Social statistics by industry - Introducing the social dimension into environmental accounts Maja Larsson & Martin Villner
Dec 14, 2015
Social statistics by industry
- Introducing the social dimension into environmental accounts
Maja Larsson & Martin Villner
What I will talk about today
● Why there is a need for a social dimension
● Method behind – the survey of living conditions in Sweden
● Some results and different ways of analysing data
● Future - other possible surveys to use
WHY?
● Serve as an information system for sustainable development - also the social dimension
● Policy interventions have social effects
● Some environmental concerns are also social, for ex. health aspects of chemical use and air pollution
Therefore need more social information in the SEEA
Purpose of the project
● To choose suitable data and present it in a form that is comparable to the environmental and economic data
● To discuss with the data providers what aggregation level and data quality is possible
● To complement the environmental accounts with also the social dimension of sustainable development
4 Areas
● Working environment (7 indicators)
● Health (7 indicators)
● Financial problems and material assets (5 indicators)
● Social networks and political resources (7 indicators)
Mentally strenuous work
01020304050607080
Agriculture, forestry, fishery (1-5)
Manufacturing, mining (10-37)
Electricity, gas, water (40, 41)
Construction (45)
Wholesale, retail trade (50-52)
Hotels and restaurants (55)
Transports (60-64)
Finance (65-67)
Real estate activities (70)
Renting, business service (71-74)
Public administration (75, 99)
Education (80)
Health service (85)
Ohter services (90-95)
All industry (1-99)
%0 10 20 30 40 50 60 70 80
Agriculture, forestry, fishery (1-5)
Manufacturing, mining (10-37)
Electricity, gas, water (40, 41)
Construction (45)
Wholesale, retail trade (50-52)
Hotels and restaurants (55)
Transports (60-64)
Finance (65-67)
Real estate activities (70)
Renting, business service (71-74)
Public administration (75, 99)
Education (80)
Health service (85)
Ohter services (90-95)
All industry (1-99)
%
Accidents at work
0 2 4 6 8 10 12 14
Agriculture, forestry, fishery (1-5)
Manufacturing, mining (10-37)
Electricity, gas, water (40, 41)
Construction (45)
Wholesale, retail trade (50-52)
Hotels and restaurants (55)
Transports (60-64)
Finance (65-67)
Real estate activities (70)
Renting, business service (71-74)
Public administration (75, 99)
Education (80)
Health service (85)
Ohter services (90-95)
All industry (1-99)
%
Workers
Salaried employees
Self-employed, farmers
Severe problems because of long illness
Women
0
2
4
6
8
10
12
14
16
18
20
88/90 91/93 94/96 97/99 00/02
P ercent
Men
0
2
4
6
8
10
12
14
16
18
20
88/90 91/93 94/96 97/99 00/02
P ercent
Agriculture, forestry, fishery (1-5)
Manufacturing, mining (10-37)
Construction (45)
Wholesale, hotels, restaur. (50-52, 55)Transports (60-64)
Research, education, healthservice (73, 80, 85)All industry (1-99)
Obesity
02468101214
Agriculture, forestry, fishery (1-5)
Manufacturing, mining (10-37)
Energy production (40, 41)
Construction (45)
Wholesale, retail trade (50-52)
Hotels and restaurants (55)
Transports (60-64)
Finance (65-67)
Real estate activities (70)
Renting, business service (71-74)
Public administration (75, 99)
Education (80)
Health service (85)
Ohter services (90-95)
All industry (1-99)
Unemployed
All individuals, aged 16-64
%
97/99 00/02Women
Data missing
Data missing
0 2 4 6 8 10 12 14
Agriculture, forestry, fishery (1-5)
Manufacturing, mining (10-37)
