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. Author manuscript; available in PMC: 2020 Nov 20.
Published in final edited form as: J Fam Econ Issues. 2019 Jun 20;40:673–680. doi: 10.1007/s10834-019-09636-0

Relative Income and Subjective Well-being of Urban Residents in China

Jichao Wang 1, Wei Yan 2, Jie Zhang 3,2
PMCID: PMC7677900  NIHMSID: NIHMS1532336  PMID: 33223788

Abstract

The purposes of this study are to examine subjective well-being and to test its correlation with social reference and self-expectations of urban residents in China. Data are obtained from the 2015 Chinese General Social Survey, and we focus on urban residents (N=4,857). Because the dependent variable is a sequence variable, the ordered logit model is used for data analysis. We find that absolute income remains an important factor in determining people’s subjective well-being. We also find that when relative income factors are included, the correlation between absolute income and subjective well-being is reduced. This suggests that the subjective well-being of urban residents is influenced not only by absolute income itself, but also – more importantly – by relative income based on social comparison and self-expectations. These findings have implications for the formulation of social policies to improve citizens’ happiness.

Keywords: subjective well-being, relative income, social reference, self-expectation, urban residents

With the development of China’s economy, the living standards and income level of urban residents in China have continuously improved. According to data from the National Bureau of Statistics of China, the per capita disposable income of urban residents increased by at least 500% from 2000 to 2016 (National Bureau of Statistics of China 2001; 2017). However, the subjective well-being of urban residents in China has not risen concurrently with economic growth (Wu and Li 2013; Knight and Gunatilaka 2010). In the 2017 World Happiness Report – a United Nations survey of 155 countries and regions around the world– mainland China ranked only 79th (Helliwell et al. 2017). What is the reason for this phenomenon?

Relevant literature has clearly shown that scholars have done substantial research on the relationship between income and happiness. Some studies have confirmed that the improvement of absolute income level can likewise improve people’s subjective sense of happiness (Ferrer-i-Carbonell 2005; Luo 2009). However, some scholars point out that there is not always a positive correlation between absolute income and subjective well-being; instead, they have identified an inverted U-shaped relationship (Brockmann et al. 2009; Easterlin et al. 2012). According to these studies, income level reaches a satiation point, above which further income has no effect on well-being (Di Tella and MacCulloch 2005). That is to say, economic development induces changes in intermediate factors, and these intermediate factors further trigger some psychological mechanisms that lessen the improvement of subjective well-being (Li and Shi 2017). Therefore, exploring the psychological factors that affect people’s subjective well-being is the key to explaining why subjective well-being does not increase synchronously with economic growth.

In the existing research, two possible explanations for this psychological mechanism have been proposed: social reference and self-expectations. Although the explanations of these two mechanisms are logically different, its core emphasizes the role of the reference group. The first explanation is based on horizontal cohorts and longitudinal temporal changes; the second interpretation positions the reference population above individual expectations. But the factors that cause people to feel different levels of happiness may be multifaceted; for instance, social reference and self-expectations may be relative to people’s subjective well-being at the same time. Thus our study attempts to analyze the multifaceted factors that affect people’s happiness by constructing a multidimensional research framework. Our goal was to use this multilayered research paradigm to study the relationship between income and happiness.

Literature Review

Social Reference and Subjective Well-Being

Social reference theory focuses on the nature of the relationship between a reference and how judgments are made (Zhang et al. 2014). It postulates that an individual’s perception of an external social fact or self-evaluation is primarily based on the reference that the individual consciously or unconsciously uses as a comparison (Zhang 2013; Zhang et al., 2010). As a subjective psychological experience, subjective well-being might also be a function of social reference.

Because subjective well-being is determined by the comparative reference that a person chooses (Zhang et al. 2014), each person has a different perception of happiness according to different reference groups. These different social reference groups can be divided into horizontal reference groups and vertical reference groups (Huang 2016). Horizontal reference groups refer to peers who can be observed, are closely related or have some similar attributes. When people perceive themselves to be disadvantaged in relation to their peers, they will experience negative feelings (Brockmann et al. 2009), which decreases their perception of happiness. Vertical reference groups refer to each person’s own past. When individuals perceive that their current economic status is declining in comparison to their past status, negative emotions are generated, which diminishes their perception of happiness. In other words, people’s perception of a change in their happiness depends on their current economic and social status as well as on relative changes in their economic and social status over time (Liu 2002). Only when an individual’s income rises above that of the self-defined reference group will happiness be perceived; however, the gains obtained will only bring about momentary happiness and may even give rise to sadness (Blanchflower and Oswald 2004; Dynan and Ravina 2007; Wood 1996).

