OSIPP Discussion Paper : DP-2007-E-003

The Socioeconomic Determinants of Individual
Environmental Concern: Evidence from Shanghai Data
April 16, 2007
Junyi Shena and Tatsuyoshi Saijob
a Assistant Professor, OSIPP, Osaka University
b Professor, ISER, Osaka University【キーワード】C25, C81, Q59, Socioeconomic determinants, Environmental Concern,
Ordered Probit Model, Chinese【要約】This study examines the influence of socioeconomic characteristics on elevenmeasures of environmental concern by applying a pooled sample of 1200 individuals in
Shanghai, China. Previous studies, which made efforts to explain environmental
concern as a function of social structure, suggest that there are traditionally fivehypotheses (the age, gender, social class, residence, and political hypotheses) for
socioeconomic determinants, which are associated with individual environmental
concerns. Unlike those methodologies adopted in many previous studies, we apply anordered probit model to test three hypotheses (the age, gender, and social classhypotheses) in this study. As a result, high income and high education level are found to
be positively related to environmental concern as expected. However, we find that incontrast to most of the existing studies, the marginal effect of age on the probability of
being environmentally concerned is positive in several measures, implying that theolder are more concerned about the environment than the younger. In addition, weakevidences indicate that women are less concerned about the environment than men.
Other socioeconomic characteristics such as employment status and household size are
not significant in most of the environmental concern measures we defined.

The authors would like to appreciate the financial support of Japanese Ministry of theEnvironment through the project numbered as H-062. Comments and suggestions on
the survey issues from Yoshiyuki Shimoda, Osamu Saito, Yugo Yamamoto, and Kenju
Akai are greatly appreciated. All the views expressed in this paper and any errors are
the sole responsibility of the authors. Correspondence to: Junyi Shen, Osaka School ofInternational Public Policy (OSIPP), Osaka University, 1-31 Machikaneyama, Toyonaka,
Osaka 560-0043, Japan. E-mail: junyi@osipp.osaka-u.ac.jp
11. Introduction
Over the past three decades, it has been indicated that the protection of the naturalenvironment has become not only a major social and political issue but also an
important assignment in academic research. For many years, both the environmental
conservation professionals and the social science academics with interests inenvironmental conservation have commonly recognized that personal and social
awareness, and subsequent concern regarding the quality of the natural environment,
are at the heart of environmental protection (Hackett 1993). Although several
researchers have attempted to document the changing levels of environmental concern
among the general public, the central issue these researchers increasingly addressed
has been to determine the social bases of concern for environmental quality (Van Liere
and Dunlap 1980). The link between socioeconomic characteristics and environmental
concern has been explored by several researchers. Of interest with respect to thepresent study, the following studies examined the relationships of environmental
concern with: the gender (Arcury and Christianson 1990; Davidson and Freudenburg
1996; Dietz et al. 2002; Hunter et al. 2004; Mohai 1992; Schahn and Hotzer 1990; Stern
and Dietz 1993); age (Eagly and Kulesa 1997; Howell and Laska 1992; Lyons andBreakwell 1994; Nord et al. 1998); income (Adeola 1994; Antil 1984; Arcury andCristianson 1990; Buttel and Flinn 1974; Koenig 1975; Newell and Green 1997;
Samdahl and Robertson 1989); education (Arcury and Cristianson 1990; Howell and
Laska 1992; Jones and Dunlap 1992; Schahn and Hotzer 1990; Scott and Willits 1994);
and household size (Oskamp et al. 1991; Poortinga et al. 2004). They are to identify
what type of individual is most concerned about environmental issues. However, theprevious studies have not exhibited a consistent result in explaining socioeconomic
determinants of individual environmental concern. Given the large number of paststudies, the reasons of such mixed results seem to be their sample survey techniques,empirical methodologies, and measures of environmental concern.
The present study aims to investigate the socioeconomic determinants of individual
environmental concern in more details. The main contribution of this study is threefold.
First, we define eleven environmental concern indices covering general environmental
problem as well as specific environmental issues and pro-environmental behaviors. We
believe that rather than examining solely the environmental concern in general, adding
concern about some specific issues and attitude measures also in the present study
would certainly help us learn more about a respondent’s true preference towards
environmental protection. Second, we apply the data from a recent survey in Shanghai,
China. The previous studies focus mainly those individuals in developed countries
especially in the U.S. Considering the well known fact of huge differences between
China and most western countries, not only on political institutions but also on people’sviews in various social problems, it is worthwhile and necessary to study the social2bases of individual environmental concern in this country. However, there has been noliterature published to date that has examined this issue on Chinese. This blank spacemust be filled. In addition, we believe that our study based on Chinese individuals
would make international comparison between Chinese and their western counterparts
possible, which as a result enhances the studies in this field. Third, different from mostprevious studies which applied analysis of variance (ANOVA), correlation analysis or
factor analysis, we adopt an ordered probit model (ORM) in our empirical study due tothe characteristics of our measures for environmental concern. Through the ordered
probit model, we are able to not only identify which socioeconomic factor determines
individual environmental concern, but also discern which factor plays the mostimportant role through predicting each factor’s marginal effect on the probability being
the most and/or least environmentally concerned individual.
Our empirical results are somewhat different from several previous evidences,
especially in terms of the age hypothesis (discussed below). We find that in somemeasures the age is negatively related to the choice of concern as seen in previous
studies, however, in some other measures associated with living environmental issues
the younger seems to concern less about the environment than the older. In addition,strong evidences indicate that income and education level significantly affect the degreeof individual environmental concern. Meanwhile, although the evidence may besomewhat weak, men seem to be more environmentally concerned than women. Othersocioeconomic factors such as employment status and household size are not significant
in most of the measures.
The rest of the paper proceeds as follows. In Section 2, we review the hypotheses
presented in the previous studies. In Section 3, we describe the data issue. We introduce
the model specification in Section 4, and report empirical results in Section 5. The
limitations of this study, future implication as well as concluding comments areprovided in the final section.

2. Review of Hypotheses
Van Liere and Dunlap (1980) and Fransson and Gärling (1999) provide detailed review
on five hypotheses (the age, gender, social class, residence, and political hypotheses)
about socioeconomic determinants of individual environmental concern. In this section,a brief outline of these hypotheses as well as related empirical findings is presented.

