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Introduction

Residential happiness has become crucial to the government’s ultimate goals worldwide. The government has endeavored to enhance residents’ happiness through various policies, such as improving healthcare, education, and environmental quality and narrowing income disparities (Kim and Koh, 2022; Yuan et al., 2018; Zhang and Awaworyi Churchill, 2020; Zhou et al., 2023; Zuo et al., 2023). These aspects are closely linked to residents’ lives and enhance people’s happiness. However, an intriguing phenomenon is that happiness does not always align with improving these conditions. Taking China as an example, despite the GDP being the second largest in the world, China ranked only 60th in global happiness from 2021 to 2023 (Helliwell et al., 2024). Therefore, this presents a challenge in terms of how to enhance further the happiness of residents, especially those in developing countries.

Pursuing happiness has inspired numerous studies on happiness management (Ruiz-Rodríguez et al., 2023). Among these, the role of the social environmental setting has garnered widespread attention (Cueto and Jambrino-maldonado, 2024), particularly the civilization level, as a measure of social environmental quality. Yang et al. (2023) argue that in many developing countries, including China, rapid urbanization has not correspondingly improved the civilization among citizens, and these issues have severely undermined the residents’ life quality and happiness. However, there is currently a lack of understanding of the impact and mechanisms of civilization on residents’ happiness because it is extremely challenging to provide empirical evidence. On the one hand, measuring civilization is difficult. Civilization does not solely refer to narrow definitions of civil behavior but encompasses a broad sense that includes economic, political, social, cultural, and ecological dimensions of civilization. On the other hand, the improvement of civilization often coincides with changes in other factors affecting residents’ happiness, such as the behaviors of businesses and governments, which can introduce noise into identifying causal effects.

This study aims to fill the gaps in the research by examining the effect of happiness on China’s civilized city program (CCP). Starting from 2005, the CCP, as a representative policy aimed at comprehensively enhancing city development and social harmony, is considered the highest honor in city governance (Zhang et al., 2021). Civilized cities are selected every three years, recognizing over 146 prefecture-level civilized cities across six selection waves. Each round of selection in China triggers a fervor of construction campaigns featuring diverse and highly competitive assessment criteria. These assessment indicators include civilization’s economic, political, social, cultural, and ecological dimensions. They are closely intertwined with residents’ daily lives and should significantly impact residents’ happiness within the city. To this end, this study proposes the following questions: Can the title of a civilized city enhance residents’ happiness? If so, what are the potential mechanisms? What heterogeneity exists among individuals in different cities?

This paper uses the selection of the CCP as a quasi-natural experiment to empirically examine the impact and mechanisms of the CCP on residents’ happiness. This approach avoids the difficulty of measuring the level of civilization, and the gradually rolled-out policy allows us to use a multi-period difference-in-differences (DID) strategy, minimizing the confounding effects of other factors. Specifically, we use the China Family Panel Studies (CFPS), a ten-year longitudinal micro-dataset containing approximately 50,000 representative observations of Chinese residents. The dataset includes wealthy individual and household characteristics, attitudes towards life, and government actions, allowing us to examine heterogeneity and mechanisms of effect. Additionally, we investigate the impact of the CCP on environmental attitudes and income inequality, which are essential measures of residents’ happiness in the future.

Our study contributes to several strands of literature. Firstly, we contribute to the field of happiness management from the perspective of civilization. Examining the interplay between government policies and individual happiness has become a focal point of happiness management (Frijters et al., 2020). Existing literature has investigated the impact of social security, environmental protection, and retirement policies on residents’ happiness (Bonasia et al., 2022; Easterlin, 2013; Li and Xie, 2023; Liu et al., 2020; Zhang et al., 2022). However, little literature focuses on how civilization influences residents’ happiness. Our research provides new insights into enhancing residents’ happiness from the perspective of civilization.

Secondly, we enriched the assessment of the welfare consequences of the CCP. It is believed to bring significant improvements in public services such as education, healthcare, and ecology within cities (D. Li et al., 2022). Existing research has confirmed that regions awarded the brand of civilized city exhibit noticeable enhancements in corporate social responsibility (Chai et al., 2022), energy efficiency (B. Li et al., 2022), green innovation levels (Zhang and Hong, 2023), and environmental quality (Liu et al., 2023). However, there is still limited research on how CCP affects residents’ welfare). Distinguishing from D. Li et al. (2022), this paper not only explores the heterogeneous effects and mechanisms of the CCP on residents’ happiness but also the perceptions of environmental quality and income inequality.

Lastly, we extend the impact of tournament-style evaluation policies in politics. In recent years, the Chinese government has increasingly employed a “tournament” rather than a “one-size-fits-all” strategy to incentivize local governments to enhance residents’ welfare. Tournaments often lead to a “positional effect,” i.e., the influence of rankings. The CCP effectively incentivizes Chinese government officials to transition from “economic competition” to “performance competition”. However, the impact of such civilization-targeted tournament policies on residents’ happiness, particularly the role of the government in this process, has not been comprehensively investigated. This paper provides insights for countries that are formulating similar tournament policies.

Background

Since the beginning of economic reforms and the opening of the country, China has undergone rapid economic expansion and extensive urbanization. Local governments have pursued the large-scale expansion of cities to acquire additional land-related fiscal revenue. However, this development mode has resulted in rapid economic growth in the short-term and long-term non-sustainability issues. The CCP has emerged as a distinctive governance mode in China to guide cities’ scientific and sustainable development. The origins of the CCP can be traced back to 1986 when the State Council issued the Resolution of the Central Committee of the Communist Party of China on Guiding Principles for Building Socialist Spiritual Civilization” during the Sixth Plenary Session of the Twelfth Central Committee. This resolution called for simultaneous efforts to build material and spiritual civilization.

However, it was not until 2003 that the Central Committee for Spiritual Civilization Construction in China officially launched the nationwide CCP by issuing the “Interim Measures for the Selection and Commendation of Central Civilized Cities, Civilized Villages and Towns, and Civilized Units”. In 2005, the first wave comprising nine civilized cities was selected. As of 2023, six waves totaling over 300 civilized cities have been recognized (see Appendix A). Figure 1 depicts the distribution of different waves of civilized cities.

Fig. 1 [Images not available. See PDF.]

Distribution of Civilized Cities in China (prefecture-level).

Notes: The categorization “Wave 1” to “Wave 6” represents the sequential groups in which cities received the Civilized City designation. This paper focuses solely on prefecture-level cities in its analysis due to their higher administrative status compared to county-level cities, which have seen a notable increase since the fifth wave of civilized cities in 2017.

The selection of civilized cities can be divided into two steps. The first step is meeting application criteria and attaining the “Civilized Advanced City” status, while the second is formal evaluation. There are three basic application criteria for civilized cities: (1) Consistently maintaining a per capita GDP higher than the national average for two consecutive years. (2) Receiving a moral and ethical evaluation score for minors below 85 points. (3) Strict adherence to party integrity and anti-corruption building. During the formal evaluation phase, assessments are based on the “National Civilized City Evaluation System” issued by the Central Committee for Spiritual Civilization Construction (see Appendix B). This evaluation primarily focuses on the government, legal, cultural, ecological, market integrity, and living environment. The formal assessment is conducted as scoring, with each city’s total score comprising basic and specific indicator scores. Furthermore, the evaluation for the CCP includes an exit mechanism, which means that the title may be revoked if significant construction errors occur in a city or it fails in a random inspection.

Since the waves of the CCP, cities nationwide have allocated substantial human, material, and financial resources. They have developed detailed plans and implemented them under the requirements. In terms of policy implementation effects, existing research has found that attaining the title of civilized city enhances the officials’ likelihood of promotion, the level of urban innovation, prospects for corporate development, air quality, and tourism industry growth (Liu et al., 2023; Yao et al., 2023). Simultaneously, we believe there have been noticeable changes in residents’ happiness. As illustrated in Fig. 2, residents’ life satisfaction in civilized cities (the treated group) experienced relatively higher growth than in non-civilized cities (the control group) after 2012. However, the gap between them gradually narrowed four years approximately later. As for whether there is a causal relationship between the CCP and happiness, further empirical tests will be conducted despite both groups exhibiting a relatively consistent trend in changes before 2012.

Fig. 2 [Images not available. See PDF.]

Changes in Life Satisfaction among Residents of Civilized and Non-Civilized Cities in 2011.

Notes: The solid green line represents the life satisfaction of the treatment group, while the yellow dashed line represents the control group. The changes in residents’ life satisfaction from 2012 onwards are presented since the CFPS data is biennial starting from 2010. The vertical line indicates the time of policy implementation.

