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In almost every city, some neighbourhoods are more pleasant to live in than others. Different consideration such as safety, adequate street lightning, the presence of green spaces, access to public transportation, educational and health facilities, etc. exemplifies this assessment. This phase calls attention to how different urban services affect overall urban environmental quality and QoL with the ultimate goal of developing operational indexes to measure the effect on urban life. Praag and Carbonell (2010) have argued that an index can be used to compare the amenities offered by different neighbourhoods within a city and their contribution to citizen’s QoL. Then a better understanding of the type of urban policies that are most favourable for citizen’s QoL can be differentiated. Such amenities and dis-amenities that are not bought directly on the market, but presumably are important for life quality, range from air quality to safety and include aspects of environmental quality. Praag and Carbonell (2010) point out that:

“Under certain assumption, those and other urban features should be reflected in housing prices” (p.66)

The sale or rental prices of housing in a city are a synthesis of how the market values certain characteristics or attributes, not only those of a house itself but those of its surroundings. Housing prices therefore are a good synthetic measure of the quality of urban life that residents may enjoy, provided that those prices reflect all of the city’s characteristics that have an effect on well-being and QoL. In addition home and city

satisfaction are two of many dimensions that people may implicitly take into account when they evaluate their overall QoL. Here is where life satisfaction comes into play. Although life satisfaction cannot be measured as the price of house, it can be fairly well estimated using a simple QoL survey. Life satisfaction is a synthetic measure of the recognition that each person gives to all aspects of their live including the home and the city in which they live. Life satisfaction depends on different factors, such as income, health, family situation, and working conditions. It is also influenced by the quality of urban environment. Until recently economists focused mainly on private variables such as health satisfaction (Ferrer-i-Carbonel Ada and Bernard M.S. van Praag, 2002; Oswald Andrew and Nattavudh Powdthavee, 2007), relative income (Easterlin Richard A., 1995; Ferrer-i-Carbonel Ada, 2005; Clark Andrew E. et al., 2008), and life satisfaction impact of one’s own income or work conditions (van Praag Bernard M.S., 1971; Clark Andrew E. and Andrew J. Oswald, 1994; Di Tella Rafael et al., 2001). However, economists have often excluded other highly relevant factors that are difficult to measure and frequently are not included in data sets at hand. These factors which cannot be bought on the market have been ignored on the grounds that traditionally they are within the research field of other behavioural sciences. Nonetheless, these factors have an undeniable effect on QoL. Although this is a very new field of study, particularly in Iran, different methodologies are proposed to researchers, however looking at a similar work by Lora et al., (2010a) that has recently been published by The Inter-American Development Bank and World Bank. The combination of the Hedonic Pricing (HP) and Life Satisfaction (LS) approach is proposed as a methodological framework for interpreting this study, the results of which will be compared to a second approach using a Choice Experiment (CE) method. An explanation of each approach and its relation to one another is now provided.

5.4.1 Hedonic Pricing Method (HPM)

As explained in the previous chapter, the hedonic approach has a long tradition in placing monetary values on the welfare impact of city amenities and public goods. The location in which a family decides to live reflects their preference regarding to a set of characteristics pertaining to the house purchase or rented, the neighbourhood where the house is located, and the amenities and services that are offered in that neighbourhood. A reasonable public transportation system can increase the accessibility of a location although it may be far from the destination. Parks and green areas can form the aesthetic aspect of the matter; they can also decrease pollution as well. This examples show the relation between the locational attribute and urban services. Thus, a good neighbourhood

will be perceived as a desirable place to live when it provides peace tranquillity and security for it residents. This happens when police station is nearby or other daily urban services (e.g. parks, schools, banks, post office, etc.) are in reasonable proximity to the residential location. Therefore the HPM is a suitable method to assess the role of urban services in the housing price in order to observe the pros and cons of public service and their location in a city; to make the city a more sustainable place and environment in which to live.

Having said that, a feature of the hedonic approach is that it only assumes an ordinal utility function. Using the ordinal assumption only does not allow for translating an income gain into a utility gain; nor does it allow for interpersonal comparison of level of QoL and wellbeing.

Here is where the life satisfaction (LS) approach comes into play. That approach does not assume that the individual is at any time observed in his optimum in a perfect market. Moreover, the LS approach allows for both ordinal and cardinal satisfaction measurements.

5.4.2 Life Satisfaction Approach

The term LS was coined by Clark and Oswald (1994), with predecessors in van Praag (1971), Easterlin (1974) and so-called Leyden School. The approach asks individuals how satisfied they are with their life or how happy they are. The rationale for this approach is evidence that each individual evaluates their satisfaction from life as a whole. For these evaluations, questions can be from verbal categories, such as “unsatisfied”, “acceptable” and “very satisfied”; or it may use an ordinal scale for example 0 as worse conceivable situation to 10 as conceivable situation. Demonstration has been provided that these measurements are well correlated with various aspects of behaviour related to happiness. Individuals that are happy according to this measurement also are measured happy by their friends and families and express positive emotions more frequently and are more optimistic, social and extroverted.