The age hypothesis
The age hypothesis suggested by Van Liere and Dunlap (1980) and Fransson and
Gärling (1999) states that younger people tend to concern more about environmental

3

quality than elders. The majority of previous studies report that the age is negatively
correlated with different environmental concern measures they applied, which could beviewed as supportive of the age hypothesis.

The gender hypothesis
The previous studies have been inconclusive about the effects of gender on individual
environmental concern. Some studies such as Arbuthnot and Lingg (1975) and Arcury
and Christianson (1990) indicate that women are less environmentally concerned thanmen, while other studies, for example Schahn and Holzer (1990), Mohai (1992) and
Hunter et al. (2004), suggest that women do express greater concern for environment
than men. These mixed results imply that there is no agreement on the direction of therelationship between gender and individual environmental concern.

The social class hypothesis
The social class hypothesis states that education and income is positively correlatedwith environmental concern. One explanation for this hypothesis is based on Maslow’s
hierarchy of needs theory (Maslow 1970). This hypothesis rests on the assumption thatconcern about environmental quality has the property of luxury goods which can be
indulged only after more basic material needs such as adequate food, shelter, andeconomic security are met (Van Liere and Dunlap 1980). Support for a positive
correlation between education and environmental concern has been found in several
studies (e.g. Arcury and Christianson 1990; Howell and Laska 1992; Schahn and Hotzer
1990; Scott and Willits 1994). However, concerning the relationship between income andenvironmental concern, the findings are mixed. For example, one study reports that
income is negatively related to the perceptions of environmental problems, as well as
the support for environmental regulations and ecological behavior (i.e. Samdahl andRobertson 1989), while another study suggests that income may be positively related toconcern about the environment (i.e. Buttel and Flinn 1974). Moreover, most studies
indicate that income is not predictive of environmental concern (e.g. Adeola 1994; Antil
1984; Koenig 1975, etc.).

The residence hypothesis
The residence hypothesis states that urban residents are more likely to beenvironmentally concerned than rural residents. A possible explanation for thisdifference is given in Fransson and Gärling (1999) that urban residents are more
exposed to the signs of environmental deterioration such as air pollution. Thishypothesis receives support in several studies (e.g. Arcury and Christianson 1990;

4

Buttel and Flinn 1974; Howell and Laska 1992, etc.).

The political hypothesis
The political hypothesis assumes that in the U.S., liberals are more environmentallyconcerned than conservatives. Three possible reasons for this assumption are noted in
Dunlap (1975). First, environmental reforms generally are opposed by business andindustry which typically support conservatives. Second, an extension of government
activities and regulations entailed by environmental reforms is generally opposed byconservatives. Third, environmental reforms often require innovative action which is
opposed by conservatives. The evidences supporting this hypothesis can be found inseveral studies such as Dunlap (1975), Hine and Gifford (1991), Samdahl and Robertson(1989), Howell and Laska (1992), and Daneshvary et al. (1998). However, it has beenshown that the relationship between environmental concern and political ideology
decreased in the 1980s (Howell and Laska 1992).

3. The Data

Data Collection
The data used in this study are drawn from a field survey on individual’s environmental
concern in Shanghai, China. The survey was conducted by two professional marketingfirms at the beginning of November 2006. One firm called Nikkei Research was incharge of collecting 600 observations from randomly selected Shanghai residents
through face-to-face interviews, while another firm called Searchina Research
conducted the survey through Internet and collected another 600 valid samples. Bothdata sets had the same contents, which comprised of a series of questions on different
environmental concern measures, attitudes towards tradeoff between environmental
consideration and other factors, and information on most common socioeconomic
characteristics such as gender, age, education level, occupation, annual householdincome, and household size. Table 1 summarizes the socioeconomic characteristics ofthese two samples and pooled sample. Since our main purpose is to examine thesocioeconomic determinants of environmental concern, we pool these two data sets inthe present study despite slight differences found in between the results of theinterviews and Internet samples as shown in the table.

Measures of environmental concern indices
A number of questions are used in the questionnaire to illustrate the different measures5

Table 1 Socioeconomic characteristics of the sample
Characteristics
Pooledn%Gender
Male
583
48.58
Female617
51.42
Age (years)
Below 20
22
1.83
20-29
521
43.42
30-39
245
20.42
40-49
140
11.67
50-59
145
12.08
Over 60
127
10.58
Education level
Elementary school
Junior high school
Senior high school
Technical degree
Undergraduate degree
Graduate degree
Household annual income< 30,000 RMB
30,000-49,999 RMB
50,000-69,999 RMB
70,000-99,999 RMB
100,000-149,999 RMB
150,000-199,999 RMB>200,000 RMBHousehold size
1 person
2 persons
3 persons
4 persons
5 persons
Above 6 persons
Occupation
Fulltime-employed
Self-employed
Part time
RetiredStudent
Unemployed
Total observations

Interview

Internet
%

n

%

n

300
300

50.00
50.00

283
317

47.17
52.83

0
120
120
120
120
120

0.00
20.00
20.00
20.00
20.00
20.00

22
401
125
20
25
7

3.67
66.83
20.83
3.33
4.17
1.17

8
97
202
78
761
54

0.67
8.08
16.83
6.50
63.42
4.50

8
93
168
43
273
15

1.33
15.50
28.00
7.17
45.50
2.50

0
4
34
35
488
39

0.00
0.67
5.67
5.83
81.33
6.50

143
240
244
246
191
76
60

11.92
20.00
20.33
20.50
15.92
6.33
5.00

99
163
129
100
70
21
18

16.50
27.17
21.50
16.67
11.67
3.50
3.00

44
77
115
146
121
55
42

7.33
12.83
19.17
24.33
20.17
9.17
7.00

57
239
635
149
103
17

4.75
19.92
52.92
12.42
8.58
1.42

30
117
313
87
42
11

5.00
19.50
52.17
14.50
7.00
1.83

27
122
322
62
61
6

4.50
20.33
53.67
10.33
10.17
1.00

872
43
26
147
98
14

72.67
3.58
2.17
12.25
8.17
1.17

350
42
20
145
36
7

58.33
7.00
3.33
24.17
6.00
1.17

522
1
6
2
62
7

87.00
0.17
1.00
0.33
10.33
1.17

1200

100

600

100

600

100

of individual environmental concern (see Table 2). We gauge three types of measures.
The first type is to examine the level of the respondent’s concern about generalenvironmental issue (marked as A in Table 2), which is measured with a single question:

