Social Expectations for Charitable Giving in China

Abstract

The rapid rise of philanthropy in China has motivated extensive research on why people make charitable donations as a personal decision, but few studies have explored the social dimension of these decisions. We propose that the legacy of government welfare provision and the culture of trust have led Chinese citizens to form different expectations for others in philanthropic situations. Our survey results point to some interesting asymmetries: Generalized trust and institutional trust toward local governments inflate people’s expectation for philanthropic contributions from others, whereas particularized trust and trust toward the central government reduce it. Also, Chinese citizens expect government employees to make larger contributions, but they don’t expect charities with government backing to receive correspondingly larger donations. We conclude with some observations on how the unique pattern of social expectation may shape the future of Chinese philanthropy.

Keywords

philanthropy social expectation trust government ties charitable giving

China’s rapid economic growth in recent decades has been followed by a significant increase in charitable giving. According to China Charity Alliance, donations worth 143.9 billion RMB, or 0.16% of China’s gross domestic product (GDP), were made across the Mainland in 2018, with individual donors contributing 36 billion RMB in total (China Charity Alliance, 2019). The transition has become more visible to the Chinese public due to a surge of high-net-worth donors, of whom the more notable include Lu Weiding (4.96 billion), Chen Yidan (3.61 billion), and Xu Jiayin (0.75 billion) (China Charity Alliance, 2019). These developments, indicative of an emerging source of welfare resources driven by private giving in China, have led to a new line of research on what motivates people to engage in charitable giving, where welfare provision has long been dominated by the government and affiliated entities.

With an emphasis on why people make the decision to contribute to charitable causes (Bekkers & Wiepking, 2011; Sargeant, 1999; Wang & Graddy, 2008; Wu et al., 2018), the literature on philanthropy offers few insights into what people expect others to do in similar situations. The lopsided focus is problematic. Like other pro-social behaviors, charitable giving cannot be driven by intrinsic preferences alone (Clotfelter, 1997; Teunenbroek et al., 2020). People form expectations about others in pro-social situations and adjust their own response accordingly (Frey & Meier, 2004; Hasegawa et al., 2007). In this vein, the legacy of unusually extensive involvement of the government in welfare provision in China may lead these expectations about philanthropic giving—a largely private act—to interact with political factors. It becomes meaningful to explore how such expectations operate in China’s unique context.

Results from our national survey in mainland China show that social expectations are conditional on sociopolitical attributes. We also report asymmetric expectations in charitable giving, whereby Chinese citizens expect public sector employees to donate more, but a corresponding expectation that charitable organizations with stronger ties to the government should be given larger donations than those with weaker connections is absent. The patterns suggest that grassroots organizations are as capable of attracting private giving as government-backed organizations. At the same time, Chinese philanthropy continues to grow in the shadow of government-led welfare provision, whereby affiliation with the state is expected to correlate with charitable giving despite the private nature of the act.

Trust and Social Expectations

People entering into social interactions run the risk of exposing themselves to defection, shirking, and other social dilemmas. In an effort to contain exposure, they develop stable expectations about the actions and intentions of others (Denzau & North, 1994). Specifically, they may adopt “a state of favourable expectation regarding other people’s actions and intentions” (Möllering, 2001, p. 404) by assigning trust to general others in cooperation (Gambetta, 1988), institutional development (Putnam, 2000; Sønderskov, 2011), and charitable activities (Taniguchi & Marshall, 2014). Although in situations where joint actions present greater risks to cooperation, social expectations are likely to be less favorable since trust is assigned only to specific others and withheld from those whose credibility cannot be directly and personally ascertained. Therefore, trust and social expectations are closely related. Möllering (2001) conceptualized trust as a mental process and argued that expectation is the outcome of trust process. Expectations about people’s socially meaningful behaviors further determine the growth of civil society (Hasegawa et al., 2007). However, questions remain concerning why people expect others to behave pro-socially. To address this missing link in trust studies, we explore the relationship between trust and social expectations and further examine how this relationship operates in the special policy conditions of Chinese philanthropy.

