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date: 16 December 2017

The Life Satisfaction Approach to Environmental Valuation

Summary and Keywords

The method and practice of placing monetary values on environmental goods and services for which a conventional market price is otherwise unobservable is one of the most fertile areas of research in the field of natural resource and environmental economics. Initially motivated by the need to include environmental values in benefit-cost analysis, practitioners of non-market valuation have since found further motivation in national account augmentation and environmental damage litigation. Despite hundreds of applications and many decades of refinement, shortcomings in all of the techniques remain, and no single technique is considered superior to the others in all respects. Thus, techniques that expand the suite of options available to the non-market valuation practitioner have the potential to represent a genuine contribution to the field.

One technique to recently emerge from the economics of happiness literature is the “experienced preference method” or “life satisfaction approach.” Simply, this approach entails the inclusion of non-market goods as explanatory variables within micro-econometric functions of life satisfaction along with income and other covariates. The estimated coefficient for the non-market good yields, first, a direct valuation in terms of life satisfaction and, second, when compared to the estimated coefficient for income, the implicit willingness to pay for the non-market good in monetary terms.

The life satisfaction approach offers several advantages over more conventional non-market valuation techniques. For example, the approach does not ask individuals to directly value the non-market good in question, as is the case in contingent valuation. Nor does it ask individuals to make explicit trade-offs between market and non-market goods, as is the case in discrete choice modeling. The life satisfaction approach nonetheless has some potential limitations. Crucially, self-reported life satisfaction must be regarded as a good proxy for an individual’s utility. Furthermore, in order to yield reliable non-market valuation estimates, self-reported life satisfaction measures must: (1) contain information on respondents’ global evaluation of their life; (2) reflect not only stable inner states of respondents, but also current affects; (3) refer to respondents’ present life; and (4) be comparable across groups of individuals under different circumstances. Despite these conditions, there is growing evidence to support the suitability of individual’s responses to life satisfaction questions for non-market valuation. Applications of the life satisfaction approach to the valuation of environmental goods and services to date include the valuation of air quality, airport noise, greenspace, scenic amenity, floods, and drought.

Keywords: life satisfaction, happiness, experienced preference, geographic information systems

The method and practice of placing monetary values on environmental goods and services for which a conventional market price is otherwise unobservable is one of the most fertile areas of research in the field of natural resource and environmental economics. Initially motivated by the need to include environmental values in benefit-cost analysis, practitioners of non-market valuation have since found further motivation in national account augmentation and environmental damage litigation.

By convention, valuation techniques are divided into two approaches. The revealed preference approach relies on observations about peoples’ behavior in markets that are someway related to the environmental good or service under consideration, while the stated preference approach uses surveys to question how respondents value that good or service. Techniques can be further divided into direct and indirect, depending upon whether a value is directly measured or inferred. Commonly used revealed preference techniques include hedonic pricing and the travel cost method; commonly used stated preference techniques include contingent valuation and discrete choice modeling.

Despite hundreds of applications and many decades of refinement, shortcomings in all of the techniques remain, and no single technique is considered superior to the others in all respects. For example, authors who favor the use of revealed preference techniques generally point to the hypothetical nature of the stated preference approach, claiming that revealed preference techniques are superior because they are based on observations of actual behavior and therefore not subject to strategic or other biases. On the other hand, authors who favor the use of stated preference techniques point toward the increased flexibility (including the ability to measure non-use values) offered by this approach. Thus, techniques that expand the suite of options available to the non-market valuation practitioner have the potential to represent a genuine contribution to the field.

The life satisfaction approach (or experienced preference method) is one such technique. Simply, the approach entails the inclusion of non-market goods as explanatory variables within econometric functions of life satisfaction along with income and other covariates. The estimated coefficient for the non-market good yields, first, a direct valuation in terms of life satisfaction and, second, when compared to the estimated coefficient for income, the implicit willingness to pay for the non-market good in monetary terms (Frey, Luechinger, & Stutzer, 2010). That is, the approach relies on the identification of the relationship between changes in the quality and/or quantity of environmental goods and services and an individual’s subjectively reported well-being. In doing so, the implied costs and benefits of environment changes can be quantified in monetary terms. The approach has been put forward as both a complement to existing environmental valuation techniques (Ferreira & Moro, 2010) and a substitute for conventional non-market valuation and cost-benefit analysis (Bronsteen, Buccafusco, & Masur, 2013).