There have been several empirical studies that have confirmed social reference theory. For example, Stouffer et al. (1949) found that American soldiers’ feelings of dissatisfaction were less related to the actual degree of hardship they had experienced than to the situation of the unit or group to which they compared themselves. Clark and Oswald’s (1996) study of British workers showed that the reference group’s income level was an important factor affecting people’s subjective well-being; when the reference group’s wage level were higher, people’s perceptions of happiness were reduced. Hagerty (2000) analyzed sample data from various American communities and noted that the scope and deviation of income distribution were important factors affecting people’s subjective well-being. Luttmer (2005) showed that living in neighborhoods with higher average earnings had a negative effect on individuals’ subjective well-being. Knight and Gunatilaka (2010) found that when migrant workers arrived in cities, they had new reference groups that, by comparison, placed them in a weaker position, so their level of happiness was lower than that of ordinary rural residents. Guan (2010) analyzed statistical data from Beijing, Shanghai and Guangdong and found that relative income status had a significant and positive relationship with happiness: the higher one’s relative income, the stronger one’s sense of happiness.

Self-Expectation and Subjective Well-Being

Self-expectation refers to an individual’s belief that he or she should meet a certain goal or requirement (Guan 2010). As a cognitive variable, it expresses the subjective intent of an action by oneself or others. Self-expectation theory asserts that an individual’s perception of happiness is formed through comparisons with certain reference standards. However, the size of an expectation does not itself represent one’s level of happiness. Only when an expectation is combined with actual conditions and internal and external resources can it become an important indicator for evaluating subjective well-being. In other words, the difference between one’s goals and results after comprehensive consideration of their actual situation has an important influence on subjective well-being. The closer an individual’s actual achievement is to his or her self-expectations, the stronger that individual’s perception of happiness (Diener and Fujita 1995).

Empirical studies also have confirmed this theory. Clark and Oswald (1994) examined death, suicide, crime and divorce rates as alternative variables of individual well-being and concluded that a strong, negative correlation existed between unexpected unemployment and subjective well-being. Because the decrease in personal income caused by accidental unemployment is not consistent with people’s psychological expectations, it can result in negative emotions, such as anxiety and low self-esteem, and a corresponding decrease in subjective well-being. Winkelmann and Winkelmann (1995) used German panel data to arrive at the same conclusion. Moreover, some studies have noted that highly educated individuals have higher expectations for their relative income levels. When their expectations cannot be realized, their perceptions of happiness may decrease significantly (Huang 2013; Layard 2005; Wilson 1967).

Although several studies have examined the relationship between relative income and subjective well-being, relatively few have focused on urban residents in China. There are numerous and significant differences between the economies, cultures and education systems of China and Western countries, as well as clear differences in their relative income and subjective well-being (Zhang et al. 2017). The existing literature shows that scholars usually adopt a single perspective to explain the relationship between relative income and subjective well-being. However, the relationship between relative income and subjective well-being is multidimensional, and social reference and self-expectations may simultaneously affect people’s subjective well-being. Therefore, the purpose of this study is to determine whether there is a direct relationship between relative income and subjective well-being through experimental research and to further explore the mechanisms underlying the subjective well-being of urban residents in China. This will provide new insights for the formulation of social policies to increase citizens’ happiness.

Methods

Data Source

The data used in this study come from the 2015 Chinese General Social Survey (CGSS), part of a large-scale panel data collection project managed by Renmin University in China. A multistage probability sampling method was used to select the sample, which covered 478 villages in 28 provinces, municipalities and autonomous regions across the country. A total of 10,968 valid cases were collected, including 6,470 urban cases and 4,498 rural cases. Considering that China’s urban-rural income gap is large, if all residents were selected as research objects, the results would be biased. Therefore, this paper focuses on urban residents in China as the research object. After removing some cases due to missing or invalid data, the final sample of urban residents was 4,857.

