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Journal of Leisure Research Copyright 20152015, Vol. 47, No. 5, pp. 556–576 National Recreation and Park Association

• 556 •

Leisure Time, Leisure Activities, and Happiness in ChinaEvidence from a National Survey

Xiang WeiChinese Academy of Social Sciences

Songshan (Sam) HuangUniversity of South Australia

Monika StodolskaUniversity of Illinois at Urbana-Champaign

Yihua YuRenmin University of China

Abstract

This study utilized a nation-wide survey (n=73,622) to examine the associations of leisure time, leisure activities, and demographics with happiness among residents in China. Ordered logit re-gression analyses indicated that leisure time was positively associated with happiness. While pas-sive leisure activities (e.g., watching TV, Internet surfing) were found to contribute to happiness, active leisure activities (e.g., exercising, socializing, and shopping) had no significant association with happiness. Among demographic variables, income was found to have a positive association with happiness; females were found to be generally happier than males, and urban residents happier than their rural counterparts. While age was surprisingly found to have no relation to happiness, education levels seemed to have varied non-linear relationships with happiness. The study contributes to empirically verifying the relationship between leisure and happiness and generates implications directing leisure policies and industry practices in China.

Keywords: leisure, Chinese happiness, life satisfaction, China

Xiang Wei is an associate professor at National Academy of Economic Strategy, Chinese Academy of Social Sciences and adjunct professor at National School of Development, Peking University. Songshan (Sam) Huang is an associate professor in the School of Management at the University of South Australia. Monika Stodolska is a professor in the Department of Recreation, Sport and Tourism at the University of Illinois at Urbana-Champaign. Yihua Yu is an associate professor in the School of Economics, Renmin University of China. Please send correspondence to Songshan (Sam) Huang, [email protected]

Leisure and Happiness in China • 557

Introduction

This paper aims to examine the associations of leisure time, leisure activities, and relevant demographic variables with happiness among residents in China. Although some research has been conducted to investigate how leisure affects Chinese people’s well-being (Lau, Cummins, & McPherson, 2005; Lu & Hu, 2005; Spiers & Walker, 2009; Vong, 2005), most of the previous studies in this regard focused on residents in Hong Kong, Macao, and Taiwan who are facing relatively different social realities and environments compared to mainland Chinese residents. Some researchers (e.g., Jim & Chen, 2009; Lee & Zhang, 2010; Liu, 2006) studied residents in specific mainland Chinese cities; with relatively small samples of less than 1,000, existing studies are limited in presenting a national profile. A review of the literature has not revealed any study that investigated the national profile of how leisure is related to happiness of mainland Chinese residents. In the current study, we utilized data from a nationwide survey jointly implemented by the China National Bureau of Statistics (CNBS), the General Post Office of China (GPOC), and the China Central Television (CCTV), and ran a thorough analysis on the relationships between leisure, relevant demographics and mainland Chinese residents’ self-reported happiness.

China has become the second largest economy in the world. In 2011, China’s gross domestic product (GDP) reached US$ 7.298 trillion and its population was 1.344 billion, accounting for approximately one fifth of the world’s population (World Bank, 2011). Since the 1980s, China’s annual economic growth rate has seen an average of above 9%, well above the 2.3% growth rate in developed economies (World Bank, 2011). As a consequence of its rapid economic development, living standards of people in China have been greatly improved (Zhou, Li, Xue, & Lei, 2012). In the meantime, mainland Chinese residents not only have the adequate financial resources to participate in leisure activities, they also have enough time to do so (Liang & Walker, 2011).

In the literature, a positive relationship between leisure and happiness has been well sup-ported (Bailey & Fernando, 2012; Crandall, 1980; Heo, Lee, Kim, & Chun, 2012; Ragheb & Tate, 1993; Spiers & Walker, 2009). However, as most of the studies confirming such a relationship were conducted in the context of western developed countries, it is necessary to test whether such a relationship holds in contemporary China whereby a unique economic and social devel-opment stage is witnessed. It is commonly conceived that China’s transition from socialism to capitalism brings greater happiness to its nationals, as personal income will be raised by a more efficient allocation of resources and increased incentives for private investment (Easterlin, Mor-gan, Switek, & Fei, 2012). Also, in such a transition period, residents in China have witnessed a significant increase of leisure time (Yin, 2005) as well as leisure consumption (Zhai & Xiao, 2004). Therefore, it is reasonable to postulate that leisure would be a significant factor that in-forms people’s happiness in the rapid transition of the modern Chinese society. As such, China represents a most desirable context to further test the leisure-happiness relationship. Most of the existing conceptualizations on how leisure is associated with happiness have been derived from the Western cultural contexts (Iwasaki, 2006; Spiers & Walker, 2009). Therefore, the current study is hoped to contribute to the literature by examining the relationship between leisure and happiness in the context of China.

Literature Review

Happiness and Chinese HappinessInterest in happiness has become a global phenomenon, and the ability to be happy is a cen-

tral criterion of positive life (Lyubomirsky, Sheldon, & Schkade, 2005). Happiness means good

558 • Wei, Huang, Stodolska, and Yu

life that can be examined with both cognitive (e.g., Quality of Life, QOL) and affective (e.g., Sub-jective well-being, SWB) aspects (Spiers & Walker, 2009). Although there are subtle differences between SWB and QOL, the two aspects could be used as interchangeable measures for overall feeling of happiness (Easterlin, 2004). In the present study, SWB is treated as a suitable proxy for happiness. As demonstrated in the literature, direct reporting of SWB may have a useful role in the measurement of consumer preferences and social welfare (Kahneman & Krueger, 2006). In this study, the self-reported measure for happiness is used in a large-scale questionnaire survey.