6

Table 2 Summary of environmental concern indices
Description
A. Concern about general environmental problem:
4= concern; 3=somewhat concern; 2=neither concern nor unconcern;
1=not quite concern; 0=not concern
B. Concern about global warming problem:
4= concern; 3=somewhat concern; 2=neither concern nor unconcern;
1=not quite concern; 0=not concern
C. Concern about cross-boundary pollution and acid rain problem:
4= concern; 3=somewhat concern; 2=neither concern nor unconcern;
1=not quite concern; 0=not concern
D. Concern about air/water/soil pollution problem:
4=concern; 3=somewhat concern; 2=neither concern nor unconcern;
1=not quite concern; 0=not concern at all
E. Concern about urban energy problem:
4= concern; 3=somewhat concern; 2=neither concern nor unconcern;
1=not quite concern; 0=not concern
F. Concern about green land and ecological problems:
4= concern; 3=somewhat concern; 2=neither concern nor unconcern;
1=not quite concern; 0=not concern
G. Concern about the effect of harmful substances on health:4= concern; 3=somewhat concern; 2=neither concern nor unconcern;
1=not quite concern; 0=not concern
H. Concern about disposal, reduction and recycling of waste:
4= concern; 3=somewhat concern; 2=neither concern nor unconcern;
1=not quite concern; 0=not concern
I. Concern about living environmental problems such as noise/odor:
4= concern; 3=somewhat concern; 2=neither concern nor unconcern;
1=not quite concern; 0=not concern
J. Tradeoff between life convenience and environmental conservation:
3=environmental conservation always weighs more; 2=conserve theenvironment even if sacrificing life convenience to some extent;
1=conserve the environment without sacrificing life convenience;0=life convenience always has higher priority
K. Rank of environmental consideration when buying electronics:
4=Regard its environmental impact as the first issue to consider;
3=Regard its environmental impact as the second issue to consider;
2=Regard its environmental impact as the third issue to consider;
1=Regard its environmental impact as the fourth issue to consider;
0=Consider its environmental impact out of the first four issues

Mean

S.D.

3.468

0.675

3.219

0.858

3.003

0.995

3.228

0.868

3.113

0.899

3.361

0.821

3.557

0.761

3.343

0.795

3.578

0.714

1.753

0.787

1.810

0.791

“Do you care about the environmental problems”. The answers for this question arecoded as five scale points (‘concern’ (1), ‘somewhat concern’ (2), ‘neither concern nor
unconcern’ (3), ‘not quite concern’ (4) and ‘not concern’ (5)).1
1 In our empirical analysis, we manipulate the answers chosen by the respondents as 4

denoting ‘concern’, 3 denoting ‘somewhat concern’, 2 denoting ‘neither concern nor
unconcern’, 1 denoting ‘not quite concern’ and 0 denoting ‘not concern’. Note that this7

The second type of measures, which includes eight indices (from B to I in Table 2),
aims to indicate individual’s concern about specific environmental issues ranged fromlocal pollution problem to global warming. Five scale points that are coded as same as
those for general environmental issue is also provided as the answers for these specificenvironmental issues. One previous study (i.e. Wall 1995) compares two measures ofenvironmental concern (concern about the environment in general and concern about aspecific, local environmental issue) and reports that measuring reaction to a specific,
local environmental issue and posing economic tradeoffs as a consequence do not resultin substantially improved explanatory ability, or more pronounced class differences. In
contrast, a recent study (Poortinga et al. 2004) suggests that concern about different
specific environmental issues is found to have correlation with different socioeconomic
characteristics. In the present study, we believe that it will be more helpful to examine
not only the concern about the environment in general, but also to add concern aboutsome specific issues in order to learn more about the respondent’s true preference
towards environmental protection.
The third type of measures, which comprises of two indices, is the attitude towards
pro-environmental behavior (see J and K in table 2). The first index of this type istermed as tradeoff between life convenience and environmental conservation, while thesecond one is measured by ranking the consideration about environmental impacts
when purchasing electronics. The former is asked as a simple question: “How do you
consider the issue on environmental conservation in comparison with life convenience”.
The answers for this question are valued by four scale points (‘environmental
conservation weighs more’ (1), ‘conserve environment even if sacrificing life convenience
to some extent’ (2), ‘conserve the environment without sacrificing life convenience’ (3),‘life convenience always has higher priority’ (4)).2 The latter index is asked through fourquestions and rearranged by the authors. The four questions are stated as: “What is themost important issue you consider firstly when purchasing electronics”, “What is themost important issue you consider secondly when purchasing electronics”, “What is themost important issue you consider thirdly when purchasing electronics”, “What is themost important issue you consider fourthly when purchasing electronics”. We provide
nine choices including price, daily running cost, design, function, material used,production method, environmental impact, health impact, and other factors for the
respondents to select. We mark those who chose environmental impact as the first issueof concern as 4, the second issue of concern as 3, the third issue of concern as 2, thefourth issue of concern as 1, and not chose it as the first four issues of concern as 0. The
manipulation does not alter the estimation results and interpretations.
2 The answers are manipulated as 3 for ‘environmental conservation weighs more’, 2 for‘conserve the environment even if sacrificing life convenience to some extent’, 1 for‘conserve the environment without sacrificing life convenience’, and 0 for ‘life
convenience always has higher priority’.
8

Table 3 Summary of independent variables
Variable nameFemaleAge
High_incMiddle_inc
High_edu
Full-time-employed
Self-employed
Part-time-employed
Household_size

Description=1 if female
actual age of the respondent=1 if household annual income of the respondentis larger than 100,000 RMB=1 if household annual income of the respondentis between 50,000 and 99,999 RMB=1 if the respondent’s education level is above
undergraduate degree=1 if the respondent is full-time-employed=1 if the respondent is self-employed=1 if the respondent is part-time employed
Actual household size

Mean
0.514
36.133
0.273

S. D.
0.500
14.412
0.445

0.408

0.492

0.679

0.467

0.726
0.036
0.022
3.044

0.446
0.186
0.146
0.991

above two indices are generated in order to measure the individual’s pro-environmental
attitude, which in turn indicates environmental concern.
As a summary of the above discussions, we develop eleven indices to measure thedegree of individual environmental concern. These measures are to serve as thedependent variables in our empirical analysis conducted below.

