The monetary value of social capital

Accepted Manuscript

The monetary value of social capital Johannes Orlowski , Pamela Wicker PII: DOI: Reference:

S2214-8043(15)00049-X 10.1016/j.socec.2015.04.007 JBEE 112

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Journal of Behavioral and Experimental

Received date: Revised date: Accepted date:

24 July 2014 21 April 2015 22 April 2015

Please cite this article as: Johannes Orlowski , Pamela Wicker , The monetary value of social capital, Journal of Behavioral and Experimental (2015), doi: 10.1016/j.socec.2015.04.007

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Highlights We examine the monetary value of social capital in its multidimensional form EVS data from 45 European countries are used for the empirical analysis Shadow prices of social capital are estimated based on a well-being function Social capital has significant monetary value to individuals A one SD increase in institutional trust is worth on average € 7,405 per year in terms of foregone income

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The monetary value of social capital Johannes Orlowskia and Pamela Wickerb a

Department of Sport Economics and Sport Management, German Sport University Cologne, Am Sportpark Muengersdorf 6, 50933 Cologne, Germany

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Department of Sport Economics and Sport Management, German Sport University Cologne,

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Am Sportpark Muengersdorf 6, Cologne 50933, Germany

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Correspondence concerning this article should be sent to Pamela Wicker, Department of Sport Economics and Sport Management, German Sport University Cologne, Am Sportpark Muengersdorf 6, Cologne 50933, Germany; Phone: +49-221-4982-6107; E-mail: [email protected] Abstract

The purpose of this study is to estimate the monetary value of social capital by considering its multidimensional nature. Four dimensions are conceptualized: Interpersonal trust, institutional

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trust, trustworthiness, and participation in civil society (formal and informal). The monetary

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value is obtained by including social capital in a well-being function and estimating the shadow price of social capital. The empirical analysis is based on data from the European

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Values Survey covering 45 European countries. A generalized ordered response model is

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estimated to account for possible heterogeneity of social capital indicators among the ten different subjective well-being levels. The results show that on average a one standard

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deviation increase in interpersonal trust (people’s fairness) is worth an extra € 7,913 per year in terms of foregone income, the same increase in institutional trust is worth € 7,405, and the same increase in the importance of family is worth € 7,312. The findings indicate that social capital has significant monetary value to individuals. This should be considered when designing government policies aiming at e.g., labor market mobility that are accompanied by a decreasing social capital stock that, in turn, may negatively affect economic and political development.

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Keywords: Happiness; monetary value; shadow price; compensation valuation; social capital; subjective well-being; trust; generalized ordered probit model

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JEL classification: A13; D60; I30

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1. Introduction Social capital is relevant to societies because it facilitates the living together of individuals (Putnam, 1993b). Following Putnam (1993a, p. 167) social capital “refers to features of social organization, such as trust, norms, and networks that can improve the efficiency of society by facilitating coordinated actions.” Cooperation for mutual benefit is

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critical when an individual’s resources are not sufficient to complete a task alone or provide a good. In these cases individuals would be better off when they would cooperate; however, in the absence of social capital, i.e., when individuals do not trust each other, coordination of efforts and cooperation will not happen (Coleman, 1990). This situation has been described in

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a variety of ways including the prisoner’s dilemma and, in economic terms, the problem of public goods (Putnam, 1993a).

Since social capital improves the benefits of investment in physical and human capital

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(Putnam, 1993b), it is important to the economy. For example, social capital contributes to economic development (Knack & Keefer, 1997; Woolcock, 1998) and GDP (Peiro-Palomino

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& Tortosa-Ausina, 2014). Specifically, trust was found to be relevant for economic growth (Zak & Knack, 2001), since trust reduces transaction costs leading to higher market efficiency

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and a more prosperous economy (Fukuyama, 1995). Surprisingly, despite the economic

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relevance of social capital, only a few attempts have been made to quantify the effects of social capital (e.g., Mentzakis, 2011; Powdthavee, 2008). However, these studies only looked

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at one facet of social capital, i.e., participation in civil society (e.g., Colombo & Stanca, 2014) or interpersonal trust (Helliwell & Huang, 2010), and did not consider the multifaceted nature of this concept. The purpose of this study is to extend previous studies by using a multifaceted conceptualization of social capital. Specifically, we evaluate the contribution of five facets of social capital, i.e., formal and informal participation in civil society, interpersonal trust, institutional trust, and trustworthiness of individuals themselves to life satisfaction and assign

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a monetary value using the shadow price approach. We advance the following main research question: What monetary value can be assigned to the different facets of social capital? The empirical examination is undertaken using data from the most recent wave of the European Values Study where individuals from 45 European countries were surveyed. Thus, our sample covers more countries than previous single-country studies (Colombo & Stanca, 2014;

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Powdthavee, 2008). The findings show that the monetary values of social capital vary across the different levels of well-being. Thus, this research strengthens the argument for using

generalized ordered response models in well-being research. This study contributes to the body of research on the relationship between social capital and subjective well-being (SWB)

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and more general to the literature attempting to quantify intangible resources.