Literature review and theoretical analysis

Literature review

Happiness, as an overall evaluation of an individual’s state, reflects a lasting and stable positive emotional experience (Diener, 1984). Happiness is considered to have two main properties: subjectivity and relativity. Subjectivity means that compared to objective welfare indicators, an individual’s subjective feelings are the best judgment of their living conditions (Nikolova and Graham, 2012). Relativity means that when individuals judge whether they are happy, they often consciously or unconsciously compare themselves with others or their past (Veenhoven, 1991). Happiness is usually measured through surveys, which list various happiness levels and emotional labels, and people choose according to their situations (Liu and Netzer, 2023). Fisher (2010) argues that happiness includes three dimensions: affective well-being, eudaimonic well-being, and evaluative well-being. Feelings of joy can measure these: a sense of meaning and purpose in life and life satisfaction, respectively. However, since the different dimensions of happiness are positively correlated, some scholars believe that using a single measurement is enough to assess whether residents are happy (Steptoe, 2019). The most commonly used indicators are “life satisfaction” and “happiness level” (Helliwell et al., 2023; Perez-Truglia, 2020).

To enhance residents’ happiness, scholars have primarily focused on the impact of individual, social, and environmental factors on happiness management. The influence of personal characteristics on happiness has been extensively discussed, including factors such as age (Blanchflower, 2021), health (Bieda et al., 2019), gender (Blanchflower and Bryson, 2024; Verma and Ura, 2022), appearance (Campbell et al., 2017; Karraker et al., 2017), employment (Guerci et al., 2022; Jahoda, 1981), income (Knight and Gunatilaka, 2022), sports (Liu and Zhong, 2023) and so on. Besides, external economic development, technological connectivity, and societal harmony also have effects on happiness (Kang and Kim, 2022; Lu and Kandilov, 2021; Somarriba Arechavala et al., 2022; Su et al., 2022; Wang and Sohail, 2022; Zhang, 2020). Finally, with the increasing occurrence of extreme weather events and natural disasters globally, scholars are paying more attention to the impact of environmental conditions on residents’ happiness. For instance, environmental and noise pollution significantly affect residents’ happiness (Li and Zhou, 2020; Rehdanz and Maddison, 2008; Xu et al., 2022).

Since this paper focuses on the impact of the CCP on residents’ happiness, the policy evaluation of the CCP is also relevant to this study. A limited number of studies have examined the impact of the CCP on corporate behavior and government officials’ behavior. Liu et al. (2023) found that cities awarded the CCP significantly reduced air pollutants and greenhouse gases such as PM2.5, SO2, and CO2, primarily through promoting industrial upgrading and technological innovation. Being awarded the CCP also pressures local enterprises to improve their environmental performance (Zhang et al., 2021) and social responsibility (Chai et al., 2022). Furthermore, studies by Zhang et al. (2021) and D. Li et al. (2022) have confirmed that cities awarded the CCP are more likely to promote their leaders than non-awarded cities. D. Li et al. (2022) explained this increased probability of promotion as a performance contest model. Unlike the traditional economic contest model, the performance contest model emphasizes improving economic, political, social harmony, and ecological performance.

However, the impact of the CCP on residents’ happiness has not received enough attention. The analysis by D. Li et al. (2022) is particularly relevant to our study, which indicates that CCP incentives significant improvements in public services closely related to national happiness, such as education, ecology, and culture. It is shown to increase residents’ average happiness by 3.9%. However, their focus is primarily on the “competition” and does not explore the mechanism and heterogeneity of the happiness effect. Furthermore, their data interval is only two years, making it impossible to examine dynamic effects. This paper provides a detailed discussion about the happiness effects of CCP from novel perspectives, offering valuable insights for policy improvement.

Theoretical analysis

The honor of the CCP requires multifaceted efforts from the government to create a harmonious and civilized social atmosphere. In China, being awarded this honor means that the government needs to lead significant improvements in the city’s economic and political environment and address “urban issues” such as pollution, crime, inequality, lack of green spaces, high disease exposure, and indifferent community relations (D. Li et al., 2022). Through government efforts, cities awarded the CCP have achieved actual improvements in external social and ecological environments and increased social harmony characterized by social trust. This is why being awarded the CCP can enhance residents’ happiness.

Additionally, once a city is awarded the CCP, residents experience a high level of inner satisfaction, enhancing their sense of honor and identity as city members. According to Maslow’s hierarchy of needs, the highest pursuit of human beings is spiritual needs, represented by self-actualization. As the highest honor for cities nationwide, the CCP can satisfy individuals’ highest needs and improve their sense of city identity. Furthermore, according to behavioral economics theory, residents’ recognition of the CCP creates a positive feedback mechanism—high levels of identity recognition enhance residents’ self-efficacy and sense of belonging, which in turn motivates them to participate more actively in urban development and community activities (Heath et al., 2017). With more active participation and proactive contribution, residents’ self-efficacy and sense of belonging will continue to improve (Marshall et al., 2020; Zhang, 2016). Enhancing self-efficacy is the intrinsic key to improving happiness (Chen and Gao, 2023). Therefore, this study proposes Hypothesis 1:

Hypothesis 1: Residents’ happiness in cities awarded the civilized city title will increase.

According to the selection criteria of the CCP, the mechanisms through which the CCP influences residents’ happiness manifest in the following three aspects.

Firstly, the government must exert efforts to enhance governance ability and urban infrastructure to obtain a civilized city. Government effectiveness plays a crucial role in people’s happiness (Helliwell et al., 2023). An essential motivator for government efforts lies in the political incentives under the promotion tournament mechanism. In other words, local officials with higher political promotion incentives may pay greater attention to the CCP to seize more promotion opportunities (Zhang et al., 2021). Yang et al. (2023) found that within China’s government-led top-down system of the CCP, local governments have heightened their environmental awareness, strengthened environmental regulations, and promoted sustainable urban development. Therefore, we believe that local-government officials are incentivized to improve the city’s economic, cultural, and social aspects. This would make residents in civilized cities more keenly aware of government efforts, enhancing their happiness. Therefore, this study proposes Hypothesis 2:

Hypothesis 2: From the government’s perspective, government efforts serve as a channel through which the CCP enhances residents’ happiness.

Secondly, the CCP can enhance social trust by elevating residents’ quality and optimizing the social atmosphere. Social trust is a crucial component of social capital, providing resources to collectives and individuals through social interactions (Han, 2015). Existing research suggests that social trust can drive economic growth (Bjørnskov, 2012), improve educational quality (Coleman, 1988), enhance individual health (Rose, 2000), and ultimately increase societal happiness (Helliwell et al., 2014). In fact, as an informal social institution, the fundamental mechanisms through which social trust enhances happiness include reducing transaction costs and improving cooperation efficiency (Alesina and La Ferrara, 2002); enhancing residents’ evaluations of perceived community trust (Knack and Keefer, 1997); improving social relationships, including with strangers; and elevating perceptions of social fairness and subjective socioeconomic status (Lu et al., 2020). The CCP stimulates the overall economic development, perceived fairness, social status, and community trust in society. Consequently, this leads to a marked improvement in residents’ overall quality of life and fosters a more positive social atmosphere in civilized cities, culminating in increased residents’ happiness. Therefore, this study proposes Hypothesis 3:

Hypothesis 3: From the societal perspective, social trust serves as a channel through which the CCP enhances residents’ happiness.

Thirdly, from an individual perspective, receiving the civilized city designation will increase the residents’ sense of honor and social identity. Akerlof and Kranton (2000) introduced the concept of identity economics, suggesting that each person belongs to different categories and is assigned different identities. Each identity corresponds to distinct social norms, determining the permissible behaviors for that identity, ultimately affecting residents’ utility levels (Akerlof and Kranton, 2000). As the highest honor for Chinese cities, the CCP can easily foster an internalized, exclusive sense of identity among residents. Identity is rooted in the social environment and individual interactions, typically involving self-identification and group recognition. The government conducted extensive propaganda and mobilization activities, guiding and reinforcing residents’ collective consciousness. When residents become part of a civilized city, they start to see themselves as members of a refined community, boosting their sense of belonging, identity, and happiness. Lastly, this study proposes Hypothesis 4:

Hypothesis 4: From the individual perspective, identity recognition serves as a channel through which the CCP enhances residents’ happiness.

In summary, this paper’s theoretical framework and hypotheses are depicted in Fig. 3.

Fig. 3 [Images not available. See PDF.]

Theoretical framework and hypothesis.

