Different from the literature, this paper differentiates between personal trust and community trust. Compared with the general social environment that social trust reflects, individuals measure the trustworthiness of different people based on their relationships with them, and they must continually maintain, enforce, and adjust these beliefs through their interactions. Gift giving is frequently used to show a willingness to maintain a relationship or construct a new network link with someone. Gift giving as a form of social exchange mostly occurs in one-to-one personal relationships. Gift giving may serve different purposes, and it can play a role in collective actions. For example, when a poor household faces an unfortunate event, the village leaders may call on the villagers to provide goods or money to help the family. In this case, the gift transfer will increase community trust at the individual and collective levels and influence the affective associations between individuals. Later, if the help providers or gift givers face difficulties, the receiver will have a moral obligation to return the kindness in some way.
This paper examines how gift giving helps to form and maintain social capital in relation to trust at the community and individual levels. Community level trust is evaluated in terms of the average level of trust in the community. For personal trust, it is assumed that the more often mutual help occurs between one agent and other villagers, the more mutual trust exists between them. Thus, the frequency of mutual help between one agent and other households is included in the questionnaire to indicate the individual levels of trust.
Because the villagers are assumed to behave in a reciprocal rather than altruistic manner, whether an individual can obtain a loan depends on whether he or she is deemed to be trustworthy. We use credit access channels, namely formal institutions and informal personal loans, to evaluate the effect of social capital. In addition, the purposes for the loans are differentiated into production, house construction, medical care, education, consumption, and other factors. Although all of the personal loans are based on informal commitments, investments in production and housing can generate valuable outputs, which the lenders may use as a kind of collateral. The loans obtained for other purposes are mainly based on trust or risk-sharing motivations.
In the empirical model, we first test whether people give gifts to accumulate or maintain social capital at the community trust or personal trust levels. We then test whether the effects of the two levels of trust along with gift giving help with credit accessibility via the formal and informal channels.
3.1.1. Social Trust Formation: Community Trust and Personal Trust
Because villagers are assumed to be reciprocally rather than altruistically minded, whether an individual can obtain a loan depends on whether he or she is deemed to be trustworthy and whether the creditor is willing to make an informal commitment based on the interaction. Gift giving can be used to help form social trust or commitment as a cost of set up or to maintain social links and send signals. We first distinguish personal trust from community trust. Because the independent variable indicating the strength of social trust is an order variable, we use an ordered probit model to estimate the impact of gift giving on the formation of social capital, which is specified as
where
S is social trust and its subscript,
k =
c,
p, indicates community trust and personal trust, respectively. Community level trust
Sc is measured by the respondents’ answers to a question about how much they trust their neighbors and other residents in the village (options: 1 = strongly distrust, 2 = distrust, 3 = generally trust, 4 = trust, 5 = strongly trust). Personal trust
Sp is measured by a question about frequency of the mutual help between households and other residents in the village (options: 1 = seldom, 2 = few, 3 = general, 4 = frequent, 5 = very frequent).
G is the amount of gift giving of a household,
X includes other control variables, and
ζ is the error term.
We assume that people use gifts as tools to maintain or enforce social relationships. Gifts may not only help facilitate trust between individuals but also increase the social capital at the community level by lifting the overall level of trust. Here, we propose hypothesis H1.
Hypothesis 1a (H1a). The gift giving of households increases social trust at the community level.
Hypothesis 1b (H1b). The gift giving of households increases social trust at the individual level.
3.1.2. Credit Accessibility Affected by Community Trust and Personal Trust
We explore the effect of social capital on credit accessibility by testing whether social capital helps households to access credit and whether social capital affects the credit accessibility channels.
Because we only include households with loans in the sample, to avoid sample selectivity bias, we use the Heckman selection model [
14]. The first stage of the selection model can be written as
The binary probit regression is used to estimate the effects of social trust on loan accessibility. Here, Loani* is assumed to be a latent variable representing the existence of a loan, Zi refers to a vector of the control variables, and νi ~N (0,1) is the error term. Note that Loani* is not observed, and we can only observe Loani. If Loani* > 0, Loani* = 1; and if Loani* ≤ 0, Loani* = 0.
Let the variable
Amount represent the borrowing amount (in log form); then,
Amounti =
θ0 +
θ1Si,k +
θ′Xi +
μi, where μ
i is a normally distributed error term with a mean of zero and standard deviation
σ. We only observe
Amounti when
Loani* is greater than zero. We assume that the error terms
μi ~ N (0,
σ2), corr (
μi, ν
i) = ρ, where ρ represents the correlation between the two error terms to be estimated. The parameter
λ =
σρ, known as the inverse Mills ratio, is the estimated selection coefficient (Greene, 1993). Then, the second-stage regression model can be written as
In the first step, the probit regression is used to model the sample selection process in Equation (2), and the inverse Mills ratio
λ is calculated based on the probit regression results. In the second step, the inverse Mills ratio is added to the multiple regression analysis as an independent variable and ordinary least squares is used to provide the consistent parameter estimates in Equation (3). According to Wooldridge (2006), the explanatory variables in Equation (3) should be a subset of the explanatory variables in Equation (2). Thus, at least one explanatory variable in Equation (2) does not appear in Equation (3). We also include variables that refer to the existence of banks, cooperative organizations, and the distance to the nearest town in Equation (2), which are excluded in Equation (3). We consider these variables to have a direct effect on the occurrence of a loan, but less effect on the borrowing amount.
Furthermore, we explore the influence mechanism of gift giving on the borrowing amount using a causal mediation analysis [
34,
35]. Community level trust and personal trust may be potential mediators of the effect we wish to estimate. Thus, to identify the casual direct effect, we need to posit and fit regression models for the mediator
Si,k and the outcome of interest (
Amounti|
Loani* > 0). The mediator model is listed as Equation (2). The outcome is modeled as
where the borrowing amount is a function of the mediator
Si,k and gift expenditure, and all of the covariates. A mediator variable can either account for all or some of the observed relationship between gift giving and the borrowing amount. If the inclusion of the mediation variables eliminates the effect of gift giving on the borrowing amount and the coefficient of variable
G is insignificant, there exists full mediation of social trust for gift giving. When the inclusion of the mediation variables only weakens the effect of gift giving, there exists partial meditation. The partial mediation effect of gift giving implies that giving gifts not only increases the level of social trust, which helps form the belief in fulfilling the commitment and affects the borrowing amount through the other functions it brings.
Social trust at different levels, such as community trust and individual trust, is worth studying—in particular, how they influence families to seek resources from formal institutions or through informal channels. Monetary loans are often considered an effective means of studying social networks because there is a relatively clear record of where and how much a household borrows. Rural households usually have two main ways to borrow money: formal lending from banks and financial cooperatives, and informal lending from individuals based on informal commitments. According to Chinese property law, rural households do not possess full property rights on their farmlands and estates and thus usually cannot use them as guarantees. The lack of a personal credit evaluation system for Chinese farmers also makes the formal and informal lenders heavily dependent on trust. In addition, the different levels of trust play different roles in these financial channels. Thus, we propose hypothesis H2.
Hypothesis 2a (H2a). Personal trust helps households access credit through informal channels.
Hypothesis 2b (H2b). Community trust helps households access credit through formal channels.
Different from formal institutions that pursue profits, informal loans are mostly a way of sharing risk and providing help. Moreover, when households require loans to deal with costs such as medical or tuition fees rather than investments, the householders will have difficulty accessing the credit through formal channels such as banks. We propose hypothesis H3.
Hypothesis 3 (H3). Personal trust helps more in unprofitable loans.