The role of social value in the investment decision incleaner technology

Dorothée CHARLIER∗ Marion PODESTA†

April 30, 2015

Abstract

This paper studies the effect of social value on the investment decision in cleanertechnology. Using a theoretical framework where we distinguish conformist andanti-conformist behaviours, we study the consumer’s decision to adopt an envi-ronmentally cleaner technology according to his environmental consciousness andaccording to a social value derives from other individuals respect. Then, using PHE-BUS database, we study the profile of households with a high social value. Thispaper provides three major contributions. First, this model of social value is use-ful for understanding environmental decisions of investment. Indeed, we show thatthe weight of social value for consumer signaling his preferences for environmentinfluences the decision to invest. Second, results underline the importance for aneconomy to understand the consumption profile of individuals. In a conformist soci-ety, information campaigns which stress the importance of environmental attributeswould be successful. Third, the empirical analysis lets us to determine a profile ofhouseholds with a high social value. The results obtained are interesting for policymakers: they should focus information campaigns towards young men with a highenvironmental consciousness because they are more willing to invest in solar panels.JEL classification: D11, Q4, Q5Keywords: cleaner technology; social value; consumers; conformist situation;

social interactions

1 Introduction

Since Kyoto protocol in 1997, concerns about the global warming and the climate changecaused by human-induced greenhouse gas emissions are dominant for governments. Cli-mate change has important negative consequences such as health effect of air pollution.One solution to limit these negative outcomes can be increasing the share of green tech-nology1. Renewable energies represent one-fifth of electricity generation worldwide and

∗Université Montpellier 1, Site Richer, Rue Raymond Dugrand, 34960 Montpellier Cedex 2.†Corresponding author: marion.podesta@univ-savoie.fr ; Tel: +33 (0)4 50 09 24 46, IREGE, University

of Savoie, 4 Chemin de Bellevue, BP 80439 Annecy-le-Vieux, France.1Eurostat (2009) defines a green technology as the acquisition of technologies, goods, and services

whose main purpose is to limit the degradation and depletion of natural resources.

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buildings represent 32% of total final energy consumption (IEA, 2010). According tothe IEA (2011): "There are many reasons for developing and deploying solar energywhile fossil fuels still dominate the global economy’s energy balance. Its ubiquity andsustainability mean that it is among the most secure sources of energy available to anycountry, even in comparison to other renewable sources of energy. It is also one of theleast polluting". Stern (1998) shows that residential sector offers considerable potentialto reduce energy uses and GHG emissions, particularly with energy-saving investment.Today, residential and commercial buildings account for 35% of total global final energyconsumption, notably for lighting, sanitary water heating, comfort ambiance, cooking andmany electricity-driven devices (IEA, 2011). Buildings also offer large surfaces to the sun’srays. Capturing the sun’s energy will also enable buildings to cover a shareof their heatconsumption. At the same time, there are an increasing number of consumers claimingthat they have an environmental consciousness, i.e. they are more concerned about envi-ronmental damage caused by their consumption (Eurostat, 2009). The recent theoreticalliterature in environmental economics considers environmental friendliness as a verticalattribute of a product and shows that environmentally conscious (green) consumers pay aprice premium for an environment-friendly product (see Cremer and Thisse (1999), Aroraand Gangopadhyay (2003), Bansal and Gangopadhyay (2003), Mahenc (2008)).

In this paper, we focus on the consumer’s decision to adopt an environmentally cleanertechnology according to his environmental consciousness and according to a social valuederives from other individuals respect. More precisely, we introduce a social value tosignal environmental concerns due to the implementation of photovoltaic (PV) plants orsolar panels, for instance. We show that the weight of social value for consumer signalinghis preferences for environment influences the decision to invest. Afterward, we usesdata to better understand the determinant of the social value. A substantial part of theliterature analyzes the decision to invest in energy effi cient technology and especially insolar panels. Authors stress the importance of socio-demographic characteristics, buildingcharacteristics and they find that adoption of green technology is often associated withcosts for investments and energy use. For instance, studies show that age influencesheating costs. Elderly people are less likely to adopt green technology than youngerones (Mahapatra and Gustavsson, 2008), because of their uncertainty about whetherthe investment will be paid off during their house occupancy and their relative lack ofawareness of energy-effi ciency measures (Linden et al., 2006). Education also influenceshouseholds’decisions to renovate. Households who are more educated are more likely toinvest in green technology (Nair et al., 2010). In contrast, the literature on the role of socialvalue and environmental cosciousness as a determinant of households’investment decisionand green expenditures is rather sparse. Consequently, the decision to adopt a cleanertechnology is related to the environmental valuation and also affect other individuals.Taking into account social influences and social value as determinant of green technologyinvestment are the major original feature of our approach and constitutes the main valueadded to the literature.

According to a recent European survey, “Slightly more than 8 in 10 EU citizens an-swered that a product’s impact on the environment is an important element when decidingto purchase. A product’s environmental impact is perceived as being more important inpurchasing decisions by respondents who are generally more aware of the impact on theenvironment of products they buy or use. Environmental impact and energy effi ciency asdeciding factors when consumers decide buying products”(Eurobarometer, 2009). Thus,a particular attention is paid by environmental consciousness consumer to green technol-ogy. Theoretical papers explain the decision to invest in a green technology but neglectsocial influences. Baker (1974) was the first to study social interactions in the economic

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analysis. He shows that social interactions have an impact on the decision and the be-haviour of consumers. Bernheim (1994, p. 864) shows that “when status is suffi cientlyimportant relative to intrinsic utility, many individuals conform to a single, homogeneousstandard of behavior, despite heterogeneous underlying preferences”. According to Lubell(2002) « citizens with strong environmental values are more likely to receive psychologicalbenefits from expressing their preferences through environmental activism or enjoy thesocial benefits of participating with like-minded citizens » . Olli et al. (2001) explorethe effect of the social context on environmentalism in Norway and show that ecologicalattitudes explained about 25 per cent of active environmental behaviours. They showthat consumers’willingness-to-pay is motivated by both private (energy cost savings)and public (environmental) benefits. The role of social interactions is essential to betterunderstand economic behaviour.