Notes: This figure plots event study estimates of Eq. (2). Coefficients of periods before and after CCP and 95% confidence intervals are plotted in the figure. Regression results are reported in Appendix D.

Methodology

Data source

CFPS

The data for individual surveys utilized in this research are derived from the CFPS spanning 2010 to 2020, a nationally representative longitudinal survey conducted by the Institute of Social Science Survey of Peking University. In 2010, the CFPS conducted its baseline survey in 25 provinces/municipalities/autonomous regions across China, successfully interviewing 14,960 households and 42,590 individuals. The CFPS is conducted every two years, starting in April and lasting for about six months. These samples represent about 95% of the Chinese population. This survey collects individual, family, and community data through the probability-proportional-to-size sampling method, facilitating the examination of social and economic changes. Many studies have utilized CFPS data to investigate various issues related to happiness (Nie et al., 2021), income (Zhang and Awaworyi Churchill, 2020), education (Chen et al., 2021; Zhao et al., 2023), and health (Hou et al., 2023). We obtained an unbalanced panel dataset of 158,760 individuals by carefully matching individual and household datasets. We refined our analysis to include a balanced panel of 49,998 individuals to account for potential estimation biases arising from non-contiguous individuals. The demographic characteristics of our data can be found in Appendix C.

List of civilized cities

According to the China civilization network, civilized cities have been evaluated in six waves since 2005, totaling 146 prefecture-level cities and 163 district and county-level cities. To match with the CFPS data, we retained the lists of three batches of civilized cities, which were announced in December 2011 (23 cities), December 2014 (28 cities), and October 2017 (35 cities), respectively. The CFPS is conducted biennially, with data collection between April and August each year. Considering information lag effects, we matched the lists of civilized cities announced in the third, fourth, and fifth batches with CFPS data from 2012, 2016, and 2018, respectively. The data for the sixth wave of civilized cities announced in 2020 were not included as CFPS had already completed before the list announcement. Considering differences in city administrative levels, we include only prefecture-level cities and do not include county-level cities and districts. We finally obtained 36 civilized cities as the treatment group, with the residents of the remaining 80 cities serving as the control group.

Urban-level data

We obtained economic conditions and industrial structure data for cities from the China City Statistical Yearbook to control for city-level factors that do not vary with individual changes and may affect residents’ happiness. Additionally, we obtained the Baidu index related to environmental concerns to examine changes in residents’ environmental attitudes resulting from the CCP.

Identification strategy

This paper constructs a DID model to identify the causal effects of the CCP on residents’ life satisfaction. Since the CCP did not consider residents’ life satisfaction as an assessment indicator, it can be regarded as an exogenous shock. The multi-period DID model is as follows:

L i f e_s a t i_{i j t} = β_{0} + β_{1} C i v i_c i t y_{i j t} + X_{i t}^{'} γ + Z_{j t}^{'} λ + μ_{i} + η_{t} + ε_{i j t}

Where

L i f e_s a t i_{i j t}

represents the life satisfaction of resident i in city j at year t; if city j is selected as a civilized city in year t,

C i v i_c i t y_{j t} = 1

; X′ denotes the set of individual-level variables, and Z′ represents city-level control variables.

μ_{i}

and

η_{t}

respectively denote individual-fixed and time-fixed effects, capturing individual characteristics that do not vary over time and time-specific shocks that do not change across individuals.

ε_{i j t}

is the random error term assumed to be independently and identically distributed. The estimated coefficient

β_{1}

is the focus of this paper, measuring the average difference in life satisfaction for residents before and after their city is designated as a civilized city.

Dependent variable

This paper chooses life satisfaction as the indicator of happiness. Happiness is defined as the combination of feeling good and functioning well—the experience of positive emotions (such as joy and contentment) combined with the development of personal potential, such as having a sense of control over one’s life, having a sense of purpose, and experiencing positive relationships (Huppert, 2009). It can be measured using a single indicator, such as life satisfaction, perceived happiness, self-perceived positive emotions, or a composite index covering multiple happiness dimensions (Huppert and So, 2013). In previous literature, life satisfaction is typically defined as an individual’s subjective evaluation of their situation (Miller et al., 2019; Rose and Stavrova, 2019). Helliwell et al. (2023) also suggest that a natural way to measure the happiness level of a country is to ask a nationally representative sample of people how satisfied they are with their current lives. Therefore, we use life satisfaction as a representation of residents’ happiness.

In the CFPS questionnaire, the item used for this purpose is: “Are you satisfied with your life?” It is measured on a scale from 1 (very unsatisfied) to 5 (very satisfied). In our sample, most respondents rated their life satisfaction above 3 points, with the proportions for ratings of 3, 4, and 5 being 30.33%, 30.22%, and 29.40%, respectively. Individuals rating below 3 points constituted approximately 10.05% of the sample. The average life satisfaction among Chinese residents is 3.76 points, which aligns with findings from other related studies, such as Asadullah et al. (2018) and Zheng et al. (2023). In robustness checks, we use residents’ subjective happy scores as an alternative indicator. The item related to happiness is: “How happy are you (scored)?” using a scale of 1 (very unhappy) to 10 (very happy). This metric is measured on a scale from 1 to 10. However, due to data limitations, this indicator was only surveyed in 2014, 2018, and 2020. This results in a significant loss of sample size.

Control variables

We controlled for specific characteristics of individuals and their cities, which might also affect residents’ happiness. Firstly, the type of household registration is represented by “whether it is an urban household (Urban).” Due to the different social security systems enjoyed by urban and rural residents, this may cause differences in their happiness. Membership in the Communist Party of China (Party) is also considered, as evidence suggests that Communist Party members may be happier than non-members (Zhang et al., 2020). Given the controversial impact of age (Age) on happiness, it is also controlled. Some scholars believe that the relationship between happiness and age is non-decreasing, while other studies suggest a U-shaped relationship (Blanchflower, 2021). The perception of happiness varies with different levels of education (Edu) and thus needs to be controlled for. Health status (Health) also affects happiness, with some believing that healthier groups are happier, while others suggest that people who have experienced major illnesses or accidents may feel happier (Bieda et al., 2019; Steptoe, 2019). Marital status (Marry) and family members’ relationships are essential factors affecting happiness. Therefore, we control for family size (Fsize) as a simple proxy for family relationships. Lastly, and most importantly, family economic status is controlled for, including absolute family income (Finc), relative income level (Rinc), and family net assets (Fasset) (D’Ambrosio et al., 2020).

Furthermore, to control the differences in the development of different cities, we control for city-level factors that may influence residents’ happiness, including per capita GDP (Gdp_per), GDP growth rate (Gdp_rate), the proportion of GDP contributed by the secondary sector (Gdp_two) and the tertiary sector (Gdp_three), population density (Popu). Descriptive statistics for all variables are presented in Table 1.

Table 1. Descriptive statistics.

	Variables	Count	Mean			S.D.	Min	Max
	Variables	Count	All	Treated	Control	S.D.	Min	Max
Personal Information	Life satisfaction	54,360	3.76	3.81	3.73	1.05	1	5
	Happy Score	35,965	7.67	8.10	7.49	2.13	0	10
	Urban	54,360	0.45	0.56	0.41	0.50	0	1
	Party	54,357	0.10	0.10	0.09	0.29	0	1
	Age	54,360	48.88	47.99	49.27	13.05	16	80
	Edu	54,357	7.48	8.37	7.09	4.54	0	22
	Health	54,360	3.04	2.99	3.07	1.30	1	5
	Finc	53,791	4466.07	5010.54	4231.43	4583.65	113.33	40,000
	Rinc	53,859	2.57	2.53	2.58	1.05	1	5
	Marry
	Unmarried	54,360	0.05	0.05	0.04	0.21	0	1
	Married	54,360	0.90	0.89	0.90	0.30	0	1
	Cohabit	54,360	0.00	0.00	0.00	0.06	0	1
	Divorce	54,360	0.01	0.02	0.01	0.12	0	1
	Widowed	54,360	0.04	0.04	0.04	0.19	0	1
	Fsize	54,360	4.16	4.05	4.21	1.85	1	26
	Fasset	52,491	12.23	12.44	12.14	1.41	8.32	15.98
	Social status	54,360	2.98	2.97	2.98	1.05	1	5
	Government efforts	52,723	3.50	3.52	3.50	0.92	1	5
	Social trust	45,203	0.56	0.59	0.55	0.50	0	1
	Environment cognition	44,898	6.27	6.37	6.23	2.78	0	10
	Inequality cognition	44,847	6.83	6.97	6.77	2.49	0	10
City Information	Gdp_per	49,884	5.53	6.93	4.89	5.30	0.52	26.13
	Gdp_rate	49,884	0.08	0.09	0.08	0.08	−0.37	0.38
	Gdp_two	49,884	43.55	47.14	41.91	10.93	15.83	73.23
	Gdp_three	49,884	44.31	44.96	44.01	11.62	17.53	83.87
	Popu_density	49,884	36.14	20.29	43.41	33.89	3.78	175.96

Marry includes five categories: unmarried, married, cohabiting, divorced, and widowed. Finc is calculated using the average monthly income over the past 12 months, while Rinc is measured using residents’ perceived income levels. Popu_density is calculated as the metropolitan land area divided by the total population.