Trust takes different forms. Generalized trust refers to trust toward anonymous others and particularized trust toward recognized others in a well-defined group, such as family members and friends (Luhmann, 1979; Uslaner, 2002). Generalized trust comes with faith in human nature and expectation of goodwill (Yamagishi & Yamagishi, 1994). Prior studies found a positive relationship between generalized trust and charitable giving and volunteering activities (Bekkers & Schuyt, 2008; Glanville et al., 2016; Taniguchi & Marshall, 2014). Psychologists and economists have demonstrated that people would “look to others” before making their own decisions (Bicchieri & Xiao, 2009; Croson et al., 2009; Goeschl et al., 2018; Teunenbroek et al., 2020). As they look to others, people glean important information about what others do, which they then use to produce expectations about what others will do (Bicchieri, 2006; Bicchieri & Xiao, 2009). In discussing how these expectations are produced, Neilson and Paxton’s (2010) proposed that people with generalized trust tend to expect others to contribute to the common good, because for these people, pro-social behaviors are moral obligations (Cheung & Chan, 2000). In line with their proposition, we argue that generalized trust is associated with the favorable expectation that others will act pro-socially. We hypothesize that

Hypothesis 1 (H1): Chinese citizens with higher generalized trust expect others to react positively to philanthropic opportunities.

In contrast, particularized trust is selective and group-based, where people selectively develop trust toward in-group members and mistrust for those outside. Therefore, the emphasis on personal ties in collectivist societies such as China may lead to preference for mutual help offered to or received from specific others; instead, common good targeting unknown others receives less interest (Hwang, 1987; Taniguchi & Marshall, 2014; Wu et al., 2018). For example, Uslaner and Conley (2003) examined Chinese people in the United States and found that those deeply committed to their ethnic communities were less active in broader civic life. As such, we argue that particularized trust is contrary to generalized trust in its effects, associated with unfavorable expectations about other people’s pro-social actions. We hypothesize that

Hypothesis 1a (H1a): Chinese citizens with higher particularized trust expect less charitable contributions from other people in society.

In our survey, we further look into institutional trust toward three types of organizations in China: Charities, local governments, and the central government. These institutions operate outside people’s acquaintance network and could shape their attitudes toward out-group members (Irwin, 2009). Trust in charities is traditionally associated with greater willingness to give to charitable causes (Sargeant & Lee, 2004). As charities operate in the public sphere and deliver welfare to the general public, trust in charities reflects public good awareness. Thus, similar to generalized trust that is associated with favorable expectations about others’ actions for common good (Neilson & Paxton, 2010), we argue that trust in charities is related to favorable expectations as well. We hypothesize that

Hypothesis 2 (H2): Chinese citizens with higher trust toward charities expect others to make more charitable contributions.

Our hypotheses about institutional trust toward the government engage the different welfare roles the central and local governments play in China. The central government is often seen as the policymaker at the national level, while local governments implement the decisions on the ground (L. Li, 2016). Social expectations are hypothesized to interact with this structure. Positive attitudes toward the central government could crowd out expectations for charitable giving. For citizens who hold the central government in higher esteem, the government plays a prioritized role in welfare provision through policy-making and resource allocation; as a result, supporting philanthropic work as an alternative to government provision of welfare becomes less relevant. Therefore, trust in the central government is likely to mitigate one’s expectation for giving by the society. We hypothesize that

Hypothesis 3a (H3a): Chinese citizens with higher trust toward the central government expect less philanthropic contributions from others.

Trust toward local governments should have the opposite effect of crowding in expectations for charitable giving. As local governments are in direct touch with individual citizens, government performance at the local level is a strong correlate with public trust (Meng & Yang, 2012). Citizen trust toward local governments reflects not only satisfaction with existing public service performance but also affirmation of local governments’ role as a reliable steward of public welfare (Meng & Yang, 2012). Citizen trust, therefore, represents a positive assessment of the governments’ worthiness of citizens’ support, which is likely to associate with the expectation for others to behave pro-socially in support of local governments. Extending from that observation, we hypothesize that

Hypothesis 3b (H3b): Chinese citizens with higher trust toward local governments expect larger contributions by others in philanthropic situations.