Recently, authors link social interactions and environmental considerations. Axsen etal. (2013) study the role of social influences in formation of consumer preferences andperception for pro-environmental technologies in the transport sector. They show thatneglect social influence processes can lead to underestimation of the potential for shift inconsumer preferences regarding green technology. Preferences, attitudes and values arekey determinants to understand the consumer beheviour to environmental technologies(Axsen et al., 2012). Empirically, Mills and Schleich (2012) analyze the role of social valuein consumer preference design in 10 EU countries and Norway. They underline a lack oftheoretical papers taking into account consumer environment consciousness. In our paperenvironmentally aware consumers can signal or not their preferences for environmentallyproducts to others consumers. Signaling their preferences for the environment involved asocial benefit from the interactions with other individuals. The model considers energydemand and consumer has the choice between two alternatives: to invest in green tech-nology by installing photovoltaic plant or to purchase energy directly on the market. Ifconsumer adopts the cleaner technology, on the one hand it receives a private benefit fromthe consumption of energy and a social benefit from the improvement of environment. Byinstalling a photovoltaic plan, consumer signals his environmental consciousness, and thissignal involves social interactions with other individuals which affect his social utility. Ifconsumer buys energy directly on the market, it can buy conventional energy or green en-ergy according his preferences for environment. The green energy consumption entails alsoa social benefit from the improvement of environment but there is no exogenous signal.Green consumers may gain utility from knowing that their ecological footprint is small.Within green communities there may be greater access to environmental friendly tech-nologies (Kahn, 2007).This decision-making process can be close to innovation adoptionliterature. Kim and Park (2011) show that social influence is important in the context ofprompting behaviour. Diffusion is “the process by which an innovation is communicatedthrough certain channels over time among the members of social systems”(Rogers, 1995).Researchers also suggest that a social system beyond the individual’s and the innovation’sidiosyncratic characteristics influences adoption decisions (e.g., Cooper & Zmud, 1990).A common explanation is that potential adopters feel uncertain about an innovation’sexpected consequences. Individuals are generally uncomfortable with uncertainty, andwill, therefore, tend to interact with people in their social network to consult them ontheir adoption decisions (Katz & Tushman, 1979). Consumers can be influenced on amarket by other consumers when they are affected by neighborhood effect for exemple.Therefore, they wait for other individuals invest in a high tech product before buying it.In our model, the share of consumers who have already invested in green technology haveconsequences on the individual investment decision. In the case where consumer signalshis environmental consciousness by adopting a cleaner technology, he benefits from beingclosed from others. If a large part of the population behaves rather as follower (conformist

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situation), when the number of consumers investing in cleaner technology increases, thislead to an increase in the social value because consumers want to mimic others.

The following section presents the basic model and the main assumptions. The decisionof investment in green technology is presented in section 3. The section 3.3 computed theequilibrium outcomes. We find to estimate the social value in an empirical analysis insection 4.The final section contains the conclusion.

2 The model

•Consumers. The model focuses on energy demand to satisfy a fundamental needfor lighting, heating or air conditioning needs, for example. The monopolist faces ademand composed of two types of consumers differentiated by their taste for the goodand their preferences for environment. The parameter θ can be viewed as consumer-specificenvironmental consciousness index and is distributed uniformly on the interval [0, 1]. Notethat a lower value of θ implies a more environmentally conscious consumer.•Options of consumption. To satisfy its energy needs, a buyer has the choice betweentwo alternatives: to invest in green technology by installing photovoltaic plant or topurchase energy directly on the market (conventional or green energy). In other words,from a consumption point of view, these options are perfect substitutes. In the model,people take care about their own utility and about social utility. Because individuals canhave different attitudes towards environmental protection and so for social well-being,this causes heterogeneity between agents.(i) If the consumer adopts the cleaner technology, on the one hand he receives a

private benefit from the consumption of energy and a social benefit from the improvementof environment, and on the other hand he pays a price for each unit produced plus aninvestment cost. By installing a photovoltaic plant, consumer signals his environmentalconsciousness, and this signal involves social interactions with other individuals whichaffect his social utility.(ii) If the consumer buys energy directly on the market, he can buy conventional

energy or green energy according his type. The green energy consumption entails also asocial benefit from the improvement of environment but there is no exogenous signal.The decision to invest in solar panels or to purchase green energy will depend on the

importance according to the society opinion and the preferences for the environment.Individuals who care about other consumer decisions can have a higher probability tosignal their green behavior.•Social interactions. We introduce social interactions in the utility function of con-sumers. Here it will be assumed that the private and social benefit enter consumer’sutility function in a separable way. Let f the private benefit from the consumption ofenergy, g the social benefit to improve the environmental quality and h is relative to socialinteractions entailed by the solar panels. We note q the total level of energy achieved andQ =

∑qi (i = s, b, g) with qs the solar energy, qb the brown (or conventional) energy and

qg the green energy. Therefore the consumer utility is given by:

U = f(qi) + g(θ,Q− qb) + s h(β, qs)

where s = {0, 1} is a binomial variable when the consumers signal or not their environ-mental consciousmess by installing photovoltaïc plant. The parameter β represents the

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proportion of consumers investing in solar panels technology with 0 < β < 1. The totalquantity of energy consumed is denoted Q where Q = β qs+ (1− β)(qg + qb).We can specify the private utility function as: f(qi) = qi(θ − qi

2). A consumer with a

high level of θ (i.e with a less environmental consciousness) would purchase more energythan a consumer more environmentally friendly.The social benefit to improve the environmental quality when a consumer purchase

green energy (via the market or the solar panel) can be also specify as: gi(θ, q − qb) =(qi − θ) with i = s, g.