Socioeconomic determinants
We provide the description of all the associated socioeconomic characteristics as theindependent variables of our empirical model in Table 3. As introduced in Section 2, inorder to test the age, gender, and social class hypotheses, we include female, age,household annual income, and education level in the model. 3 In addition, we also
examine another two socioeconomic factors (employment status and household size) as
in Witzke and Urfei (2001), to capture other direct and indirect effects of social factors
on the respondent’s degree of environmental concern.
A possible problem on whether there is any co-linearity among the independent
variables is examined by correlations among these socioeconomic characteristics. Table
4 provides the correlation matrix. Due to the low correlation between any two variables
as shown in the table, we believe that the possibility of co-linearity is not a problem inthe present study.

3 Since the sample in the present study is strictly urban, therefore, we cannot test theresidence hypothesis in our empirical analysis. Moreover, due to the political institution
in China, the political hypothesis is also impossible to be tested.
9

Table 4 Correlation matrix of independent variables
Female

Age

High
_inc

Female1.000

Age-0.076

1.000

High_inc0.011-0.1181.000

Middle
_inc

High
_edu

Full
time

Selfemployed

Part
time

Middle_inc

0.017-0.066-0.2081.000

High_edu

0.018-0.228

0.256

0.099

Full time-0.014-0.260

0.145

0.032

0.222

1.000

Self-employed-0.073

0.051

0.003

-0.023-0.117-0.3141.000

Part-time-0.0160.025-0.078-0.031-0.143-0.242-0.0291.000

Household size

0.033

0.030

0.097

0.030

-0.090-0.008-0.022

0.057

Household
size

1.000

1.000

4. Model Specification
As mentioned in the previous section, the respondent’s choice of concern scenario in thesurvey is measured on an ordinal scale. Thus, we may describe the choices of concern as
a discrete variable y i . Following our classification, this variable can take one of thefollowing five values
y i = 0 , if the degree of concern is chosen as ‘Not concern’
y i = 1 , if the degree of concern is chosen as ‘Not quite concern’

y i = 2 , if the degree of concern is chosen as ‘Neither concern nor unconcern’
y i = 3 , if the degree of concern is chosen as ‘Somewhat concern’
y i = 4 , if the degree of concern is chosen as ‘Concern’ 4Then, we assume that the choice of concern is based on a continuous and latentvariable y i* . This latent variable is assumed to be a linear function of all thesocioeconomic variables and given as
for i = 1,2, … , N(1)
y i* = β ′X i + ε iwhere X i is a vector of independent variables, N is the number of respondents, and ε i

4 Measure J (tradeoff between life convenience and environmental conservation) takes

four values as y i = 0 if the answer chosen as ‘life convenience always has higher
priority’, y i = 1 if the answer chosen as ‘conserve the environment without sacrificing
life convenience’, y i = 2 if the answer chosen as ‘conserve the environment even if
sacrificing life convenience to some extent’, and y i = 3 if the answer chosen as‘environmental conservation always weighs more’. Moreover, measure H (ranks ofenvironmental consideration when buying electronics) takes five values as y i = 0 if theelectronics’ environmental impact is not considered as the first four important issues,
y i = 1 if the electronics’ environmental impact is considered as the fourth important
issue, y i = 2 if the electronics’ environmental impact is considered as the third
important issue, y i = 3 if the electronics’ environmental impact is considered as thesecond important issue, and y i = 4 if the electronics’ environmental impact isconsidered as the first important issue.
10

is the error term. Let κ 1 < κ 2 < κ 3 <κ 4 be unknown cut points or threshold parameters,
and define
y i = 0 , if y i* ≤ κ 1
y i = 1 , if κ 1 < y i* ≤ κ 2

y i = 2 , if κ 2 < y i* ≤ κ 3
y i = 3 , if κ 3 < y i* ≤ κ 4
y i = 4 , if y i* > κ 4

(2)
(3)
(4)
(5)
(6)

Note that the four cut points are estimated along with the coefficients of the
independent variables of vector X i . Consequently, the probabilities of y i beingclassified as ‘not concern’, ‘not quite concern’ ‘neither concern nor unconcern’, ‘somewhat
concern’, and ‘concern’ are given byPr( y i = 0) = Pr( β ′X i + ε i ≤ κ 1 )Pr( y i = 1) = Pr(κ 1 < β ′X i + ε i ≤ κ 2 )Pr( y i = 2) = Pr(κ 2 < β ′X i + ε i ≤ κ 3 )Pr( y i = 3) = Pr(κ 3 < β ′X i + ε i ≤ κ 4 )Pr( y i = 4) = Pr( β ′X i + ε i > κ 4 )

(7)
(8)
(9)
(10)
(11)

If we assume that the error term ε i in Eqs. (7)−(11) follows normal distribution, the cut
points κ and coefficients β can be estimated as an ordered probit model (ORM) by
maximum likelihood method (Greene, 2003; Long, 1997; Wooldridge, 2002). However, it
should be noted that when the dependent variable is ordered, estimated parameters do
not reflect the marginal effects of an independent variable on probability. Thus, theinterpretation of the estimated coefficients in the ordered probit model is unclear. For
the sake of this issue, we calculate the associated marginal effects and examine in what
direction those effects are exerted.5

5. Empirical Results
In this section, we report the empirical results concerning the socioeconomic
determinants of individual environmental concern. We estimate the specification forgeneral environmental problem (one index), specific environmental issues (eightindices), and attitude towards pro-environmental behavior (two indices) by using theordered probit model discussed in the previous section. The results are reported inTables 5−15.6
First, concerning the socioeconomic determinants of general environmental concern
For detailed issues on how to calculate the marginal effects on probability in anordered probit model, see Greene (2003), Long (1997), and Wooldridge (2002).
6 The cut points are estimated but not reported here for the sake of saving space. They
are available upon request.
5