Measurements

Dependent variable.

The self-report method is a popular way to measure subjective well-being. Wilson (1967) examined the reliability and validity of this method by comparing the results of individual subjective evaluation and expert evaluation. The results showed that – in most cases – the two methods were highly consistent. Easterlin (2003) pointed out that data obtained through self-reporting scales are valuable for carrying out cross-group, cross-cultural, transnational and cross-system research. Therefore, we used the self-report method to measure the subjective well-being of urban residents in China. Rural residents were not included in this study because in China, there are big differences in the factors influencing the subjective well-being of urban and rural residents. Thus we chose to focus on just one of the two populations in this study.

Following the CGSS 2015 survey questionnaire, we used the question, “Generally, do you feel your life is happy?” to measure the subjective well-being of urban residents. Respondents had five options: 1 = not at all happy, 2 = not happy, 3 = average, 4 = happy, 5 = very happy.

Independent variables.

There are two main ways to measure relative income. One involves selecting a factor (such as age, education, etc.) as the standard set of the reference group and then adding the relevant variables of the reference group to the model for control. The other uses respondents’ subjective feelings of relative status as the measurement standard (Guan 2010). We selected the second approach to measure relative income and divided relative income into two dimensions: horizontal and vertical differences based on comparisons to different reference groups and the psychological gap between expectations and reality.

To measure the impact of vertical and horizontal comparisons on people’s subjective well-being, we selected two questions from the 2015 CGSS questionnaire. One question was, “Compared with your peers, what do you think your own economic status is?” and the other was, “Compared with three years ago, what do you think your socioeconomic status is?” The first question had four options: 1 = lower, 2 = similar, 3 = higher and 4 = hard to say. We excluded those who responded “hard to say,” and we selected “lower than their peers” as the reference group. The second question also had four options: 1 = lower, 2 = similar, 3 = higher and 4 = hard to say. Excluding “hard to say,” we selected “lower than three years ago” as the reference group.

To measure self-expectations, we used the question, “Considering your ability and working conditions, do you think your current income is reasonable?” There were four options: 1 = very reasonable, 2 = reasonable, 3 = unreasonable, 4 = very unreasonable. As the proportion of “very reasonable” and “very unreasonable” were small, the two options “very unreasonable” and “unreasonable” were merged and encoded as 0, and “very reasonable” and “reasonable” were combined and encoded as 1.

Control variables.

To eliminate error caused by the omission of variables from the model estimation to the extent possible, we introduced other related control variables based on existing research results. The control variables in this article included: an individual’s gender (male = 0; female = 1), age, Communist Party membership (no = 0; yes = 1), health status (unhealthy = 1; average = 2; healthy = 3), marital status (unmarried = 0; married = 1), education level (less than primary school = 1; junior high school = 2; senior high school = 3; college and above = 4) and personal annual absolute income. Based on previous literature, the square of age was included in the model (Huang, 2016; Wu and Wang, 2017).

Statistical Model and Analysis Strategy

As described earlier, subjective well-being in our study was measured by using self-reported responses, with happier individuals scoring higher than those who were unhappy. This is an ordered selection variable, in that the distance between adjacent options was incomparable. Therefore, it was “not scientific enough” to use the ordinary least squares method for estimation. Considering the particularity of the explanatory variables, the ordered logit model was selected for this research. We estimated the subjective well-being of urban residents in China using the following formula:

SWB*=β0+β1level1+β2level2+βicontrol+εi

In this formula, level 1 represented the social reference variables, including self-rated economic status compared with peers and self-rated economic status compared with three years ago. Level 2 represented the self-expectation variable. Control represented the control variables, including: the individual’s gender, age, political status, health status, marital status, educational level and absolute annual income. The symbol εwas the perturbation term of the model.

In the operation of the model, we used Stata 14 for data analysis. The bivariate analyses used the chi-squared and Pearson correlation coefficients. Ordered logit regression was used to assess the model for prediction of subjective well-being.