2. Conceptual framework: Multifaceted nature of social capital Following Lin (2001, p. 24), many researchers “share the understanding that social

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capital consists of resources embedded in social relations and social structure”. Researchers also agree that social capital is a multifaceted concept (e.g., Nahapiet & Goshal, 1998;

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Putnam, 1993a). Although many definitions of social capital share common traits, there is no consensus in the literature about the conceptualization of social capital and the dimensions,

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attributes, indicators, features, or elements it contains (Maxwell & Taylor, 2010). In most

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conceptualizations of social capital (e.g., Lillbacka, 2006; Putnam, 2000) the aspects connectedness of people (networks) and trust can be found suggesting they are critical

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elements of social capital. Given the variety of terms used in previous research, we refer to connectedness and trust as the two dimensions of social capital. These dimensions contain several facets: (1) connectedness comprises informal and formal participation in civil society, while (2) trust encompasses interpersonal trust, institutional trust, and trustworthiness. These dimensions and facets are interrelated (Nahapiet & Ghoshal, 1998). The first dimension is the connectedness of people (Putnam, 2000) respectively the ability of people to form social relationships and networks (Coleman, 1990). This is what

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Nahapiet and Ghoshal (1998) called structural embeddedness – links between people or units. This dimension has two facets – informal and formal participation in civil society (van Schaik, 2002). Informal participation refers to informal contacts among people such as friends, relatives, or neighbors (Pinquart & Sörensen, 2000). These are contacts without any institutional affiliation. Particularly small communities may be characterized by a strong

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social network, but do not have many formal associations (Lillbacka, 2006). Informal participation in civil society can be considered the most basic facet of social capital.

Formal participation in civil society is associated with membership and/or voluntary work in civil associations with membership representing the basic form of participation.

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These associations are typically all kinds of voluntary or non-profit organizations including sport and recreation organizations, religious organizations, and environmental organizations. They are known for teaching their members habits like solidarity and co-operation (Putnam,

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1993a). Therefore, they reinforce collective behavior and establish a sense of responsibility for others. A more intense form of formal participation in civil society is engaging in

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voluntary work in civil associations. Voluntary work can be supplementary to membership when it is performed by members (like in sport organizations); but there are also civil

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associations that rely on volunteers without membership. Membership and voluntary work in

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civil associations facilitate the development of social contacts and relationships and, thus, the development of social capital (Lillbacka, 2006). Thus, formal participation in civil society

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positively contributes to the development of informal participation supporting a supplementary relationship. The second dimension of social capital is trust which is supplementary to the first

dimension, connectedness: specific social structures such as civil associations reinforce and promote norms, trust, and values of the civic community (Putnam, 1993a; 1993b). Thus, participation in civil society results in an increased level of trust. Nahapiet and Ghoshal (1998) called this dimension relational embeddedness. Several scholars argued that trust is at

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the core of social capital (Coleman, 1990; Delhey & Newton, 2005; Fukuyama, 1995). The literature typically distinguishes three facets of trust, i.e., interpersonal trust, institutional trust, and trustworthiness of the individuals themselves (Knack & Keefer, 1997; Lillbacka, 2006; Paxton, 1999) that are also central to this study. Interpersonal trust refers to the expectation that other individuals act benevolently and

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would prefer cooperation if it is in the interest of collective benefits (Kunioka & Woller, 1999). In short form, interpersonal trust implies that people are virtuous citizens who are

trustful, helpful, and respectful (Putnam, 1993a). Institutional trust refers to the extent people trust in governmental institutions such as the legal system, parliament, and police (Evers &

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Gesthuizen, 2011). It can also be applied to non-governmental institutions like churches or other institutions that affect the well-being of society. For example, research shows that the financial crisis has eroded the citizen’s trust in the European Central Bank (Roth, Gros, &

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Nowak-Lehmann, 2012). Interpersonal and institutional trust are interrelated because institutions are comprised of (leading) individuals who make decisions and are thus

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responsible for how the institution is perceived by the public. In addition to interpersonal and institutional trust, the trustworthiness of the

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individuals themselves is relevant to the concept of social capital. Similar to the definition of

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interpersonal trust, trustful people are expected not to deliberately or knowingly harm others or behave selfishly themselves (Delhey & Newton, 2005). Trustworthiness and interpersonal