11

Table 5 Determinants of concern about general environmental problem
Variable
Coefficient
Marginal effects on probabilities
y=4
y=3
y=2
y=1
**
Female-0.153(-2.21)-0.060
0.039
0.018
0.004
Age
0.007(2.42)**0.003-0.002-0.001
0.000***
High_inc0.273(2.80)
0.106-0.071-0.029 -0.006
Middle_inc
0.062(0.76)
0.025-0.016-0.007 -0.001***
High_edu
0.323(3.82)
0.128-0.078-0.040 -0.009
Full-time-employed-0.136(-1.41)-0.053
0.035
0.015
0.003
Self_employed-0.223(-1.16)-0.089
0.053
0.029
0.007
Part-time-employed -0.060(-0.25)-0.024
0.015
0.007
0.002
Household_size-0.051(-1.42)-0.020
0.013
0.006
0.001

y=0
0.000
0.000
0.000
0.000
-0.001
0.000
0.001
0.000
0.000

Log likelihood-1092.381
2Count R
0.613
Observations
1200
Note: z statistics are in the parentheses. Cut points are not reported here for the sake ofsaving space. Due to its meaninglessness for Pseudo R2 in the ordered probit model, we
report Count R2, which is the proportion of outcomes correctly predicted by the model. ***, **and * indicate 1%, 5%, and 10% significance level, respectively.

as shown in Table 5, we find that gender, age, high income, and high education level are
significant in the choice of different degrees of environmental concern, while middle
income class, employment status, and household size are exhibited to be irrelative toconcern about general environmental problem. We note that the model correctlypredicts 61.3 percent of the choice even though only four of eleven variables havesignificant coefficients. In regards to the hypotheses reviewed in Section 2, social classhypothesis is supported in our model, as expected, in which education and income ispositively correlated with environmental concern. However, this correlation is only withthe outcome of y = 4 and not including y = 3 , i.e. including only ‘concern’ but not‘somewhat concern’ (see the results of marginal effects on probability in Table 5). Age isfound to be positively related to the choice of ‘concern’, which is not supportive of the age
hypothesis. A possible reason for this may be due to the fact that we categorize thedegree of concern into five levels, which is seldom done by the previous studies.
Therefore, it cannot be distinguished whether a respondent measured as anenvironmentally concerned individual in previous studies actually concerns about theenvironment entirely or just somewhat. Indeed, our results indicate that for generalenvironmental issue, a one-year increase in age increases the probability of choosing‘concern’ by 0.003 but decreases the probability of choosing ‘somewhat concern’ by 0.002,
holding all other independent variables at their means. In addition, comparing to male,
female is found to be relatively less concerned about the environment. As for the issue
on which factor is more contributed to individual environmental concern, we compare12Table 6 Determinants of concern about global warming
Variable

Coefficient

FemaleAge
High_incMiddle_inc
High_edu
Full-time-employed
Self_employed
Part-time-employed
Household_size-0.197(-3.00)***Log likelihood
Count R2
Observations
Note: See Table 5.

0.003(2.03)**
0.113(2.22)**0.024(0.30)
0.269(3.25)***-0.141(-1.68)*-0.308(-1.54)
0.253(0.96)
0.013(0.37)

Marginal effects on probabilities
y=4-0.077
0.002
0.045
0.010
0.105
-0.056-0.117
0.101
0.005

y=3
0.030
-0.001-0.018-0.004-0.0370.023
0.032-0.047-0.002y=2
0.029-0.001-0.017-0.004-0.0410.020
0.048-0.035-0.002

y=1
0.014
0.000
-0.008-0.002-0.0200.009
0.027-0.015-0.001

y=0
0.004
0.000
-0.0020.000-0.0070.003
0.010-0.0040.000-1356.595
0.606
1200

Table 7 Determinants of concern about cross-boundary pollution and acid rain problem
Variable
Coefficient
Marginal effects on probabilities
y=4
y=3
y=2
y=1
y=0
**
Female-0.101(-1.99)-0.038
0.006
0.016
0.011
0.005
Age
-0.003(-1.04)-0.001
0.000
0.000
0.000
0.000
High_inc0.213(2.33)**
0.081-0.017-0.033 -0.022-0.009Middle_inc
0.084(1.06)
0.031-0.005-0.013 -0.009-0.004***
High_edu
0.353(4.25)
0.128-0.014-0.055 -0.041-0.019Full-time-employed-0.018(-0.19)-0.006
0.001
0.003
0.002
0.000
Self_employed-0.088(-0.49)-0.032
0.004
0.014
0.010
0.004
Part-time-employed0.489(1.86)*
0.191-0.066-0.071 -0.040-0.014
Household_size
0.002(0.06)
0.001
0.000
0.000
0.000
0.000
Log likelihood
Count R2
Observations
Note: See Table 5.

-1522.830
0.611
1200

the magnitude of marginal effects of each significant variable on the probability ofchoosing category 4, i.e. ‘concern’. We find that education with at least anundergraduate degree, of which the marginal effect’s magnitude is about 20% and 410%
larger than those of high income and age, plays the most important role in determining
individual concern about general environmental problem in Shanghai.
Turning to the issue on concern about specific environmental issues, a number ofresults are found to be inconsistent with those in concern about general environmental

13

Table 8 Determinants of concern about air/water/soil pollution problem
Variable

Coefficient

Marginal effects on probabilities
y=4
y=3
y=2
y=1
-0.023
0.009
0.009
0.004
0.001
0.000
0.000
0.000
0.050
-0.019-0.020 -0.009-0.017
0.006
0.007
0.003
0.096
-0.032-0.040 -0.019-0.024
0.009
0.009
0.004
-0.041
0.013
0.017
0.008
0.000
0.000
0.000
0.000
0.006
-0.002-0.002 -0.001

FemaleAge
High_incMiddle_inc
High_edu
Full-time-employed
Self_employed
Part-time-employed
Household_size-0.059(-1.90)*
0.005(2.10)**0.126(2.06)**-0.043(-0.54)
0.245(3.08)***-0.060(-0.62)-0.103(-0.54)-0.001(-0.00)
0.016(0.47)

y=0
0.001
0.000
-0.0030.002-0.006
0.001
0.003
0.000
0.000

Log likelihood
Count R2
Observations
Note: See Table 5.