Analyses and Results

Bivariate Analyses

Overall, 897 (18.46%) of the 4,857 participants considered their lives to be very happy, 2,950 (60.73%) thought their lives were happy, 704 people (14.49%) thought their lives were average and 259 (5.33%) thought their lives were not happy. Only 47 (1%) thought their lives were very unhappy. This shows that a large proportion of urban residents in China were satisfied with their current lives. Table 1 illustrates the distribution (frequency or mean) of each of the correlates of subjective well-being of urban residents in China with different levels of happiness.

Table 1.

Chinese Urban Residents’ Subjective Well-being and Demographics

Independent
variables		 Total SWB (Column %)
 χ2/F
(n=4,857) Not at
all happy
(n=47)		 Not happy
(n=259)		 Average
(n=704)		 Happy
(n=2,950)		 Very happy
(n=897)
(Mean±
SD/N(%))		 (Mean±
SD/N(%))		 (Mean±
SD/N(%))		 (Mean±
SD/N(%))		 (Mean±
SD/N(%))		 (Mean±
SD/N(%))
Gender 11.36*
 Male 2,429 (50%) 22 (0.91%) 121 (4.98%) 382 (15.73%) 1,488 (61.26%) 416 (17.13%)
 Female 2,428 (50%) 25 (1.03%) 138 (5.68%) 322 (13.26%) 1,462 (60.21%) 481 (19.81%)
Age 50.04 (16.66) 49.57 (16.51) 50.97 (14.97) 48.12 (15.71) 50.00 (16.58) 51.44 (17.93) 4.15***
Party membership 64.31***
 No 4,074 (83.88%) 45 (1.10%) 234 (5.74%) 646 (15.86%) 2,441 (59.92%) 708 (17.38%)
 Yes 784 (16.12%) 2 (0.26%) 25 (3.19%) 58 (7.41%) 509 (65.01%) 189 (24.14%)
Marital status 74.74***
 Unmarried 1,095 (22.54) 21 (1.92%) 86 (7.85%) 218 (19.91%) 164 (55.34%) 164 (14.98%)
 Married 3,762 (77.46) 26 (0.69%) 173 (4.60%) 486 (12.92%) 2,344 (62.31%) 733 (19.48%)
Educational level 69.28***
 Less than primary school 1,020 (21%) 14 (1.37%) 77 (7.55%) 166 (16.27%) 592 (58.04%) 171 (16.76%)
 Junior high school 1,361 (28.02%) 14 (1.03%) 88 (6.47%) 220 (16.16%) 781 (57.38%) 258 (18.96%)
 Senior high school 1,203 (24.77%) 11 (0.91%) 63 (5.24%) 182 (15.13%) 742 (61.68%) 205 (17.04%)
 College and above 1,273 (26.21%) 8 (.63%) 31 (2.44%) 136 (10.68%) 835 (65.59%) 263 (20.66%)
Health condition 214.89***
 Unhealthy 599 (12.33%) 15 (2.50%) 85 (14.19%) 109 (18.20%) 302 (50.42%) 88 (14.69%)
 Average 1,156 (23.8%) 14 (1.21%) 65 (5.62%) 235 (20.33%) 670 (57.96%) 172 (14.88%)
 Healthy 3,102 (63.87%) 18 (.58%) 109 (3.51%) 360 (11.61%) 1,978 (63.77%) 637 (18.47%)
Personal annual absolute income 10.25 (0.99) 9.67 (1.09) 9.73 (1.12) 10.19 (0.89) 10.29 (0.98)) 10.37 (1.02) 7.63***
Compared with peers 378.01***
 Lower 1,429 (29.42%) 33 (2.31%) 166(11.62%) 309 (21.62%) 735 (51.43%) 186 (13.02%)
 Similar 3,118 (64.2%) 12 (0.38%) 87 (2.79%) 386 (12.38%) 2,031(65.14%) 602 (19.31%)
 Higher 310 (6.38%) 2 (0.65%) 6 (1.94%) 9 (2.90%) 184 (59.35%) 109 (35.16%)
Compared with three years ago 202.65***
 Lower 459 (9.45%) 17 (3.7%) 59 (12.85%) 97 (21.13%) 277 (49.46%) 59 (12.85%)
 Similar 2,820 (58.06%) 21 (0.74%) 162 (5.74%) 444 (15.74%) 1,734 (61.49%) 459 (16.28%)
 Higher 1,578 (32.49%) 9 (0.57%) 38 (2.41%) 163 (10.33%) 989 (62.67%) 379 (24.02%)
Compared with revenue expectations 176.92***
 Unreasonable 1,683 (34.65%) 32 (1.9%) 159 (9.45%) 319 (18.95%) 933 (55.44%) 240 (14.26%)
 Reasonable 3,174 (65.35%) 15 (0.47%) 100 (3.15%) 385 (12.13%) 2,017 (63.55%) 657 (20.70%)
Open in a new tab
*