The literature on happiness is equally mixed with economists’ and psychologists’ perspec-tives. Most economists place particular emphasis on the importance of income and employment situation to happiness and, at the extreme, this view tends to employ real GDP per capita as a measure of well-being (Fuchs, 1983, p. 14). However, Easterlin (1974) documented stagnant average happiness levels in the United States even with large income increases. After that, some other empirical studies provided further evidence in support of the above finding in a number of countries (Blanchflower & Oswald, 2011; Easterlin, 1995, 2005). Across the research camps, the finding explored by economists was somewhat fully explained by psychologists who typically view the impact of material conditions on well-being as being adjusted by “adaptation processes” (Oswald & Powdthavee, 2008). At the extreme, this process led to the notion “effect of hedonic treadmill” (Kahneman, 1999, p. 13), meaning that good and bad events temporarily influence happiness, but people can quickly adapt back to the neutral state of their hedonic feeling. This view is also typically formulated as the “set-point model” in which “each individual is thought to have a fixed setpoint of happiness determined by genetics and personality; life events such as marriage or divorce, job loss, or serious injury or disease may temporarily deflect a person above or below this setpoint, but in time each individual will adjust to the new circumstances and re-turn to the given setpoint” (Easterlin, 2004, pp. 26–27).

Happiness research in psychology has a profound impact on happiness research in econom-ics. It revealed that the policies to maximize a society’s welfare should pay more attention to increasing social contacts than to increasing consumption opportunities (Layard, 2005). More-over, adaptation in SWB reminded that people should shift their attention from an emphasis on the importance of income to an emphasis on the importance of people’s social status (Kahneman & Krueger, 2006).

There have been quite a number of recent studies on Chinese people’s SWB or happiness. Liu (2006) indicated that Chinese people’s perceptions of QOL are mainly around five impor-tant life domains: health, family, work, social relations and the natural environment. Lu (2001), after investigating Chinese conceptualizations of happiness, added that Chinese happiness can be understood from three different philosophical perspectives: Confucianism, Taoism, and Bud-dhism. While Confucianism sees happiness to be in constant self-cultivation to achieve moral greatness, Taoism regards happiness to be derived from following “Tao,” the Great Natural Force, and personal liberation from human desires. Happiness in Buddhism can only be found in the other world after “nirvana,” imbued with eternal bliss beyond everyday misery of this world (Lu, 2001). Burkholder’s (2005) study based on a Gallup survey found that Chinese happiness almost remained constant in recent decades; similar findings were disclosed by Crabtree and Wu (2011) and Easterlin et al. (2012). On the other hand, the think tank organization PEW Research Cen-tre (2011) revealed that Chinese nationals experienced rising life satisfaction along with rising incomes. In a cross-sectional study, Lee (2005) studied 109 randomly selected Chinese people aged 60 in Hong Kong and mainland China, and found that mental health status, number of days staying in hospital, life satisfaction, age, and self-esteem were significant factors predicting these elderly Chinese people’s happiness.


Recently, Easterlin and his colleagues (2012) found that China experienced a U-shape pat-tern of life satisfaction from 1990 to 2010. They further concluded that life satisfaction in China has declined remarkably among the lowest income and least educated segments of the popula-tion; however, rising life satisfaction was found among the upper socioeconomic stratum. Re-search on Chinese people’s subjective well-being (SWB) has found that among different samples, SWB was found to be positively correlated with income, good health, being married, female and a Community Party member (Appleton & Song, 2008; Monk-Turner & Turner, 2012). In a recent study, Sun et al. (2015) found that among a national sample of 8,000 Chinese respondents, SWB increased with levels of subjective health, income and education, but was lowered among unemployed and divorced individuals. However, after controlling for socioeconomic character-istics and subjective health status, SWB was also found to be higher in rural areas than urban areas in the same region. However, whether there is a rural-urban divide of Chinese happiness is not clear. Davey, Chen and Lau (2009)’s study on a sample of Chinese peasants living in a remote farming village found that despite the respondents’ relatively low socioeconomic condi-tions, their reported life satisfaction levels were still within the normative range for the Chinese population.

With intensifying income inequality in China, some researchers have attended to study-ing the relationship between inequality and happiness (Jiang, Lu, & Sato, 2012; Smyth & Qian, 2008). Smyth and Qian found that high income individuals who perceive unequal income dis-tribution reported higher levels of happiness while low income individuals who perceive income inequality report lower levels of happiness. Zhu and Xie’s (2015) analysis on the survey data in 60 counties of China from 2005 to 2010 revealed that Chinese people’s life satisfaction does not vary much with regional differences in economic development but closely relates to temporal changes of local level economic development over time. In summary, the current research on Chinese happiness acknowledged that socioeconomic variables are closely associated with hap-piness; however, with the fast social and economic changes in China, Chinese people’s happiness as determined by temporal changes need to be further addressed. Particularly, social life changes such as the increased leisure time and leisure activities among Chinese nationals need to be ex-amined in explaining Chinese happiness.

The Role of Leisure in HappinessThe relationship between leisure and happiness has been extensively studied. Spiers and

Walker’s study demonstrated that lasting happiness was influenced by involvement in leisure activities that produce flow experiences (Csikszentmihalyi, 1975; Diene, 2000). It is believed that leisure activity, as an antecedent of leisure satisfaction (Ragheb & Tate, 1993) can also be-come the best predictor of happiness (Spiers & Walker, 2009). However, a study on 8,000 Dutch respondents indicated that there was no causal relationship between leisure exercise and happi-ness, despite that exercise participation was associated with higher levels of happiness (Stubbe, de Moor, Boomsma, & de Geus, 2007). Other researchers (e.g., Rojas, 2006) also question that the causal relationship between leisure exercise and happiness may not be valid.

Many research studies supported the positive relationship between leisure and happiness. Lu and Argyle (1994) found that leisure satisfaction is correlated with happiness, and social aspects of leisure satisfaction predicted happiness on a longitudinal basis. Leisure activities were found to be a major source of happiness (Hills & Argyle, 1998, Lloyd & Auld, 2002). For example, church activities were found to produce resonating emotions, often accompanied by feelings of great joy; these activities seem to be an important determinant of well-being, especially for elderly people (Hills & Argyle, 1998). Hills and Argyle also noted that given the available leisure


activities, individuals’ personality might influence personal choice in leisure, and then affect the degree of happiness. This view is consistent with Kahneman’s theory of “hedonic adaptations,” which stresses that individual happiness is determined primarily by personality and genetics. Sakkthivel (2011) disclosed that nonmonetary leisure behavioral styles (e.g., reading novels, watching television, outdoor game, cycling, fishing) provided higher happiness than monetary leisure behavioral styles (e.g., visiting entertainment centers, visiting night clubs, visiting casi-nos, scuba diving). Studies have found that when controlling for demographic variables (e.g., employment, social class, and gender), a strong correlation between leisure satisfaction and hap-piness is evident (Ateca-Amestoy, Serrano-Del-Rosal, Vera-Toscano 2004; Van Praag & Ferrer-i-Carbonell, 2004). Generally speaking, leisure plays a significant role in affecting individual happiness (Wang & Wong, 2011).