This article provides an overview of the origins of the approach before presenting a brief exposition of how the approach can be utilized in practice. Methodological developments and the advantages and disadvantages of the approach relative to other (more conventional) non-market valuation techniques are then discussed. The issue of whether the life satisfaction approach is a complement to, or substitute for, conventional techniques is considered. A brief overview of existing applications in the literature is then presented before a conclusion is drawn.

An Approach with Its Beginnings in the Economics of Happiness

The life satisfaction approach is situated at the crossroads between two key subfields in economics: (1) environmental and resource economics, which provides the theoretical framework for environmental valuation, and (2) the economics of happiness.1 Both subfields have roots in welfare economics and the maximization of social welfare, where social welfare is regarded as the aggregate of individual utilities.

Environmental and resource economics involves the application of economic theory and methods to environmental issues and problems. The subfield represents an earlier broadening of the domain of mainstream economic inquiry. This is extended further still by the heterodox subfield of ecological economics, formed by economists and natural scientists in the 1980s, transcending disciplinary boundaries in order to address environmental problems (Perman, Ma, McGilvray, & Common, 2003). The transdisciplinary approach espoused by ecological economics provides a pluralistic setting fertile for the development of new and novel approaches to environmental valuation. Unsurprisingly, a number of applications of the life satisfaction approach have been published in the journal Ecological Economics. These studies share the common goal of maximizing social welfare by aiming to improve the allocation of scarce resources (including those not traded in markets) through their monetization and inclusion in cost-benefit analyses.

The re-emergence of the study of happiness in economics can be traced to a 1997 symposium on economics and happiness in The Economic Journal (Frank, 1997; Ng, 1997; Oswald, 1997). This symposium and seminal reviews on happiness in economics that followed soon after (Frey & Stutzer, 2002a, 2002b) set in motion a flurry of research that would advocate a more central role for happiness in economics. The modern re-emergence of happiness in economics has been accompanied by a re-examination of the boundaries of economic science drawn in the 1930s (Colander, 2007). The direct measurement of utility or happiness as envisaged by classical economists (e.g., Edgeworth’s concept of a hedonimeter) has received some criticism among economists as it relies on subjective evaluations of one’s own happiness (arguably the best judge of this subjective state). As eloquently expressed by McCloskey (1983, p. 514):

Unlike other social scientists, economists are extremely hostile towards questionnaires and other self-descriptions … One can literally get an audience of economists to laugh out loud by proposing ironically to send out a questionnaire on some disputed economic point. Economists … are unthinkingly committed to the notion that only the externally observable behaviour of actors is admissible evidence in arguments concerning economics.

The argument that sometimes people may not tell the whole truth seems to stymie the use of questionnaires in mainstream economics (McCloskey, 1989). Nevertheless, much of economics relies on information gathered through questionnaires. Prior to the modern return of happiness in economics, environmental and resource economics reconciled itself with the need to use questionnaires to elicit individuals’ non-use values and ex ante values regarding hypothetical environmental changes. Considerable research effort has been, and continues to be, devoted to refining stated preference methods (e.g., contingent valuation and discrete choice modeling) (Mitchell & Carson, 1989). As a consequence, carefully constructed stated preference questionnaires are able to yield important and useful information that would otherwise be unavailable (Kling, Phaneuf, & Zhao, 2012).

In the same way in which an aversion to questionnaires can be unhelpful, a denunciation of interpersonal comparisons of utility (essential for the application of the life satisfaction approach to the monetary valuation of environmental goods and services) may also be less than constructive. It constrains economic analysis to the preference satisfaction of theoretically conceived economic agents (Edwards & Pellé, 2011). It neglects extensive research and reassurances in psychology (Kristoffersen, 2010), and it precludes the evaluation of welfare changes (Gowdy, 2005; Ng, 1997). Further, it should be noted that interpersonal comparisons are indispensable to the field of public economics more generally and to the theory of optimal taxation in particular.

An Exposition of the Life Satisfaction Approach

The life satisfaction approach differs from conventional environmental valuation techniques in quite a fundamental way. Conventional environmental valuation techniques concern themselves with decision utility, whereas the life satisfaction approach aims to directly measure an environmental good’s contribution to experienced utility (Dolan & Kahneman, 2008; Kahneman & Sugden, 2005). The distinction between the two was introduced by Kahneman, Wakkeer, and Sarin (1997). As eloquently explained by Welsch and Ferreira (2014, p. 207):

Experienced utility is the ex post hedonic quality associated with an (economic) outcome. Decision utility describes the ex ante expectation of experienced utility. Experienced utility thus entails a retrospective (or contemporaneous) assessment of outcomes whereas decision utility involves a prospective assessment. Ideally, decision utility and experienced utility would coincide, but evidence from behavioral economics casts doubt on the general validity of their equivalence. Specifically, deviations between decision utility and experienced utility (and the associated decision errors) may arise because of failures in affective forecasting, that is, in figuring out the utility consequences of one’s choices.