The social interactions h(β, qs) can be the esteem accorded to an individual and de-termined by public perceptions. In other words, environmental consciousness consumersreceive psychological benefits from expressing his preferences through environmental ac-tivism and by improving the environmental quality through other people’s perception.Leibenstein (1950) has coined the terms bandwagon and snob effects to describe theglobal impact of such attitudes. In the model, the social value can be specified as:

h(β, qs) = ξ β qs

where ξ can be view as an externality affecting the utility of consumer (as Grilo, Shyand Thisse, 2000). Finally, h(β, qs) is the social benefit of the consumer to invest in solarpanels and to show to others this investment decision.•Conformist or anti-conformist beheviour. Two cases are studied.(i) If ξ > 0, a consumer benefits to a positive externality from the consumption of

solar panel (it can be close to the "bandwagon effect") and this case corresponds to theconformist situation. If the part of the population who invests in cleaner technologyincreases, this lead to an increase in the social value because consumers want to mimicothers.(ii) However, if ξ < 0, a consumer is considered as a "leader", he expects received a

negative social value to be distinct from others. If a large part of the population behaves asleader, when the number of consumers investing in cleaner technology increases, this leadsto a decrease in the social value. This case corresponds to the anti-conformist situationand it can be close to the "snob" or "vanity effect" defined by Leibenstein (1950) andGrilo, Shy and Thisse (2000). There is a model of "anti-conformism" behaviour in thesense that in France few people have installed a cleaner technology in their house, so whenan individual decides to invest in a green technology he benefits to a social utility due toother consumers considerations. In the same way, when there are many people who haveinvested in solar panels, for example, the consumer earns an insignificant social utility inturn by installing the cleaner technology.In these different cases, the effect on social value can be positive or negative on the

investment’s decision. In the case where everyone is alike i.e with an important shareof solar panels proportion consumers, we have β close to 1, therefore the social value ofinvestment is higher. In a such context, higher the number of solar PV plants in theeconomy, higher the signal’s value of investment due to social interactions.•Energy tariffs. To take into account the tariff paid by the consumer, the net utilitycan be rewritten as:

u(q, e, θ) = U − I − ts qs − tb qb − tg qg +m (1)

where I is the investment, note that if consumer decides to not invest in the green tech-nology I = 0.

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Concerning energy tariffs, ts is the unit price of solar energy with ts = −α I whereα ∈ [0, 1] is a positive parameter to measure the energy effi ciency of investment in greentechnology. A high value of α implies a technology more effi cient. Concerning energypurchased in the market, tb (respectively tg) is the tariff of brown (respectively green)energy, and we assume tb < tg.Mahenc (2008) shows that high environmental performanceis signaled through a high price when less polluting products are more costly to produce.Finally, m is the numéraire good.

3 The investment decision

3.1 The green consumer’s decision

•Investment in green technology.

When a green consumer decides to invest in green technology, installing a photovoltaicplan for instance, he signals his type, he receives value of improving environment and hepays the investment cost plus a price for each unit of energy consumed. In the model, weconsider a proportion β of green consumers signaling their environmental consciousnesswith photovoltaic plant. Therefore, its maximization problem under the budget constraintis given by:

maxqsUs = f(qs) + g(θi, Q− qb) + h(β, qs) +m (2)

s/c tsqs + I +m ≤ R

where R is the consumers’income.•No investment in green technology.

When consumer prefers to buy energy from the market, he has the choice betweenconventional electricity or green electricity. We consider a proportion (1 − β) of greenconsumers who not signaling their environmental consciousness with photovoltaic plant.If consumer purchases green energy from the market, he doesn’t signal his environmentalconsciousness (s = 0) but he receives social benefit to improve the environment quality.He pays a high price for each unit of energy consumed and the maximization problem isthe following:

maxqgUg = f(qg) + gg(θ,Q− qb) +m (3)

s/c tg qg +m ≤ R

3.2 The brown consumer’s decision

Finally, consumer can decide to purchase conventional energy on the market. This typeof consumer is called as brown consumer and he doesn’t benefit to a social value. He paysa low price for each unit of energy purchased and its maximization problem is given by:

maxqbUb = f(qb) +m (4)

s/c tb qb +m ≤ R

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3.3 Equilibrium

At the equilibrium, we solve the total utility for each type of consumers according to theirbudget’s constraint, then we can compute the indifferent consumers and the aggregateddemand in the economy. At equilibrium, in the case where the consumer invests in solarPV plants, we obtain:

qs = θ + ξβ − ts + 1 (5)