Bonke, Deding, and Lausten’s (2009) work provided more insights in understanding the relationship between leisure and happiness. Firstly, they noted that leisure satisfaction depended on both the quality and quantity of leisure. The quality of leisure is reflected on two dimensions: good intensiveness and social intensiveness. The good intensiveness of leisure is expressed by ex-penditures on leisure goods (e.g., sports equipment or hobby items), while the social intensive-ness of leisure can be shown by the number of family members and friends and social activities. Empirical evidence showed that good intensiveness is more important for men, while social intensiveness is more important for women (Bonke et al., 2009). Secondly, holding the tradi-tional theory of economic well-being, Bonke et al. assume that income and leisure time are the main sources of utility for well-being. They further argue that while money (income) and time (leisure) can be substitutes to each other, satisfactions with these two domains are seemingly complementary. To enjoy income, one has to have free leisure time; and to enjoy leisure, money for leisure activities is needed. Therefore, income and leisure should be considered together as determinants to happiness. Thirdly, they found that intra-household effects and individual char-acteristics mattered more for women than men for both economic and leisure satisfactions.

There also exists other empirical evidence to support intra-household effects on well-being. For instance, Burton and Phipps (2007) examined the association between children’s well-being and parents’ leisure time spared with children in the UK, the US, Canada, Germany, and Sweden. They found that children’s well-being could be reduced due to their parents’ effort to increase work hours to generate more money.

In summary, the literature suggests a well-established relationship between leisure satisfac-tion and happiness. On such a basis, we proposed both leisure time and leisure activities would be significantly related to people’s happiness in China.

Chinese Leisure and HappinessThere has been little research examining the relationship between leisure and happiness in

Chinese contexts. A few studies, however, focused on overseas Chinese or Chinese residents in Hong Kong, Macao or Taiwan. Spiers and Walker (2009) examined how ethnicity and leisure sat-isfaction are related to happiness among Chinese Canadians and British Canadians. They found that ethnicity is significantly associated with standard of living, life achievement and life as a whole. In addition, overall leisure satisfaction significantly affected happiness; and happiness and personal relationships were positively correlated for some Chinese Canadians. In a study of university students in Taiwan, Lu and Hu (2002) found that leisure had short-term benefits, which include positive mood, physical fitness and better structuring of time, as well as long-term effect on happiness. In a later study, Lu and Hu (2005) examined the relationships among per-


sonality, leisure involvement, leisure satisfaction and happiness. The study findings revealed that 1) neuroticism was not correlated to leisure activities, 2) extraversion was positively correlated with leisure satisfaction, and 3) leisure satisfaction had incremental effect on happiness. Simi-larly, Vong (2005) studied Chinese residents in Macao and found a positive correlation between leisure satisfaction and emotional well-being.

In summary, the literature informs that leisure is associated with happiness, and happiness varies with different demographic variable (e.g., gender, age, income). However, in the context of contemporary China, the relationships between leisure, demographics and happiness may be subject to both cultural and societal influences. Leisure time is needed for people to enjoy leisure activities. However, under the influence of the Confucian tradition, people may prefer the qual-ity of leisure time to the amount of leisure time they have (having too much leisure time or idling is not appreciated in a Confucian culture). Therefore, leisure time may serve as a necessary con-dition for performing leisure activities that will eventually affect happiness; but its incremental value may be limited. Similarly, people in China may see values associated with different leisure activities differently based on their cultural preferences. Hence, some leisure activities may be associated with happiness more than others. From a social policy making perspective, it is im-portant to know which leisure activities leverage happiness. In China’s fast social and economic transformation, different social groups may face different social expectations and living pressure, the current social milieu may determine some demographic variables to be more prominent than others in explaining happiness. For instance, as ostentation appears a prevalent social phe-nomenon in China, the association between income and happiness in China is expected to be more significant than that in other countries. To further clarify the relationship between leisure and happiness and that between demographics and happiness in China, the following specific research questions are formulated in the current study:

RQ1: How is leisure time related to happiness in contemporary China?

RQ2: How are different leisure activities associated with happiness in contemporary China?

RQ3: What are the relationships between sociodemographic characteristics and hap-piness in contemporary China?

Methods

Data CollectionData for this study came from the Survey of the Chinese Economic Life (SCEL). SCEL is

an annual national survey jointly conducted by the China Central Television (CCTV), the Chi-na National Bureau of Statistics (CNBS) and the General Post Office of China (GPOC). In the implementation of the SCEL survey, CCTV is in charge of promoting and releasing the results; GPOC is responsible for delivering and collecting returned questionnaires through the national post system, whereas CNBS takes charge of coding and data screening. The Survey has been in operation since 2006. All respondents of the SCEL are residents in mainland China. We sourced our data from the 2011 SCEL survey.

The 2011 SCEL survey was administered through the General Post Office of China (GPOC). The GPOC is the central post authority in charge of the national post system in China. The SCEL questionnaire was printed on postcards with prepaid return postage. GPOC appointed special postal employees to distribute the SCEL postcard questionnaires.


The 2011 SCEL survey data were collected from all 31 provinces, autonomous regions, and municipalities of Mainland China from May 2011 to February 2012. A total of 100,000 question-naires were distributed across Mainland China by local postal employees. Each city/village post office was given a certain number of questionnaires based on the population of the area; post de-livery staff randomly delivered the postcards questionnaires to the households by using methods like delivering a postcard to every ith household in a street. In order to minimize omissions, im-properly completed surveys, and to overcome the problem of limited literacy, postal employees recorded the responses to the survey. The postmen were then responsible for mailing the surveys to the Computing Center of CNBS. This process yielded 73,622 complete questionnaires with a valid response rate of 73.6%.