From the descriptive statistics, it can be observed that there are no significant differences in the means of most variables between the treatment and the control group. However, the treatment group exhibits higher levels of life satisfaction, per capita GDP, and the proportion of the tertiary sector compared to the control group. On the other hand, the control group has advantages in terms of family size, GDP growth rate, and per capita urban land area. It suggests that cities with more substantial economic capabilities are more likely to be awarded the title of civilized city, making it necessary to control for these factors.

Primary results

Baseline results

Table 2 reports the baseline results for Eq. 1. We can observe that the CCP significantly positively impacts the residents’ life satisfaction. Columns (1)–(4) in Panel A present the results for the unbalanced dataset, including the model without control variables, with only personal-level control variables, with both personal-level and city-level controls, and with clustered standard errors at the family level. All regressions control for individual and time-fixed effects.

Table 2. Effects of civilized city on life satisfaction.

Panel A: Unbalanced panel
	(1)	(2)	(3)	(4)
Civi_city	0.108***	0.100***	0.094***	0.094***
	(0.011)	(0.012)	(0.012)	(0.014)
Personal controls		Y	Y	Y
City controls			Y	Y
Individual FE	Y	Y	Y	Y
Year FE	Y	Y	Y	Y
Cluster	Individual	Individual	Individual	Family
R²	0.101	0.146	0.148	0.148
N	157,856	134,330	118,384	118,384
Panel B: Balanced panel
Civi_city	0.100***	0.092***	0.096***	0.096***
	(0.017)	(0.017)	(0.019)	(0.020)
Personal controls		Y	Y	Y
City controls			Y	Y
Individual FE	Y	Y	Y	Y
Year FE	Y	Y	Y	Y
Cluster	Individual	Individual	Individual	Family
R²	0.129	0.166	0.167	0.167
N	49,908	47,576	43,269	43,269

Standard errors in parentheses, ^***p < 0.01.

The results indicate that whether adding control variables or changing the clustering level of standard errors, the positive impact of CCP on the residents’ life satisfaction is statistically significant. Hypothesis 1 is confirmed. Taking Column (4) in Panel A as an example, residents living in the city awarded experienced an increase in life satisfaction by 0.094, which is statistically significant at the 1% level.

Considering that for a substantial portion of the sample, individuals in the treatment group might have dropped out for reasons such as children growing up, relocation, or survey discontinuity, our estimation results may be biased. Therefore, we transform the total sample into a balanced dataset as Panel B. Column (4) in Panel B indicates that when CCP selects a city, residents’ life satisfaction will significantly increase by 0.096 points, accounting for approximately 2.6% of the overall sample mean1. The results above all indicate that the happiness effect of CCP is robust and is consistent with D. Li et al. (2022).

Parallel trend and dynamic effect

The DID method relies on the parallel trend assumption, which assumes that the treatment group and the control group had similar trends before receiving the title of civilized city. Since the CCP launched several waves, it is necessary to establish relative time dummy variables for each wave of civilized cities. Drawing from Wang et al. (2024), we replaced the $C i v i_c i t y_{j t}$ variable in Eq. (1) with a series of biennial dummy variables, as shown in Eq. (2):

L i f e_s a t i_{i j t} = β_{0} + \sum_{k = - 4, k \neq - 1}^{k = 4} β_{k} \cdot C i v i_c i t y_{i j t}^{k} + X_{i t}^{'} γ + Z_{j t}^{'} λ + μ_{i} + η_{t} + ε_{i j t}

Where

C i v i_c i t y_{j t}^{k}

represents the period k observation of city j before/after being awarded the civilized city in year t. We selected the period one before policy implementation as the baseline group to eliminate the interference of policy anticipation effects, i.e.,

k \neq - 1

. Additionally, there are only samples for the first wave of civilized cities in 2011 for one period before the policy and four periods after. Similarly, the last wave of civilized cities in 2017, its impact on happiness will be observed in 2018. Hence, there are four periods before the policy and only one period after. That is,

k \in [- 4, 4]

. Other variables defined in Eq. (2) are the same as in Eq. (1).

The results are shown in Fig. 4 (specific coefficients are shown in Appendix D). The parallel trend results indicate that the time dummy variables are insignificant and nearly zero before CCP’s selection and in the current period ( $k \in [- 4, - 2]$ ). The first and second periods after receiving the title of a civilized city (representing the second year and the fourth year after policy implementation) are significantly positive.

Fig. 4 [Images not available. See PDF.]

Parallel trend test.

Notes: the figure plots event study estimates of Eq. (2). Coefficients of periods before and after CCP and 95% confidence intervals are plotted in the figure. Regression results are reported in Appendix D.

Furthermore, the assumption of parallel trends is met if the coefficient β_k before policy implementation is insignificant. Zhang and Huang (2023) pointed out that the significance of a single estimated coefficient β_k is related to the choice of the base period, so the joint significance of β_k should also be tested. The result suggests that β_k before the policy shock, was not jointly significant (p = 0.79), indicating no significant difference in the trend of life satisfaction before receiving the title of a civilized city, satisfying the prerequisites of the DID method.

Regarding the dynamic effects of the CCP, Fig. 4 shows that the happiness effect gradually strengthens and diminishes within four years after the policy implementation. This suggests that the happiness effect brought about by the CCP is not permanent, possibly due to reducing government efforts and identity effects, which have often been observed in previous literature (Guo et al., 2023; Liu et al., 2023). As the number of cities awarded to the CCP increases, the scarcity diminishes, causing the sense of honor and happiness to decline gradually. Currently, more than half of the cities in China have been awarded the title of Civilized City, which means that cities participating in the CCP will face more intense competition later. This could lead to issues such as overdevelopment in urban planning, which can harm residents’ happiness. Furthermore, according to the social comparison theory in behavioral economics (Chetty, 2015), when the title of Civilized City is no longer scarce, residents may compare themselves with higher-ranked cities, leading to feelings of inferiority and thus weakening the happiness effect of the CCP.

Robustness checks

Heterogeneous treatment effects

The growing literature on DID confirms that heterogeneity in treatment effects across groups and time can lead to bias in the two-way fixed-effects model even if the parallel trends assumption holds (de Chaisemartin and D’Haultfœuille, 2020). Therefore, potential heterogenous happiness effects should be tested since the civilization city selection policy was not completed simultaneously.

We first examine the presence of heterogeneous treatment effects by employing two-way and Bacon decomposition methods. In the Two-way decomposition, the proportion of positive weights is 84%, indicating the weaker heterogenous happiness effects. The Bacon decomposition chart shows that the weight of “late treatment vs. early treatment” is close to 0, demonstrating that the “bad” control individuals only constitute a minority. Both results suggest that the happiness effect is robust and minimally affected by heterogenous treatment effects.

Furthermore, we re-estimated Eq. (1) using heterogenous robust estimators, and the average treatment effects are presented in Table 3. The three types of estimators are as follows: the estimator (DIDM) proposed by de Chaisemartin and D’Haultfoeuille (2023), the estimator (CSDID) proposed by Callaway and Sant’Anna (2021), and the synthetic DID (SDID) estimator by Arkhangelsky et al. (2021). Columns (1), (3), and (5) of Table 3 show the results without including covariates, while Columns (2), (4), and (6) contrast. It can be found that the happiness effect is consistent with the baseline results, which indicates that the results are robust.

Table 3. Robust estimation considering heterogeneous treatment effects.

	(1)	(2)	(3)	(4)	(5)	(6)
	DIDM		CSDID		SDID
	Life_sati	Life_sati	Life_sati	Life_sati	Life_sati	Life_sati
Civi_city	0.064***	0.080***	0.065***	0.097***	0.073***	0.102**
	(0.020)	(0.029)	(0.021)	(0.027)	(0.020)	(0.027)
Controls		Y		Y		Y
Individual FE	Y	Y	Y	Y	Y	Y
Year FE	Y	Y	Y	Y	Y	Y
95% conf. interval	[0.024, 0.103]	[0.023, 0.137]	[0.023, 0.107]	[0.044, 0.149]	[0.034, 0.112]	[0.049, 0.155]
N	49,908	43,269	54,357	46,904	45,426	38,787

Standard errors in parentheses ^**p < 0.05, ^***p < 0.01.