-1371.048
0.609
1200

Table 9 Determinants of concern about urban energy problem
Variable
Coefficient
Marginal effects on probabilities
y=4
y=3
y=2
y=1
Female-0.111(-1.62)-0.043
0.011
0.020
0.009
Age
-0.003(-2.30)**-0.002
0.001
0.001
0.000
High_inc0.153(1.67)*
0.059-0.017-0.026 -0.012
Middle_inc
0.076(0.97)
0.029-0.008-0.013 -0.006
High_edu
0.192(2.41)**0.073-0.016-0.034 -0.017
Full-time-employed0.016(0.18)
0.006-0.002-0.003 -0.001
Self_employed-0.186(-0.97)-0.069
0.012
0.033
0.018
Part-time-employed
0.057(0.27)
0.022-0.006-0.010 -0.005
Household_size
0.050(1.94)*
0.019-0.005-0.009 -0.004

y=0
0.003
0.000
-0.003-0.002-0.0050.000
0.006-0.001-0.001

Log likelihood
Count R2
Observations
Note: See Table 5.

-1440.691
0.577
1200

problem (see the estimated results in Tables 6−13). First, there is no effect of gender onindividual environmental concern in such issues as urban energy problem, green land
andecologicalproblems,theeffectofharmfulsubstancesonhealth,disposal/reduction/recycling of waste, and living environment problems. It may be truethat male and female are almost same in these local and personal environmental issues.
Additionally, men are found to be more concerned about some ‘purely’ environmental
problems (global warming, cross-boundary pollution and acid rain, and air/water/soil
pollution). Second, age is a significant and negative factor for choosing ‘concern’ in
14

Table 10 Determinants of concern about green land and ecological problems
Variable

Coefficient

FemaleAge
High_incMiddle_inc
High_edu
Full-time-employed
Self_employed
Part-time-employed
Household_size

0.001(0.02)
0.007(3.42)***
0.117(1.85)*-0.007(-0.09)
0.226(2.69)***-0.085(-1.84)*-0.189(-1.75)*-0.246(-1.00)-0.035(-0.97)

Log likelihood
Count R2
Observations
Note: See Table 5.

-1262.282
0.590
1200

Marginal effects on probabilities
y=4
y=3
y=2
y=1
0.001
0.000
0.000
0.000
0.003
-0.002-0.0010.000
0.046-0.023-0.014 -0.007-0.003
0.001
0.001
0.000
0.089
-0.041-0.029 -0.016-0.034
0.016
0.011
0.005
-0.075
0.032
0.025
0.014
-0.098
0.041
0.033
0.019
-0.014
0.007
0.004
0.002

y=0
0.000
0.000
-0.0020.000-0.004
0.001
0.004
0.005
0.001

Table 11 Determinants of concern about the effect of harmful substances on health
Variable
Coefficient
Marginal effects on probabilities
y=4
y=3
y=2
y=1
y=0
Female0.015(0.21)
0.005-0.003-0.002 -0.001
0.000
*
Age
0.006(1.91)
0.002-0.001-0.0010.000
0.000
High_inc0.099(2.94)***0.035-0.019-0.010 -0.004-0.001
Middle_inc-0.033(-0.36)-0.012
0.006
0.003
0.002
0.001
High_edu
0.253(2.78)***0.091-0.047-0.028 -0.013-0.004Full-time-employed0.049(0.49)
0.017-0.009-0.005 -0.002-0.001
Self_employed
0.460(1.92)*
0.143-0.086-0.039 -0.015-0.004Part-time-employed -0.090(-0.34)-0.032
0.017
0.010
0.005
0.001
Household_size-0.085(-2.28)**-0.030
0.016
0.009
0.004
0.001
Log likelihood
Count R2
Observations
Note: See Table 5.

-1053.016
0.735
1200

urban energy problem, waste problem, and living environment problems, while it ispositively contributed to concern about global warming issue, air/water/soil pollution,
green land and ecological problems, and the effect of harmful substances on health. It
seems that the younger generation in Shanghai pays more attention to environmental
problems closely associated with living, while the older generation concerns more about‘purely’ environmental problems and some issues affecting their health. Third,
compared to the result in general environmental problem model, employment status

15

Table 12 Determinants of concern about disposal, reduction, and recycling of waste
Variable

Coefficient

Marginal effects on probabilities
y=4
y=3
y=2
y=1
-0.006
0.003
0.002
0.001
0.002
-0.001-0.0010.000
0.078-0.041-0.027 -0.008
0.038-0.019-0.013 -0.004
0.059-0.028-0.021 -0.006-0.036
0.018
0.013
0.004
-0.012
0.006
0.004
0.001
0.009
-0.004-0.003 -0.001
0.006-0.003-0.002 -0.001

FemaleAge
High_incMiddle_inc
High_edu
Full-time-employed
Self_employed
Part-time-employed
Household_size-0.014(-0.21)-0.006(2.17)**0.197(2.09)**
0.095(1.16)
0.147(2.02)**-0.090(-0.95)-0.031(-0.15)
0.022(0.08)
0.014(0.41)

y=0
0.000
0.000
-0.004-0.002-0.003
0.002
0.001
0.000
0.000

Log likelihood
Count R2
Observations
Note: See Table 5.

-1259.860
0.557
1200

Table 13 Determinants of concern about living environmental problems
Variable
Coefficient
Marginal effects on probabilities
y=4
y=3
y=2
y=1
Female-0.020(-0.28)-0.007
0.004
0.002
0.001
Age
-0.007(2.39)**0.003-0.002-0.001
0.000
High_inc0.047(2.18)**0.017-0.010-0.004 -0.001
Middle_inc
0.008(0.12)
0.004-0.002-0.001
0.000
High_edu
0.117(2.30)**
0.042-0.026-0.011 -0.004
Full-time-employed-0.166(-1.62)-0.058
0.037
0.014
0.005
Self_employed0.332(1.32)
0.108-0.072-0.025 -0.008
Part-time-employed -0.194(-0.74)-0.072
0.041
0.020
0.007
Household_size-0.021(-0.55)-0.007
0.005
0.002
0.000

y=0
0.000
0.000
-0.0010.000-0.0020.002-0.0040.004
0.000

Log likelihood
Count R2
Observations
Note: See Table 5.