So far no uniformity exists on how to phrase satisfaction questions. Respondents may be asked how happy or satisfied they are with life in general or they may also be evaluated by asking about other aspects of their life domains, such as financial situation, housing, health etc. Although there are different wordings of satisfaction questions, in practice the results are fairly well comparable.

LS evaluation depends on a set of variables explaining the individual’s situation such as age, marital status, income, employment, family size, health, travel distance to work etc. in short, a vector of X of K different variables X1,…,XK. These can be called dimensions

or aspects of an individual’s life situation. Some of these aspects or dimensions can be influenced by the respondents themselves for example number of working hours and travel time to work. Others, like gender, age… cannot be changed by the individual. In addition, urban and environmental features like safety, climate and cleanness variables can be included in LS evaluation.

LS is a relatively new method of placing a value on public goods. This method corresponds more closely to stated-preference approach. The method uses the marginal utility of a public good as well as the marginal utility of income to calculate the trade-off between income and public goods such as urban services (the implicit price).

LS has certain advantages over hedonic pricing. First, because the LS approach is not based on observed behaviour, the underlying assumptions are less restrictive and non-use values can be measured to some extent. Furthermore, individuals are not asked to value the public good directly, but to evaluate their general subjective satisfaction. Arguably, this task is less cognitively demanding and does not allow for strategic behaviour - two issues that have been critical and problematic in affecting contingent valuation methods. In the basic empirical analysis of the LS approach, a micro econometric happiness function is estimated in which an individual’s utility is approximated by self-reported subjective well-being. Income and socioeconomic variables are the explanatory variables. Proximity to different neighbourhood and city services and amenities (or dis-amenities) could be included. The typical regression has the following form:

𝐿𝐿𝑆𝑆𝑖𝑖𝑗𝑗 = 𝑝𝑝 + 𝑏𝑏 𝑒𝑒𝑖𝑖𝑗𝑗+ 𝑒𝑒 𝑝𝑝𝑎𝑎𝑒𝑒𝑖𝑖𝑗𝑗 + 𝑑𝑑 𝑝𝑝𝑎𝑎𝑒𝑒𝑖𝑖𝑗𝑗2+ 𝑒𝑒 𝑒𝑒𝑓𝑓𝑖𝑖𝑗𝑗+ 𝑎𝑎 𝐻𝐻𝑖𝑖𝑗𝑗 + ℎ 𝑍𝑍𝑖𝑖𝑗𝑗+ 𝑣𝑣𝑖𝑖𝑗𝑗 (1) Where y, age, and fs, respectively, represent income, age, and family size of individual i living in neighbourhood j. H and Z, respectively are two vectors of housing and neighbourhood characteristics. The error term 𝑣𝑣_{𝑖𝑖𝑗𝑗} = 𝑒𝑒_𝑖𝑖 + 𝑧𝑧_𝑗𝑗 is a composite error term that combines a neighbourhood-specific error component,𝑧𝑧_𝑗𝑗 and a house-specific error component, 𝑒𝑒_𝑖𝑖. Empirical applications of this approach consistently have found that income has positive effect on life satisfaction (b positive) and that age has a negative but decreasing impact (c negative and d positive).

Table 5.1 summarizes significant factors that influence LS in Latin American cities published by the World Bank and the Inter-American Development Bank (Lora et al., 2010a).

Characteristics Factors Housing

Characteristics

Numbers of rooms, Quality of Floors, Satellite TV services, Quality of Floors

Neighbourhood Characteristics

Security during the day, Sidewalk condition, Cultural and sports activities, Amount and quality of green areas, Robbery, Condition of streets, Safety, running water, Street lights, Traffic, Evaluation of neighbours, Quality of garbage collection, quality of telephone services, Average education in the neighbourhood, Distance to main or connector street.

Socioeconomic Characteristics

Income, Age, Marital status, Family size, Health variables Table 5.1 Significant factors that influence LS in Latin American cities

Apart from judging which housing and neighbourhood characteristics are particularly important, the LS approach can be used also to place a value on living in a neighbourhood or on a particular house or neighbourhood characteristic. Because income influences life satisfaction along with certain characteristics (say, the condition of street) the trade-off between greater income and ‘better street’ can be used to estimate the value of improving streets. At no point do interviewed people actually express how much they are willing to pay for these characteristics. The LS approach is particularly helpful, therefore, because it can be used to value amenities that do not yet exist or for which no market price is available.

The LS approach then provides one possible route to determining which amenities actually are considered valuable, to placing values on those characteristics, and to monitoring the valuation over time to see if they change as socioeconomic developments occur and as the characteristics of cities change.