Environment and Happiness: New Evidence for Spain

Juncal Cuñado

Fernando Pérez de Gracia

(University of Navarra)

* Financial support from the Ministerio de Ciencia y Tecnología (Spain) and European Science Foundation is acknowledged

Outline of the Presentation

1. Motivation and objectives

2. Literature review

3. Empirical analysis (Spanish regions)

- Significant regional differences in happiness (after controlling for socio-economic variables)

- Impact of regional climate and pollution variables on happiness

- Monetary value of non-market goods

4. Concluding remarks

5. Future research

1. Motivation and objectives

- Economics of happiness: monetary socio-economic indicators (per capita GDP) are insufficient measures of well-being of citizens (United Nations, 1954; Erikson, 1993)

- Evaluate welfare effects of different factors, such as- Health (Berger and Leigh, 1989, Blanchflower and Oswald, 2008)- Education (Di Tella et al, 2001)- Macroeconomic variables (Di Tella et al, 2001)- Terrorism (Frey et al, 2009)- Noise (Van Praag et al, 2005)- Air pollution (Welsch 2002, 2006, 2007; Di Tella and MacCulloch,

2006; Ferrer-i-Carbonell, 2007; Luechinger, 2009, 2010; MacKerron and Mourato, 2009)

- Climate (Frijters and van Praag, 1998; Rehdanz and Maddison, 2005 2008; Brereton et al., 2008), ...

- This paper: implications of environmental policies on individual well-being (Spanish regions)

1. Motivation and objectivesObjectives:

- Impact of climate and air pollution conditions on happiness in Spanish regions using individual-level data from the European Social Survey and regional data on macroeconomic, climate and pollution from INE, AEMET and MMA

- Do climate and pollution variables at regional level affect individual happiness?- Are these variables more significant than macroeconomic variables such as per capita GDP or unemployment in

explaining individual happiness? - Do these variables explain regional differences in

subjective well-being (individual happiness)?- Monetary value of non-market goods (climate, pollution)

2. Literature review

Climate and pollution on happiness:

- Rehdanz and Maddison (2005): temperature plays a significant role in explaining happiness (data for 67 countries)- Becchetti (2007): non-linear effects of climate variables on happiness- Brereton et al. (2008): empirical analysis for Ireland- Welsch (2006): negative and significant effect of air pollution, using data for ten European countries- Luechinger (2010): air pollution affects negatively on SWB- Ferrer-i-Carbonell and Gowdy (2007): concern about ozone pollution and concern about species extinction- Zidanseck (2007): happier people tend to care more about the environment and people who live in a better environment tend to be happier

3. Empirical analysis

- Happiness (ESS): individual´s responses to the question “How happy are you”. The respondent answers on a scale from 1 (not happy at all) to 10 (completely happy).

- Socio-economic individual variables (ESS)- Gender - Age- Income- Subjective general health: discrete variable with takes the following

values: 1 (very good), 2 (good), 3 (fair), 4 (bad), 5 (very bad)- Marital status: 1 (married), 2 (in a civil paternship), 3 (separated), 4

(divorced), 5 (widowed), 6 (never married, never civil paternship)- Children: 1 (yes), 0 (no)- Main activity: 1 (paid work); 2 (education); 3 (unemployed looking for

job)...- ...

3. Empirical analysis- Macroeconomic variables (INE, Instituto Nacional de Estadística)

- Per capita GDP- Unemployment rate

- Climatological variables (AEMET, Agencia Estatal de Meteorología)- T: anually averaged mean temperature (ºC) - Tmax: average mean temperature in hottest month, July (ºC)- Tmin: average mean temperature in coldest month, January (ºC)- R: regional averaged mean precipitation, July and January (mm)- H: regional relative humidity- DR: rain (number of days)- DN: snow (number of days)- DT: storms (number of days)- DF: fog (number of days)- DH: freeze (number of days)- DD: sun (number of days)- I: sun (number of hours)

3. Empirical analysis

- Pollution variables (MMA, Ministerio de Medio Ambiente)- CO2 emissions (tons per km2)- NO2 concentration- PM10 (number of days per year in which PM10 concentration

exceeds 35 g/m3)