Higher the share of consumers who signal, higher the energy quantity consumed. Ifthe consumer want to invest in order to be similar to others (ξ > 0), it entails a signifi-cant social utility when the quantity of solar energy increases and this especially as theproportion of consumers installing solar panel grows. Graziano and Gillingham (2014)empirically show that there exists a relationship between adoption of residential solarphotovoltaic system and the number of nearby previously installed systems. The effectof nearby system diminishes with distance and time, suggesting a spacial neighbor effectconveyed through social interaction and visibility. For example, their results indicate thatadding one more installation within 0.5 miles of adopting households in the six monthsprior to the adoption increases the number of installations in a block group by 0.44 pho-tovoltaic systems per quarter on average. The solar energy purchased is also increasingwith the investment cost (as ts = −αI) and accordingly with the energy effi ciency of in-vestment in green technology. If the individual install an effi cient huge solar panel, he willconsume a high quantity of energy. This result show that higher the level of investment,lower the energy cost and this leads to increase the energy consumption. Indeed, even ifthe energy is green, the consumer who invest consumes more energy to increase its levelof welfare. Even if the investment is beneficial for environmental quality because the con-sumer invests in a green technology, there is a rebound effect. The rebound effect refersto the behevioural reactions due to the introduction of new technologies which increasethe effi ciency of heating system. These reactions tend to offset the benefits (in monetaryand energy consumption terms) of the new technology.In the anti-conformist case, when people invest to distinguish themselves from others

(ξ < 0), the quantity of solar panel decreases with the proportion of people signaling theirenvironmental consciousness.If the consumer buys energy on the market, equilibrium quantities are:

qg = 1 + θ − tg (6)

qb = θ − tb (7)

Energy quantities are decreasing function of energy tariff. Higher the energy cost,lower the quantity of energy consumed. This result is different from whose obtained withsolar PV. Contrary to the quantity of solar energy, the green and the conventional energiesare not influenced by the effects of vanity or conformity.

In all options of consumption, the quantity consumed also depends on parameter θ thatcan be viewed as consumer-specific environmental consciousness index. A lower value ofθ implies a more environmentally consciousness consumer and a lower quantity of energyconsumed. We can infer that to inform consumers about their energy use and to giveadvice on how, can fall the global energy consumption and make consumers awarenessof the environmental cause. European Commission (2013) compares different campaign

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strategies. They conclude that energy audits and consultation, when individuals areinformed about their own energy use and given advice on how to lower their consumption,were the most effective. Under this strategy, consumers reduced their energy use by13.5% on average. Moreover, results show that the best second approach was providingindividuals with comparisons with their peers’energy use, this reduced consumption by11.5% (Delmas, M. A., Fischlein, M. and Asensio, O. I., 2013).

3.4 The indifferent consumer

•Indifferent consumer between to install a solar PV or to buy the green energyon the market:

θ1 =1

2

[tg − αI − ξβ − 2 +

2I

κ

]where κg = tg + ξβ + αI.

Concerning the effect of green energy tariff, if the value of I is suffi ciently high2, ahigher value of the green energy tariff lows the value of the cousciouness index θ1. If thegreen energy become costly compared to the solar investment, the consumer becomesmore environmental consciouness and prefer to invest in solar PV. Conversely, the valueof θ1 is decreasing with the investment cost I, if the installation of solar panel becomeexpensive, more people would prefer to buy green energy directly on the market. Thesensibility analysis of θ1 to the different parameters is given in the appendix 7.1. Higherthe value of α, which measures the energy effi ciency of investment in green technology,lower the value of θ1.. Consumers are more willing to invest in solar PV because theybenefit to a higher environmental consciousness.An interesting result is about the social benefit of the consumer to invest in solar

panels and to show to others this investment decision (ξ). A high value of ξ implies alow value of θ1. Higher the social benefit to consumer to invest, higher the environmentalconsciousness of consumers. Higher the social benefit to consumer to invest, higher theenvironmental consciousness of consumers.Concerning a rising of parameter β, results depend on the sign and the magnitude

of parameter ξ. In the conformist case, i.e, when ξ > 0, a higher value of β implies alower value of θ1. When the social value due to showing its investment to others peopleis positive, higher the proportion of consumers who have already invested in solar PV,higher the index environmental consciousness. The consumer wants to invest in order tobe similar to others. In the conformist case, when a consumer mimics others it entailsa significant social utility and the quantity of solar energy increases and this especiallyas the proportion of consumers installing solar panel grows. This effect is close to the"bandwagoon effect". However, in the anti-conformist case, when ξ < 0, an oppositeresults is obtained. The consumers want to differentiate themselves from others, andhigher the proportion of persons who signaling their environmental consciousness, lowerthe environmental consciousness of consumers. The snobbism or vanity effect appears.This result is interesting for public policies. Indeed, according to the type of consumer,people can have a green behavior but anti-conformist people want to distinguish fromothers and are not willing to invest in technology what show their preferences.

2 if κ <√2I thus ∂θ1∂tg

< 0.

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•Indifferent consumer between to install a solar PV or to buy the brown energyon the market:

θ2 =1

2

(−2 + tb− αI − ξβ + −1 + 2tb + 2I

κb

)where κb = tb + ξβ + αI.

The value of indifferent consumer between to install solar panels or to buy brown or"conventional" energy on the market is increasing with the tariff of brown energy. If thetariff raises, more people would invest in cleaner technology. The sensibility analysis ofθ2 according to the different parameters is given in the appendix 7.1.The value of θ2 is decreasing with α, which measures the energy effi ciency of in-

vestment in green technology, and I, the amount of investment. Analyzing the effectof I on θ2, a higher investment implies a lower value of θ2 in the case where I <−αtb−ξβ+

√2α(tb−αtb+ξβ)+α2α2

. In the other case, if the investment is strongly increasing,i.e. the investment in solar PV is very costly, the share of environmental consicousnessconsumer decreases. These results could be analyzed in the empirical part.An interesting result is about the social benefit of the consumer to invest in solar

panels and to show to others this investment decision (ξ). A higher value of ξ implies alower value of θ2. Higher the social benefit to consumer to invest, higher the environmentalconsciousness of consumers.Concerning a rising of parameter β, results depend on the sign and the magnitude3 of

parameter ξ. In the conformist case, i.e, when ξ > 0, a higher value of β implies a lowervalue of θ2. When the social value due to showing its investment to other is positive,higher the proportion of consumers who have already invested in solar PV, higher theindex environmental consciousness. The consumer want to invest in order to be similarto others: this is the bandwagon effect.However, in the anti-conformist case, when ξ < 0, an opposite results is obtained.