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trust are interrelated in the sense that in a society with a high share of trustworthy persons the overall level of interpersonal trust is expected to be higher too. The same applies to institutional trust since institutions are led by persons. In summary, social capital consists of two dimensions, connectedness and trust, that have several facets – informal and formal participation in civil society (connectedness) as well as interpersonal trust, institutional trust, and trustworthiness (trust). Following Putnam (1993b), stocks of social tend be self-reinforcing and cumulative meaning that social capital

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can be accumulated by investing in all five facets. Since social capital is central to the production and maintenance of collective well-being (Putnam, 1993b), the relationship between social capital and SWB is discussed in the next section. 3. Literature review 3.1. Social capital effects on subjective well-being

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Since the monetary value of social capital is often estimated using a well-being function (Powdthavee, 2008), the concept of SWB is explained. Following Diener, Lucas, and Oishi (2002, p. 63), SWB can be defined “as a person’s cognitive and affective evaluations of his or her life.” It can be considered a broad concept that “includes experiencing pleasant

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emotions, low levels of negative moods, and high life satisfaction” (Diener et al., 2002, p. 63). The concept of SWB has been increasingly applied in economics research (Downward & Rasciute, 2011). In empirical economics research, SWB is typically measured with a general

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question assessing overall life satisfaction (Powdthavee, 2008; Ruseski et al., 2014) or happiness (Downward & Rasciute, 2011).

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Previous research examined the determinants of SWB (for an overview of the economic literature see Dolan, Peasgood, & White, 2008). Since the purpose of this research

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is the monetary valuation of social capital, this review briefly mentions the income effect

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(which is needed for the valuation based on the shadow price approach) and focuses afterwards on the effect of social capital and on studies on social capital valuation. Regarding

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income, previous research has shown that income has a positive effect on SWB (e.g., Downward & Rasciute, 2011; Huang & Humphreys, 2012). While this effect holds in crosssectional analyses, it was documented that in many developed countries, the reported levels of SWB did not increase in line with income levels over time. This phenomenon is referred to as the Easterlin Paradox (e.g., Diener & Biswas-Diener, 2002; Easterlin, 1995). Turning to the effect of social capital on SWB, most previous studies provided evidence of a positive relationship (e.g., Helliwell, 2006; Pinquart & Sörensen, 2000). For

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example, it was shown that friends contributed positively to SWB (Fox & Kahneman, 1992). Taylor et al. (2001) used a variety of social capital indicators including subjective family closeness, support from family, number of friends, presence of fictive kin, and frequency of contact with neighbors which all had a significant effect on well-being among African Americans. Interpersonal and institutional trust was also found to have a positive effect on

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SWB (Helliwell, 2006; Helliwell & Putnam, 2004). Regarding trustworthiness, Helliwell (2003) detected a positive relationship between the wrongness to cheat on one’s taxes and SWB. The evidence on the relationship between participation in civil society and SWB is mixed: While the number of memberships in community organizations affected SWB

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positively in Pichler’s (2006) study, no significant relationship was observed in the work of Li, Pickles, and Savage (2005). Also, Haller and Hadler (2006) observed no significant relationship between volunteering and SWB. This overview indicates that previous research

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has only looked at specific facets of social capital, mainly at the role of family and friends, but has not considered its multifaceted nature.

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3.2. Monetary valuation of social capital A few studies provided monetary valuations for social capital (Colombo & Stanca,

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2014; Helliwell & Huang, 2010; Mentzakis, 2011; Powdthavee, 2008). The valuation of

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social capital is challenging because of the intangible nature of social capital – no quantities and prices can be observed that are usually used for monetary valuations – and because it

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lacks an explicit market (Clark & Oswald, 2002; Mentzakis, 2011; van Prag & Baarsma, 2005). Therefore, the literature has developed several monetization approaches including the shadow price approach (as a form of compensating variation), stated preference techniques, and hedonic approaches. The shadow price approach is based on a well-being equation that contains income, the variables of interest (here: social capital indicators), and a set of control variables as independent variables. Using the income coefficient and the coefficient of the social capital

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indicator a monetary value can be calculated. This calculation is based on the idea of compensation, i.e., it is calculated how much compensation an individual needs to be kept at the same level of SWB when the level of social capital decreases and vice versa. It is a common valuation method that has been applied to various activities, situations, or commodities including, for example, different life events (Clark & Oswald, 2002), airport

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noise (van Praag & Baarsma, 2005), and different health conditions (Powdthavee & van den Berg, 2011).

While the shadow price approach suffers from the vulnerable nature of SWB

questions, it overcomes the criticism of hypothetical bias which is expressed for stated

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preference techniques (for further methodological discussion we refer to Mentzakis, 2011). Stated preference approaches such as the contingent valuation method use hypothetical scenarios where the respondents are asked to state their willingness-to-pay that the scenario

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occurs or is avoided (for an overview see Carson, 2000). Both approaches typically use survey data.