Links to Government

Our next set of variables concern a more specific issue in Chinese philanthropy: Whether social expectations change when the government is more or less involved in the philanthropic situation. In democratic regimes, an independent, self-governed, and voluntary-based civic sector is assumed to exist in parallel with the state (Putnam et al., 1994; White et al., 1996). In China, however, charitable activities have long been dominated by the party-state. Under such “state corporatism,” the state is the core dominator that controls the society and civic life (Oi, 1992; Unger & Chan, 1995); nonprofits, private associations, and civic groups formed from bottom-up are largely marginalized in the political arena despite their efforts in policy advocacy and public problem-solving. Nonprofits and civic groups find it easier to survive if they are deemed to provide utilitarian benefits for the authoritarian state (Kang & Han, 2008; Spires, 2011).

Registration, taxation, and direct funding are three tools that the Chinese government exerts control over the nonprofit sector. Through registration requirements, only those nonprofits with operational missions in line with the state preferences are allowed to register (Saich, 2000), and only registered nonprofits can enjoy preferential tax policies. The amounts of direct government funding also seriously affect the nonprofits whose operations depend on the funds.

The Wenchuan earthquake in 2008, however, saw the rapid mobilization in disaster relief and reconstruction at the grassroots level, leading to the rise of grassroots organizations as an alternative target for private giving (Peng & Wu, 2018). Multiple scandals involving major government-backed charities, such as the Red Cross (the Guo Meimei Incident) and the Henan Soong Ching Ling Foundation, also intensified the trend (Ni & Zhan, 2017). Grassroots charities began to receive more sizable amounts of contributions. For example, One Foundation received private donations worth nearly 400 million RMB after the Lushan earthquake in 2013. More recently, within 1 week after the COVID-19 outbreak, Han Hong Love Charity Foundation raised more than 300 million RMB in private cash donations.

As of March 2020, a total of 5,958 charitable organizations were registered and recognized by the Chinese government. Our research team reviewed and coded these organizations based on their relationships with the government, and found that 2,879 (48.3%) of them were founded and operated by government agencies at the central or local levels. Most of the major Chinese charities, such as Red Cross Society of China, Charity Federations, and China Foundation for Poverty Alleviation, are government-organized. While more grassroots entities have emerged in recent years, most philanthropic activities are still conducted under direct government auspices (Deng & Jeffreys, 2019; Lai et al., 2015), with the Red Cross Society and Charity Federations being the largest collectors of private donations. During the COVID-19 outbreak in early 2020, the authorities required private donations be made to designated charities organized by the government. The general institutional setup of Chinese philanthropy suggests that Chinese citizens may remain more accustomed to government-organized charities, despite the recent emergence of grassroots alternatives (M. Li et al., 2020). We thus hypothesize that

Hypothesis 4 (H4): Chinese citizens expect others to make larger contributions to charitable organizations with government backing.

We also propose that ties with the government interact with social expectations that Chinese citizens form about others in the philanthropic context. The notion that it is the government’s responsibility to provide for the people forms one of the central tenets of Confucianism and continues to shape the ethos of good governance in contemporary China (Pye, 1992). As China’s political institutions continue to centralize control at the expense of community self-organization (Han et al., 2011), the official narrative also promotes the idea that government officials, rather than civic organizers, have a duty to safeguard the public welfare. Such a notion exists not only on the demand side but also the supply side. Prior research in public management has found that employees in public and nonprofit organizations tend to be driven by public service motivation (PSM), which can be defined as “the belief, values and attitudes that go beyond self-interest and organizational interest, that concern the interest of a larger political entity and that motivate individuals to act accordingly whenever appropriate” (Vandenabeele, 2007, p. 547). With its altruistic orientation, PSM is positively associated with pro-social behaviors; empirical research has shown that public and nonprofit employees are more engaged in charitable activities such as volunteering, compared with their counterparts in the private sector (Houston, 2006; Taylor, 2010). Building on these prior research findings, we hypothesize that

Hypothesis 5 (H5): Chinese citizens expect government employees to contribute more to philanthropy.