The consumers want to differentiate themselves from others, and higher the proportionof persons who signaling, lower the environmental consciousness of consumers. In thissituation the snob effect appears.

•Indifferent consumer between to buy the green energy and the brown one onthe energy market:

θ3 =1

2

t2b − (−1 + tg)2

tb − tgThe situation where the consumer is indifferent between buying green energy on the

market or buying brown energy only depends on each energy tariffs. As tb < tg, thecondition tb < tg−1 implies a positive θ3. The θ3 value is increasing with tb and decreasingwith tg. When θ3 raises there are more people who use green energy (from the marketor PV plants). Results show the importance of the difference between green and browntechnology. This result can also show to policy makers that a solution to encourage buyinggreen energy tariff is to subsidy it.

From the indifferent consumers, we can derive the demand for the different optionof consumption (given in the appendix 7.2) and we can estimate the social value withempirical data.

3The proofs of the resut are in appendix 7.1.

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4 Empirical Analysis

The objective of this empirical analysis is to understand the determinant of the socialvalue. We want to assess the effect of households’characteritics and building character-istics’on the magnitude of the social value.

4.1 The data

We use the "PHEBUS (Enquête Performance de l’Habitat, Équipements, Besoins et Us-ages de l’énergie)" database. This survey consists of two parts made separately, a housingunits survey, and a energy Performance diagnosic of the housing. The energy performancediagnostis is a document that provides an estimate of energy consumption and greenhousegas emissions of the housing. It contains 2389 housing units. The sample of housing unit’ssurvey is drawn into the INSEE sample annual census survey 2011. It consists of 5045housing representative regions, climate zones of habitat types (individual house or apart-ment collective) and years of construction. Merging these two databases, information isavailable on effective and theoretical energy consumption, on GHG emissions, on house-holds’characteristics and building’s characteristics for 2299 households.

To compute the social value which is the only variable unavailable in the database,we use equations (equations 7), (6) and (5) to compute the total quantity at equilibriumconsumed in the economy. Rearranging the equation of quantity at equilibrium accordingto the social value, we obtain:

ξ =−1− q − ts,g,b(β − 2) + (β − 2)θ

β2

We consider that the energy tariff, t, is a carbon tariff. Data are available for oneyear and we do not observe the fluctuations of energy prices. In order to obtain this tarifffor each household (or housing units), we divided the energy expenditures per squaremeter by GHG emissions in kg.CO2 per square meter. Thus, each housing units have aproper energy tariff. Higher the quantity of GHG emissions, lower the energy cost. Thisresult is consistent with the model assumption. q is the quantity of energy consumedin kWh/m2/year for each housing units. To compute the value of β, i.e, the proportionof households who have solar panels, we divide for each French department the numberof housings units with solar panels on the number of housing units. Thus, for eachdepartment we have a value for β. Finally, about θ the environmental consciousness ofhouseholds, we have in the database information about households preferences concerningtheir behavior dedicated to energy consumption according different end-uses (heating,hot water and electricity). We know if households prefer achieving energy savings orprefer comfort. Thus, we consider as a brown environmental consciousness consumer, ahousehold who prefer comfort for all the three end-uses. In this case, the value of θ is 1.In the opposite case, if a household prefer achieving energy savings, the value of θ is 0. Inthe case where the household prefers the comfort for only one end-use, the value of θ is0.33. In the case where the household prefers the comfort the two end-uses, the value θ ofis 0.66. These theta values are arbitrary, but in line with the assumptions of the model.So we have the following diagram:

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Finally, we obtain in the database that only 1.3% of households have solar panels(which is not surprising). This result is consistent with national French data where 1.15%of dwellings are equipped with solar panels (INSEE, 2014; SOes, 2014). We introduce asmain determinant socio-demographic characteristics of households (age, occupancy statusof the dwelling, income), localization information (size of the city where the dwelling islocated), and information about the number of vehicles. The number of vehicles can bea proxy for the environmental sensitivity. The description of the variable used in theanalysis is available in appendix 8.Main descriptive statistics are summarized in the following table:

Table 1: Main descriptive statistics

Variable Mean Standard Deviation Min Max Nb. ObservationsSocial Value 0.16 1.34 0 15.35 2299Man 0.60 0.49 0 1 2299Age 3.94 0.33 2.56 4.54 2299Homeowner 0.69 0.46 0 1 2299Quintile 1 0.20 0.40 0 1 2299Quintile 2 0.20 0.39 0 1 2299Quintile 3 0.20 0.40 0 1 2299Quintile 4 0.20 0.40 0 1 2299Quintile 5 0.20 0.41 0 1 2299Township 0.036 0.19 0 1 2299Town20000 0.154 0.36 0 1 2299Town40000 0.143 0.35 0 1 2299Town200000 0.373 0.18 0 1 2299Paris 0.155 0.36 0 1 2299Vehicle 0.76 0.41 0 2.197 2299

In a first step, we only consider the households sample who have a nonzero socialvalue (i.e whose who have solar panels). The analysis of the social value if we consider

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all households (whose with a positive social value and whose with a zero social value) iscomplicated because of the zero value magnitude. Even if the sample size only contains 30observations, we can identify which factors are responsible for a high social value. Then,we use a selection model where we take into account the zero value.