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Most social capital valuation studies used the shadow price approach (Helliwell & Huang, 2010; Mentzakis, 2011; Powdthavee, 2008). Powdthavee (2008) analyzed two social

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capital indicators, i.e., meeting friends and relatives and talking to neighbors using panel data

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from the British Household Panel Survey (BHPS; 1997-2003). He ran linear, ordered probit, and fixed effects models. The obtained shadow prices from linear models were lower than

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those from ordered probit models. His shadow price estimates resulting from fixed effects models suggest that a move from meeting friends and relatives less than once or twice a month (reference category) to once or twice a month is worth £ 57,500 per year, a move to once or twice a week is worth £ 69,500, and a move to on most days is worth £ 85,000. Increasing the frequency of talking to neighbors and moving from the same reference category to once or twice a week was found to be worth £ 22,500 per year and a move to meeting them on most days was worth £ 37,000.

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Mentzakis (2011) also used BHP panel data (waves 8, 10, 12, and 14) and estimated monthly shadow prices for the frequency of talking to neighbors and meeting people (we present the figures for a move from almost never to on most days). Using linear models, he obtained shadow prices of £ 11,238 for talking to neighbors and of £ 11,058 for meeting people. When applying standard ordered probit Mundlak (1978) models, the respective

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shadow prices were slightly lower: £ 10,710 on average for talking to neighbors and £ 10,039 for meeting people. He also examined the monetary value of attending local groups; the shadow prices were £ 10,312 (linear model) respectively £ 10,180 on average (standard ordered probit). Moreover, generalized ordered response models that account for

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heterogeneity of effects were estimated. The respective shadow prices obtained with these models were substantially lower: £ 2,770 (talking to neighbors), £ 3893 (meeting people), and £ 2,666 (attending local groups). Therefore, Mentzakis (2011) concluded that the values

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obtained with the two earlier specifications should be treated with caution. Yet, since the latter models included some inconsistencies regarding significance of effects and changes in

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signs, he acknowledged that the simplicity of the standard approaches (linear and ordered probit) can also be considered attractive.

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Helliwell and Huang (2010) were the first to evaluate social capital at the workplace.

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They used cross-sectional data from three surveys; the second wave of the Canadian Equality, Security, and Community (ESC) survey, the 2003 General Social Survey (GSS), and the 2002

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Ethnic Diversity Survey (EDS). Ordered probit models were preferred over linear models. Estimating survey-ordered probit models, the compensating differentials for trust in coworkers were 48.4% (GSS) and 300.6% (EDS), respectively. The implied percentage income equivalent of trust toward management was 92.0% (ESC) for the same move. The figures show that individuals place great value on workplace trust. While the shadow price approach uses a well-being equation, hedonic approaches are based on price or income (wage) equations. The monetary value of the variable(s) of interest

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is also obtained by examining the coefficients of regression models. Since the dependent variable is monetary in nature, the coefficients already reflect monetary values. While the shadow price approach and stated preference techniques require individual-level data, the hedonic approach can also be applied to other levels (e.g., organizational level, regional level). To the knowledge of the authors, only Colombo and Stanca (2014) applied this method

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to social capital valuation. They estimated the monetary value of social capital in Italian provinces using house prices and wages. A one standard deviation increase in the percentage of those people who meet their friends most frequently was found to be worth € 1,150 per year to individuals in terms of higher housing prices and foregone income.

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The reviewed studies made a significant contribution to the monetization of social capital. Nevertheless, some shortcomings can be observed. The above studies only examined one facet of social capital, mostly participation in civil society (Colombo & Stanca, 2014;

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Mentzakis, 2011; Powdthavee, 2008), while one study examined interpersonal trust (Helliwell & Huang, 2010). The multifaceted nature of this concept was not considered. Moreover, it is

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difficult to compare shadow price estimates among studies because of different datasets, countries, time periods, and currencies. Therefore, the reviewed studies (and we) were

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hesitant to undertake comparisons. If comparisons between different facets of social capital

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are envisaged, data are needed that contain indicators measuring the various facets. 4. Data and empirical strategy

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4.1. Data source

This research is based on data from the most recent wave of the European Values

Survey (EVS) which includes data for all 47 European countries. The current study uses data from the 2008 wave where the data were actually collected in 2009 or 2010. In earlier waves, the income variable which is needed for the calculation of the monetary value of social capital was not, or poorly, assessed and therefore these data could not be used. In all countries, faceto-face interviews were conducted and a representative multi-stage or stratified random