MeasurementsIn the 2011 survey, two questions about leisure time and leisure activities were added in

the questionnaire, enabling the examination of the effect of leisure time and leisure activities on Chinese people’s happiness. The questionnaire comprises two sections. Section One includes 14 questions, three of which referred to leisure time, leisure activity, and subjective well-being (SWB), respectively. The SWB measure was deemed a suitable proxy to happiness in the current study. Section Two consists of question items collecting demographic information of the re-spondents, including age, gender, household income, education, residence identity, and marital status.

The question measuring leisure time was: “How much leisure time (except for sleeping, schooling, and eating) on average per day do you have in 2011?” Discrete answer options to this question ranged from “none,” “less than 1 hour,” “1-2 hours,” “2-3 hours,” “3-4 hours,” “4-5 hours,” to “above 5 hours.” These answer options were coded in a 7-point scale ranging from 1 for “none” to 7 for “above 5 hours.” Following Bhat and Koppelman’s (1993) classification of everyday activities into three categories of maintenance, subsistence, and leisure activities, Zhou, Li, Xue, and Lei (2012) surveyed Chinese people’s time allocation in 2008 and found the time-use ratio among the three categories (maintenance, subsistence, and leisure activities) in China follows 60:24:16. This indicates that Chinese nationals’ daily average leisure time approximates 3.84 hours, and the range of 0 to 5 hours in soliciting leisure time is appropriate.

Leisure activities were solicited using the question “What do you usually do in your leisure time in 2011?” Respondents were asked to choose three leisure activities from the following nine listed common leisure activities: 1. Watching TV 2. Surfing the Internet 3. Reading books 4. Shopping 5. Eating out/partying 6. Exercising 7. Resting at home 8. Going to cinema/theater/stadium9. Playing cards

In designing these leisure activity items, we referred to the relevant leisure studies in China (eg., Jim & Chen, 2009; Wang, Zhang, & Gong, 1999; Zhou, Li, Xue, & Lei, 2012) to ensure the leisure activities are valid in the Chinese context. Leisure activities were coded with five dummy


variables: 1) “Passivity” is a dummy variable indicating whether the surveyed person watched TV or surfed on the Internet; “Home leisure” is a dummy variable indicating whether the sur-veyed person spent his/her time on reading books, or resting at home. “Exercising” as a dummy variable indicates whether the surveyed person spent his/her time on exercise or not. “Social-izing” indicates whether the respondent spent his/her time on social activities such as going to cinema/theatre/stadium, eating out/partying, or playing cards. “Shopping” indicates whether the respondent spent his/her leisure time on shopping.

Happiness was measured in a five-point Likert scale ranging from 1 for very unhappy to 5 for very happy. The question was stated as “How satisfied are you with your life as a whole?” This question was designed with reference to the direct report measure of SWB from Easterlin (2004), and also resembles that of the World Values Survey (WVS) and the General Social Survey (GSS) (e.g., Burt, 1984; Bruni & Stanca, 2006). Such direct report questions are useful enough in mea-suring happiness (Kahneman & Krueger, 2006). As Easterlin (2004, p. 26) pointed out, “Over the years, a substantial methodological literature has developed to consider the value of the answers to such questions. The professional consensus is that the responses, though not unproblematic, are meaningful and reasonably comparable among various groups of individuals.”

In terms of the demographic variables, annual family income information was sought on a 4-point scale: 1= below 20 thousand RMB, 2 = between 20-50 thousand RMB, 3 = between 50-100 thousand RMB, and 4 = above 100 thousand RMB. Marital status categories include un-married with boyfriend/girlfriend, unmarried without boyfriend/girlfriend, married, divorced/separate, and widowed. Other demographic variables include gender (male vs. female), resi-dence (urban vs. rural), and age (18–35 years old, 36–59 years old, or over 60 years old).

Data AnalysisData were analyzed with STATA 11.0. After data screening, ordered logit regressions were

used to examine the relationships of leisure time, leisure activities, and demographic variables with the respondents’ self-reported happiness. A diagnostic test for multicollinearity based on traditional linear regression model showed that all variance inflation factors (VIF) were not larger than 10 (Hair, Black, Babin, & Anderson, 2009); therefore, we conclude that the multicol-linearity is not an issue among the independent variables in the regressions.

The happiness equation was estimated with ordered logit regression extracted from Blanch-flower and Oswald (2004) and Easterlin (2006). The estimation equation is as follows:

Hi = bLi + gZi + ei (1)

where is the happiness score for individual i; Li represents an individual’s leisure time or leisure activities; Z is a vector of other determinants such as the demographic variables; b is the coef-ficient on the leisure measures; g represents the vector of coefficients on demographic determi-nants of happiness; ei represents the error term.

Kahneman and Krueger (2006) argued that subjective satisfaction is dependent on how people spend their time and non-work activities. Therefore, we further differentiate leisure time from leisure activities with the concept of leisure. In addition to leisure, demographic variables including age, gender, marital status, education household income, and place of residence were also included as determinants of individual happiness.

In practical terms, following Blanchflower and Oswald (2004) and Wang and Wong (2011), we specify the empirical model as follows:


happyi = α + β1’leisure-ti + β2’leisure-ai + γ1incomei + γ2marriagei + γ3edui + γ4agei

+ γ5urbani + γ6Malei + γ7provi + εi (2)

where happyi is the dependent variable happiness. Leisure-ti indicates individual i’s leisure time. Leisure-ai is the vector of individual i’s leisure activities. Incomei, marriagei, edui, agei, urbani and Malei are explanatory demographic variables. Provi refers to the vector of province-specific dummy variables that are used to capture unobservable characteristics to affect an individual’s happiness due to which province individual i lives in.

To estimate equation (2), we applied the ordered logit modeling approach as proposed by Han and Hausman (1990). Ordered logit modeling is an appropriate estimation method for this study as the dependent variable (happiness) was measured as an ordinal variable.