Energy production (40, 41)
Construction (45)
Wholesale, retail trade (50-52)
Hotels and restaurants (55)
Transports (60-64)
Finance (65-67)
Real estate activities (70)
Renting, business service (71-74)
Public administration (75, 99)
Education (80)
Health service (85)
Ohter services (90-95)
All industry (1-99)
Unemployed
All individuals, aged 16-64
%
97/99 00/02 Men
No cash reserve of SEK 13 000Women
0
2
4
6
8
10
12
14
16
18
20
22
88/90 91/93 94/96 97/99 00/02
PercentMen
0
2
4
6
8
10
12
14
16
18
20
22
88/90 91/93 94/96 97/99 00/02
P ercent
Agriculture, forestry, fishery (1-5)
Manufacturing, mining (10-37)
Construction (45)
Wholesale, hotels, restaur. (50-52, 55)
Transports (60-64)
Research, education, health service (73, 80, 85)
All industry (1-99)
No close friendWomen
051015202530
Agriculture, forestry, fishery (1-5)
Manufacturing, mining (10-37)
Energy production (40, 41)
Construction (45)
Wholesale, retail trade (50-52)
Hotels and restaurants (55)
Transports (60-64)
Finance (65-67)
Real estate activities (70)
Renting, business service (71-74)
P ublic administration (75, 99)
Education (80)
Health service (85)
Ohter services (90-95)
All industry (1-99)
Unemployed
All individuals, aged 16-64
%
Men
0 5 10 15 20 25 30
Agriculture, forestry, fishery (1-5)
Manufacturing, mining (10-37)
Electricity, gas, water (40, 41)
Construction (45)
Wholesale, retail trade (50-52)
Hotels and restaurants (55)
Transports (60-64)
Finance (65-67)
Real estate activities (70)
Renting, business service (71-74)
P ublic administration (75, 99)
Education (80)
Health service (85)
Other services (90-95)
All industry (1-99)
Unemployed
All individuals, aged 16-64
%
Lack the ability to appeal against a public authority
0 5 10 15 20 25 30 35 40 45
Agriculture, forestry, fishery (1-5)
Manufacturing, mining (10-37)
Electricity, gas, water (40, 41)
Construction (45)
Wholesale, retail trade (50-52)
Hotels and restaurants (55)
Transports (60-64)
Finance (65-67)
Real estate activities (70)
Renting, business service (71-74)
P ublic administration (75, 99)
Education (80)
Health service (85)
Other services (90-95)
All industry (1-99)
Unemployed
All individuals, aged 16-64
%
Workers
Salariedemployees
Self-employed,farmers
Other ways of presenting data
● Environmental profiles
● Decoupling
● By level of education
● By region
● By age
Profile – the construction industry
02468101214
Production value
Value added
Employment
Accidents at w ork, men
Accidents at w ork, w omen
Bad state of health, men
Bad state of health, w omen
Economic crisis, men
Economic crisis, w omen
Member of a trade union, men
Member of a trade union, w omen
All fuels
Biomass
El. and district heating
CO2
SO2
NOx
%
Decoupling - hectic/monotonous work
All industry
60
70
80
90
100
110
120
130
140
150
160
170
180
190
91/93 94/96 97/99 00/02
Index =1991/93
Value added
Hectic/monotonous work, women
Hectic/monotonous work, men
Manufacturing, mining industry
60
70
80
90
100
110
120
130
140
150
160
170
180
190
91/93 94/96 97/99 00/02
Index = 1991/93
By region – economic crisis
0 10 20 30
Agriculture, forestry, fishery (1-5)
Manufacturing, mining (10-37)
Electricity, gas, water (40, 41)
Construction (45)
Wholesale, retail trade (50-52)
Hotels and restaurants (55)
Transports (60-64)
Finance (65-67)
Real estate activities (70)
Renting etc (71-74)
Public administration (75, 99)
Education (80)
Health service (85)
Other services (90-95)
All industry (1-99)
Percent
Stockholm,Gotherburg, Malmö
Other largemunicipalities andsouthern andcentral Sweden
Northern denselyand sparselypopulated areas