4.2 Models and Results

4.2.1 The linear regression

Linear regression analysis is often a starting point of an empirical analysis. The purposeof this linear regression is to evaluate the role of specific regressors on social value. Themultiple linear regression model is used to study the relationship between a dependentvariable and one or more independent variables. The generic form of the linear regressionmodel is:

y = f(x1, x2, ..., xK) + ε

Social_value1 = f(man1, Age1, ...) + ε

where social_value is the dependant variable and and x1,...,xK are the independentor explanatory variables. The term ε is a random disturbance. The observed value of yiis the sum of two parts, a deterministic part and the random part, εi . Our objectiveis to estimate the unknown parameters of the model, use the data to study the validityof the theoretical propositions, and perhaps use the model to predict the social value.The estimation is corrected from heteroscedasticity. The results of the estimation arepresented in Table 2.

Table 2: results of the estimation

Variable Coeffi cient Robust Standard ErrorSocial Value (in logarithm)Man 3.103*** (0.678)Age -1.943*** (0.437)Homeowner 0.885** (0.344)Quintile 1 2.082*** (0.337)Quintile 2 2.255*** (0.352)Quintile 3 1.097** (0.417)Quintile 4 2.269*** (0.446)Town20000 1.940*** (0.388)Town40000 3.012*** (0.636)Town200000 2.416*** (0.492)Paris 3.409*** (0.494)Vehicle -2.042*** (0.666)Constant 14.84*** (1.673)F( 12, 17) = 39.60 Prob > F = 0.0000R-squared = 0.8970 Adj R-squared = 0.8243

*** p<0.01, ** p<0.05, * p<0.1

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The F Value is the Mean Square Model divided by the Mean Square Residual, yieldingF = 39.60. The p-value associated with this F value is very small (0.0000). These valuesare used to test the global significance of the model. The p-value is compared to youralpha level (typically 0.05) and we can conclude that the independent variables reliablypredict the dependent variable. Thus, the regressors are jointly statistically significant.At the same time, much of the variation is explained. The R-Square is the proportionof variance in the dependent variable (social value) which can be predicted from theindependent variables. This value indicates that 89.7% of the variance in social valuecan be predicted from the variables. But, according to the number of observations, theAdjusted R-squared is more appropriated. The value of the R-squared and the adjustedR-squared are quite similar and we can conclude the model is globally significant. We alsocontrol that is not missing explanatory variables and the model is generally well specified.We transformation of the explanatory variable in log is validated. All the explanatoryvariables are significant in the model. Large effects are obtained. For example, one to behomeowner compared to tenant increases the social value of 88%. Large marginal effectsare obtained with the income quintile. Belonging to first income quintile compared to thefifth increases the social value of 202%. So, the social value is positively determined bythe occupancy status, the size of the city, the income quintile and the sex. In contrary,the social value is negatively determined by the number of vehicles (which is a proxy forthe environmental consciousness) and the age. The social value is higher for young manwith a low income, living in a big city with an environmental consciousness.

4.2.2 The two-parts model

Now, we study the social value according to zero value. Now, the sample is a mixture ofobservations with zero and positive value. Estimating a linear regression in the presenceof censoring involves computational complications. We want to see in a two part model theprobability to have solar panels (solar) and then the magnitude of the social value. Thefirst part of the two-part model is a binary outcome equation that models the probabilityto have solar panels. The second part uses linear regression to model the social value. Lety denote the social value and d the probability to have solar panels. The two-part for thesocial value is given by:

f(y p x) = Pr(d = 0 p x)Pr(d = 1 p x)f (y p d = 1, x)

if y = 0if y > 0

The advantage of this two-part model is it provides the flexibility to have differentregressors in two parts. The specification of the selection equation involves delicate issuesand we introduce exclusion restrictions. This exclusion variables are the climate zone areaand the building period of construction. The results of the estimation are presented inTable 3.

13

Table 3:Results of the two parts model

Variable Coeffi cient Standard ErrorSocial Value (in logarithm)Man 3.366503*** 0.5531047Town20000 1.151329*** 0.5718619Town40000 3.730327*** 0.7250872Town200000 1.462992*** 0.5570101Paris 3.813013*** 0.67384Vehicle -2.023339*** 0.6530115Quintile 1 0.8756141 0.9534022Quintile 2 1.005016 0.8787031Quintile 3 -0.4588411 0.8518897Quintile 4 1.416023 0.8923912Homeowner -0.6496377 0.527887Solar Panels (binary)Man 0.1310241 0.1754168Town20000 0.376773 0.2477431Town40000 0.232153 0.3091902Town200000 0.2731755 0.2291048Paris -0.1439415 0.3703497Vehicle -0.2911925 0.2159401Quintile 1 0.6859369** 0.2806144Quintile 2 0.3728386 0.3101448Quintile 3 0.2301861 0.3103002Quintile 4 0.5361056* 0.2850983Homeowner 0.235924 0.1933367Climate zone H1b -0.5390828 0.4019174Climate zone H1c 0.1099224 0.2454183Climate zone H2a -0.3236222 0.4036057Climate zone H2b -0.0417659 0.282226Climate zone H2c 0.24637 0.2636572Climate zone H2d 0.4885767* 0.3011696Climate zone H3 -0.0755456 0.333051Wald chi2(6) = 96.34 Prob > chi2 = 0.0000Mills Ratio Lambda= -2.320 - -1.646* 0.9582105

Standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

According to the results, The Mills ratio is significant at 10% level and the selectionmodel is suitable. But, very few variables are significant to explain the decision to havesolar panels. Only climate zone area and income quintile explain the decision. Individualsinstall solar panels in sunny zone.Low income households have a higher probability to havesolar panels. Unfortunately, It is not possible in the database to know if they install them

14

or if they bought the dwelling with the solar panels. Then, results for the social value arequite similar than the linear regression model. Only the income is not significant. Theyoung men located in big city have a higher social value. The effect of the environmentalconsciousness is significant on the magnitude of the social value.