-1020.927
0.728
1200

and household size are found to be significant in several cases. For example, theself-employed respondents concern more about the effect of harmful substances on
health (see Table 11), an one-person increase in household significantly increases theprobability of choosing ‘concern’ about urban energy problem by 0.019 (see Table 9), andrespondents are found to be less concerned about green land and ecological problems ifthey are employed full-time or self-employed (see Table 10).
In addition, in all eight models for specific environmental problems, other twosocioeconomic characteristics (high income and high education) show consistent results

16

Table 14 Determinants of tradeoff between life convenience and environmental conservation
Variable

Coefficient

FemaleAge
High_incMiddle_inc
High_edu
Full-time-employed
Self_employed
Part-time-employed
Household_size-0.187(-2.85)**-0.005(-1.99)**
0.478(5.03)***0.362(4.41)***0.059(2.22)**-0.225(-2.61)***-0.620(-3.25)***-0.328(-1.08)-0.055(-1.59)

Log likelihood
Count R2
Observations
Note: See Table 5.

-1282.672
0.616
1200

Marginal effects on probabilities
y=3
y=2
y=1
-0.053-0.021
0.071-0.001-0.001
0.002
0.145
0.038
-0.1770.104
0.038-0.1360.016
0.007-0.022-0.066-0.0220.084-0.131-0.1090.217-0.080-0.0510.121-0.015-0.006
0.021

y=0
0.003
0.000
-0.007-0.006-0.001
0.004
0.023
0.009
0.001

Table 15 Determinants of ranks of environmental consideration when buying electronics
Variable
Coefficient
Marginal effects on probabilities
y=4
y=3
y=2
y=1
y=0
Female-0.090(-1.32)-0.008-0.010-0.010 -0.006
0.034
Age
-0.003(-0.91)
0.000
0.000
0.000
0.000
0.001
High_inc0.168(1.71)*
0.016
0.020
0.018
0.011
-0.065
Middle_inc
0.095(1.08)
0.009
0.011
0.010
0.007
-0.036
High_edu
0.097(3.59)***
0.009
0.011
0.010
0.007
-0.037Full-time-employed-0.133(-1.48)-0.013-0.016-0.014 -0.009
0.052
Self_employed-0.505(-2.53)**-0.031-0.048-0.053 -0.044
0.176
Part-time-employed -0.347(-1.23)-0.024-0.035-0.037 -0.029-0.125
Household_size
0.005(0.14)
0.000
0.001
0.001
0.000
-0.002Log likelihood
Count R2
Observations
Note: See Table 5.

-1412.001
0.658
1200

with those in concern about general environmental issue. Meanwhile, the predictive
power indices (Count R2) of all the models are from 55.7 percent to 73.5 percent, which
are within a statistically acceptable range. Moreover, as in the case of generalenvironmental issue, education level is also found to be the most influential factor inchoosing ‘concern’ among all the significant variables in most of the cases.7
7 Exceptions can be found in model C (Table 7), model G (Table 11), and model H (Table12), which the magnitude of marginal effect of high education on probability of choosing
17

Let us examine our third type of measure: attitude towards pro-environmental
behavior. The estimated results are presented in Tables 14 and 15. Concerning the firstindex (i.e. tradeoff between life convenience and environmental conservation), we findthat although the magnitude is small, both the estimated marginal effects of age on
probabilities of choosing ‘environmental conservation always weighs more’ and‘conserve the environment even if sacrificing life convenience to some extent’ areconsistent with the age hypothesis proposed by Van Liere and Dunlap (1980) andFransson and Gärling (1999). Meanwhile, besides high income and high education, therespondents belonging to middle income class also indicate that, compared with the low
income group, they are more likely to conserve the environment than considering life’s
convenience. The significantly negative marginal effects of female, full-time employed,
and self-employed on probabilities of choosing ‘environmental conservation always
weighs more’ or ‘conserve the environment even if sacrificing life convenience to someextent’ indicate that female or full-time employed or self-employed respondents are
relatively less willing to sacrifice their life’s convenience. Turning to the second index(i.e. rank of environmental consideration when buying electronics), only high income,high education, and self-employed are estimated as significant determinants. It should
be noted that unlike the case of other environmental concern measures, the marginal
effect of income on choice probability is larger than that of education level in the cases of
the above two ‘attitude’ measures. This difference implies that when facing a tradeoff
between environmentally friendly behavior and other factors, income, rather thaneducation, plays a relatively more important role.
As a summary of the above empirical results, we find that income and education level
are the two consistent determinants of each environmental concern measure defined in
the present study. Age is a significant factor in most of the measures with either positiveor negative signs. The mixed results of age factor imply that the effect of age on
environmental concern depends heavily on which measure is used. Additionally, men
are found to be more concerned about environment than women in five of eleven indices.
Other socioeconomic characteristics such as employment status and household size
hardly exhibit any significant roles in determining the degree of concern.

6. Conclusion
In this study, we present an empirical analysis on examining what the roles of different
socioeconomic characteristics are in determining individual environmental concern, byapplying data recently collected in Shanghai. A part of the results of this study seems tocomplement previous results, which indicate that individuals with high education‘concern’ is the second largest one, comparing to other significant variables.
18and/or high income are more concerned about the environment as a group. These twosocioeconomic characteristics of high education and high income are especiallyconsistent and robust in all the environmental concern measures defined in the present
study. In addition, the results of testing the gender hypothesis weakly support that men
in Shanghai are more concerned about the environment than woman in several
measures. One finding of this study, which is contrary to most previous studies, is thatin five of the measures, the marginal effects of age on the probability of choosing‘concern’ are estimated as significant with positive signs, implying that the older
generation is more concerned about the environment. Although a number ofsocioeconomic characteristics such as gender, age, income, and education level are foundto be important determinants of individual environmental concern, other factors such as
employment status and household size are almost irrelative.
It should be noted that the results and findings of this study are mainly based on theenvironmental concern measures applied. Therefore, future studies should employ more
multiple measures of environmental concern to help ensure the validity of the findings.
In addition, because the current sample is strictly urban and only drawn from Shanghai,
it cannot be viewed as a representative of all Chinese, considering the large differencesamong different provinces in China. Consequently, to examine the socioeconomic
determinants of environmental concern for entire Chinese population will require thecollection of samples from other urban and rural areas. Finally, concerning an
econometric technique issue, we treat the eleven environmental concern measures
separately by applying the ordered probit model in this study. With the possible
correlations among these measures, it may be more appropriate to use a multivariate
ordered probit model with eleven equations being simultaneously estimated. Thismodeling, however, cannot be run by today’s most statistical software. We leave theprogramming of this model as our future task to be solved.