Results

The Sample Profile As shown in Table 1, the sample was more dominated by males (57.6%) than females

(42.6%). In terms of age, most of the respondents were in the 18–35 age group (46.2%) and the 36–59 age group (45.8%). Nearly 70% of the respondents were married. Most respondents held an education level at high school (48.1%) or at junior college (31.9%). More than 74.9% of the respondents were urban residents, while rural residents accounted for 25.1% of the sample. More than 40% (43.3%) of the respondents reported their annual family income in the range of 20,000–50,000 RMB yuan (exchange rate in 2011: US$1=6.46 RMB yuan), while another 33.9% of the respondents had annual family income below 20,000 RMB yuan. Comparing with the 2010 National Census data, the sample appears to have an overrepresentation of male, well-educated and urban residents in the population. When a household survey is managed, it is likely that the survey is filled by a patriarchal male family member, or those who are better educated. By the end of 2011, China’s urban population outnumbered its rural population (Bloomberg, 2012); and it is expected more Chinese residents will live in urban areas in the future. Therefore, the over-representation of urban residents in the survey reflects on the population change trend in China.

Model Estimation Findings Estimations of the ordered logit regression model were done with STATA 11.0 and the re-

sults are reported in Table 2. Results indicate that leisure time (β=0.049, p<.01) was significantly related to happiness suggesting that the more leisure time an individual has per day, the happier she/he tends to be. The odds-ratio (1.05) for leisure time indicates that those respondents with more leisure time are 1.05 times happier than those with limited leisure; judging from the odds-ratio, the association between leisure time and happiness, although statistically significant, does not seem to be strong.

Leisure activities had varied associations with happiness. Passive leisure activities (passivi-ty) such as watching TV or surfing on the Internet had a positive association (β=.052, p<.01) with happiness; however, active leisure activities such as exercising, socializing, and shopping did not affect individual happiness. Judging from mean values (0.02–0.06) of these active leisure activi-ties (Table 2), it can be concluded that these active leisure activities were not commonly practiced among the respondents. Therefore, caution needs to be applied in interpreting the insignificant relationships. In summary, as most of the leisure activities are not related to happiness, the over-all contribution of leisure activities to happiness in China seems to be limited.


In terms of the demographic variables, annual family income was found to be positively related (γ=.215, p<.01) to happiness. The predicted probability of an individual in the highest income category (over 100,000 RMB yuan) being very happy was calculated as 18.7%, higher than the probability of members from any other income groups being very happy; especially, this probability is 8 points higher than that for the lowest income group member (below 20,000 RMB yuan) to be very happy. Generally speaking, the probability of being very happy appeared to be low among all income groups.

Holding other variables constant, females tended to be happier than males in China. This finding seems to be consistent with the study results released by the Economist (2010) and the 2003 worldwide survey conducted by the PEW Research Center, but inconsistent with Strick-land (1992) who states that females are more susceptible to depression. Further analysis indi-

Table 1

Sample ProfileTable 1 Sample profile

Variable* Valid N Frequency Percentage (%)* Gender 73622 Male (Male) 42402 57.6 (50.9) Female (Female) 31220 42.4 (49.2) Age(year) 18-35 (15-39) 33998 46.2 (48.9) 36-59 (40-59) 33741 45.8 (35.1) Over 60 (Over 60) 5883 8.0 (16.0) Marital status 73622 Unmarried with boyfriend/girlfriend 10941 14.9 Unmarried without boyfriend/girlfriend 8753 11.9 (Unmarried) (21.6) Married (Married) 50280 68.3 (71.3) Divorced (Divorced) 2401 3.3 (1.4) Widowed (Widowed) 1247 1.7 (5.7) Education 73622 Primary school or below 6807 9.2

(Primary school or below) (29.1) secondary school or secondary technical school

35440 48.1

(Junior high school) (43.6) (Senior high school) (16.7) Junior College (Junior College) 23498 31.9 (6.2) Bachelor degree or above 7877 10.7 (Bachelor degree or above) (4.5) Annual family Income (RMB Yuan) 73622 0-20,000 24931 33.9 20,000-50,000 31869 43.3 50,000-100,000 13722 18.6 Over 100,000 Residence

73621

3100 4.2

Urban (Urban) 55168 74.9 (31.9) Rural (Rural) 18453 25.1 (68.1)

*contents in parentheses are demographics and figures compiled from the 6th National Census of China in 2010.


cated that the predicted probability of a female being very happy was less than 5%, the probability of a female being very unhappy was 13.7%. The predicted probability of a female being just happy was 42.4%.

Age had no significant correlation (γ1=-0.016, p>.10) with happiness. This result is con-sistent with the U.S. happiness study conducted by Wang and Wong (2011), but not consistent with Wallis (2005), Jha (2008) and Bakalar (2010), who all argue that people are most likely to become depressed in middle age and experience “midlife crisis.” Easterlin (2006), on the other hand, found that in the United States until people approach 50 years old, the growing satisfaction with family life and work would continue to outweigh declining satisfaction with health and thus contribute to overall happiness.

The coefficients of dummy variables of “secondary school or secondary technical school,” “junior college” and “bachelor degree or above” were all statistically significant and negative, implying that people with higher education levels were generally less happy than those only receiving primary school education. However, judging by the absolute value of the coefficients, secondary school leavers (-.0113) may be less happy than junior college graduates (-0.065), and those holding bachelor or above degrees (-0.076).

Results indicate that urban respondents (γ=0.089, p<.01) appeared happier than rural re-spondents. This finding implies that the overall life satisfaction of urban residents may be higher than that of rural residents in 2011. It also supports a general view that happiness levels may fluctuate between urban and rural residents in China. According to a survey conducted by the Chinese Academy of Social Sciences (CASS), the average happiness level of urban residents was lower than that of rural residents in 2000–2005, higher in 2006, and became lower again in 2007–2010 (CASS, 2011). Some studies (e.g., Davey, Chen, & Lau, 2009; Sun et al., 2015) suggest rural residents may be happier than their urban counterparts or at least enjoy the same level of perceived life satisfaction as their urban counterparts in China. However, whether rural lifestyle would produce happy life or not is still unanswered. The findings of our study suggest that with the rapid urbanization in China, urban people are feeling happier than their rural counterparts. There may be profound societal reasons to explain. With China’s effort to turn rural communi-ties into small urban dwellings (The Economist, 2014), rural lifestyles in China are gradually en-croached and urbanized. This may cause rural residents to change their reference income group from a rural standard to an urban standard which eventually will cause them less happy (Jiang, Lu, & Sato, 2012; Smyth & Qian, 2008).