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sample of the adult population was drawn. Interviewers received training before the field work and made at least three revisits when they did not reach the selected respondent at the first visit. The field work was coordinated by Tilburg University, CEPS/Instead, and GESIS (European Values Study, 2014). A total of n=67,768 people participated in the survey. The country-specific samples typically consist of approximately 1,500 observations with smaller

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countries only having 500 (Northern Cyprus, Northern Ireland) and 800 (Iceland) observations, respectively. Two countries (Turkey, Germany) have more than 2,000

observations. For this research, Northern Ireland was merged with Great Britain and coded as United Kingdom. Further, Northern Cyprus was dropped from the sample since it is not

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acknowledged as an independent state by the international community of states. In line with Powdthavee (2008), our sample is restricted to individuals of working age between 16 to 65 years because the opportunity of earning own income is critical for the calculation of shadow

4.2. Measures and variables

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prices. Altogether, n=38,963 observations from 45 countries are left for the analysis.

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Several steps were taken to ensure the high scientific quality standards of the EVS. The questions in the EVS were reviewed by a Theory Group which ensured that all questions

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were standardized between countries. The whole process of the questionnaire development

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was overseen and approved by the Council of National Program Directors. A Methodology Group was responsible for standardizing the translation process, fieldwork procedures, and

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data processing (European Values Study, 2014). The wording of the EVS survey questions can be found on the GESIS website (GESIS, 2013). Table 1 provides an overview of the variables used in this study and the concrete wording of the questions. In line with previous research SWB is assessed with a question for overall life satisfaction (e.g., Downward & Rasciute 2011; Powdthavee, 2008; Rasciute & Downward 2010). Satisfaction is measured on a 10-point scale. The two dimensions of social capital are measured with a total of ten indicators. Regarding the first dimension (connectedness),

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informal participation in civil society is captured by the importance of family, friends, and meeting nice people in an individual’s leisure time (measured on 4-point scale). Formal participation in civil society was measured with two variables that reflect the number of voluntary organizations individuals belong to as a member (Membership) and do unpaid work for (Voluntary_work).

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Turning to the second dimension (trust), interpersonal trust is captured with three indicators: Trust_people is a measure of general trust in other persons, while

Trust_people_fair and Trust_people_helpful specify interpersonal trust in terms of fairness and helpfulness. For institutional trust one variable is computed based on a set of questions

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that ask for the level of confidence in 18 different institutions. Trust_inst was obtained by calculating the mean value of these 18 variables that were originally assessed on a 4-point scale. The trustworthiness of individuals themselves (Trustworth) was measured with a set of

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nine questions relating to the extent an individual justifies untrustworthy or non-virtuous behavior (measured on a 10-point scale). Of the resulting nine variables, a mean value

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variable was calculated. The original list included 20 questions; however, eleven answers (i.e., homosexuality; abortion; divorce; euthanasia; suicide; having casual sex; prostitution;

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experiments on human embryos; manipulation food; invitro fertilization; death penalty) were

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excluded from the analysis because they did not specifically measure trustworthiness, rather morale opinions.

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An individual’s income is critical to this research because it is needed to estimate the

monetary value of social capital. Out of the various income variables in the EVS, a metric income variable measuring annual household income was selected to allow precise estimations. This income variable has already been adjusted by purchasing power parity (PPP) to allow cross-country comparisons. Annual per capita income was obtained by dividing annual household income by household size. Similar to previous research (e.g., Clark & Oswald, 2002; Downward & Rasciute, 2011; Kavetsos & Szymanski, 2010; Powdthavee,

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2008), this study also controls for various socio-demographic factors that could potentially affect an individual’s life satisfaction including gender, age, age squared, education, employment, health, life control, marital status, household size, children, and experience of several life events (Table 1). Insert Table 1 here

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4.3. Statistical modeling

The statistical analysis is performed with STATA 13. A set of regression models with Satisfaction as the dependent variable is estimated to obtain the parameters needed for the estimation of the monetary value of social capital. All other variables from Table 1 are

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included as independent variables in the models; the reference categories for education, employment, and marital status are Employed, Married, and Edu_basic. The empirical strategy follows the work of Boes and Winkelmann (2010), Mentzakis (2011), and

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Powdthavee (2011) applying a generalized ordered response model, more precisely a generalized ordered probit model (GOPROBIT), to estimate coefficients necessary to

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calculate monetary values. The GOPROBIT is our preferred method since it does not only account for the ordinal scale of the dependent variable, but further allows the income

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coefficient to vary across SWB levels.