Empirical Strategy

To evaluate these hypotheses, we performed a national survey of Mainland Chinese citizens aged 18 years or above, conducted through Qualtrics—a survey company of international repute. It maintains a pool of Mainland Chinese respondents, whose sociodemographic profiles are regularly updated. Following similar surveys in China, sample matching techniques were used to recruit respondents whose overall demographic profiles were aligned with the figures from latest official census data on age, location, gender, and ethnicity (see Figure 1). The survey was administered online to avoid desirability bias, which is prevalent in China and often amplified in face-to-face or phone surveys (Chang & Krosnick, 2010; Huang, 2015). From May 23 to July 19, 2019, 2,035 valid responses were returned.

Figure 1.

National census data versus research sample.

Measuring Trust

Our survey questions on social trust are drawn from the Social Capital Community Benchmark Survey, which has been applied across countries to measure the level of trust toward different targets on a Likert-type scale (Glanville et al., 2016; Taniguchi & Marshall, 2014; Wang & Graddy, 2008; Wu et al., 2018). We measure generalized trust by asking respondents “To what extent do you agree with the statement that ‘Generally speaking, most people can be trusted?’” on a scale from 0 (strongly disagree) to 10 (strongly agree). In measuring particularized trust toward known others, we ask respondents “In general social interactions where money isn’t involved, do you think your neighbors (relatives) can be trusted?”; the answers range from 0 (most cannot be trusted) to 10 (most can be trusted). Institutional trust includes trust toward charities, local governments, and the central government, which we gauge by asking “How much do you trust [institution]?.” Respondents rate their trust from 0 (complete mistrust) to 10 (complete trust).

Experimental Design

The experimental portion contains a vignette in which an individual is presented with an opportunity to make a charitable donation. Survey respondents are then asked to suggest how much that individual should donate. The control group is offered the following baseline vignette:

Zhang Wen [A common, gender-neutral Chinese name] is a citizen. Recently, the newly established “Society for Children Welfare” is raising donations across the country. The Society is a charity, and provides education services, bursaries, and poverty relief for children in poverty.

If Zhang Wen has 100 RMB to spare, how much should he/she donate to this charitable organization?

The setup allows for two treatments. First, the donor is “a citizen” in the control group vignette, but his or her occupation is specified as either “a government employee,” “a company employee,” or “a charity employee” in the treatment vignettes. Second, the organization receiving the donation is simply described as “a charity” in the control vignette, but it would be described either as “a charity set up by the government” or “a charity set up by grassroots groups” in the treatment groups. The treatments regarding identity of the donor and type of charitable organization form 12 scenarios, and a respondent would be randomly assigned to one of them in the survey (Table 1). For example, respondents in Group 12 would see the following vignette:

Table 1.

Randomization of Vignette Setting.

Experiment setup (number of respondents)	“A charity” (697)	“A charity set up by government” (671)	“A charity set up by grassroots groups” (667)
“A citizen” (523)	Group 1 (baseline) (196)	Group 5 (158)	Group 9 (169)
“A government employee” (527)	Group 2 (175)	Group 6 (170)	Group 10 (182)
“A company employee” (518)	Group 3 (157)	Group 7 (187)	Group 11 (174)
“A charity employee” (467)	Group 4 (169)	Group 8 (156)	Group 12 (142)

Zhang Wen is a charity employee. Recently, the newly established “Society for Children Welfare” is raising donations across the country. The Society is a charity set up by grassroots groups, and provides education services, bursaries, and poverty relief for children in poverty.

If Zhang Wen has 100 RMB to spare, how much should he/she donate to this charitable organization?

Table 1 reports some minor imbalances in group size. First, responses given by those aged under 18 years, living in non-Mainland regions, or claiming to be non-Chinese are screened out from the data set. Second, as a matter of research ethics, respondents could quit the survey at any point before submission, but that means completion rates can vary across groups. Third, responses that do not contain key covariates (e.g., no respondent input on the vignette, which is the dependent variable in this study) are excluded (see Table 3).

Other Controls

We control for personal attributes and other conditions that may influence social expectations, including age, gender, income, education, religion, marital status, household conditions, and geographical region. Existing studies have drawn mixed conclusions about their effects on civic participation in general (Glanville et al., 2016; Putnam, 2000; Putnam et al., 1994; Wang & Graddy, 2008; Wu et al., 2018), but they might shape people’s expectations for philanthropic choices to some extent. We also ask the respondents to report past involvement in voluntary work and giving (Lee et al., 1999). Table 2 defines all the variables used in this research; Table 3 shows the covariant balance across the control and treatment groups.