Taking the divorced respondents as reference group, people in other marital status catego-ries tended to be happier. Married people (γ=0.637, p<.01) seems to be the happiest, followed by those unmarried with boy/girl-friend (γ=0.560, p<.01), those unmarried without boy/girl-friend (γ=0.423, p<.01), and Widowed (γ=0.155, p<.01). Finally, taking Beijing as the reference variable, we found most provinces in South China, say, Shanghai (γ=-0.401 , p< .01), Chongqing (γ= -0.300, p< .01), Zhejiang (γ= -0.294, p< .01), Guangdong (γ= -0.319, p< .01), and Hainan (γ=-0.248, p< .01) exhibited significant negative coefficients. This result suggests that people living in North China are relatively happier than those in South China. This corresponds to a report elaborating on provincial differences of leisure and happiness in China using the same data source (eChinacities.com, 2012). The report disclosed a dichotomy between northern and southern cities for “happiness” and “leisure” rankings. While the top 10 “happiness” provincial capital cities are mainly from northern China, 8 of the top 10 “leisure” capital cities are located in southern China.

25

H

appiness 2.40

0.98

Male

-0.135*** (9.76)

0.872*** (9.76)

[0.845, 0.90] A

ge

-0.016 (1.35)

0.983 (1.35) [0.96, 1.01]

Single with girl/boy-friend

0.560*** (12.85)

1.750*** (12.85)

[1.61, 1.92] Single w

/o girl/boy-friend

0.423

*** (9.55) 1.527

*** (9.55) [1.40, 1.67]

Married

0.637*** (15.94)

1.891*** (15.94)

[1.76, 2.05] W

idowed

0.155* (2.31)

1.168* (2.31)

[1.03, 1.34] Secondary school

-0.113** (4.42)

0.892** (4.42)

[0.841, 0.931] Junior college

-0.065* (2.40)

0.936* (2.40)

[0.89. 0.99] bachelor degree or above

-0.076* (2.31)

0.926* (2.31)

[0.87, 0.99] Incom

e

0.215

*** (23.15) 1.239

*** (23.15) [1.22, 1.26]

Urban

0.089*** (5.50)

1.093*** (5.50)

[1.06, 1.13] Leisure tim

e 2.65

1.59 0.049

*** (11.00) 1.050

*** (11.00) [1.04, 1.06]

Passivity 0.71

0.44 0.052

** (2.87) 1.053

** (2.87) [1.01, 1.09]

Exercising 0.02

0.14 -0.044 (0.53)

0.956 (0.53) [0.81, 1.13]

Socializing 0.03

0.17 0.051 (0.76)

1.053 (0.76) [0.92, 1.20]

Shopping 0.06

0.23 0.028 (0.84)

1.028 (0.84) [0.96, 1.10]

Province dumm

y

controlled

controlled

Cut 1

-2.236

C

ut 2

-1.255

Cut 3

0.958

C

ut 4

2.651

χ2 (prob > χ

2)

2451.61 (0.000)

Pseudo R2

0.02

O

bservations.

73,622

Note: A

bsolute t values are reported in parentheses. ***, **, * stand for .01, .05, and .10 significance level, respectively. 'Hom

e leisure' was

taken as reference variable for leisure activities, and 'divorced' was taken as reference variable for m

arital status categories, and “primary school

or below” w

as taken as reference variable in the education level categories in the regression and therefore are not listed.

Leisure and Happiness in China • 567Table 2

Ordered Logit R

egression Model of H

appiness in China (2011)

Variable

M

ean S.D

. Coeffi

cient O

dds Ratio

95% C

onfidence

Interval

25

H

appiness 2.40

0.98

Male

-0.135*** (9.76)

0.872*** (9.76)

[0.845, 0.90] A

ge

-0.016 (1.35)

0.983 (1.35) [0.96, 1.01]

Single with girl/boy-friend

0.560*** (12.85)

1.750*** (12.85)

[1.61, 1.92] Single w

/o girl/boy-friend

0.423

*** (9.55) 1.527

*** (9.55) [1.40, 1.67]

Married

0.637*** (15.94)

1.891*** (15.94)

[1.76, 2.05] W

idowed

0.155* (2.31)

1.168* (2.31)

[1.03, 1.34] Secondary school

-0.113** (4.42)

0.892** (4.42)

[0.841, 0.931] Junior college

-0.065* (2.40)

0.936* (2.40)

[0.89. 0.99] bachelor degree or above

-0.076* (2.31)

0.926* (2.31)

[0.87, 0.99] Incom

e

0.215

*** (23.15) 1.239

*** (23.15) [1.22, 1.26]

Urban

0.089*** (5.50)

1.093*** (5.50)

[1.06, 1.13] Leisure tim

e 2.65

1.59 0.049

*** (11.00) 1.050

*** (11.00) [1.04, 1.06]

Passivity 0.71

0.44 0.052

** (2.87) 1.053

** (2.87) [1.01, 1.09]

Exercising 0.02

0.14 -0.044 (0.53)

0.956 (0.53) [0.81, 1.13]

Socializing 0.03

0.17 0.051 (0.76)

1.053 (0.76) [0.92, 1.20]

Shopping 0.06

0.23 0.028 (0.84)

1.028 (0.84) [0.96, 1.10]

Province dumm

y

controlled

controlled

Cut 1

-2.236

C

ut 2

-1.255

Cut 3

0.958

C

ut 4

2.651

χ2 (prob > χ

2)

2451.61 (0.000)

Pseudo R2

0.02

O

bservations.

73,622

Note: A

bsolute t values are reported in parentheses. ***, **, * stand for .01, .05, and .10 significance level, respectively. 'Hom

e leisure' was

taken as reference variable for leisure activities, and 'divorced' was taken as reference variable for m

arital status categories, and “primary school

or below” w

as taken as reference variable in the education level categories in the regression and therefore are not listed.


Discussion

The purpose of this study was to examine how leisure time, leisure activities, and demo-graphic factors affect people’s happiness in China. Ordered logit regressions indicated that both leisure time and leisure activities were associated with happiness. As for demographic variables, income was a significant predictor to happiness. However, education levels had varied effects on happiness. The lowest education group seems to have the highest level of happiness; secondary school leavers tend to be mostly unhappy, while junior college graduates tended to be happier than both secondary school leavers and bachelor-or-above degree holders. Furthermore, urban residents, married people, and females tended to be happier than their respective counterparts. However, age was not associated with happiness.