3. Descriptive statisticsTABLE 3. Happiness in Spanish regions, 2008 data

N Mean Std. Deviation Minimun Maximum

Galicia 499 7.41 1.61 2 10

Principado de Asturias 53 7.57 1.49 3 10

Cantabria 23 7.96 0.83 5 9

País Vasco 105 7.88 1.57 0 10

Comunidad Foral de Navarra

26 7.46 1.36 5 10

La Rioja 8 6.88 1.55 4 9

Aragón 50 7.72 1.37 4 10

Comunidad de Madrid 272 7.65 1.41 2 10

Castilla y León 114 7.14 1.40 2 10

Castilla- La Mancha 80 8.00 1.42 2 10

Extremadura 55 7.38 1.76 2 10

Cataluña 527 7.60 1.67 0 10

Comunidad Valenciana 181 7.69 1.47 2 10

Islas Baleares 43 7.44 1.28 5 10

Andalucía 402 8.10 1.88 0 10

Región de Murcia 60 7.43 1.69 2 10

Canarias 67 7.07 1.76 3 10

Total 2565 7.63 1.63 0 10

ANOVA F test for equal regional means= 4.703 (0.00)***

3. Descriptive statistics

Significant regional differences in happiness (F=4.70***)Andalucía, Castilla-la Mancha, CantabriaLa Rioja, Canarias

3. Descriptive statistics N Happiness Temperature

January Temperature July Precipitation

January Precipitation

July NO2 PM10 CO2 Population

density Regional income

Galicia 499 7.41 8.00 17.82 100.74 22.86 34 107 1.00 93.84 20,546 Principality of Asturias

53 7.57 5.91 16.79 83.99 36.55 37 31 2.44 101.79 22,427

Cantabria 23 7.96 7.2 16.95 55.47 41.69 29 18 1.35 109.46 24,222 Basque Country 105 7.88 7.51 17.67 32.92 52.09 33 33 3.16 298.38 31,791 Navarra 26 7.46 6.08 20.08 25.97 56.48 27 35 0.77 59.73 30,296 La Rioja 8 6.88 4.43 18.77 32.12 48.61 24 29 0.74 62.98 25,631 Aragon 50 7.72 4.85 20.90 32.74 55.97 49 175 0.44 27.80 26,093 Madrid 272 7.65 6.67 23.38 50.8 4.35 61 77 3.36 781.77 30,928 Castilla - Leon 114 7.14 5.03 20.01 55.83 19.15 28 146 0.42 27.14 23,206 Castilla La Mancha

80 8.00 6.47 23.97 44.79 7.03 24 100 0.32 25.73 18,425

Extremadura 55 7.38 9.01 25.61 69.54 0.72 12 17 0.22 26.34 16,845 Catalonia 527 7.60 6.43 20.54 22.37 62.36 55 100 1.69 228.68 27,897 Valencia 181 7.69 8.93 24.04 32.41 11.56 50 -- 1.40 216.21 21,392 Balearic Islands 43 7.44 10.42 24.1 40.06 29.64 33 15 2.18 213.72 25,706 Andalucia 402 8.10 9.77 25.5 48.31 0.11 34 64 0.66 93.63 18,384 Murcia 60 7.43 9.13 24.54 17.77 0.50 18 47 1.10 126.09 19,694 Canary Islands 67 7.07 15.51 21.13 26.21 0.34 26 122 2.30 278.82 20,827 Spain (average) 2565 7.63 7.82 21.47 51.16 25.21 40.81 86.14 1.39 211.07 23680

Figure 1. Spanish regions.

- Higher temperatures in Southern regions (Extremadura, Andalucía,

Murcia)- Higher precipitation values in Northern regions (Galicia, Asturias)- More polluted regions: Aragón, Castilla-León (thermic centrals)

3. Methodology

1. Regional differences in subjective well-being (ANOVA test on mean differences)

2. Model including socio-economic individual indicators, macroeconomic, climate and pollution variables

3. Monetary value of non-marketed goods

kikkiki TENVIRONMENHAPPINESS ,,, '' x

k,ik,ikk,ik,i εYδTENVIRONMENγβαHAPPINESS x

δγ

Y/HAPPINESS

TENVIRONMEN/HAPPINESSMRS

ik,i

kk,i

3. First resultsTABLE 4. Happiness regressions

Model 1 Model 2 Model 3 Model 4 Model 5 Constant 7.01 (9.17)*** 7.12 (9.11)*** 6.80 (8.62)*** 6.16 (7.72)*** 5.48 (2.17)*** Age -0.06 (-4.00)*** -0.06 (-3.81)*** -0.06 (-3.81)*** -0.06 (-3.76)*** -0.06 (-3.98)*** Age*age 0.001 (3.63)*** 0.001 (3.33)*** 0.001 (3.43)*** 0.001 (3.33)*** 0.001 (3.51)*** Education 0.2(3.26)*** 0.09 (3.08)*** 0.09 (3.02)*** 0.09 (3.01)*** 0.10 (3.13)*** Educ*Educ -0.003 (-2.18)** -0.003 (-2.07)** -0.002 (-1.94)* -0.002 (-1.93)* -0.003 (-2.07)* Income 0.039 (2.14)** 0.031 (1.97)** 0.031 (2.01)** 0.029 (1.96)** 0.032 (1.98)** Gender Male 0.045 (0.54) 0.05 (0.56) 0.04 (0.51) 0.05 (0.56) 0.04 (0.47) Health Very good