Where decision utility and experienced utility diverge, the implications of environmental changes for individual well-being and social welfare more broadly may be quite different. Underlying the life satisfaction approach is a probabilistic model of well-being or life satisfaction. This micro-econometric function expressed in its simplest form for individual i, in location k, at time t is:

WBi,k,t=ω+αln(yi,k,t)+βxi,k,t+θxi,k,t+εi,k,t

In this regression, yi,k,t is income, xi,k,t is the environmental variable of interest to value (e.g., air quality), and θxi,k,t represents socio-economic and demographic characteristics. The income variable is transformed using the natural log to appreciate the diminishing marginal utility of income, which is well established in the economics literature. Employing this regression, it is possible to perform environmental valuation by taking the partial derivative of the regression with respect to the environmental variable and placing this effect in terms of the partial derivative of the regression with respect to the income variable. Using the estimates α^ and β^ it is feasible to calculate the change in income that an individual would be willing to pay for an increase in, for example, air quality. This willingness-to-pay (WTP) calculation is:

WTP=WBi,k,txi,k,t/WBi,k,tyi,k,t=y¯β^α^

This is the “income equivalent” value or willingness-to-pay value. Conversely, these estimates can be used to calculate the “compensating income,” capturing the amount of income individuals would be willing to receive following a decline in air quality. Distinct from conventional environmental valuation methods, this amount is an amount implied by an individual’s experiential preferences to the extent that they are captured in the regression. The ordinal nature of the dependent variable (often self-reported life satisfaction or happiness) requires the maximum likelihood estimation of an ordered probit or ordered logit model. While the coefficient estimates of such a model have no meaningful interpretation, as they refer to an underlying latent variable, this does not preclude the interpretation of the ratios of the coefficient estimates (Frey et al., 2010). Note, however, that Ferrer-i-Carbonell and Frijters (2004) and others have shown that estimates of the determinants of life satisfaction are virtually unchanged whether one models the ordinal nature of the variable or treats the responses as cardinal (allowing estimation via ordinary least squares), contingent on individual heterogeneity being addressed appropriately.

Take as a numerical example the results from Ambrey, Fleming, and Chan’s (2014) estimation of the cost of air pollution in South East Queensland, Australia. In this study, the authors employ life satisfaction and socio-economic and demographic data from the Household Income and Labour Dynamics in Australia survey coupled with air pollution data on PM10 exceedances generated by the Commonwealth Scientific and Industrial Organisation’s The Air Pollution Model. The ordered probit model results for the micro-econometric life satisfaction function yield coefficient estimates of −0.0159 for PM10 exceedances and 0.1236 for the natural log of household income. Combining these estimates with the sample mean household income of AUD 40,0702 and employing the WTP equation presented above yields an implicit WTP of approximately AUD 5,150 (in terms of annual household income) to reduce by one day the average number of days that the PM10 concentration in an individual’s local area exceeds national health guidelines over a 12-month period.

Methodological Developments

A number of complementary methodological developments have helped to spur progress with the technique. Readily available large nation-wide household panel datasets (Haisken-DeNew, 2001), repeated representative cross-sectional surveys, and cross-country surveys containing self-reports of happiness or life satisfaction provide the necessary data in an easily accessible form. Furthermore, the volume and strength of evidence from psychology and other fields on the validity of self-reports of happiness (De Neve, Christakis, Fowler, & Frey, 2012; Diener, Inglehart, & Tay, 2013; Diener & Suh, 1999; Frey & Stutzer, 2002b; Kahneman & Krueger, 2006; Lucas & Donnellan, 2012) has helped to underpin the foundation on which the experienced preference method relies. Alongside these research efforts, some economists (MacKerron & Mourato, 2009, 2013; van Praag & Baarsma, 2005) have even started to implement their own novel questionnaires matched with objective data on the environment to permit the application of the life satisfaction approach.