It is not surprising to find that more leisure time would lead to higher levels of happiness, given that leisure time serves as a necessary condition for individual’s life satisfaction or happi-ness1 (Bonke, Deding, & Lausten, 2009; Burton & Phipps, 2007; Kahneman & Krueger, 2006). Commonly, a positive and moderate relationship between leisure time and happiness emerges (Singh & Joseph, 1996). This could especially apply to the busy and fast-paced urban Chinese life. People in urban China would yearn for more leisure time as more leisure time seems to make them happier. However, in this specific study context, the relationship between leisure time and happiness, although statistically significant, was not strong. Therefore, the contribu-tion of leisure time to happiness should not be overestimated. As Bonke et al. (2009) suggested, happiness may be determined by both quality and quantity of leisure. While leisure time may represent the quantity feature of leisure, the quality of leisure may be more important in generat-ing an individual’s sense of happiness. On the other hand, only passive activities were found to be associated with happiness. This empirical finding is inconsistent with Wang and Wong’s (2011) study, which found no relationship between leisure time and happiness. Such a difference may be attributed to the different social and economic development stages in the two countries. Other than that, Wang and Wong’s use of weekly working hours as the proxy of leisure time may be less accurate than our direct measurement of leisure time.

Besides leisure time, leisure activities are commonly regarded as major sources of happiness (Hills & Argyle, 1998). Furthermore, active leisure (e.g., exercise) may have different effect on happiness from passive leisure activities (e.g., watching TV) (Kahneman & Krueger, 2006). The current study revealed two interesting findings in China: 1) passive leisure activities (watching TV and surfing on the Internet) had a significant positive relationship with happiness; and 2) active leisure activities (e.g., exercising, shopping), however, were not significantly associated with happiness.

As for the first point above, although watching TV is a kind of passive activity, it is not surprising to find a positive relationship between such activity and happiness. There is some evidence that TV shows can create a cheerful and sociable state although watchers may describe it as drowsy and passive (Kubey & Csikszentmihalyi, 1990). It was also found that frequent soap TV drama watchers were happier than others (Lu & Argyle, 1993). In addition, according to theories of social motivation, leisure activities (including watching TV and surfing on the Inter-net) can enhance individuals’ happiness by meeting some social needs (Hills & Argyle, 1998). In Hills and Argyle’s study, watching TV was found to contribute to happiness, although its effect on happiness was less than that of other active leisure activities.

1Happiness and life satisfaction could be treated as interchangeable measures of overall feelings of well-being, that is, of subjective well-being (Easterlin, 2004).


It is somewhat out of our expectation that active leisure activities were not found as predic-tors of happiness in our study. Many studies have provided empirical support that that active leisure activities (such as exercising and socializing) enhanced happiness. Exercise can produce a state of reduced tiredness, more energy, and less tension, anger, and depression (Steptoe & Bolton, 1988), and a high level of joy after excercise can enhance happiness (Argyle, 1996). In Csikszentmihalyi and Hunter’s (2003) study, the highest level of happiness was reported when participants engaged in social activities (e.g., talking with friends). The insignificant effects of ac-tive leisure activities on happiness in this study may be explained in the following aspects. Firstly, culture may be an essential reason. Under the influence of Confucianism, Chinese people are work oriented and usually hold a negative attitude toward leisure (Li, 2009). To Chinese people, leisure may appear to be a means to achieve a tranquil and peaceful life (Wang & Stringer, 2000). Active leisure activities such as socializing and shopping may be considered as opposing a peace-ful life. Leisure may be highly related to rest and relaxation for Chinese people. Consequently, such quiet and relaxing activities as watching TV and surfing on the Internet may be perceived more positively as leisure activities that can enhance Chinese happiness. Moreover, the Chinese idiom of “strong limbs, simple mind” clearly shows a disapproving cultural attitude toward ex-ercising activities for physical strength (Qin, Way, & Rana, 2008). This may partly explain why exercising did not have a positive effect on happiness. Secondly, the self-efficacy theory may offer further explanations. As noted by Bandura (1977), people enjoy leisure activities that they are good at. Self-efficacy can predict whether individuals will continue to engage in the same lei-sure activity (McAuley, 1992). The Western sense active and serious leisure (Stebbins, 2007) still seems to be distant to common people’s life in China. Chinese nationals seem to lack interest, appreciation, and skills to engage in active leisure activities. As there has been a void of educa-tion for leisure as promoted by Brightbill (1961)2 in China, young people in China mostly feel incompetent or even helpless in understanding what leisure really means (Sun, 2002; Shi, 2005). Consequently, people in China may not take sufficient joy or happiness out of active leisure ac-tivities. Thirdly, it is also likely that these active activities may work as endogenous variables to happiness, rather than determinants. If an individual feels unhappy and wants to have a change of mood during her/his leisure time, she/he may decide to do more exercises, shop (especially for urban females in China, see Lee & Zhang, 2010), or attend more social activities such as getting together with friends or relatives. Finally, we need to reiterate that judging from the mean scores of these active leisure activities, it seems most people in China are not taking active leisure ac-tivities. Therefore, there may be an issue whether these activities have the cross-cultural validity towards respondents in China.

In our study, females were found to be happier than males. This is consistent with Wang and Wong’s (2011) study in which females in the United States were found to be happier than males. In the literature, contrasting findings could be found regarding the relationship between gender and happiness. While some studies confirmed that gender was related to leisure satisfac-tion and life satisfaction or happiness (e.g., Brown, Frankel, & Frennell, 1991; Juniu, 1997), Spiers and Walker’s study (2009) indicated that gender had no correlation with happiness. The societal context should be scrutinized in explaining such differences. In China, men would be expected to take more responsibilities in raising a family and dealing with various social relations. It is understandable that males may face more pressure than females in a patriarchal society like China. Recent societal changes, such as decreased housing affordability and social disillusions

2Charles Brightbill, one of the first scholars to study education for leisure wrote that “education for leisure is the process of helping all persons develop appreciations, interests, skills, and opportunities that will enable them to use their leisure in personally rewarding ways” (Brightbill, 1961).


among Chinese youth (Szablewicz, 2014), may have put more pressure on males than females. Nevertheless, it is worth noting that the current study provided a counter-case to previous stud-ies by identifying that gender is uncorrelated with life satisfaction and happiness (e.g., Cavette, 1999; Csikszentmihalyi & Hunter, 2003).