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Altogether, eight models are estimated. The first model includes the total sample.1 Afterwards, the sample is split by age and gender to examine the monetary value of social

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capital for different population groups. In order to test for slope heterogeneity within the model the sample was split into five age groups (16-25 years; 26-35 years; 36-45 years; 46-55 years; 56-65 years) as well as by gender (Mentzakis & Moro, 2009). These subsamples were chosen since the different groups scored significantly different values within the social capital variables. 1

Since the dependent variable is highly disaggregated, we conducted a sensitivity check and collapsed the ten SWB levels into five categories. Even though the p-values across the different SWB levels slightly improve, the general pattern of results remains unchanged.

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Since previous research identified country-specific differences in the determinants and levels of life satisfaction (Clark et al., 2005; Pedersen & Schmidt, 2011) and the underlying dataset includes 45 countries, there would be a need to disentangle the country-level estimates. In line with Pedersen and Schmidt (2011), the aim was to compare social capital indicators across four different countries (i.e., Denmark, France, Italy, and Ireland) which

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were considered representative of four different types of European welfare states. However, a comparison of monetary values of social capital among these countries was not possible since the income coefficients and most of the social capital coefficients were not significant in the regression models. This might be due to the reduction of observations when looking at

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individual countries.

In the existing models, the year of the survey (2009 vs. 2010) had to be dropped because of multicollinearity issues. The variance inflation factors (VIFs) of the other

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independent variables are – with the exception of age and age squared – below 5 and, thus, below the suggested threshold of 10 (Hair et al., 2010). The overall sample size for the

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statistical models is adjusted to n=38,963 since cases with missing values are omitted. To control for unobserved heterogeneity across countries, a set of country dummies is included in

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the model for the total sample (reference: Sweden). All regression models are estimated using

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robust standard errors clustered by country. Estimates for models including all countries are not affected when applying weights based on population statistics (age and gender).

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4.4. Assigning a monetary value to social capital In line with previous research (e.g., Helliwell & Huang, 2010; Mentzakis, 2011;

Powdthavee, 2008), we apply the shadow price or compensation valuation approach to assign a monetary value to social capital. Following Powdthavee (2008), we use the suggested generalized well-being function introduced by Blanchflower and Oswald (2004) which is of the following form: 𝑟 = ℎ(𝑢(𝑠, 𝑦, 𝑧, 𝑡)) + 𝑒

(1)

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where r is a measure of well-being, say life satisfaction measured on a ten-point scale; u represents the true utility of the individual which is thought to be influenced by an individual’s social capital (s), income (y), a set of demographic variables (z) and time (t). Yet, in our case the time effect is constant since we only have cross-sectional data. Since the respondents’ true utility is only observable to the individual, the reported level of well-being

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is described by h( ), a non-differentiable function linking both utilities. The error term (e) is added to the function to cover possible non-observed effects influencing the level of SWB. Applying the general well-being equation (1), the monetary value of social capital is estimated in two steps. In a first step, in line with Boes and Winkelmann (2006), Mentzakis

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(2011), and Powdthavee (2011), the following well-being equation in terms of a cumulative conditional probability function is estimated: 𝑃(𝑆𝑊𝐵𝑖 ≤ 𝑗|𝑥𝑖 ; 𝜃𝑗 ) = Φ(−𝑥𝑖 𝜃𝑗 )

𝑗 = 1, … , 𝐽 − 1

(2)

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where SWB ϵ{1,…,J} represents a measure of SWB of individual i=1,…,n; xi represents a vector of covariates explaining SWB including the ten social capital indicators (Table 1); 𝜃𝑗

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represents a vector of SWB category-specific parameters. Further, Φ(. ) indicates the

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distribution function of the standard normal distribution. Additionally, 𝜃𝑗 is required to fulfill the following inequalities in order to ensure positive cell probabilities: 𝑥𝑖𝑗 𝜃𝑘 >. . . > 𝑥𝑖𝑗 𝜃𝐾−1

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(Powdthavee, 2011). Rewriting 𝑥𝑖 𝜃𝑗 as 𝑗 = 1, … , 𝐽 − 1

(3)

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𝑥𝑖 𝜃𝑗 = 𝛼𝑗 + 𝑥̃𝑖 𝛽𝑗

and in case 𝛽1 = ⋯ = 𝛽𝐽−1, equation (3) represents the standard ordered probit model. However, under the generalized model the hypothesis of equal slope parameters is not implied. Instead, for every point on the SWB scale a set of coefficients is estimated on the covariates 𝑥𝑖 . For a detailed description of ordered response models in general and GOPROBIT in particular we refer to Boes and Winkelmann (2006; 2010).