Table 2.

Variable Definitions.

Variable	Measurement
Agency type	1 = A charity; 2 = Set up by government; 3 = Set up by grassroots groups
Donor’s background	1 = Citizen; 2 = Government employee; 3 = Company employee; 4 = Charity employee
Trust in general population	To what extent do you agree with the following statement, “Generally speaking, most people can be trusted”? 0 (Strongly disagree) ~ 10 (Strongly agree)
Trust in neighbors	In general social interactions where money isn’t involved, do you think your neighbors can be trusted? 0 (Most cannot be trusted) ~ 10 (Most can be trusted)
Trust in relatives	In general social interactions where money isn’t involved, do you think your relatives can be trusted? 0 (Most cannot be trusted) ~ 10 (Most can be trusted)
Trust in charities	How much do you trust in charities? 0 (Complete mistrust) ~ 10 (Complete trust)
Trust in central government	How much do you trust in the central government? 0 (Complete mistrust) ~ 10 (Complete trust)
Trust in local governments	How much do you trust in local government? 0 (Complete mistrust) ~ 10 (Complete trust)
Voluntary work	In the past 12 months, have you ever done volunteering work? 1 = Yes; 0 = No
Donation	In the past 12 months, have you ever donated money? 1 = Yes; 0 = No
Age	Please indicate your year of birth
Gender	1 = Male; 0 = Female
Income	Please indicate your after-tax income (RMB) in 2018: 1. Less than 10k 2. 10k–20k 3. 20k–50k 4. 50k–100k 5. 100k–200k 6. 200k–300k 7. 300k–500k 8. 500k–1m 9. 1m–2m 10. 2m–5m 11. More than 5m
Education	Please indicate your highest education level: 1. Uneducated 2. Primary school 3. Junior secondary school 4. Senior secondary school 5. Junior college 6. Bachelor’s degree 7. Master’s degree 8. Doctoral degree
Religion	Do you have religious belief? 1 = Yes; 0 = No
Marital status	1 = Unmarried; 2 = Married; 3 = Divorced; 4 = Widowed
No. of family members under 18 years	Number of family members (living together) under 18 years
No. of family members over 65 years	Number of family members (living together) over 65 years
Region	Current residential province

Table 3.

Covariant Balance Across Groups.

Agency type
Variable	Charity	Set up by government	Set up by grassroots groups		p-value
Age	41.16	41.26	41.22		.99
Gender	0.51	0.56	0.54		.15
Income	4.41	4.40	4.46		.77
Education	5.34	5.34	5.35		.99
Religion	0.27	0.27	0.28		.86
N	697	671	667
Missing	35	43	49
Donor’s background
Variable	Citizen	Government employee	Company employee	Charity employee	p-value
Age	42.00	41.06	40.11	41.73	.13
Gender	0.56	0.51	0.55	0.51	.23
Income	4.47	4.49	4.38	4.34	.50
Education	5.34	5.43	5.37	5.23	.03
Religion	0.30	0.26	0.26	0.27	.40
N	523	527	518	467
Missing	25	32	34	36

Note. p-value corresponds to F-test results.

Empirical Model

The regression framework is shown in Figure 2, demonstrating the key independent variables that we are going to test, with hypothesized direction.

Figure 2.

Regression framework with key variables and hypothesized direction.

Results

The detailed sociodemographic information of the sample is shown in Table 4, including age, gender, income, education, religion, and region. Similar to other online samples collected from China (e.g., Truex, 2017), our sample contains citizens that are wealthier and better educated. Moreover, the religious population are oversampled in our survey. Thus, our findings can be at best generalized to online population.

Table 4.

Sociodemographic Information of Research Sample (N = 2,035).