The results obtained are interesting for policy makers. Indeed, in the theoretical part,we showed that the social value had a positive effect on the decision to install solar panels.In the empirical part, we determine which profile have the households with a high socialvalue. We show that policy makers should focus information campaign towards youngmen with a high environmental consciousness because they are more willing to invest.

5 Conclusion

This paper allows to better understand the decision to invest in a green technology re-garding social influences. More precisely, we focus on the consumer’s decision to adoptan environmentally cleaner technology according to his environmental consciousness andaccording to a social value derives from other individuals respect. We introduce a socialvalue to signal environmental concerns due to the implementation of photovoltaic plantsor solar panels, for instance.At the equilibrium, the quantity of energy consumed depends on the level of con-

sumers’environmental consciousness: higher environmental consciousness, lower quantityof energy consumed. We can infer that to inform consumers about their energy use and togive advice on how, can fall the global energy consumption and make consumers awarenessof the environmental cause. Energy tariffs are also a key variable: the value of indifferentconsumer between to install solar panels or to buy brown or "conventional" energy onthe market is increasing with the tariff of brown energy. If the tariff raises, more peoplewould invest in cleaner technology.In the conformist case: higher the share of consumers who signal, higher the solar

energy quantity consumed. If the consumer want to invest in order to be similar to others,it entails a significant social utility when the quantity of solar energy increases and thisespecially as the proportion of consumers installing solar panel grows. This effect is closeto the "bandwagoon effect". We show that even if the energy is green, the consumer whoinvest consumes more energy to increase its level of welfare. Even if the investment isbeneficial for environmental quality, there is a rebound effect. The rebound effect refersto the behevioural reactions due to the introduction of new technologies which increasethe effi ciency of heating system. These reactions tend to offset the benefits (in monetaryand energy consumption terms) of the new technology.In the anti-conformist case, when people invest to distinguish themselves from others,

the quantity of solar panel decreases with the proportion of people signaling their environ-mental consciousness. The consumers want to differentiate themselves from others, andhigher the proportion of persons who signaling their environmental consciousness, lowerthe environmental consciousness of consumers. The snobbism or vanity effect appears.This result is interesting for public policies. Indeed, according to the type of consumer,people can have a green behavior but anti-conformist people want to distinguish fromothers and are not willing to invest in technology what show their preferences.Then, using the results obtained in the theoretical part, we study the profile of in-

dividuals with a high social value using the PHEBUS database. We want to determinewhich factors can explain the existence and the magnitude of the social value in order to

15

provide policy recommendation. If the decision to have solar panels is mainly due to thegeographical situation (i.e. living in a sunny area), the magnitude of the social value isdetermined by socio-demographic characteristics. Young men with a low income and ahigh environmental consciousness living in a city have a higher social value ceteris paribus.The social value in this paper can be viewed as the esteem accorded to an individual anddetermined by public perceptions. Emphasize the social value, self-esteem and uniquenessof investment by information campaign is a way to install solar panels and to improveenvironment in a long run. In order to target the population properly by informationcampaigns, the empirical analysis is very useful. Indeed, we show that policy makersshould focus their campaigns towards young men with environmental consciousness livingin cities.

16

6 References

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[9] Delmas, M. A., Fischlein, M. and Asensio, O. I. (2013) "Information strategies andenergy conservation beheviour: A meta-analysis of experimental studies from1975 to2012". Energy Policy, 61, pp 729—739.

[10] European Commission (2013) "Do information campaigns about energy use reallyhelp to reduce consumption?" Science for Environment Policy.

[11] Eurostat. (2009) " The Environmental Goods and Services Sector (Egss Handbook),"Eurostat European Commission, Luxembourg.

[12] Graziano, M. and Gillingham,K. (2014) "Spatial patterns of solar photovoltaic sys-tem adoption: The influence of neighbors and the built environment". Journal ofEconomic Geography, Forthcoming.

[13] Grilo, I., Shy, O. and Thisse, J-F. (2001) "Price competition when consumer behavioris characterized by conformity or vanity", Journal of Public Economics, 80, pp. 385-408.

[14] INSEE. (2014). "Le parc de logements en France au 1er janvier 2014", Insee et SOeS,estimation du parc de logements au 1er janvier.

[15] International Energy Agency, (2011)"Solar Energy Perspective", Renewable Energy.http://www.iea.org/publications/freepublications/publication/Solar_Energy_Perspectives2011.pdf

17

[16] Kahn (2007) "Do green drive Hummers or hybrids? Environmental ideology as adeterminant of consumer choice". Journal of Environmental Economics and Manage-ment, 54, pp. 129-145.

[17] Katz, R., and Tushman, M. (1979) "Communication patterns, project performance,and task characteristics: An empirical evaluation and integration in an R&D setting".Organizational Behavior & Human Performance, 23.

[18] Khazzoom, J. D. (1980) "Economic Implications of Mandated Effi ciency in Standardsfor Household Appliances." The Energy Journal, 1(4), pp. 21-40.

[19] Kim, S-H. and Park, H.J. (2011) "Effects of social influence on consumers’voluntaryadoption of innovations prompted by others" Journal of Business Research, 64, pp.1190-1194.

[20] Leibenstein, H. (1950) "Bandwagon, snob and Veblen effects in the theory of con-sumers’demand". Quarterly Journal of Economics, 64, pp. 183—207.

