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 objectives
Objectives:
- 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 mg/m3)
3. Descriptive statistics
TABLE 3. Happiness in Spanish regions, 2008 data
N
Mean
Std. Deviation
Minimun
Maximum
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
105
7.88
1.57
0
10
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
43
7.44
1.28
5
10
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
2565
7.63
1.63
0
10
Galicia
País Vasco
Comunidad Foral de
Navarra
Islas Baleares
Andalucía
Total
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, Cantabria
La Rioja, Canarias
3. Descriptive statistics
Galicia
Principality of
Asturias
Cantabria
Basque Country
Navarra
La Rioja
Aragon
Madrid
Castilla - Leon
Castilla La
Mancha
Extremadura
Catalonia
Valencia
Balearic Islands
Andalucia
Murcia
Canary Islands
Spain (average)
N
Happiness
Temperature July
7.41
7.57
Temperature
January
8.00
5.91
499
53
Precipitation
July
22.86
36.55
NO2
PM10
CO2
17.82
16.79
Precipitation
January
100.74
83.99
23
105
26
8
50
272
114
80
7.96
7.88
7.46
6.88
7.72
7.65
7.14
8.00
55
527
181
43
402
60
67
2565
7.38
7.60
7.69
7.44
8.10
7.43
7.07
7.63
1.00
2.44
Population
density
93.84
101.79
Regional
income
20,546
22,427
34
37
107
31
7.2
7.51
6.08
4.43
4.85
6.67
5.03
6.47
16.95
17.67
20.08
18.77
20.90
23.38
20.01
23.97
55.47
32.92
25.97
32.12
32.74
50.8
55.83
44.79
41.69
52.09
56.48
48.61
55.97
4.35
19.15
7.03
29
33
27
24
49
61
28
24
18
33
35
29
175
77
146
100
1.35
3.16
0.77
0.74
0.44
3.36
0.42
0.32
109.46
298.38
59.73
62.98
27.80
781.77
27.14
25.73
24,222
31,791
30,296
25,631
26,093
30,928
23,206
18,425
9.01
6.43
8.93
10.42
9.77
9.13
15.51
7.82
25.61
20.54
24.04
24.1
25.5
24.54
21.13
21.47
69.54
22.37
32.41
40.06
48.31
17.77
26.21
51.16
0.72
62.36
11.56
29.64
0.11
0.50
0.34
25.21
12
55
50
33
34
18
26
40.81
17
100
-15
64
47
122
86.14
0.22
1.69
1.40
2.18
0.66
1.10
2.30
1.39
26.34
228.68
216.21
213.72
93.63
126.09
278.82
211.07
16,845
27,897
21,392
25,706
18,384
19,694
20,827
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
HAPPINESSi ,k     ' xi ,k   ' ENVIRONMENTk   i ,k
3. Monetary value of non-marketed goods
HAPPINESSi , k  α  βx i , k  γENVIRONMENTk  δYi , k  εi , k
MRS 
HAPPINESS i , k / ENVIRONMENTk
HAPPINESS i , k / Yi

γ
δ
3. First results
TABLE 4. Happiness regressions
Constant
Age
Age*age
Education
Educ*Educ
Income
Gender
Health
Marital status
Family size
Main activity
Macroeconomic
regional variables
Climate variables
Pollution
variables
Coast
Population dens.
Adjusted R2
Monetary value
Male
Very good
Fair
Bad
Very bad
Married
Civil partnership
Separated
Divorced
Widowed
Never married,
never civil pat.
Paid work
Education
Unemployed,
looking
Sick, disabled
Retired
Housework
Per capita GDP
Unemployment rate
January min temp.
January max temp.
July min temp.
July max temp.
January prec.
July prec.