Variable	Mean	SD	Freq.
Age (numerical, 18–99)	41.21	0.309	18–30: 554 (27.22%)31–50: 916 (45.01%)>50: 565 (27.76)
Gender (dichotomy, 0/1)	0.534	0.499	M: 1,087 (53.42%)F: 948 (46.58%)
Income (ordinal, 1–11)	4.422	1.724	0–100k: 1,076 (52.87%)≥100k: 959 (47.13%)
Education (ordinal, 1–8)	5.343	1.069	Non-Bachelor: 938 (46.09%)Bachelor: 1,097 (53.91%)
Religion (dichotomy, 0/1)	0.274	0.446	Religious: 558 (27.42%)Nonreligious: 1,477 (72.58%)
Region (dummy, 1–31)			Eastern: 1,135 (55.77%)Non-Eastern: 900 (44.23%)

Our model results are shown in Table 5 and a visualized presentation of the results is displayed in Figure 3. Models 1 to 3 are the key models, taking expected donation as the dependent variable. Consistent with our hypotheses, generalized, particularized, and institutional trust exert uneven effects on the social expectations about charitable giving. First, people with greater generalized trust expect others to donate more, supporting H1a. The expectations for social giving fall for those with particularized trust toward their relatives and neighbors, which supports H1b. These results are stable across different models. Specifically, in Model 3, one unit increase in the level of trust toward the general public is associated with a 1.8 unit increase in expected donation; one unit of increase in trust toward neighbors and relatives, however, is related to decreases of 1.2 and 1.9 units in expected donation, respectively.

Table 5.

Regression Results.

	DV = expected donation
Variable	Model 1	Model 2	Model 3
Agency type (base = unspecified)
Set up by government	0.799 (1.558)	0.670 (1.514)	1.301 (1.482)
Set up by grassroots groups	−0.188 (1.547)	−0.212 (1.499)	0.160 (1.462)
Donor’s background (base = citizen)
Government employee	5.457*** (1.804)	5.573*** (1.755)	5.934*** (1.728)
Company employee	0.507 (1.762)	0.924 (1.698)	1.284 (1.650)
Charity employee	3.227* (1.832)	3.221* (1.788)	3.299* (1.737)
Social trust
Trust in general population		1.723*** (0.394)	1.830*** (0.403)
Trust in neighbors		−1.212** (0.477)	−1.213*** (0.470)
Trust in relatives		−2.134*** (0.463)	−1.864*** (0.458)
Trust in charities		2.259*** (0.391)	1.934*** (0.381)
Trust in central government		−1.057** (0.510)	−1.000** (0.507)
Trust in local governments		1.210** (0.496)	1.107** (0.494)
Giving experience
Voluntary work (1 = yes in past year)			4.391*** (1.438)
Donation (1 = donated in past year)			−1.240 (1.340)
Demographic factors
Age			0.016 (0.059)
Gender (1 = male)			−3.040** (1.230)
Income			1.079** (0.480)
Education			−3.700*** (0.724)
Religion (1 = religious)			5.311*** (1.453)
Marital status (base = unmarried)
Married			−5.669*** (2.063)
Divorced			−10.89* (6.004)
Widowed			−15.85 (11.01)
Household
No. of family members under 18 years			1.903*** (0.605)
No. of family members over 65 years			1.698*** (0.564)
Region	Yes	Yes	Yes
Constant	34.74*** (2.652)	32.66*** (4.437)	48.28*** (6.837)
Observations	2,035	2,035	2,035
R ²	0.03	0.09	0.138

Note. Models 1 to 3 apply ordinary least squares regression analysis. Robust standard errors in parentheses.

p < .1. **p < .05. ***p < .01.

Figure 3.

Forest plot of regression results.

Second, people who trust more in charitable organizations expect others to contribute more to charities, and thus,H2 is supported. This pattern echoes previous research findings that trust toward charities induces more pro-social contributions. Interestingly, institutional trust toward the central government and local governments operates in different directions: While trust in the central government associates with decreased expectation for charitable giving, trust in local governments potentially relates to increased expectation for it. The patterns support both H3a and H3b. Specifically, in Model 3, one unit increase in trust toward the central government is associated with one unit decrease in expected donation; in the case of trust toward local governments, one unit increase in trust is related to about a 1.1 unit increase in expected donation.

Third, the evidence also underlines the ambiguous effect of government on philanthropic participation as a private decision. Government employees are expected to contribute more to charitable causes, supporting H5. However, this pattern does not extend to the recipients of donations, in that Chinese citizens do not expect others to donate more to government-backed charities. In fact, the treatment of charity types—whether a charity is government-backed or grassroots-based—does not show any significant effect on social expectations for donations; H4 is thus refuted.