Fair Bad Very bad

0.57 (5.42)*** -0.37 (-3.91)*** -1.10 (-7.41)*** -1.22 (-3.03)***

0.63 (5.86)*** -0.36 (-3.57)*** -1.03 (-6.36)*** -1.12 (-2.62)***

0.63 (6.02)*** -0.37 (-3.66)*** -1.05 (-6.49)*** -1.11 (-2.62)***

0.63 (6.02)*** -0.37 (-3.66)*** -1.05 (-6.49)*** -1.11 (-2.62)***

0.99 (7.75)*** -0.36 (-3.58)*** -0.68 (-4.15)*** -1.75 (-1.74)*

Marital status Married Civil partnership Separated Divorced Widowed Never married, never civil pat.

1.21 (1.99)** 0.99 (1.54) 0.081 (0.12) 0.407 (0.64) 0.42 (0.67) 0.48 (0.77)

1.23 (2.03)** 0.96 (1.50) 0.06 (0.1) 0.4 (0.62) 0.39 (0.63) 0.52 (0.85)

1.31 (2.16)** 1.02 (1.60) 0.14 (0.22) 0.47 (0.74) 0.47 (0.74) 0.61 (0.99)

1.31 (2.16)** 1.02 (1.60) 0.14 (0.22) 0.47 (0.74) 0.47 (0.74) 0.61 (0.99)

1.25 (2.05)** 0.95 (1.49) 0.08 (0.12) 0.38 (0.59) 0.41 (0.65) 0.53 (0.87)

Family size 0.046 (1.34) 0.07 (2.00)** 0.08 (2.10)** 0.08 (2.10)** 0.07 (1.82)* Main activity Paid work

Education Unemployed, looking Sick, disabled Retired Housework

0.13 (0.78) 0.18 (0.78)

-0.60 (-2.62)*** -0.19 (-0.61) 0.44 (2.29)** 0.20 (1.23)

0.1 (0.57) 0.13 (0.55)

-0.6 (-2.53)*** -0.06 (-0.17) 0.49 (2.49)** 0.22 (1.28)

0.12 (0.71) 0.14 (0.55)

-0.57 (-2.41)** -0.026 (-0.08) 0.50 (2.54)** 0.25 (1.50)

0.12 (0.71) 0.14 (0.55)

-0.57 (-2.41)** -0.026 (-0.08) 0.50 (2.54)** 0.25 (1.50)

0.14 (0.65) 0.16 (0.59)

-0.54 (-2.06)** -0.02 (-0.05) 0.53 (2.38)** 0.25 (1.29)

Macroeconomic regional variables

Per capita GDP Unemployment rate

0.00(0.98) 0.026 (1.43)

0.00 (0.78) 0.01 (0.27)

Climate variables January min temp. January max temp. July min temp. July max temp. January prec. July prec.

-0.001 (-0.88)

-0.01 (-2.70)***

-0.05 (-0.28) 0.21 (0.86)

-0.26 (-1.89)* 0.093 (1.16) -0.003 (-0.62) -0.005 (-0.49)

Pollution variables

NO2 PM10 CO2

0.01 (1.27) -0.003 (-2.36)** -0.16 (-2.61)***

0.01 (1.14) -0.003 (-1.89)* -0.128 (-1.40)

0.02 (1.27) -0.003 (-1.66) 0.123 (0.94)

0.03 (1.36) -0.006 (-1.83)* -0.27 (-1.69)*

Coast 0.24 (2.01)** 0.15 (1.15) 0.07 (0.20) Population dens. -0.00 (-0.17) -0.002 (-2.29)** -0.02 (-1.47) Adjusted R2 0.194 0.202 0.207 0.208 0.208 Monetary value Pollution (PM10)

Climate (July prec) Coast

325 euros 325 euros --

26,000 euros

336 euros 1,000 euros 16,250 euros

609 euros 500 euros

8,000 euros

4. Concluding remarks

- Increasing number of papers relating subjective well-being with environmental variables

- Climate and pollution variables help explaining regional differences in subjective well-being

- Negative significant impact of pollution variables (PM10 concentration)- Other geographical variables (“coast” dummy variable)- Multicolinearity among climate variables- Negative impact of higher July minimum temperature

- Usual results of individual socio-economic variables on happiness: health, income, being unemployed, age...

- Non significant effects of regional macroeconomic variables (per capita GDP, unemployment rate) on individual happiness

- Monetary value of climate and pollution variables

5. Future research

- Multilevel modelling approach

- Extend the analysis to the European regions

THANK YOU