Concurrent advancements in terms of geographic information systems (GIS) and the availability of spatially referenced data have been a significant boost for innovation in environmental sciences. Moreover, these data are an integral tool for environmental and resource economics where environmental externalities or spillover effects have, almost by definition, a strong spatial dimension (Tietenberg & Lewis, 2009). For environmental changes it allows for the explicit modeling and parameterization of spatial heterogeneity rather than simply ignoring it and/or treating it as a nuisance (Bateman, Jones, Lovett, Lake, & Day, 2002). The advantages of GIS extend to the life satisfaction approach, where it has featured as the main mechanism for linking information on an individual’s environment to individual respondents in household panel surveys. Furthermore, increasingly fine-grained GIS data and spatially referenced information on individuals present tremendously underutilized opportunities for more accurate modeling that appreciate the decay in spatial dependence over distance (Conley, 1999). This final point is particularly pertinent to environmental valuation using the life satisfaction approach.

Advantages of the Life Satisfaction Approach

The life satisfaction approach offers several advantages over more conventional environmental valuation techniques. For example, the method does not rely on the assumption of weak complementarity between the environmental good and consumption expenditure (an assumption underpinning the travel cost method), nor does it rely on housing markets being in equilibrium (an assumption underpinning the hedonic property pricing method). The experienced preference method also avoids the issues of incomplete information and mistaken perceptions of environmental amenity or disamenity that may otherwise lead to underestimates of monetary values due to inaccurate affective forecasting.

Furthermore, unlike the contingent valuation method, the life satisfaction approach does not ask individuals to value the environment directly. Instead, individuals are asked to evaluate their general life satisfaction. This is perceived to be less cognitively demanding because specific knowledge of the good in question is not required, nor are respondents asked to perform the unfamiliar task of placing a monetary value on the environment. This addresses many of the concerns surrounding the focusing illusion (Kahneman, Krueger, Schkade, Schwarz, & Stone, 2006) and hypothetical bias that may arise from the lack of real monetary incentives, credible policy mechanisms, or convincing changes in policy or environmental condition. It also avoids the problem of protest responses, strategic behavior (e.g., free riding), and social desirability bias (where an individual responds to a contingent valuation question in what they perceive to be a socially desirable way) (Welsch & Kuhling, 2009).

The life satisfaction approach also avoids the problem of lexicographic preferences, where respondents to contingent valuation or choice modeling questionnaires demonstrate an unwillingness to trade the environment for income (Spash & Hanley, 1995). From a practitioner’s perspective, the experienced preference method avoids the problem of how to make the environmental issue understandable to the population of interest, a task that can be particularly difficult when valuing complex environmental goods such as biodiversity (Christie et al., 2006).

Disadvantages of the Life Satisfaction Approach

Unfortunately, the life satisfaction approach is no panacea for environmental valuation. While it overcomes many difficulties with conventional environmental valuation, the approach also faces some challenges common to environmental valuation techniques broadly and necessarily introduces some new sources of uncertainty that researchers, practitioners, and policymakers should be mindful of.

For example, while there is growing evidence to support the suitability of individual’s responses to life satisfaction questions for the purpose of environmental valuation (Frey et al., 2010), some potential limitations remain. Crucially, self-reported life satisfaction must be regarded as a good proxy for an individual’s utility. Furthermore, in order to yield reliable non-market valuation estimates, self-reported life satisfaction measures must: (1) contain information on respondents’ global evaluation of their life; (2) reflect not only stable inner states of respondents but also current affects; (3) refer to respondents’ present life; and (4) be comparable across groups of individuals under different circumstances (Luechinger & Raschky, 2009).

The implementation of the life satisfaction approach requires a carefully considered research design. The conspicuous application of this method to observational data provokes predictable concerns regarding various forms of endogeneity shared by applied economics and the social sciences more broadly. Given the common finding of relatively smaller income coefficients (leading to higher monetary valuation estimates), a great deal of research effort has been devoted to obtaining unbiased and causal estimates of the income coefficient. As such, apart from adjusting for potential confounders, instrumental variable approaches have been employed. Instruments employed include household expenditure (Kingdon & Knight, 2007), father and spouse’s education (Knight, Song, & Gunatilaka, 2009), social class (Brown, 2013; Ferreira & Moro, 2010), and industry of employment (Pischke, 2011; Powdthavee, 2010). This has generally led to higher income coefficients and significantly reduced implicit willingness-to-pay estimates, although there are cases where the reverse is true (Ferreira & Moro, 2010). The validity of the instrumental variables employed in these studies, however, has been questioned because many factors may plausibly be directly or indirectly related to well-being (Pischke & Schwandt, 2012; Stutzer & Frey, 2012). An alternative approach put forward by Ambrey and Fleming (2014a) is to use restricted windfall income (such as lottery winnings) as a substitute for the more conventional household income monetary measure. In applying this alternative to the valuation of physical health, the authors find the effect of income on life satisfaction to be substantially higher (and willingness-to-pay estimates substantially lower). Importantly, their results also indicate that restricted windfall income is not statistically significantly associated with factors such as household income and a range of unobserved individual-specific time-invariant characteristics.