References
Adeola, F. O. 1994. Environmental hazards, health, and racial inequity in hazardous
waste distribution. Environment and Behavior, 26(1): 99-126.
Antil, J. H. 1984. Socially responsible consumers: Profiles and implications for public
policy. Journal of Macromarketing, 19(Fall): 18-39.
Arbuthnot, J. and S. Lingg. 1975. A comparison of French and American environmental
behaviors, knowledge and attitudes. International Journal of Psychology, 10: 275-281.
Arcury, T. A. and E. H. Christianson. 1990. Environmental worldview in response toenvironmental problems: Kentucky 1984 and 1988 compared. Environment andBehavior, 22(3): 387-407.
Buttel, F. H. and W. L. Flinn. 1974. The structure of support for the environmental
movement. Rural Sociology, 39: 56-69.
19Daneshvary, N., R. Daneshvary, and R. K. Schwer. 1998. Solid-waste recycling behavior
and support for curbside textile recycling. Environment and Behavior, 30(2): 144-161.
Davidson, D. J. and W. R. Freudenburg. 1996. Gender and environmental risk concerns.

Environment and Behavior, 28(3): 302-339.
Dietz, T., L. Kalof, and P. C. Stern. 2002. Gender, values, and environmentalism. Social

Science Quarterly, 83(1): 353-364.
Dunlap, R. E. 1975. The impact of political orientation on environmental attitudes andactions. Environment and Behavior, 7(4): 428-454.
Eagly, A. H. and P. Kulesa. 1997. Attitudes, attitude structure, and resistance to change:
Implications for persuasion on environmental issues. In M. H. Bazerman, D. M.
Messick, A. E. Tenbrunsel, and K. A. Wade-Benzoni (Eds), Environment, ethics, andbehavior: The psychology of environmental valuation and degradation. San Francisco:
New Lexington Press.
Fransson, N. and T. Gärling. 1999. Environmental concern: Conceptual definitions,
measurement methods, and research findings. Journal of Environmental Psychology,
19: 369-382.
Greene, W. H. 2003. Econometric analysis. 5th edition, Prentice Hall.
Hackett, P. M. W. 1993. Modeling environmental concern: Theory and application. The

Environmentalist, 13(2): 117-120.
Hine, D. W. and R. Gifford. 1991. Fear appeals, individual differences, andenvironmental concern. Journal of Environmental Education, 23(1):36-41.
Howell, S. E. and S. B. Laska. 1992. The changing face of the environmental coalition: A
research note. Environment and Behavior, 24(2): 134-144.
Hunter, L. M., A. Hatch, and A. Johnson. 2004. Cross-national gender variation inenvironmental behaviors. Social Science Quarterly, 85(3): 677-694.
Jones, R. E. and R. E. Dunlap. 1992. The social bases of environmental concern: Havethey changed over time. Rural Sociology, 57(1): 28-47.
Koenig, D. J. 1975. Additional research on environmental activism. Environment andBehavior, 7(4): 472-485.
Long, J. S. 1997. Regression models for categorical and limited dependent variables.
SAGE Publications, Inc.
Lyons, E. and G. M. Breakwell. 1994. Factors predicting environmental concern andindifference in 13- to 16-year-olds. Environment and Behavior, 26(2): 223-238.
Maslow, A. H. 1970. Motivation and personality. New York: Viking Press.
Mohai, P. 1992. Men, women and the environment: An examination of the gender gap inenvironmental concern activism. Society and Natural Resources, 5(1): 1-19.
Newell, S. J. and C. L. Green. 1997. Racial differences in consumer environmental
concern. The Journal of Consumer Affairs, 31(1): 53-69.
Nord, M., A. E. Luloff, and J. GT. Bridger. 1998. The association of forest recreation withenvironmentalism. Environment and Behavior, 30(2): 235-246.
20

Oskamp, S., M. J. Harrington, T. C. Edwards, D. L. Sherwood, S. M. Okuda, and D. C.
Swanson. 1991. Factors influencing household recycling behavior. Environment andBehavior, 23(4): 494-519.
Poortinga, W., L. Steg, and C. Vlek. 2004. Values, environmental concern, andenvironmental behavior. Environment and Behavior, 36(1): 70-93.
Samdahl, D. M. and R. Robertson. 1989. Social determinants of environmental concern:
Specification and test of the model. Environment and Behavior, 21(1): 57-81.
Schahn, J. and E. Hotzer. 1990. Studies of individual environmental concern: The role ofknowledge, gender and background variables. Environment and Behavior, 22(6):767-786.
Scott, D. and F. Willits. 1994. Environmental attitude and behavior: A Pennsylvania
survey. Environment and Behavior, 26(2): 239-260.
Stern, P. C. and T. Dietz. 1993. Value orientations, gender, and environmental concern.

Environment and Behavior, 25(5): 332-348.
Van Liere, K. D. and R. E. Dunlap. 1980. The social bases of environmental concern: A
review of hypotheses, explanations and empirical evidence. The Public Opinion

Quarterly, 44(2): 181-197.
Wall, G. 1995. General versus specific environmental concern: A western Canadian case.

Environment and Behavior, 27(3): 294-316.
Witzke, H. P. and G. Urfei. 2001. Willingness to pay for environmental protection inGermany: Coping with the regional dimension. Regional Studies, 35(3): 207-214.
Wooldridge, J. M. 2002. Econometric Analysis of Cross Section and Panel Data. The
Massachusetts Institute of Technology (MIT) Press.

21