Our study findings indicated that income is positively related to happiness, married cou-ples are generally happier than singles, and urban residents report significantly higher happiness levels than rural residents. These results are mostly consistent with previous happiness studies conducted in other countries and historical periods. Kahneman and Krueger (2006) showed that income had a moderate correlation with happiness cross-sectionally, but such correlation did not hold longitudinally. The current study used cross-sectional data and found a similar relationship between income and happiness to Kahneman and Krueger’s. Some researchers have argued that relative rank of income in the society or in one’s peer group is more important than the absolute level of income (Clark & Oswald, 1996; Luttmer, 2005). As for the relationship of marriage and marital status with happiness, most psychologists, sociologists and economists have agreed that establishing close and intimate relationships through marriage would typically make relationship partners happier and more satisfied with life in general (Easterlin, 2004). This seems to be confirmed by the current study.

Most happiness study survey samples tend to be disproportionately overwhelmed by urban respondents (cf. Inoguchi, 2008, PEW Research Center, 2011). Our study enabled a more com-prehensive sample including both urban and rural respondents. In China, the average income and quality of life in urban areas are higher than that of rural regions. Thus, despite that in the literature, some studies showed a positive relationship between rural lifestyle and happiness (Davey, Chen, & Lau, 2009), it is not surprising to see urban residents happier than their rural counterparts in China, as both income and quality of life are positively related to happiness (Van Praag, Frijters, & Ferrer-i-Carbonell, 2003). Glaeser (2011) also contends that cities offer benefits and amenities that make people richer, smarter, greener, healthier, and happier. However, Berry and Okulicz-Kozaryn (2011) noted that in the United States, in contrast to many other parts of the world, people’s happiness rises from its lowest levels in large central cities to its highest levels in small towns and peripheral rural communities. In a transition economy such as China’s, the urban-rural happiness divide may be volatile in the long term.

Our study found that age was not associated with happiness. This is not consistent with pre-vious studies. Prior research has shown that life satisfaction or happiness often increases along one’s life cycle, or at least does not drop when age increases (Argyle, 2001). More recent studies revealed an inverted U shape for the average trajectory of life cycle happiness (Easterlin, 2006; Mroczek & Spiro, 2005). But as all these studies applied point-of-time comparisons of happiness with age (Easterlin, 2006), the generalization about life cycle experience would be question-able, because respondents of different ages in such comparisons are persons from different birth cohorts with different life histories. Therefore, the age-happiness relationship should always be interpreted with considerations of the historical and social contexts.

The literature generally informs that education is positively associated with happiness (Blanchflower & Oswald, 2011; Oreopoulos, 2003). However, in our study, the relationship be-tween education and happiness appeared to be nonlinear and quite contradictory to what the literature shows. The lowest education group seems to have the highest happiness level; univer-sity graduates seem to be less happy than junior college graduates while secondary school leavers appeared to be the most unhappy cohort. Once again, China’s social and economic restructuring in the recent decades may help explain such an unusual education-happiness relationship. It


is likely that secondary school leavers are among those most affected by the economic reform (e.g., laid-off workers). They may perceive a significant degradation of quality of life in the social transition process. People holding primary school education or below may be from the older generations and may not feel such an impact pronouncedly. On the other hand, those who have received higher education may face high workplace pressure and competition as professionals in their career life (Headey & Wooden, 2004; Veenhoven, 1996; Wang & Wong, 2011). Nonethe-less, the education-happiness relationship seems less ascertained in China and needs further empirical tests.

Conclusion and Implications

Although considerable research has been conducted in examining the relationship between leisure and happiness, little is known on such relationships in the context of China. This study employed a large-scale nationwide survey to examine the relationships of mainland Chinese residents’ leisure time, leisure activities, and demographics with their happiness levels. The study disclosed that leisure time has a positive association with happiness among respondents in Chi-na. Accordingly, some practical implications can be generated. In China, institutionalized non-working holidays reach 115 days, approximating the 114 nonworking days in the United State as prescribed by law (Office of Personnel Management of the United States, 2012). However, un-paid overtime work is common with companies and factories in China, especially with Chinese family businesses (Ohlson, 2007). To improve workers’ well-being and happiness in China, it is essential to strictly implement the Labor Law and make sure annual paid leave be realized and overtime work be compensated in all enterprises.

This study revealed that while passive leisure activities (e.g., watching TV, surfing on the In-ternet) are related to happiness, active leisure activities (e.g., exercising, socializing, shopping) do not seem to contribute to happiness in China. A possible lack of capability and skills in active and serious leisure activities may be a reason that these leisure activities do not contribute to happi-ness at the current stage (Shi, 2005; Su, 2010). Leisure education should be advocated to enhance the leisure literacy among the general public. Our study also confirmed the possible correlation between income and happiness in the Chinese context. The Chinese government should be alert on such a finding as it means that income inequality in China could possibly create well-being and happiness inequality among social members.

Our study set the stage for further research examining leisure and happiness in China. Fu-ture research could include leisure satisfaction in the model as quite a number of studies proved that leisure satisfaction has a positive effect on happiness (Hills & Argyle, 1998; Lloyd & Auld, 2002; Wang & Wong, 2011). Limitations of this study include 1) only cross-sectional data were collected; therefore, the generalizability of the findings is also discounted as noted by Easterlin (2006); 2) leisure activities in this study were classified into five categories with nine types, much less than those listed in some previous studies (e.g., leisure activities were classified into 28 types in Lee and Zhang (2010), 27 types in Leung et al. (2011) and 12 types in Walker, Halpenny, Spi-ers, and Deng (2011)). While our questionnaire remains very concise and straightforward for a large-scale national survey, it is likely we may miss some regionally or locally relevant leisure activities (e.g., city square group dance) that may be significant in creating happiness.


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