1 Towards an Urban Quality of Life Index Basic theory & econometric methods Bernard M.S. van Praag University of Amsterdam and Ada Ferrer -i-Carbonell ICREA & Institut d'Anàlisi Econòmica (CSIC), Barcelona

2 Basic questions  How is Urban Quality of Life (UqoL) measured?  Which factors determine UQoL?  Is it possible to translate UQoL –variables in terms of money?  Can one construct an Urban UQoL–index ?  Can it be used as a benchmark for urban policy?  Can it be used to make quality comparisons between cities?

3 Two approaches  Hedonic equations  Trade offs made in the market  Limitations: (1) people do not optimize, (2) there are market failures & (3) decisions depend on external factors. (Roback (1982), Rosen (1979), Blomquist et al. (1988), Gyourko, J. (1991)  Happiness economics offers an alternative

4 Hedonic equations (1) Rent determinants in Lima (in green urban variables) Source: Quality of Life in Urban Neighbourhoods in Metropolitan Lima, Peru, L. Alcázar & R. Andrade (2008).

5 Hedonic equations (2) Rent (r) depends on house characteristics (h) and urban factors (u)  Rent is decomposed into hedonic factors  Ratio α 1 /α 2 is the market ratio between two urban factors.  Is it the subjective trade–off ratio of the owner?  True only if house owner lives in a house of optimal choice, given income and other individual variables.  Strong assumption, especially for long term purchases  If there is no optimum, then is a rent index but not a subjective Urban Quality of Life – index.

6 Happiness economics  Key tool: Satisfaction questions Clark and Oswald (1994), Easterlin (1974), Van Praag (1971), Frey and Stutzer (2002), Van Praag & Ferrer-i- Carbonell (2004,2007), Graham (2007), DiTella, MacCulloch & Oswald (2001), Oswald & Powdthavee (2007), Blanchflower & Oswald (2004), DiTella, Haisken–DeNew, MacCullogh (2007), Helliwell (2007).

7 Life Satisfaction Question In conclusion, we would like to ask you about your satisfaction with your life in general. Please, answer according to the following scale: 0 means ´completely dissatisfied´, 10 ´completely satisfied´. How satisfied are you with your life, all things considered? 0___1___2___3___4___5___6___7___8___9___10 completely dissatisfied satisfied

8 Peruvian questionnaire (2008). En una escala del 1 al 10, donde 1 es totalmente insatisfecho y 10 es totalmente satisfecho, ¿cuán satisfecho se encuentra usted con los siguientes aspectos de su distrito...( LEER ATRIBUTOS)? (MOSTRAR TARJETA 62 Y ANOTAR PUNTAJE) Puntaje El nivel del tráfico y congestión vehicular El servicio del transporte públic El grado de la contaminación La tranquilidad / silencio en su vecindad

9 Main characteristics  Assumption: Respondents who give the same answer are equally satisfied. (ordinal interpersonal comparability)  What are factors defining life satisfaction?  Age, gender, income, health, family size, social relations, urban environment, etc..  In short :a vector x=() of satisfaction determinants.

10 Indifference curves (1)  Respondents with different x may be equally happy.  Say, in the sample we find 100 respondents in the same response category. With different combinations of satisfaction determinants: x (1),…, x (100)  The set of points {x (1),…, x (100) } in x – space constitutes a satisfaction indifference set.

11 Satisfaction Indifference Curve We represent the persons as points in the x –space. x1x1 x2x2 Satisfaction

12 Indifference curves (2)  In case of response categories we have indifference bands.  An indifference curve is described by an equation f(x 1,…, x k )=u, where u stands for a specific level of satisfaction.  Linear indifference curves are described by α 1 x 1 +…+ α k x k +α 0 =u

13 Neo-classical & Happiness Economics  The x–variables are :  Neo-class: private goods & services bought on the market at market prices (e.g. cars, houses, medical services)  Happiness Economics also public goods (e.g. urban environment), and intangible circumstantial variables (e.g. health, age, social relations)  Identification: –Neo-class by marginal conditions, assuming respondent is in optimum situation. –Happiness Economics by means of satisfaction questions

14 Estimation of indifference curves  Various estimation methods yield essentially same outcome (Van Praag and Ferrer -i-Carbonell 2004,2007)  Ordinal (OP) and cardinal utility indicators  Cardinal Median Utility (CM)  Assume ordinal utility function: U(inc,x)=N(α inc ln(inc)+α 1 x 1 +…+ α k x k +α 0 ;0,σ)  Cardinalization:If response is = 7  set u n =N -1 (0.7) Responses [0-10] replaced by their normal quantiles. And we should get approximately: To be estimated by OLS on

15 Example: Job satisfaction Estimated by 5 methods (GSOEP)

16 Coefficients normalized

17 Life & Domains Satisfactions  Life satisfaction can be decomposed into domains, the two– and multi–layer model  The satisfaction approach is applicable to domains of life.  Job satisfaction, but also satisfaction with health, financial situation, social relations, marriage, the government, housing situation, one's neighborhood & supply of urban amenities.

18 Domain satisfactions as components of satisfaction with life as a whole

19 Example: German sample from BvP,FiC,Happiness Quantified

20 Example: Costa Rica Hall L.J.,Madrigal R., J. Robalino (CATIE, Costa Rica) (2008), "Quality of Life in Urban Neighbourhoods in Costa Rica", forthcoming in IDB-publication.

21 Index of Urban Quality  Cardinal index per person –Assumption: cardinal interpersonal comparability S u =S u (A n,Z n ) urban amenities (A n ) & individual characteristics (Z n )  The quality of Lima may be evaluated by the inhabitants of Lima  Or by the inhabitants of Buenos Aires by

22 Separability of the index  Separability?  Vignet analysis (cf. Kapteyn, Smith, Van Soest, AER 2007)

23 Conclusions  Satisfaction measurement is possible  Without neo-classical behavioral assumptions  Natural extension of variables to non- market variables, external effects, rationing.  Indifference curves can be estimated  Wide variety of methods lead to the same result for trade-off estimates  Quality index requires a cardinalization  Further research necessary for practical implementation.