Placebo test

To mitigate the potential impact of unobservable omitted variables on the estimates of the treatment effects, we conducted a placebo test by constructing virtual CCP shocks. As the timing of policy shocks varies for the treatment group, generating pseudo-treatment and pseudo-control group dummy variables is necessary. We randomly selected a sample of the same size as the treatment group and assigned different election times for residents of civilized cities 500 times. The hallmark of passing the placebo test is the disappearance of the happiness effect after changing the assumed timing of CCP.

Figure 5 displays the kernel density curve of the estimated coefficient β₂ and corresponding p-values from 500-time regressions. The vertical red dashed line in the graph represents the earlier baseline estimate. All the coefficients are approximately normally distributed around zero, with most p-values exceeding 0.1, significantly differing from the baseline results. This suggests that our results are less likely to be confounded by other policies or random factors. In other words, the happiness effect of CCP does indeed exist.

Fig. 5 [Images not available. See PDF.]

Placebo test.

Notes: Fig. 5 presents the cumulative distribution density of the estimated coefficients for 500-time regressions using random datasets. The black solid dots are the p-values of the estimated coefficients, and the curve is the kernel density distribution of the estimated coefficients. The vertical dotted line presents the result of the primary effects of Column (3) in Table 2; the horizontal dotted lines represent p = 0.1.

An alternative measurement of happiness

We replace the dependent variable $L i f e_s a t i$ in Eq. (1) with $H a p p y_s c o r e$ . In this case, the multi-period DID model is transformed into a standard DID model since only residents of civilized cities from 2017 were examined. Table 4 shows that residents’ happy scores will increase by 0.242 points after receiving the CCP brand, accounting for approximately 3% of the average score. This increase is slightly larger than the improvement in life satisfaction. However, regardless of which measure of happiness is used, the regression coefficient $C i v i_c i t y$ is significantly positive, indicating that the happiness effect of CCP substantially exists.

Table 4. Effects of the civilized city on the subjective happy score.

	(1)	(2)	(3)
	Happy score	Happy score	Happy score
Civi_city	0.268^***	0.242^***	0.242^***
	(0.056)	(0.061)	(0.066)
Controls		Y	Y
Individual FE	Y	Y	Y
Year FE	Y	Y	Y
Cluster	Individual	Individual	Family
R²	0.005	0.034	0.034
N	27,339	23,182	23,182

Standard errors in parentheses ^***p < 0.01.

PSM-DID method

The selective bias is another concern, given that the CCP is not an actual natural selection experiment. Therefore, we further conduct a robustness test using the PSM-DID model. Considering that propensity score matching (PSM) and DID are suitable for cross-sectional and panel data, there are two competitive approaches when applying the PSM-DID. One is to mix all observations into a cross-sectional dataset to match, and the other is to match by year. We employ both methods for PSM, with a 1:4 nearest neighbor matching, and only the observations in the common support domain are retained.

Figures 6 and 7 present the kernel density curves before and after matching under cross-sectional and yearly PSM. The figures show substantial deviations between the two kernel density curves before matching, regardless of the matching method. After matching, the distance between the mean lines is reduced, and the two curves become closer than before. This means that cross-sectional and yearly PSM can somewhat mitigate sample selection bias. The balance test results of PSM can be found in Appendix E.

Fig. 6 [Images not available. See PDF.]

Kernel density of propensity score (cross-sectional PSM).

Note: Kernel density curves for treated and control groups before matching on the left and after on the right.

Fig. 7 [Images not available. See PDF.]

Kernel density of propensity score (Yearly PSM).

Note: Kernel density curves for treated and control groups before matching on the left and after on the right.

After obtaining the control group samples using the PSM, we again applied the multi-period DID model to estimate the happiness effect. In Table 5, Panel A presents the results of the cross-sectional PSM-DID, where the first Column (1) is the baseline results for comparison. Columns (2)–(4) represent the results of using non-zero weighted samples, samples in the common support domain, and frequency-weighted regression, respectively. Panel B displays the yearly PSM-DID results, showing that the happiness effect is significantly positive in all cases. Therefore, it can be concluded that the above results are still robust.

Table 5. PSM-DID results.

Panel A: Cross-section PSM
	(1)	(2)	(3)	(4)
	Full matched samples	Non-zero weighted samples	Common support domain samples	Frequency-weighted samples
Civi_city	0.096***	0.116***	0.094***	0.128***
	(0.019)	(0.021)	(0.019)	(0.023)
Controls	Y	Y	Y	Y
Individual FE	Y	Y	Y	Y
Year FE	Y	Y	Y	Y
Cluster	Family	Family	Family	Family
R²	0.167	0.172	0.170	0.165
N	43,269	27,635	36,549	38,968
Panel B: Year-by-year PSM
Civi_city	0.096***	0.113***	0.097***	0.124***
	(0.019)	(0.021)	(0.019)	(0.024)
Controls	Y	Y	Y	Y
Individual FE	Y	Y	Y	Y
Year FE	Y	Y	Y	Y
Cluster	Family	Family	Family	Family
R²	0.167	0.172	0.169	0.163
N	43,269	26,421	35,846	40,187

Control variables are the same as in Table 2. Standard errors in parentheses ^***p < 0.01.

Alternative policies analysis

The final concern regarding the robustness of the above results pertains to the influence of other policies in China, such as the Low-Carbon City program launched in 2010 and the National Health City policy introduced in 2012, which may also potentially impact residents’ happiness.

The Low-Carbon City program initiated in 2010, 2012, and 2017 primarily focuses on curbing greenhouse gas emissions and promoting sustainable, low-carbon development strategies (Liu et al., 2022). The National Health City policy started its stringent evaluation after 2008, concentrating on aspects like sanitation, environmental protection, and food and drug safety (Wang et al., 2023). These initiatives are deeply linked to environmental conservation and health, possibly affecting residents’ happiness.

This study examines the impact of these policies on residents’ happiness by altering Eq. (1)’s independent variables to represent Low-Carbon City and National Health City. According to Table 6, the findings show no significant effects of these policies on residents’ life satisfaction. A possible explanation is that governments primarily focus on the low-carbon development of enterprises, paying less attention to residents to be selected as a Low-Carbon City. The insignificance of the National Health City may stem from its limited assessment scope, impacting residents’ lives only on hygiene, which is insufficient to induce a happiness effect. In summary, the nonsignificant results largely negate concerns regarding interference from other policies and affirm the happiness effect of CCP.

Table 6. Effects of alternative policies on life satisfaction.

Panel A: Low-Carbon City
	(1)	(2)	(3)
Lcarbon_city	0.011	−0.011	−0.011
	(0.018)	(0.020)	(0.022)
Controls		Y	Y
Individual FE	Y	Y	Y
Year FE	Y	Y	Y
Cluster	Individual	Individual	Family
R²	0.128	0.167	0.167
N	49,907	43,268	43,268
Panel B: National Health City
Health_city	−0.015	−0.005	−0.005
	(0.022)	(0.023)	(0.024)
Controls		Y	Y
Individual FE	Y	Y	Y
Year FE	Y	Y	Y
Cluster	Individual	Individual	Family
R²	0.128	0.167	0.167
N	49,907	43,268	43,268

Control variables are the same as in Table 2. Standard errors in parentheses.

Heterogeneous results

The happiness effect of CCP may exhibit extensive heterogeneity at the individual-level. Firstly, this heterogeneity can arise due to differences in the government’s efforts and strategies across different cities. Secondly, it is susceptible to personal characteristics since happiness is a subjectively assessed indicator. Therefore, the heterogeneity analysis primarily addresses the following questions: Does the impact of the CCP on residents’ happiness vary based on different waves and city levels? Does the happiness effect differ across residents of varying ages, income levels, and household registrations?

City heterogeneity

(1) The selection waves. With the gradual expansion of the CCP, the number of awarded cities has rapidly increased from 2005 to 2020 in six waves. This expansion could potentially lead to a diminishing scarce effect. To investigate this, we separately regress the three waves of CCP selected in 2011, 2014, and 2017 using Eq. (1). Figure 8 presents all the heterogeneity at the city level, with the vertical dashed line representing the baseline happiness effect. Appendix F reports the coefficients of heterogeneity analysis.

