I investigate the relationship between the popular Mercer city ranking (livability) and survey data (satisfactions). Livability aims to capture objective quality of life such as infrastructure. Survey items capture subjective quality of life such as satisfaction with city. The relationship between objective measures of quality of life and subjective measures is weak (correlation of about 0.4). Trust is highly correlated with both, objective livability (0.8) and subjective satisfaction with city (0.65). I postulate to pay more attention to subjective indicators of quality of life. After all, what matters is what we perceive, not what is out there.
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“The Economist and Forbes base their rankings primarily on data from the Mercer consulting company”(http://www.livablecities.org/blog/value-rankings-and-meaning-livability.). Kotkin (2011) claims that the Economist ranking is “remarkably similar” to Mercer.
In fact, we have the livability ratings because they are produced for businesses. Companies producing livability lists like Mercer sell them to businesses.
There are more ratings here: http://www.mercer.com/press-releases/quality-of-living-report-2010#City_Ranking_Table.
Curiosity, openness and tolerance contribute to the key ingredient of well-being (social capital). Yet, on the other hand, diversity hinders social capital (Putnam 2007).
There is a systematic difference between what we think to influence our quality of life and what actually does. For a further discussion of the difference between expected and experienced utility see (Kahneman and Sarin (1997); Schkade and Kahneman (1998); Kahneman (2000); Kahneman and Krueger (2006).
And so is artificial the popular Human Development Index (HDI), because it is a weighted average of income, life expectancy and education. HDI is measuring objective qualities, but in a normative way. Experts assign weights to each component based on their normative ideals.
Mercer claims on its website (http://www.mercer.com/referencecontent.htm?idContent=1380465) that “Given that basic individual needs are quite general, it is fairly unlikely that the quality of living components listed by two different individuals will differ to any great extent; what is more likely is that certain criteria of quality of living will have greater weighting than others at a given moment or in certain situations.” I would say that most of the components will have different weighting, and some of them will be different. Another confusing statement from the same website says: “In fact, Quality of Life may involve a subjective assessment or opinion, whereas Mercer’s criteria are objective, neutral and unbiased.”
For instance, in Rennes a metro line was opened in 2002 and this explains why Rennes in 2004 has the highest share of satisfied residents with public transportation http://www.urbanaudit.org/UAPS%20leaflet.pdf. In later years ratings of public transportation in Rennes dropped.
There seems to be no documentation about synthetic index calculation and I was unable to obtain information from Eurostat. However, synthetic index is almost the same as proportion of respondents who agree (strongly and somewhat) to those who disagree (strongly and somewhat) with correlations of more than 0.95.
I obtained weights by contacting Mercer. Mercer data can be found at: http://www.businessweek.com/interactive_reports/livable_cities_worldwide.html. There are indices for 2006 and 2007 and they correlate at 0.99, and I just use a values for 2006. A full list of 39 factors is in the "Appendix". Additional information is available here: http://www.citymayors.com/features/quality_survey.html#Anchor-Europe-11481.
Cummins (2000) further argues that the poorer the objective conditions the higher the correlation between the objective and subjective measures. Unfortunately, I cannot test this proposition here because European cities have good objective quality of life. But good objective quality of life may explain low correlation with subjective measures per Cummins (2000).
Again, I will use a synthetic index.
Again, i use survey means over 2004, 2006 and 2009, but results are similar if I just use 2006—only correlations with Mercer index are slightly higher by .05 to 0.1— it is expected because Mercer index comes covers 2006.
Florida (2008) produced some rankings for American cities for singles, professionals, families with children, empty-nesters, and retirees.
Urban Audit also asked about satisfaction with hospitals and results were similar—correlation of 0.73.
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Appendix 1: Domain Satisfactions
In addition to survey items in the body of the paper, I use here several other indicators of satisfaction with a specific domain of city life. Items are defined in Tables 4 and 5.
Figure 10 scatters Mercer index against satisfaction with public transport. The relationship is stronger, as expected, because Mercer index measures infrastructure and material goods.
Interestingly, there is not much relationship between the Mercer Index and satisfaction with schools in Fig. 11. This is the lowest correlation between Mercer Index and satisfactions.
On the other hand, there is twice this much correlation with doctors.Footnote 19 People in Western Europe tend to be more satisfied with doctors than people in Eastern Europe (Fig. 12).
Also satisfaction with sport facilities correlates highly with Mercer index in Fig. 13.
There are many more indicators like satisfaction with culture, cinemas, green spaces, beauty of streets, public spaces, outdoor recreation, and so forth. It is not practicable to graph them all, instead a corelation matrix is shown below.
City satisfaction best correlates with the following variables: trust, safe, outdoor, green, and streets. Trust, as discussed, is important for satisfaction. Safety, as expected, is important as well. And they both also correlate highly with Mercer index. The following variables, green, streets and outdoor also correlate highly with Mercer index. An interesting pattern emerges with respect to the foreigners variable—it is the only variable that does not correlate at all (zero rounding to one digit) with some other variables, and among them Mercer index, and at the same time it correlates most highly with overall satisfaction.
Appendix 2: Mercer Full List of Components
The above list comes from http://www.mercer.com/referencecontent.htm?idContent=1380465 Table 6.
Appendix 3: Google Maps
It helps to map data—this section presents some google maps of the variables discussed earlier. It turns out that there are large differences within countries as indicated by Okulicz-Kozaryn (2010), but differences by cities are even larger than by provinces. For instance, in developing Poland, Krakow and Gdansk are both happy, while Warsaw is unhappy and so is unhappy Berlin in Germany, while Leipzig and Hamburg are happy. Map is here (preferably use google chrome web browser): http://maps.google.com/maps?f=q&source=s_q&hl=en&geocode=&q=http://people.hmdc.harvard.edu/akozaryn/keep1_sat.kml. Another interesting pattern is that in the major European cities such as London, Paris, Rome, and Berlin there are quite a few people who are very satisfied with the city but also quite a lot who are quite satisfied.
In a second map http://maps.google.com/maps?f=q&source=s_q&hl=en&geocode=&q=http://people.hmdc.harvard.edu/akozaryn/keep2_mer_trust_for.kml, trust is much lower in Eastern and Central Europe than in Western and Northern Europe. Trust is also low in Italy and in London, and Paris, but not in Berlin. Foreigners are welcomed in Eastern Europe, France, London, but not in Italy, Austria, and Germany, except Hamburg. Interestingly, people in Brussels are not happy about foreigners, but people in Amsterdam are happy.
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Okulicz-Kozaryn, A. City Life: Rankings (Livability) Versus Perceptions (Satisfaction). Soc Indic Res 110, 433–451 (2013). https://doi.org/10.1007/s11205-011-9939-x
- City rankings
- Urban quality of life
- Perceptions survey
- Best places to live
- Urban audit