Our results suggest that Chinese citizens with voluntary work experience tend to expect others to make larger donations. Experience in making donations, however, has no significant impact on expected donation from others. Expectation for donations is positively related to income levels, but negatively associated with education levels. People with religious belief place higher expectation for charitable donations. Married people are less keen on social donations, while underaged children and elderly family members living together increase social expectations for philanthropic giving.

Previous studies have found that geographical distribution of nonprofit organizations could impact on communities and regional nonprofit growth (Lecy et al., 2019; Matsunaga & Yamauchi, 2004), suggesting the possibility that the existing scale of the nonprofit sector in a given region might shape citizens’ expectations about social giving. To address the concern, we performed a robustness check by replacing the area fixed effect with the total number of nonprofit organizations in a province (taken natural log). Key results regarding the effects of agency type, donors’ background, and types of trust on expected donation are consistent with those of Model 3.

Heterogeneous Effects Analysis

We further examined heterogeneous effects by running the same model on region, gender, age, religion, income, and education subsets. Insofar as the hypotheses are concerned and with the exception of a few regions and sociodemographic clusters, the estimates are largely stable across subsets and consistent with our main findings. Full statistical results can be found in Supplemental Appendices.

The findings of our analysis show that respondents aged between 18 and 30 years expect others to donate less to government-backed charities, while those aged above 50 years expect more. It might suggest that the older generation are more accustomed to government-organized philanthropy in China. Citizens from non-Eastern regions expect company employees, but not government workers, to make more donations. Middle-aged people and those with religious belief expect both government workers and company employees to donate more.

Generalized trust positively affects citizens’ social expectations about charitable giving, except for the young or those living in less developed regions. Particularized trust, however, negatively influences citizens’ social expectations about charitable giving, except for those living in Eastern China. While the effect of trust in charities is consistent among different subsamples, trust in the central government crowds out citizens’ expectations for social giving only in the Eastern regions, and within female group. Trust in local governments tends to crowd in citizens’ expectations for social giving; such an effect is particularly strong among those who are middle-aged, well-educated, and in the medium-high income group.

Replication files for all empirical results in this study are posted on GitHub; please find them through this link: https://github.com/nelly678/Social-Expectations-for-Charitable-Giving-in-China

Discussion

The findings of this study have important theoretical and practical implications. For those who seek donations, our analysis suggests that a grassroots charity is deemed as equally deserving of private giving as a government-backed organization in China. Under the current regulatory framework, nonprofits are legally registered as associations, social service institutions, or foundations; Figure 4 shows the growth of registered nonprofits in China in the last decade. Registered nonprofits, however, are not the same as charitable organizations. According to Charity Law, a nonprofit can become a formal charity only after it obtains recognition from the Ministry of Civil Affairs. To apply for the charity qualification, a nonprofit is required to file a proper application and prepare relevant documents including financial statements and board meeting records; civil affairs departments will then make a decision on the charity status within 20 days. Our findings imply that being recognized as charity is a vital step for an organization to embed itself in the social giving context. The public expect charities to receive donations, regardless of their closeness with the authority. This finding is in line with Cheng and Wu (2021) that Chinese people would care about a nonprofit’s transparency and accountability when making donation decisions; having government ties does not necessarily advantage nonprofits in soliciting funds from the general public.

Figure 4.

Growth of registered nonprofits in China, 2005–2018.

The asymmetric effects of trust toward the central and local governments on the charitable expectations of Chinese citizens reflect some unique features of the state-society nexus in China. Attempts by the central government to control civil society activities have resulted in a complementary model of civil society development, in which the state dominates welfare provision while the nonprofits survive by focusing on unmet social needs (Lecy & Van Slyke, 2013). The state dominance not only crowds out philanthropy but also retrenches citizens’ expectation for philanthropic participation. This finding echoes the crowding-out argument (Andreoni, 1988, 1989). Citizens are rational taxpayers; when they observe an increase in government support to charitable organizations, they tend to respond by cutting down on their philanthropic contributions (Jilke et al., 2019). At the local level, government officials are often willing and keen to work with the nonprofits in public service delivery because collaboration can enhance operational efficiency. Such government-nonprofit interdependency can explain why trust toward local governments often goes hand in hand with expectations about charitable giving. The positive relationship between trust in local governments and expectations for social giving is in line with the crowding-in thesis, which argues that government support could incite more private giving (Rose-Ackerman, 1981).