Fig. 8 [Images not available. See PDF.]

Heterogeneous happiness effects among residents of different cities.

Notes: Lines represent 95% confidence intervals. The p-value for testing the difference in happiness effect between the first and second waves is 0.1793, between the second and third waves, is 0.0002, between provincial capital and noncapital cities, is 0.0681, and between small cities and medium to large cities is 0.0360.

The first three rows of Fig. 8 illustrate the varying intensities of happiness effects generated by different selection waves. It can be observed that the happiness effects of these three batches are all significantly positive, but their coefficients exhibit an “inverted U-shaped” pattern. A potential explanation could be that happiness progressively diminishes as the total number of civilized cities increases. Between 2005 and 2014, nearly 70 provincial and prefecture-level cities were awarded, including cities that had already achieved comprehensive development excellence. This led to decreased pressure for non-civilized cities to obtain the title, resulting in limited efforts and improvements in urban development, subsequently reducing the positive effect on residents’ happiness. This finding suggests that strict adherence to the civilized city selection criteria and the establishment of absolute standards, rather than relative scores, are essential in policy implementation to maximize the government’s efforts to enhance people’s happiness and sense of achievement.

(2) Provincial capital. We explore the heterogeneity between city tiers and happiness, considering the status (capital or noncapital) and population size of cities. Provincial capitals, typically with greater access to construction funding, superior talent, and favorable policies, tend to be more efficient in developing civilized cities compared to noncapital cities. Rows 4 and 5 in Fig. 8 demonstrate a significantly higher happiness effect in provincial capitals, which indicates that applying uniform criteria across these varied city tiers may not yield the most effective policy results.

Furthermore, Population size also plays a significant role, as larger cities better allocate resources. This raises the question: do larger cities experience a more notable increase in residents’ happiness following their designation as civilized cities? Cities are categorized as small (under 3 million) and medium to large (over 3 million) for this analysis. Rows 6–7 reveal that small cities do not exhibit a significant happiness effect, while in large cities, this effect notably surpasses the baseline. This finding aligns with observations in provincial versus non-provincial capitals, underscoring the urban development focus on “big cities” from a happiness perspective.

Individual heterogeneity

(1) Age. The population aged 60 and above is classified as elderly, and their happiness determinants markedly diverge from those of younger individuals. Unlike younger cohorts, the elderly often contend with increased health challenges. Consequently, their physical health is likely to influence happiness, in contrast to younger people, for whom enhancements in urban infrastructure and amenities might play a more significant role. Additionally, the elderly may pay less attention to civilized cities, suggesting that the happiness effect of civilized cities should be weaker among the elderly population. However, the results in Fig. 9 do not reveal any significant differences, indicating that the government’s efforts have also considered the needs of the elderly population.

Fig. 9 [Images not available. See PDF.]

Heterogeneous happiness effects among residents.

Notes: The p-value for testing the difference in happiness effect between the young and the elderly is 0.706, between the low-income and the high-income, is 0.804, and between the urban and rural is 0.000.

(2) Income. Income is typically considered the factor influencing happiness. Residents with higher incomes may emphasize improvements in non-economic indicators, leading to a more significant happiness effect. Figure 9 shows that although the happiness effect is higher for the high-income group, it is not statistically significant. A possible reason is that CCP affects happiness through non-economic channels, such as a sense of honor.

(3) Household Registration. Generally, urban residents exhibit greater happiness levels than their rural counterparts. This disparity may stem from the focus of civilized city initiatives, which prioritize urban development over rural areas. Figure 9, Rows (5) and (6), show that upon achieving civilized city status, urban residents’ happiness increases by an average of 0.11 points, compared to a modest 0.07-point rise for rural residents. This trend likely results from the urban-centric approach of civilized city projects, emphasizing infrastructure enhancements and promotional activities.

Mechanism analysis

Government efforts

CCP motivates local governments to improve government integrity and efficiency while also focusing on enhancing public services and infrastructure. To promote civilization construction, governments are likely to actively work toward improving government efficiency, fairness, and transparency, which concerns residents’ happiness. Utilizing residents’ evaluations of government work from the CFPS questionnaire, we analyze the impact of CCP on government efforts, as shown in Table 7. The findings show that residents’ evaluations of government work increased by 0.068 points. Therefore, we can conclude that the government’s efforts for civilized city selection are a potential channel for improving residents’ happiness. Hypothesis 2 is confirmed.

Table 7. Mechanism: Effects of the civilized city on government efforts.

	(1)	(2)	(3)
	Government efforts	Government efforts	Government efforts
Civi_city	0.086***	0.068***	0.068***
	(0.016)	(0.019)	(0.020)
Controls		Y	Y
Individual FE	Y	Y	Y
Year FE	Y	Y	Y
Cluster	Individual	Individual	Family
R²	0.012	0.018	0.018
N	48,407	42,024	42,024

Standard errors in parentheses, ^***p < 0.01. Government efforts are measured with the item: “What is your overall evaluation of the work of your county or county-level city/district government over the past year?” The evaluation ranged from 1 (significant achievements) to 5 (worse than before).

Social trust

One evaluation standard for civilized cities is a harmonious social atmosphere, which can enhance social trust. Existing literature has shown that social trust, as an informal social institution, can encourage cooperation and foster healthy social networks. The selection of civilized cities may enhance residents’ happiness through social trust. Table 8 shows that the CCP can increase trust in society by an average of 0.033 points, suggesting that social trust is also one of the potential channels to enhance residents’ happiness. Therefore, hypothesis 3 is also confirmed.

Table 8. Mechanism: Effects of the civilized city on social trust.

	(1)	(2)	(3)
	Social trust	Social trust	Social trust
Civi_city	0.043^***	0.033^***	0.033^***
	(0.010)	(0.011)	(0.011)
Controls		Y	Y
Individual FE	Y	Y	Y
Year FE	Y	Y	Y
Cluster	Individual	Individual	Family
R²	0.006	0.009	0.009
N	38,157	33,071	33,071

Standard errors in parentheses, ^***p < 0.01. Social trust is measured with the item: “Do you tend to trust or be suspicious of others?” The evaluation ranged from 1 (very cautious when dealing with people) to 5 (most people can be trusted).

Identity recognition

In addition to the government and society from external perspectives, residents’ social identity within the city is also an important factor influencing happiness. Given that the CFPS questionnaire did not explicitly address residents’ sense of city identity and belonging, we opted to assess identity through the lenses of social status and future confidence instead. Generally, the higher individuals’ evaluations of their social class and future confidence, the stronger their sense of identity (Charness and Chen, 2020). Table 9 reveals that achieving the brand of a civilized city enhances residents’ sense of identity, which indicates another channel to happiness in line with hypothesis 4.

Table 9. Mechanism: Effects of the civilized city on identity recognition.

	(1)	(2)	(3)
	Identity recognition	Identity recognition	Identity recognition
Civi_city	0.071^***	0.072^**	0.072^**
	(0.026)	(0.028)	(0.030)
Controls		Y	Y
Individual FE	Y	Y	Y
Year FE	Y	Y	Y
Cluster	Individual	Individual	Family
R²	0.090	0.208	0.208
N	49,814	43,190	43,190

Standard errors in parentheses, ^**p < 0.05, ^***p < 0.01. The sense of identity is measured by social status and future confidence. Social status is evaluated in the questionnaire through the query, ‘How would you rate your social status in your local area?’ with a scoring range from 1 (very low) to 5 (very high). Similarly, future confidence is gauged by the question, ‘How confident are you about your future?’ scored on a scale from 1 (not confident at all) to 5 (very confident).

Discussion

Overall, the results indicate that the CCP significantly impacts residents’ happiness, whether measured by life satisfaction or subjective happiness scores. This is consistent with findings by D. Li et al. (2022), who used data from the China Household Finance Survey (CHFS) in 2013 and 2015. Although they pointed out that political incentives are the main reason for local development improvement, they did not investigate the root causes of the increase in residents’ happiness. Our mechanism results, for the first time, show that government efforts, social trust, and identity recognition are essential channels through which the CCP enhances residents’ happiness. This aspect has been lacking in previous literature on CCP policy evaluation.

China’s CCP is a typical “central-government proposal, local-government efforts” mechanism. This system establishes evaluation criteria and incentive measures (including direct title awards and implicit official promotions, creating a competitive and motivational environment across regions (D. Li et al., 2022). According to game theory, this mechanism can stimulate the enthusiasm of local governments and residents, thereby achieving public goals at lower costs. Specifically, local governments will actively take measures to improve government efficiency, enhance the local ecological environment, and promote social harmony, thereby increasing residents’ happiness. In response to the local-government’s call, residents gradually developed more environmentally friendly and harmonious living habits in pursuit of a sense of honor and recognition.