Similar concerns and research energy have been directed to obtaining unbiased and consistent causal estimates of the environmental variable coefficient estimate β^. Due to the possibility for people to self-select where they reside, this estimate is theorized to be biased downwards for disamenities (as people who are more averse to the disamenity move away) and biased upwards for amenities (as people who prefer an amenity more strongly move to that location). However, as with the income coefficient, the magnitude and direction of this effect is uncertain.

As with many conventional revealed preference approaches to environmental valuation (e.g., hedonic property pricing models and the travel cost method), the approach is not well suited to addressing questions related to hypothetical scenarios or scenarios relating to future environmental change (e.g., climate change). Some authors have sought to address this through a hybrid contingent valuation-experienced preference method (Kaval & Loomis, 2007; Kaval, Yao, & Scrinigeour, 2009; Yao & Kaval, 2009).

On the “Complementarity” of the Life Satisfaction Approach

Early applications of this technique regarded the approach as potentially complementary to other conventional environmental valuation approaches. Some authors take the view that the life satisfaction approach only values the residual benefits (or costs) of the environmental goods or services not already captured in housing markets (Luechinger, 2009; van Praag & Baarsma, 2005). Ferreira and Moro (2010) suggest that the relationship depends on whether the hedonic markets are in equilibrium or disequilibrium, as well as on the econometric specification of the well-being function. If the assumption of equilibrium in the housing market holds, then no relationship should exist between the intangible good and well-being, because housing costs and wages would fully adjust to compensate. If, however, a significant relationship is found, then residual benefits or costs must remain. Very few well-being functions are specified to incorporate housing markets, although it should be noted that Welsch and Biermann (2016) find little difference in results when housing costs are included or omitted in their spatial analysis of the influence of nuclear power plants on the life satisfaction of residents of Switzerland. Goetzke and Islam (2017), while finding results that indicate spatial disequilibrium in utility, have sought to quell the controversy that such results have provoked. Specifically, the authors state: “Our results indicate that spatial disequilibrium may be a persistent phenomenon—simultaneously coexisting with a constant movement toward an equilibrium that may never be reached” (Goetzke & Islam, 2017, p. 15). The authors rightly conclude that the question is ultimately an empirical rather than theoretical one.

Another important distinction needs to be made regarding this technique compared to conventional environmental valuation techniques. While this method permits the calculation of monetary estimates, due to the technique being based on experienced utility, these estimates have a different meaning from those obtained using conventional measures that rely on decision utility. That is, monetary estimates in the case of the life satisfaction approach may be conceptualized “as the extra money which would in the long run secure for the average person an extra util of happiness” (Layard, 2006, p. C33). This relates to the amount of utility after someone has hedonistically adapted to one’s income, due to comparisons with their past income and others’ incomes (Clark, Frijters, & Shields, 2008).

Many aspects of our life choices, motivated by our pursuit of happiness (Hands, 2009a, 2009b), may be at odds with our own well-being (Haybron, 2010). There is, therefore, a compelling case for developing well-being analyses to gauge the efficacy of environmental management policies. In this regard, the life satisfaction approach may be imagined as supplanting rather than supplementing conventional cost-benefit analysis. That is, costs and benefits could be expressed in utils rather than dollars (Layard, 2006). This is a sentiment shared by Bronsteen et al. (2013) and has some similarities with the pioneering Dutch sociologist Ruut Veenhoven’s concept of Happy Life Years (Veenhoven, 1996), which captures the number of years the average citizen in a country lives happily at a certain time. It is hard to imagine a more worthwhile goal for any nation to pursue for its citizens. Undoubtedly, though, the use of subjective measures of well-being will likely remain controversial among mainstream economists. As noted by MacKerron (2012), purely happiness economists are still a relatively new phenomenon.

Existing Applications of the Life Satisfaction Approach

Applications of the life satisfaction approach to the valuation of environmental goods and services to date include the valuation of air quality, airport noise, greenspace, scenic amenity, floods, and other natural disasters. Here we briefly review notable studies within the existing literature.