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In a second step, to obtain the shadow price (SP) of social capital, the associated marginal probability effects (MPE) for the estimated coefficients are estimated by taking the first derivative of the well-being function with respect to the variable of interest (Boes & Winkelmann, 2006). MPEs are obtained for two reasons. First, regression coefficients within ordered response models are not straight forward to interpret (Powdthavee, 2011). Second, as

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Mentzakis (2011) points out using the ratio of the estimated regression coefficients to calculate shadow prices is only applicable for continuous variables. However, if the variable of interest is binary in nature, MPEs should be used. Therefore, the shadow price is calculated as the negative ratio of the MPE of the respective social capital variable over the MPE of

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income (Boes & Winkelmann, 2010; Equation 4).

𝑆𝑃 = −𝑀𝑃𝐸𝑆𝐶 /𝑀𝑃𝐸𝑦

(4)

where 𝑀𝑃𝐸𝑆𝐶 represent different categories of one social capital indicator (e.g., Membership)

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and 𝑀𝑃𝐸𝛾 represents the marginal probability effect of income.

Imagine an individual aims at becoming a member of another voluntary organization

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which would represent a move from s1 to s2, where s2 > s1. The implied shadow price of this

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movement is then equivalent to the extra income that is needed to keep the individual with the lower level of social capital at the same level of well-being (Powdthavee, 2008). Recall that a

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precondition for the calculation of the shadow price is that the income coefficient is significant, and that the coefficient on the social capital indicator must be significant too. In

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other words, from equation (4) the pleasantness of social capital can be calculated. In line with Colombo and Stanca (2014), the shadow price is standardized, hence represents a one standard deviation change in social capital. In line with (Powdthavee, 2008) we provide annual shadow prices. The units of the shadow prices are financial; in this study they are measured in TSD Euros corrected for PPP.

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5. Results and discussion The summary statistics are presented in Table 1. Within the sample 45.2% of respondents are male and 54.8% female. The mean age is 41.3 years and the general level of education can be considered rather high with 26.4% of respondents having completed a tertiary education and 51.0% finished secondary education. Only 21.0% have just basic

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education and a small share of 1.6% have not completed any kind of formal education. The average annual net income per capita is € 6167 (SD=7491). The average score on the 10-point general life satisfaction variable is 7.00 (SD=2.26).

The descriptive statistics of the social capital indicators indicate that, on average, the

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importance of family (M=3.84; SD=0.42), friends (M=3.36; SD=0.65), and meeting nice people during leisure time (M=3.39; SD=0.67) is relatively high across the sample. Respondents are members (Membership) in on average 0.84 (SD=1.64) voluntary

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organizations of any kind and engage in 0.40 (SD=1.25) organizations in voluntary work (Voluntary_work). The majority of respondents have little interpersonal trust in general

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(Trust_people) since only 31.0 % indicated that most people can be trusted. The mean score for interpersonal trust in terms of fairness (Trust_people_fair) is 5.33 (SD=2.54) on a 10-point

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scale; average interpersonal trust in terms of helpfulness (Trust_people_help) is 4.53

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(SD=2.46) on the same scale. Institutional trust (Trust_inst) has a mean value of 2.44 (SD=0.53) on a 4-point scale. The trustworthiness of the respondents themselves

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(Trustworthiness) yields a mean of 8.74 (SD=1.31) on a 10-point scale. Table 2 presents the MPEs obtained for the GOPROBIT model. Regarding

connectedness, participation in civil society is positively associated with SWB; however, compared to interpersonal and institutional trust indicators they are statistically significant for fewer SWB levels. For instance, an increase in the number of formal memberships (Membership) shows only a significant, negative MPE for the SWB level 5. Hence, one additional membership decreases the probability for reporting a 5 by 1.6 percentage points.

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These findings are similar to previous research that found no significant effect of membership in voluntary organizations (Li et al., 2005) and voluntary work (Haller & Hadler, 2006) on SWB, although there are also studies which detected a significant relationship (e.g., Pichler, 2006). Concerning informal participation in civil society, two of three indicators are significant for most levels of SWB. Meeting_people has a positive and significant effect on

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high SWB levels (9 and 10). Family has a significant, positive effect for high SWB levels (8 and 9), while Friends is insignificant for all levels (except for SWB level 7). This finding is in accordance with previous research (Martin & Westerhof, 2003). There are other studies that detected a significant relationship (Powdthavee, 2008); yet, the measures were slightly

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different and are, thus, difficult to compare.