The findings of this study also indicate that the happiness effect of the CCP does not show heterogeneity across age and income groups, which is inconsistent with the findings of Blanchflower (2021) and Perez-Truglia (2020). This suggests that the CCP, as the highest honor attainable at the urban-level in China, has happiness efficacy across all age and income groups. However, it should be noted that the effect of happiness is more evident among residents of developed and large-population cities. This implies that future policy implementation should focus more on rural and small to medium-sized cities to achieve shared development outcomes for all.

The findings above have many implications for other developing countries like China, such as India and Pakistan. Both India and Pakistan have large and young populations, but their infrastructure is relatively underdeveloped, and there is still much room for improvement in education and healthcare conditions. This affects the countries’ overall economic development and living standards (Asher and Novosad, 2020; Danon et al., 2024). Their global happiness rankings for 2021–2023 are 126 and 108, respectively (Helliwell et al., 2024). Especially for countries like Pakistan, which is still in the wave of industrialization and urbanization, it may face a series of issues like China, such as insufficient government efficiency and environmental pollution in the future. Given the strong environmental quality and social harmony externalities, market mechanisms cannot effectively resolve such issues. Therefore, government intervention is particularly important. By drawing on China’s CCP, India and Pakistan can establish similar tournament policies. Through direct and indirect incentives, the overall level of urban civilization at relatively low policy costs would be realized.

Another point worth discussing is that the happiness effect of tournament policies like the CCP has become significant in the post-COVID-19 era. The pandemic has profoundly changed people’s views on happiness, significantly increasing the importance placed on government, ecological, environmental, and social harmony indicators. This phenomenon has been validated in research by Helliwell et al. (2023), who found that post-pandemic, the global standards for evaluating happiness have gradually shifted towards aspects of ecological and social harmony. In the post-pandemic era, the economic recovery of various countries requires new growth points. The increased public attention to and demand for urban civilization development may provide governments with more opportunities for intervention. Large developing countries can follow this trend by greening economic development and promoting social harmony, ultimately enhancing national happiness.

Further study on environmental attitudes and income inequality

This paper further explores the impact of CCP on environmental attitudes and income equality. Environmental friendliness and income equality are pursuits for the government and academic concerns. China’s civilized city construction aims to achieve comprehensive civilization in various aspects, including the economy, politics, society, culture, and ecology. How will this affect environmental attitudes and income equality?

Further study on environmental attitude

Residents’ eco-friendly behaviors are deemed to possess substantial potential for energy conservation and emission reduction (Allcott, 2011; Andor et al., 2020; Bonan et al., 2020). An essential criterion for being designated as a civilized city is fostering a sustainable ecological environment. This encompasses urban greening, effective environmental management, quality enhancement, and prudent land resource utilization. Consequently, we anticipate a consequent shift in residents’ environmental attitudes.

We first examined changes in residents’ subjective evaluations of environmental quality. Residents’ perceptions of environmental quality were gauged using their responses. As displayed in Columns (1)–(3) of Table 10, there is an average perceived decrease of 0.188 points in the seriousness of environmental issues. This indicates that CCP enhances residents’ perceptions of environmental quality and indirectly signifies an improvement in China’s environment.

Table 10. Effects of civilized city on environment concern.

	(1)	(2)	(3)	(4)	(5)	(6)	(7)
	Environment cognition	Environment cognition	Environment cognition	Pollution concern	Pollution concern	Haze concern	Haze concern
Civi_city	−0.194***	−0.188***	−0.188***	0.055	0.039	0.057	0.044
	(0.057)	(0.065)	(0.070)	(0.058)	(0.059)	(0.064)	(0.065)
Controls		Y	Y		Y	N	Y
Individual FE	Y	Y	Y	Y	Y	Y	Y
Year FE	Y	Y	Y	Y	Y	Y	Y
Cluster	Individual	Individual	Family	City	City	City	City
R²	0.037	0.046	0.046	0.050	0.054	0.615	0.618
N	37,893	32,850	32,850	2438	2428	2438	2428

Notes: Standard errors in parentheses, ^***p < 0.01. The question assessing perceived environmental quality is framed as, “Overall, how serious do you perceive the environmental issues in China to be?” with responses scored on a scale from 0 (not serious) to 10 (extremely serious).

We further examined changes in public environmental concerns. Generally, lower environmental quality heightens environmental awareness, leading to environmental improvements (Xie et al., 2023). In our research, the city-level Baidu Index was utilized to gauge residents’ environmental concerns, incorporating key search terms like “environmental pollution” and “haze” across both mobile and desktop platforms. The results are shown in Columns (4)–(7) of Table 10. Our findings indicate that the CCP did not increase environmental concerns. A potential explanation for this is that the variable of environmental concern is more closely linked to elements like the disclosure of environmental information and significant pollution incidents (Barwick et al., 2024; Yu et al., 2022). The impacts of policies not explicitly targeting the environment might not be very pronounced. For the CCP, although environmental quality is included in the assessment criteria, the focus is more on factors that are closely related to residents, such as waste disposal and street greening. Considering the evidence in the existing literature that public environmental concerns can lead to stricter environmental regulations (Buntaine et al., 2024), it becomes essential to cultivate an endogenous driving force for environmental improvement from this perspective.

Further study on income inequality

Income inequality is increasingly severe worldwide, especially in developing countries, where many have exceeded the Gini coefficient warning line of 0.4 (Qin et al., 2022). Considering that government efforts to enhance infrastructure and foster a harmonious social atmosphere may improve the income of low-income groups, we aim to examine whether the CCP has improved the severe income inequality issue facing China.

We assess residents’ subjective perception of income inequality alongside the objective Gini coefficient. Table 11, Columns (1)–(3), detail the influence of the CCP on perceptions of income inequality. Compared to non-civilized cities, inhabitants of civilized cities noticeably perceive a progressive decrease in income inequality across the nation by 0.161 points. We further computed the Gini coefficient at the city level as an objective measure of income inequality. The Gini coefficient quantifies the degree of deviation from perfect income equality in a region where higher values signify more pronounced income disparities. As shown in Table 11, Columns (4)–(6), the implementation of the CCP corresponds with a 0.7% decrease in the Gini coefficient. This aligns with the observed decline in residents’ subjective perception of income inequality.

Table 11. Effects of civilized city on income inequality.

	(1)	(2)	(3)	(4)	(5)	(6)
	Inequality cognition	Inequality cognition	Inequality cognition	Gini coefficient	Gini coefficient	Gini coefficient
Civi_city	−0.120**	−0.153***	−0.153***	−0.007^***	−0.007^***	−0.007^***
	(0.051)	(0.057)	(0.059)	(0.001)	(0.001)	(0.002)
Controls		Y	Y		Y	Y
Individual FE	Y	Y	Y	Y	Y	Y
Year FE	Y	Y	Y	Y	Y	Y
Cluster	Individual	Individual	Family	Individual	Individual	Family
R²	0.014	0.017	0.017	0.290	0.318	0.318
N	37,857	32,830	32,830	49,908	43,269	43,269

Standard errors in parentheses, ^**p < 0.05, ^***p < 0.01. The item related to the perception of income inequality is framed as follows: “How serious do you think the problem of income inequality is in our country?” using a scale of 0 (not serious) to 10 (very serious). The Gini coefficient is calculated as the difference between the city’s cumulative population and income percentage divided by the total city population.

Discussion

The above results demonstrate the role of the CCP in enhancing residents’ subjective environmental quality and alleviating income inequality. The improvement in subjective environmental quality mainly stems from the government’s efforts to improve community environments, such as increasing waste management efficiency and expanding street green spaces. Since these changes are directly visible to the public, they perceive that environmental quality is gradually improving. However, for less noticeable environmental issues like air and water pollution (Barwick et al., 2024; Jalan and Somanathan, 2008), there has not been increased attention due to the CCP competition. Notably, the impact on concerns about smog is also insignificant. This may be because the public tends to associate the results of smog control with specialized environmental policies, such as air pollution control and pollution information disclosure, which are strongly correlated with public concern (Barwick et al., 2024; Yu et al., 2022). In other words, public perception of environmental quality is passive rather than proactive. Given that public environmental concern or supervision can motivate the government to improve environmental quality (Buntaine et al., 2024), future CCP standards in China and urban policy planning in other developing countries need to pay more attention to the public’s environmental perceptions.