NO2
PM10
CO2
Model 1
7.01 (9.17)***
-0.06 (-4.00)***
0.001 (3.63)***
0.2(3.26)***
-0.003 (-2.18)**
0.039 (2.14)**
0.045 (0.54)
0.57 (5.42)***
-0.37 (-3.91)***
-1.10 (-7.41)***
-1.22 (-3.03)***
1.21 (1.99)**
0.99 (1.54)
0.081 (0.12)
0.407 (0.64)
0.42 (0.67)
0.48 (0.77)
Model 2
7.12 (9.11)***
-0.06 (-3.81)***
0.001 (3.33)***
0.09 (3.08)***
-0.003 (-2.07)**
0.031 (1.97)**
0.05 (0.56)
0.63 (5.86)***
-0.36 (-3.57)***
-1.03 (-6.36)***
-1.12 (-2.62)***
1.23 (2.03)**
0.96 (1.50)
0.06 (0.1)
0.4 (0.62)
0.39 (0.63)
0.52 (0.85)
Model 3
6.80 (8.62)***
-0.06 (-3.81)***
0.001 (3.43)***
0.09 (3.02)***
-0.002 (-1.94)*
0.031 (2.01)**
0.04 (0.51)
0.63 (6.02)***
-0.37 (-3.66)***
-1.05 (-6.49)***
-1.11 (-2.62)***
1.31 (2.16)**
1.02 (1.60)
0.14 (0.22)
0.47 (0.74)
0.47 (0.74)
0.61 (0.99)
Model 4
6.16 (7.72)***
-0.06 (-3.76)***
0.001 (3.33)***
0.09 (3.01)***
-0.002 (-1.93)*
0.029 (1.96)**
0.05 (0.56)
0.63 (6.02)***
-0.37 (-3.66)***
-1.05 (-6.49)***
-1.11 (-2.62)***
1.31 (2.16)**
1.02 (1.60)
0.14 (0.22)
0.47 (0.74)
0.47 (0.74)
0.61 (0.99)
Model 5
5.48 (2.17)***
-0.06 (-3.98)***
0.001 (3.51)***
0.10 (3.13)***
-0.003 (-2.07)*
0.032 (1.98)**
0.04 (0.47)
0.99 (7.75)***
-0.36 (-3.58)***
-0.68 (-4.15)***
-1.75 (-1.74)*
1.25 (2.05)**
0.95 (1.49)
0.08 (0.12)
0.38 (0.59)
0.41 (0.65)
0.53 (0.87)
0.046 (1.34)
0.13 (0.78)
0.18 (0.78)
-0.60 (-2.62)***
-0.19 (-0.61)
0.44 (2.29)**
0.20 (1.23)
0.07 (2.00)**
0.1 (0.57)
0.13 (0.55)
-0.6 (-2.53)***
-0.06 (-0.17)
0.49 (2.49)**
0.22 (1.28)
0.08 (2.10)**
0.12 (0.71)
0.14 (0.55)
-0.57 (-2.41)**
-0.026 (-0.08)
0.50 (2.54)**
0.25 (1.50)
0.08 (2.10)**
0.12 (0.71)
0.14 (0.55)
-0.57 (-2.41)**
-0.026 (-0.08)
0.50 (2.54)**
0.25 (1.50)
0.07 (1.82)*
0.14 (0.65)
0.16 (0.59)
-0.54 (-2.06)**
-0.02 (-0.05)
0.53 (2.38)**
0.25 (1.29)
0.00(0.98)
0.026 (1.43)
0.00 (0.78)
0.01 (0.27)
0.01 (1.27)
-0.003 (-2.36)**
-0.16 (-2.61)***
0.194
Pollution (PM10)
Climate (July prec)
Coast
0.202
325 euros
0.01 (1.14)
-0.003 (-1.89)*
-0.128 (-1.40)
0.24 (2.01)**
-0.00 (-0.17)
0.207
325 euros
-26,000 euros
-0.001 (-0.88)
-0.01 (-2.70)***
0.02 (1.27)
-0.003 (-1.66)
0.123 (0.94)
0.15 (1.15)
-0.002 (-2.29)**
0.208
336 euros
1,000 euros
16,250 euros
-0.05 (-0.28)
0.21 (0.86)
-0.26 (-1.89)*
0.093 (1.16)
-0.003 (-0.62)
-0.005 (-0.49)
0.03 (1.36)
-0.006 (-1.83)*
-0.27 (-1.69)*
0.07 (0.20)
-0.02 (-1.47)
0.208
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