p < .05

**

p < .01

***

p < .001

In general, females were happier than males, and Party members were happier than non-Party members. This shows that in the Chinese context, Party membership can bring more social resources to individuals and further enhance their happiness. Married people tended to think their lives were happier than unmarried people, which suggests that marriage can bring stable emotional support and economic security to individuals, thereby enhancing people’s happiness. Happiness also was positively associated with health, as healthy people tended to think that their lives were happier than did unhealthy people. Moreover, educational level also influenced happiness: people with university-level educations and above were happier than those with lower educational levels, while those who had only completed primary school were most unhappy. In addition, bivariate analysis showed that reference groups and self-expectations positively and significantly correlated with urban residents’ subjective reports of well-being. This finding held true in the ordered logit regression analyses with all relevant correlates held constant in the same model, as shown in table 2.

Table 2.

Ordered Logit Regression Analysis on Subjective Well-being

Variables Model 1 Model 2
OR 95% C.I. OR 95% C.I.
Gender (Female=1) 1.39*** 1.24–1.57 1.34*** 1.19–1.51
Age 0.93*** .91–.95 0.95*** 0.93–097
Age2 1.0008*** 1.0007–1.001 1.0006*** 1.0004–1.0008
Party members or not (Party members=1) 1.33*** 1.13–1.58 1.31*** 1.11–1.55
Married 2.06*** 1.78–2.39 1.89*** 1.63–2.19
Educational level (Reference: Less than primary school)
Junior high school 1.17* .99–1.39 1.18* 1.00–1.41
Senior high school 1.14* .95–1.37 1.19* 1.00–1.44
College and above 1.42*** 1.16–1.75 1.48*** 1.20–1.82
Health condition (Reference: Unhealthy)
Average 1.53*** 1.26–1.88 1.375*** 1.12–1.68
Healthy 3.00*** 2.48–3.63 2.42*** 1.99–2.93
Log (income) 1.19*** 1.11–1.27 1.08** 1.01–1.15
Compared with peers (Reference: Lower)
Similar 1.67*** 1.45–1.92
Higher 2.87*** 2.20–3.74
Compared with three years ago (Reference: Lower)
Similar 1.51*** 1.24–1.85
Higher 2.42*** 1.95–3.00
Compared with revenue expectations (Reasonable = 1) 1.47*** 1.29–1.70
/cut1 −2.608 −3.49– −1.73 −2.23 −3.13– −1.33
/cut2 − 0.641 −1.48– −1.97 −0.23 −1.09– −0.63
/cut3 0.797 − 0.37–1.63 1.27 0.40–2.13
/cut4 3.828 2.98–4.67 4.43 3.56–5.30
Log likelihood −5104.52 - −4968.839 -
F 436.9 - 708.260 -
P < 0.001 - < 0.001 -
Pseudo R2 0.041 - 0.0665 -
Obs 4857 - 4857 -
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*

p < .05

**

p < .01

***

p < .001

Ordered Logit Regression Analysis

We conducted ordered logit regressions to explore whether relative income and other relevant factors predicted urban residents’ reports of their well-being. Model 1 introduced control variables into the model, and we drew the following conclusions by analyzing the model fit results: gender, political status, marital status, health condition, educational level and personal annual absolute income all had a significant relationship with the subjective well-being of urban residents (p < .001). Moreover, their perceptions of happiness demonstrated a U-shaped change with age, which was consistent with previous literature (Tsou and Liu 2001; Helliwell 2006; Asadullah et al. 2018). The inflection point was at about 42 years old.

Although all these control variables had a certain impact on the subjective well-being of urban residents, the benchmark model (model 1) accounted for only 4.1% of the dependent variable’s change in terms of model fit. Therefore, we introduced core variables to refine the model.