Regarding income inequality, evidence based on residents’ subjective perceptions of inequality and the objective Gini coefficient indicates additional benefits of the CCP. In creating civilized cities, the government strives to improve infrastructure and other livelihood projects, such as promoting the equalization of education, medical care, and health insurance, which may be more beneficial to low-income groups. Previous literature has shown that a more robust social security system can increase the income of low-income groups and reduce income inequality (Bhattacharya et al., 2016; Mahmoudi, 2023). Furthermore, creating an equal and harmonious social atmosphere can increase social trust and alleviate unequal opportunities (Akaeda, 2020). Previous literature indicates that the issue of unequal opportunities caused by social stratification is becoming a significant factor in income disparity (Aiyar and Ebeke, 2020; Lambert et al., 2014). Therefore, the positive externalities of the CCP in alleviating inequality deserve further attention.

In summary, the CCP directly enhances residents’ happiness and plays a vital role in improving residents’ environmental attitudes and addressing income inequality. Although current Chinese residents do not heavily consider these two factors when evaluating life satisfaction, they will undoubtedly be critical factors in future happiness. For rapidly growing countries like India and Pakistan, improving population civilization and environmental awareness will be beneficial for promoting sustainable economic development. The Kuznets curve suggests that economic development is often accompanied by increasing income inequality and environmental degradation. Therefore, it is necessary to introduce tournament policies like the CCP to give more attention to income inequality and the perception of environmental quality.

Conclusions and policy implications

Enhancing national happiness is a primary goal of governments globally. The CCP, representing the pinnacle of urban governance recognition in China, has driven wide-ranging urban economic, political, social, cultural, and ecological enhancements. However, the effects of such comprehensive tournament-based social policies have not been fully evaluated. In this study, we developed a multi-period DID model utilizing the CFPS dataset spanning 2010 to 2020 to investigate the impact of CCP on happiness. The results show that CCP in China contributes to an approximate 2.6% increase in residents’ happiness. However, this happiness effect gradually fades over the following years despite being confirmed by a series of specifications. Besides, the happiness effect of civilized cities exhibits heterogeneity across cities and residents. The effect is more pronounced in cities recognized earlier, provincial capitals, and those with larger populations, and it is solid among urban residents.

Furthermore, we find identity, government initiatives, and social trust as channels driving the happiness effect associated with civilized cities. This provides insights into understanding the role of tournament-style policies. The government can better grasp public reactions to the policies, thereby optimizing the evaluation criteria of such policies. Finally, the subjective perception of environmental quality and income equality has been enhanced. This indicates that civilization-targeted evaluations have positive externalities, which the government can leverage to improve social welfare further.

Summarizing the conclusions, we offer the following policy recommendations for boosting national happiness. Firstly, there should be an increased focus on the impact of the CCP on residents’ subjective experiences. This involves refining the selection and review processes to prevent policy ineffectiveness from the perspectives of government efforts and social trust. Government departments should promptly revise the selection criteria for CCP, including additional metrics tied to residents’ happiness. Implementing a regular review system to avoid internal manipulation, campaign-style governance, and establishing effective feedback mechanisms will enhance the program’s long-term happiness effects.

Secondly, the heterogeneous policy responses of different cities and residents should be considered to improve the effectiveness of CCP. Efforts should be made to stimulate the happiness effect in noncapital and smaller cities, aiming to reduce the happiness gap. This might include providing support in areas like construction funds to avoid financially burdensome methods in these cities. Furthermore, providing extra support to rural areas is crucial for enhancing the happiness effect among rural residents. Enhancing residents’ recognition of the civilized city brand can significantly boost happiness.

Finally, the implementation and publicity of CCP should be intensified to ensure the transmission of policy effects. The promotion of CCP needs to be amplified to make government efforts visible to residents, fostering a social atmosphere of voluntary participation. Simultaneously, implementing safeguard measures such as a credit penalty mechanism will improve government efficiency and social trust, ensuring the smooth transmission of happiness to residents.

This study is significant not only because it explores the direct impact and mechanisms of the CCP on residents’ happiness but also because it comprehensively examines the CCP’s externalities in improving environmental attitudes and addressing income inequality. This effectively extends the theory of happiness economics, providing new perspectives for government happiness management. Moreover, it offers valuable insights into other countries implementing similar policies to improve residents’ quality of life, such as the “All-America City” program in the United States and the “Most Attractive City” initiative in Japan.

Of course, this study has certain limitations. First, we exercise caution in interpreting the results, which is the notable time gap between the CFPS survey period and the designation of Civilized Cities. This time difference may cause a diminished perception of happiness associated with the title, possibly leading to an underestimation of the happiness effect. Secondly, due to limitations in the available data, our study did not assess the happiness effect of county-level civilized cities. Compared to the economic development gap between prefecture-level cities, the development differences among counties in China are also significant, even within the same prefecture-level city. Counties designated as Civilized Cities often indicate more substantial competitiveness; therefore, their happiness effect may be more significant. Third, this study has not yet explored the impact of COVID-19 due to the limitations of the sample data. Given the strong correlation between the pandemic and public health, the happiness effect of the CCP may be higher post-pandemic. Therefore, a potential research direction is to explore the impact and mechanisms of accidental events like the pandemic on the happiness effect and to investigate measures that could extend the happiness effect of the CCP. We leave this to future efforts when more detailed data become available.

Acknowledgements

This paper is supported by the Major grant in National Social Sciences of China [grant numbers: 23VRC037, 24VHQ018]; the National Natural Science Foundation of China [grant number: 72033005]; and Postdoctoral Fellowship Program of China Postdoctoral Science Foundation [grant number: GZB20230392]; and Fujian Provincial Social Science Foundation Youth Project [grant number: FJ2021C083].

Author contributions

Penghu Zhu: conceptualization, methodology, data curation, writing—review draft. Yingying Hu: conceptualization, methodology, software, data curation, writing—original draft. Ning Zhang: methodology, software, data curation, writing—original draft.

Data availability

The data used in this paper are from China Family Panel Studies. Due to data licensing restrictions, users are not permitted to publish or disclose the data in any form. Therefore, the data are not publicly available. However, data are available from the authors upon reasonable request and with permission of China Family Panel Studies. The data of China Family Panel Studies (CFPS) collected and analyzed in the current study are available at: https://doi.org/10.18170/DVN/45LCSO. The code for all data processing can be found in the supplementary materials.

Competing interests

The authors declare no competing interests.

Ethical approval

Ethical approval was not required as the study did not involve human participants.

Informed consent

Informed consent was not required as the study did not involve human participants.

The overall mean of life satisfaction is 3.76, 0.096/3.76 = 2.55%.

Supplementary information

The online version contains supplementary material available at https://doi.org/10.1057/s41599-024-03539-8.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

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Urban governance aims to enhance overall social welfare, while residents’ happiness frequently falls by the wayside. Civilization, as a critical factor influencing residents’ happiness, has not yet been fully understood regarding its impact and mechanisms. This paper uses the China Family Panel Studies data, which includes around 50,000 samples ranging from 2010 to 2020, to construct a multi-period difference-in-differences model. It finds that China’s highest honor for urban brands, the civilized city program, leads to an average increase of 2.6% in residents’ happiness as measured by life satisfaction. This happiness effect is robust but temporary, gradually diminishing within five years following the honor. The happiness effect is heterogeneous across different waves and city sizes and is effective only for urban residents. Mechanism analysis indicates the happiness effect of the civilized city program through three channels: government efforts, social trust, and identity recognition. Additionally, our research indicates that the civilized city initiative improves residents’ perception of environmental quality and reduces income inequality. These findings provide insights into understanding how the civilization tournament policy promotes happiness.

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Title

How does civilization promote happiness? Insights from the Civilized Cities Program in China

Author

Zhu, Penghu¹

; Hu, Yingying²; Zhang, Ning¹

¹ Shandong University, Institute of Blue and Green Development, Shandong, China (GRID:grid.27255.37) (ISNI:0000 0004 1761 1174)
² Wuhan University, School of Economics and Management, Hubei, China (GRID:grid.49470.3e) (ISNI:0000 0001 2331 6153)

Pages

1060

Publication year

2024

Publication date

Dec 2024

Publisher

Palgrave Macmillan

e-ISSN

2662-9992

Source type

Scholarly Journal

Language of publication

English

DOI

https://doi.org/10.1057/s41599-024-03539-8

ProQuest document ID

3095295860

How does civilization promote happiness? Insights from the Civilized Cities Program in China

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