the effectiveness of the measure, it is necessary to find an instrument of
economic policy which, on the one hand, is suitable for promoting energy efficiency but, on the
other hand, is also able to prevent rebound effects. Blum et. al. (2018) find in their study on the
influencing factors of rebound effects that they can be both economical and psychological and do
not necessarily occur separately from each other. They advocate the use of fiscal instruments,
such as taxation mechanisms, to compensate for the savings gained by decrease the cost of energy
services, thus preventing a rebound effect. This would also be conceivable for the promotion of
LED technology, as Blum (2018) has shown in a theoretical approach to promote LED lighting via
taxation policy. Here, the use of a unit tax for all bulbs leads to a so-called quality switch and
consequently to an increase in the average quality in the market. The advantage of this approach
is that the tax is levied equally to all bulbs. Thus the LED in comparison to the other bulbs is indeed
cheaper in its relative price, but an additionally purchased unit of this bulb is provided with the
same tax amount. Blum et. al. (2018) further suggest that a potential rebound policy must address
the fact that consumers have unsaturated needs that can now be met through energy efficiency
improvements. Following this idea, rebound management would limit the welfare maximization
of inpiduals. This study has shown that historically rebound effects often also go hand in hand
with unsatisfied needs and remain unaffected by them. Thus, observing a rebound effect in
consumption is not necessarily an expression of inefficiency, which would call for economic policy
to intervene in the market, but may be rational in the context of utility maximization. Therefore,
when choosing rebound management, care should be taken to ensure that lower income groups
are not disadvantaged by the policy measure (see Blum et. al. (2018)). Blum et. al. (2018) also
name the relevance of social and personal norms in connection with rebound behavior. Again, this
may be relevant to the lighting as well. Often, rebound behavior is evoked based on insufficient
information about the impact of the energy efficiency decision, so that an observed rebound effect
has often been unconsciously triggered by the consumer (see Blum et. al. (2018)). Ultimately, it
seems to make sense to consider various factors that can trigger rebound effects when choosing
the policy measure. We have shown that rebound management would be appropriate for the
lighting sector, as historical data and empirical observations have demonstrated the relevance of
rebound in this area. Furthermore, it seems to be expected that the demand for light will continue
to increase and thus energy efficiency improvements in lighting technology do not necessarily
produce the desired effect. An appropriate policy measure to support LED promotion must
therefore be found to make the development of light use efficient and sustainable.
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