Model 2 included social comparison, self-expectation and control variables. This model revealed that social comparison and self-expectations had a significant effect on the subjective well-being of urban residents (p < .01). Specifically, people with higher ratings of their current economic and social status had a stronger perception of happiness than their peers. Moreover, the higher people evaluated their current economic and social status compared to their own past, the stronger their perception of happiness. When there was little difference between people’s expectations and their actual efforts, they were more likely to think their current income was reasonable, and their perceptions of happiness were stronger. Finally, in model 2, the significance of the absolute income variable was reduced, which showed that decreasing the psychological gap between expectations and reality played an important role in improving urban residents’ happiness. Model 2 explained 6.65% of the variation of the dependent variable, therefore supporting the previous analysis.

Conclusions

This study analyzed data from the 2015 Chinese General Social Survey to examine the relationship between relative income level and the subjective well-being of urban residents in China. We found that absolute income remained an important factor in enhancing people’s subjective well-being, which was consistent with previous studies (Cummins 2000; Wu and Li 2013). We also found that the correlation between absolute income and subjective well-being was reduced when relative income factors were included. That is to say, the subjective well-being of urban residents was not only related to income itself; it also was influenced by reference groups and self-expectations. Specifically, when individuals found themselves in a disadvantaged position compared with their peers or their own past position, their subjective feelings of happiness were greatly diminished. When individuals’ self-expectations based on their abilities negatively deviated from their actual situation, their perceptions of happiness also decreased.

According to social reference theory and self-expectation theory, the subjective well-being of urban residents in China is correlated with their previous life situation, socioeconomic status and psychological expectations. These factors serve as reference points when evaluating their current life quality and well-being. Moreover, such factors can explain why the subjective well-being of urban residents was not uniformly synchronized with an increase in income.

In terms of policy, our shows that, in the context of China, improving people’s sense of well-being requires an awareness of their social psychology. Changes in the psychological process play an important role in connecting the macro-social environment with individuals’ unique experiences (Huang 2016). Therefore, the government should pay attention to people’s relative deprivation and seek to increase people’s happiness by focusing on factors that directly touch people’s inner feelings. In addition, the government should be aware that different people have different psychological expectations. In the process of improving people’s happiness, fairness based on differences – rather than equality – should be pursued, based on the same principle. And targeted policy guidance and economic subsidies could be used to reduce people’s relative deprivation and psychological gap to effectively enhance their perceptions of well-being.

Our study had some limitations which need to be addressed in future research. First, only urban residents in China were selected as research objects, so the conclusions may not be applicable to all residents of China. In future studies, we will increase the sample size to include rural residents and conduct a comparative study between urban and rural residents; this will fully demonstrate the relationship between the relative income of residents of China and subjective well-being. Second, our judgments on reference groups were to some extent post-inference, although most studies of this nature have used the same post-inference strategy (Dynan and Ravina 2007; Firebaugh and Schroeder 2009; Asadullah et al. 2018). If we can collect reference groups from urban residents’ subjective judgments, it may more accurately capture the relationship between relative income and subjective well-being. For this reason, future research should elaborate more precisely on the mechanisms of social comparisons. What’s more, subject to data constraints, some important variables (such as current living standard, family property, expected income, etc.) that might impact the relationship between income and happiness were not included in the analysis; this may have led to some deviations in the research results. Future research on the subjective well-being of residents in China should use a larger sample and broaden the range of possible correlates of subjective well-being.

Acknowledgments

This study is supported by a grant from Beijing Institute of Psychology (Grant Number: 2017BJXLS08).

Footnotes

Publisher's Disclaimer: This Author Accepted Manuscript is a PDF file of an unedited peer-reviewed manuscript that has been accepted for publication but has not been copyedited or corrected. The official version of record that is published in the journal is kept up to date and so may therefore differ from this version.

ETHICAL STATEMENT

We certify that the submission is our original work and not under review by any other publications. All the authors listed have approved the manuscript that is enclosed.

Contributor Information

Jichao Wang, Central University of Finance and Economics. Beijing, China

Wei Yan, Central University of Finance and Economics, Beijing, China.

Jie Zhang, Central University of Finance and Economics. Beijing, China; State University of New York Buffalo State. Buffalo, New York, USA.

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