The relationships between government support and private contributions are complex (Jilke et al., 2019). Our findings regarding the different effects of trust toward government at the central and local levels on social expectations for charitable giving further illustrate such complexity. Meanwhile, social expectation might serve as a theoretical lens through which the crowding-out/in effects can be understood, if not explained. Social expectation can be an important mediator in state–society interactions. Specifically, the different effects of trust in the central and local governments on social expectation for giving tend to create and reinforce a fragmented, localized ecosystem of nonprofit development in which some nonprofits are able to survive or even thrive through working closely with local governments and receiving philanthropic support. This activism however is likely to be confined to the local level and become less relevant beyond its region.

Conclusion

Employing the survey experimental method, this study examines citizens’ expectations for philanthropic giving in the context of China where the party-state plays a dominant role in managing different aspects of social life. The study’s findings show that the expected amount of donation increases if the philanthropic vignette involves a government employee. Generalized trust toward anonymous others, and institutional trust toward charities and local governments are found to be positively related to expected donation; particularized trust toward recognized groups and institutional trust toward the central government, however, have a negative relationship with expected donation. All but one of the hypotheses we put forth have been corroborated by the empirical results; the only anomaly is that the charities’ relationships with government do not significantly affect people’s expectation for social contributions donated to these organizations. Our results point to an interesting asymmetry—while charities with strong government backing are not expected to receive larger donations, people with strong government ties are expected to make larger donations.

This study is conducted in a nondemocratic context wherein charities are entangled in the regime; while they might help facilitate the party-state system, they hardly challenge, let along substitute, the state’s dominance in managing different functions (Ho & Edmonds, 2008; Spires, 2011). Although the conclusions of this study cannot be directly generalized to other regime types, they do point to an increasingly important role the civil society can play in public affairs. Even in authoritarian China where philanthropy has always been dominated by governments and government-backed nonprofits, citizens still form the expectation that grassroots charities are legitimate receivers of private donations.

We have found interesting patterns regarding how various factors, including government involvement, government ties, and social trust, influence expected donation; more research is needed to further identify and explain the mechanisms underlying these patterns. For instance, Chinese citizens’ expectation that government workers should donate more might have to do with the government’s long-standing reliance on bureaucrats to provide social services on the ground. Future research might help explain why Chinese citizens always presume a strong association between government and charities, and expect government officials to take up heavier charitable responsibilities such as making donations.

Supplemental Material

sj-docx-1-nvs-10.1177_08997640221100721 – Supplemental material for Social Expectations for Charitable Giving in China

Supplemental material, sj-docx-1-nvs-10.1177_08997640221100721 for Social Expectations for Charitable Giving in China by Lin Nie, Kwan Nok Chan and Wai-Fung Lam in Nonprofit and Voluntary Sector Quarterly

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Lin Nie

Kwan Nok Chan

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Lin Nie is lecturer in Department of Asian and Policy Studies, The Education University of Hong Kong. She has research interests in public administration and nonprofit management. Her research focuses on public organization management, nonprofit management, and state–society relationship. She has published in China Information, Nonprofit and Voluntary Sector Quarterly, Public Administration and Development, and Voluntas.

Kwan Nok Chan is assistant professor of Politics and Public Administration and deputy director of the Research Hub on Institutions of China, The University of Hong Kong. He specializes in the theory of the policy process, with a substantive focus on policy institutions and bureaucratic practices in China. His research has appeared in Governance, Journal of Comparative Policy Analysis, Journal of Politics, Policy Studies Journal, Regulation & Governance, and others.

Wai-Fung Lam is professor of Politics and Public Administration and Director of the Center for Civil Society and Governance at the University of Hong Kong. He is an expert in institutional policy analysis, the commons, social innovation, civil society, and public governance.

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