In an early example, Welsch (2002) uses cross-section data on reported well-being for 54 countries to value urban air pollution. The author finds that, on average, an individual needs to be given $70 per annum compensation in order to accept a 1 kiloton per capita increase in urban nitrogen dioxide load. The valuation of air quality continues to be a key focus. Welsch (2006) employs happiness data from the World Database of Happiness (Veenhoven, 2014) for 10 European countries to find that air quality improvements in Western Europe in the 1990s are valued at about $750 per capita per year in the case of nitrogen dioxide and about $1,400 per capita per year in the case of lead. A subsequent study (Welsch, 2007) estimates not only the benefits of air pollution abatement but also the associated costs in terms of income forgone due to pollution abatement (Note: air pollution is regarded as an input into income generation). This study is quite distinct in that it deconstructs an overall welfare effect into its relevant indirect and direct effects. This helps to reveal the role of the mechanistic processes underpinning well-being. In more recent times, studies of Organisation for Economic Co-operation and Development (OECD) countries find that the implicit willingness-to-pay estimates for air pollution are U-shaped in age. This is in line with epidemiological evidence, which indicates that the health-related consequences of air pollution are more severe for younger and older citizens (Menz & Welsch, 2010). Using a sample of approximately 59,000 individuals in 10 European countries from the Eurobarometer Survey, Menz and Welsch (2012) distinguish between age-specific and cohort-specific air pollution valuation dependences. Moreover, there is evidence from the application of this technique to 48 countries that individuals do not habituate to air pollution (Menz, 2011), although Levinson (2012) finds the reverse to be true.

Parallel to these cross-country studies, a number of studies investigate valuing air quality within countries. These studies require a more disaggregated level of analysis, allowing researchers to generate more precise and well-controlled findings. Almost all of these studies investigating air quality in the United States (Levinson, 2012), Europe (Ferreira et al., 2013; Luechinger, 2010), Ireland (Ferreira & Moro, 2010), and Germany (Luechinger, 2009) have adopted instrumental variable approaches when applying the life satisfaction approach. Analysis undertaken at a finer geographic scale and without the use of an instrumental variable includes MacKerron and Mourato’s (2009) study of air quality in London (modeled using 50 m × 50 m grid cells) and the aforementioned Ambrey et al.’s (2014) study of air quality in South East Queensland, Australia (modeled using 1 km × 1 km grid cells).

A small body of work has used the life satisfaction approach to examine the implied willingness to pay to reduce noise pollution. Van Praag and Baarsma (2005) provide an early application of the approach to airport noise from Amsterdam Airport. The authors carefully acknowledge the longstanding locational equilibrium theory in economics (Blomquist et al., 1988; Roback, 1982; Rosen, 1974) and provide a convincing argument for the presence of disequilibrium in house prices (the authors report an absence of correlation between noise and house prices). In fact, evidence for location disequilibrium appears to be the empirical norm rather than the exception (Ferreira & Moro, 2010; Goetzke & Islam, 2017; Rehdanz & Maddison, 2008; Stutzer & Frey, 2008). The study by van Praag and Baarsma (2005) identifies, among other things, that the implied willingness-to-pay values depend on the objective noise level, income, the degree to which house prices account for noise differences, and the presence of noise insulation. In a more recent study, Weinhold (2013) employs life satisfaction data from 28 countries across Europe to estimate the cost of all sources of noise pollution. In this case the noise variable is measured via self-reported indications of the number of reasons to complain about noise, where respondents can answer “very many,” “many,” “a few,” or “no reasons to complain.” No information is collected about the source of the noise, nor is any objective measurement of noise included within the analysis. Nonetheless, the author finds perceived noise pollution to exert a negative and highly significant effect on happiness and calculates the cost of noise pollution to be approximately €172 per month per household.

Greenspace is another environmental good that has received some attention. In an Australian context, Ambrey and Fleming (2012) employ the life satisfaction approach to value Australia’s protected areas, grouped by International Union for Conservation of Nature (IUCN) categories. The authors find significant life satisfaction effects of living in close proximity to protected areas in three of the seven IUCN categories, a result the authors suggest points toward a substantial residual shadow value associated with the provision of protected areas that is not captured in housing costs or wages. In a subsequent study (Ambrey & Fleming, 2014b), the authors examine the influence of public greenspace on the life satisfaction of residents of Australia’s capital cities, finding that the value of greenspace increases with population density and that lone parents and the less educated benefit to a greater extent from the provision of public greenspace than the general population. Also focusing on urban greenspace, Bertram and Rehdanz (2015) employ the life satisfaction approach to value greenspace in Berlin. The authors find a significant, inverted U-shaped effect of the amount of and distance to urban greenspace on life satisfaction, implying that additional urban greenspace first increases life satisfaction but tends to decrease life satisfaction above a certain threshold. The authors suggest that this might be explained urban greenspaces being associated not only with amenities but also with disamenities such as noise, congestion, and crime.