[21] Linden, A. ; Carlsson-Kanyama, A. and Eriksson, B. (2006) "Effi cient and Ineffi -cient Aspects of Residential Energy Behaviour: What Are the Policy Instruments forChange?" Energy Policy, 34(14), pp. 1918-27.

[22] Lubell, M. (2002) “Environmental Activism as Collective Action.”Environment andBehavior, 34 (4), pp. 431-454.

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7 Appendix

7.1 Indifferent consumers

• Indifferent consumer between to install a solar PV or to buy the greenenergy on the market

In order to analyze the effect of each parameter, we derivate the function accordingthese parameters, so we have:

∂θ1∂tg

=1

2− I

κ2g< 0

∂θ1∂α

= −12I − I2

κ2g< 0

∂θ1∂I

=1

2α +

1

κg− 2Iκ2g

(8)

∂θ1∂β

= −12ξ − Iξ

κ2g< 0

∂θ1∂ξ

= −12β − Iβ

κ2g< 0

withκg = tg + Iα+ βξ

The value of κ is positive even if the externality ξ which can be positive or negative.Solving the equation 8, we obtain 2 solutions and we keep the positive one:

I =−α(tg + βξ) +

√2α(tg + 2βξ)

α2

The solution mainly depends on energy effi ciency parameter, social value and greenenergy tariff. These results could be analyzed in the empirical part.

• Indifferent consumer between to install a solar PV or to buy the brownenergy on the market:

In order to analyze the effect of each parameter, we derivate the function accordingthese parameters, so we have:

∂θ2∂tb

=1 + 2I(α− 1) + 2βξ + κ2b

2κ2b> 0

∂θ2∂α

=1

2I(1− 2tb − 2I

κ2b− 1) < 0

19

∂θ2∂I

=1

κ+1

2α

(1− 2tb − 2I

κ2b− 1)< 0

∂θ2∂β

=1

2ξ

(1− 2tb − 2I

κ2b− 1)< 0

∂θ2∂ξ

=1

2β

(1− 2tb − 2I

κ2b− 1)< 0

withκb = (tb + Iα+ βξ)

The value of κ is stricly positive.The proportion of consumers who signal their environmental consciousness is given by

:

β̃ =−αI − 1 +

√t2b + 2I

ξ

The proportion of consumers who signal their preference for the environment by installingPV plants depends on the social value ξ, the amount of the investment and the tariff ofthe brown energy.•Indifferent consumer between to buy the green energy and the brown one

on the energy market:In order to analyze the effect of each parameter, we derivate the function according

these parameters, so we have:

∂θ3∂tb

=1

2

(1 +

1− 2tg(tb − tg)2

)< 0

∂θ3∂tg

=1

2

(1 +−1 + 2tb(tb − tg)2

)> 0

7.2 The demand function

• Demand function in solar panels:

Ds = θ1 =1

2

[tg − αI − ξβ − 2 +

2I

κg

](9)

• Demand function of green energy:

Dg = θ3 − θ1 =1

2

[−1 + 2tbtb − tg

+ κb −2I

κg

](10)

• Demand function of brown energy:

20

Db = 1− θ3 =1

2

2(tg − tb)− (1− tg)2 + t2b(tg − tb)

(11)

where tg > 2 +√3 + t2b − 2tb.

• The aggregate demand is given by:

D = βDs + (1− β)(Dg +Db)

Using equation 10, 9 and 11, we obtain the following result:

D =1

2(4− 6β + tg(2β − 1) + (2β − 1)

(−Iα− βξ + 2I

κg

)

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8 Empirical analysis

8.1

22

Table4:descriptionofvariables

Variable

Description

SocialValue

Thelogarithmofthesocialvalue

Man

Thepersonofreferenceisaman

Age

Thelogarithmoftheage

Homeowner

Binaryvariablewhenthehouseholdisowner-occupier

Quintile1

Binaryvariablewhenthehouseholdbelongtothefirstincomequintile(uc)

Quintile2

Binaryvariablewhenthehouseholdbelongtothesecondincomequintile(uc)

Quintile3

Binaryvariablewhenthehouseholdbelongtothethirdincomequintile(uc)

Quintile4

Binaryvariablewhenthehouseholdbelongtothefourthincomequintile(uc)

Quintile5

Binaryvariablewhenthehouseholdbelongtothefifthincomequintile(uc)

Township

Binaryvariablewhenthehouseholdlivesinatownship(lessthan20000inhabitants)

Town20000

Binaryvariablewhenthehouseholdlivesinatown(20000-40000inhabitants)

Town40000

Binaryvariablewhenthehouseholdlivesinatown(41000-200000inhabitants)

Town200000

Binaryvariablewhenthehouseholdlivesinatown(200000inhabitantsandmore)

Paris

BinaryvariablewhenthehouseholdlivesinParis

Vehicle

Thelogarithmofthenumberofvehicles

ClimatezoneH1a*

BinaryvariablewhenthehouseholdlivesinclimatezoneH1a

ClimatezoneH1b

BinaryvariablewhenthehouseholdlivesinclimatezoneH1b

ClimatezoneH1c

BinaryvariablewhenthehouseholdlivesinclimatezoneH1c

ClimatezoneH2a

BinaryvariablewhenthehouseholdlivesinclimatezoneH2a

ClimatezoneH2b

BinaryvariablewhenthehouseholdlivesinclimatezoneH2b

ClimatezoneH2c

BinaryvariablewhenthehouseholdlivesinclimatezoneH2c

ClimatezoneH2d

BinaryvariablewhenthehouseholdlivesinclimatezoneH2d

ClimatezoneH3

BinaryvariablewhenthehouseholdlivesinclimatezoneH3

*aFrench

mapispresentedto

showthelocalizationofthedifferentclimatezone

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