In a cross-country study, Kopmann and Rehdanz (2013) value changes in natural land cover across 31 European countries, finding that values increase with increasing scarcity of land cover type and that a nonlinear relationship between land cover and well-being is preferred to a linear relationship, suggesting decreasing benefits from individual landscape amenities. Relatedly, some studies have started to explore and value biological diversity at both neighborhood and cross-country scales (Ambrey & Fleming, 2014c; Rehdanz, 2007), and one study has investigated the benefits of scenic beauty as defined by ex-ante preferences (Ambrey & Fleming, 2011). Finally, natural disasters have also received a good deal of attention, with notable examples including the valuation of drought in Australia (Carroll, Frijters, & Shields, 2009), floods in 16 European countries (Luechinger & Raschky, 2009), forest fires in Spain, Portugal, Italy, and the Mediterranean provinces of France (Kountouris & Remoundou, 2011), and nuclear disasters at Chernobyl (Danzer & Danzer, 2016) and Fukushima (Rehdanz, Welsch, Narita, & Okubo, 2015).

The subjects of investigation taken up by researchers applying the life satisfaction approach are largely analogous to those that environmental and resource economics has traditionally concerned itself with. However, the method and the monetization of the environment has permitted the extension and broadening of the scope of “that part of social welfare that can be bought directly or indirectly into relation with the measuring rod of money …” (Pigou, 1932, p. I.III.I). This has led to the valuation of a diverse range of phenomena including crime (Cohen, 2008; Manning, Fleming, & Ambrey, 2016), commuting (Dickerson, Hole, & Munford, 2014; Stutzer & Frey, 2008), civil war and terrorism (Frey, Luechinger, & Stutzer, 2007, 2009; Welsch, 2008a), corruption (Welsch, 2008b), health (Ferrer-i-Carbonell & van Praag, 2002; Powdthavee & Van den Berg, 2011), and even friends (Powdthavee, 2008). While these studies are beyond the scope of this article, they point to the diverse range of applications feasible with this technique. In this regard, the life satisfaction approach allows researchers to capture hedonistic costs or benefits previously intangible and thought impossible to value. A study of two First Nations Peoples in Canada shows how the method may be used to value social, cultural, and land use activities (Kant, Vertinsky, & Zheng, 2016). Similarly, it may also prove useful for capturing the costs of bushfires, which would otherwise remain elusive (Ambrey, Fleming, & Manning, 2017; Kountouris & Remoundou, 2011).

Looking Forward

This article traces the origins of the life satisfaction approach to non-market valuation from the economics of happiness literature. It documents how the approach intersects with environmental and resource economics and reports on the methodological developments that have accompanied this technique and that have helped it to mature. An account of the advantages and disadvantages of the technique relative to other, more conventional, non-market valuation techniques is given, as is an overview of the many and varied applications of the life satisfaction approach that have been published to date.

Aside from the use of questionnaires and the direct measurement of utility, the life satisfaction approach exhibits a number of conceptual differences from conventional environmental valuation approaches typically employed by environmental and resource economists. One particularly important difference is the characterization of utility as experienced utility rather than decision utility (Dolan & Kahneman, 2008; Kahneman & Sugden, 2005). This hampers the commensurability of the monetary estimates with other traditional methods. This point is underappreciated by economists applying conventional environmental valuation techniques, although Tinch, Colombo, and Hanley (2010) provide a notable exception in the context of a choice experiment. Furthermore, the findings to emerge from the use of the approach exist in many respects as a critique of mainstream economics. Notably, finding an association between a change in the environment and well-being is contrary to locational equilibrium theory in economics (Blomquist, Berger, & Hoechst, 1988; Roback, 1982; Rosen, 1974). Both of these points greatly limit the extent to which the method may be considered “complementary” to conventional techniques.

Reflecting on the depth and breadth of research in this area, it is increasingly less appropriate to describe the life satisfaction approach as a “relatively new,” “emerging,” or “developing” technique. Still, many challenges, controversies, and debates remain, and it is only very recently that pure happiness economists have started to emerge. Nevertheless, it is anticipated that the micro-econometric techniques used to apply the life satisfaction approach will likely continue to develop and those currently underutilized (e.g., through spatially explicit modeling techniques) taken advantage of (MacKerron, 2012). Furthermore, consistent with the desire to advance science research, efforts should be directed toward identifying causal mechanisms and generating replicable and transparent evidence. This aspiration is not unique to the desire to advance the life satisfaction approach; it is a challenged shared with other environmental valuation techniques and applies to the pursuit of knowledge generally. To achieve this end, greater research effort is required to theorize and operationalize the causal pathways through which environmental changes may impact well-being. Redressing these knowledge gaps bodes well for the continued development and refinement of applications of the approach. Ultimately, these innovations and conceptual advances will improve the quality of the knowledge used to inform environmental and social policy and hence social welfare more broadly.

Suggested Readings

Ambrey, C., & Fleming, C. (2011). Valuing scenic amenity using life satisfaction data. Ecological Economics, 72(1), 106–115.Find this resource:

Ambrey, C., Fleming, C., & Chan, A. (2014). Estimating the cost of air pollution in South East Queensland: An application of the life satisfaction non-market valuation approach. Ecological Economics, 97(1), 172–181.Find this resource:

Danzer, A., & Danzer, N. (2016). The long-run consequences of Chernobyl: Evidence on subjective well-being, mental health and welfare. Journal of Public Economics, 135(1), 47–60.Find this resource:

Dolan, P., & Kahneman, D. (2008). Interpretations of utility and their implications for the valuation of health. The Economic Journal, 118(525), 215–234.Find this resource:

Frey, B., Luechinger, S., & Stutzer, A. (2010). The life satisfaction approach to environmental valuation. The Annual Review of Resource Economics, 2(1), 139–160.Find this resource:

Frey, B., & Stutzer, A. (2002). What can economists learn from happiness research? Journal of Economic Literature, 40(2), 402–435.Find this resource:

Kahneman, D., & Sugden, R. (2005). Experienced utility as a standard of policy evaluation. Environmental and Resource Economics, 32(1), 161–181.Find this resource:

Levinson, A. (2012). Valuing public goods using happiness data: The case of air quality. Journal of Public Economics, 96(9–10), 869–880.Find this resource:

Luechinger, S. (2009). Valuing air quality using the life satisfaction approach. The Economic Journal, 119(536), 482–515.Find this resource:

Luechinger, S., & Raschky, P. (2009). Valuing flood disasters using the life satisfaction approach. Journal of Public Economics, 93(3–4), 620–633.Find this resource:

MacKerron, G. (2012). Happiness economics from 35 000 feet. Journal of Economic Surveys, 26(4), 705–735.Find this resource:

Rehdanz, K., Welsch, H., Narita, D., & Okubo, T. (2015). Well-being effects of a major natural disaster: The case of Fukushima. Journal of Economic Behavior & Organization, 116(1), 500–517.Find this resource:

Stutzer, A., & Frey, B. (2012). Recent developments in the economics of happiness: A selective overview. Discussion Paper No. 7078. Bonn, Germany: The Institute for the Study of Labor (IZA).Find this resource:

van Praag, B., & Baarsma, B. (2005). Using happiness surveys to value intangibles: The case of airport noise. The Economic Journal, 115(500), 224–246.Find this resource:

Welsch, H. (2007). Environmental welfare analysis: A life satisfaction approach. Ecological Economics, 62(3–4), 544–551.Find this resource:

Welsch, H. (2009). Implications of happiness research for environmental economics. Ecological Economics, 68(11), 2735–2742.Find this resource:

Welsch, H., & Ferreira, S. (2013). Environment, well-being, and experienced preference. International Review of Environmental and Resource Economics, 7(3–4), 205–239.Find this resource:

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Notes:

(1.) In the late 1990s when happiness was first really revived as part of the economic vernacular, it was unclear whether or not the economics of happiness constituted a subfield in its own right or just a more heterodox approach to investigating conventional research questions in economics, where heterodox economics may be loosely defined as “economics with particular attachments to the kinds of investigations carried on in other science fields” (Davis, 2006, p. 18). Increasingly though, it seems that the economics of happiness is coalescing as a subfield in its own right, although the demarcation of the subfield’s boundaries is still somewhat fluid.

(2.) As of January 24, 2017: 1 AUD = 0.76 USD; 0.71 EURO; 0.61 GBP.