Regarding trust, the results show that all three indicators of interpersonal trust have a positive effect on SWB. More precisely, they decrease the probability of reporting lower

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levels of SWB (6 or lower) and increase the probability of reporting higher levels of SWB (7 or higher). For example, generally trusting others (Trust_people) increases the probability to

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report a 9 on the SWB by 2.4 percentage points whereas it decreases the probability to report a 4 or 5 by roughly 1.0 percentage points. With respect to institutional trust (Trust_inst), it

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appears that the MPEs are only significant for the lowest as well the highest SWB levels. A

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unitary positive change in institutional trust decreases the probability that a person places herself in the lower SWB levels (SWB 1-2) and increases the probability of placing herself in

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the higher SWB levels (SWB 8-10). Additionally, it can be noted that the change in probability is much higher for higher levels of SWB than it is for the lower levels. The trustworthiness of the respondents themselves is also positively associated with SWB. The positive effects of interpersonal and institutional trust as well as individual trustworthiness for most levels of satisfaction are in line with previous research (Helliwell, 2003; 2006; Helliwell & Putnam, 2004).

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The MPE of income is negative and significant for lower levels of SWB (3-6) and positive for higher levels of SWB (7-9). This is in line with previous research (Kavetsos & Szymanski, 2010) and allows the estimation of the monetary value of social capital in the next step. The control variables have in most cases the expected signs and the effects are in line with the literature: for example, males report lower levels of SWB than females across all

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SWB categories; the age effect is u-shaped (e.g., Downward & Rasciute, 2011); higher education is associated with higher probability of reporting higher SWB levels (e.g., Kavetsos & Szymanski, 2010); self-employment and retirement are associated with higher SWB, while unemployment reduces well-being; and health status has a positive effect on SWB (e.g.,

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Rasciute & Downward, 2010). Thus, the present model represents an adequate basis for the calculation of monetary values of social capital indicators. However, it should be noted that even though the MPEs for most social capital indicators across all levels of SWB are

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significant they appear to be rather small. This leads to relatively low shadow prices compared with other studies (Powdthavee, 2008; Mentzakis, 2011).

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Insert Table 2 here

Table 3 presents the monetary values of the social capital indicators for the ten SWB

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levels. In line with Mentzakis (2011), the presented means are calculated as means of all

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significant monetary values across SWB levels. To improve the comparability of monetary values in the sense that the magnitude of change is more standardized, we follow the approach

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taken by Colombo and Stanca (2014) and provide the foregone income per year when the social capital indicator increases by one standard deviation. However, this approach still suffers from the underlying scales because larger scales will also produce larger standard deviations. The monetary values obtained show that a one standard deviation increase in interpersonal trust is worth between an extra € 5,318 and € 10,528 (people’s fairness) and between € 4,848 and € 13,164 (people’s helpfulness) per year in terms of foregone income,

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respectively. A one standard deviation increase in institutional trust is equivalent to an extra € 6,196 to € 8,460 per year in terms of foregone income; the same increase in one’s trustworthiness is valued at an extra € 2,540 to € 9,710. Noteworthy here is that within the SWB level 7 a negative and relatively high negative value is obtained. This means that an individual would need to be reimbursed for a one standard deviation increase in institutional

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trust which intuitively does not make sense. A one standard deviation increase in the importance of family is worth between an extra € 4,156 and € 11,115 per year in terms of foregone income; a lower monetary value (between € 3,937 and € 5,334) is obtained for the importance of meeting nice people in one’s leisure time (again, showing a counterintuitive

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negative value at SWB level 5). Comparing the means of the various social capital indicators across SWB levels, it appears that interpersonal trust seems to be most important for an individual’s SWB. In line with Mentzakis (2011), the variety of values across SWB levels

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supports the notion that there is significant heterogeneity across SWB levels and favors the use of generalized ordered response models.

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Insert Table 3 here

In Table 4, mean monetary values of social capital indicators are reported for different

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population groups. The mean monetary values across SWB levels are presented for males and

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females as well as for five different age groups. Again, the mean values are calculated based on all significant monetary values. Comparing men and woman points to differences in the

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role social capital plays for their SWB. Across all social capital variables the monetary values calculated for women are higher than those for men. The only exception is the importance of family: whereas a one standard deviation increase in the importance of family is worth an extra of € 6,519 of foregone income per year to males, it is only worth an extra of € 927 per year to females. Also noteworthy is the relatively high monetary value necessary to compensate males for a one standard deviation increase in memberships in voluntary

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organizations: an extra of € 17,448 per year would be necessary in order for them to stay at the same SWB level while accepting a one standard deviation increase in memberships. Looking at the differences between age groups, it appears that there are very few statistically significant monetary values. This makes a comparison across groups rather difficult. However, it can be seen that the importance of family seems to increase over the life

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cycle. For 26- to 35-year-olds a one standard deviation increase in the importance of family is worth an extra of € 4,395 in terms of foregone income per year. In comparison a similar

increase in the importance of family is worth an extra of € 7,016 per year to 36- to 45-yearolds and € 7,542 per year to 56- to 65-year-olds.

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Insert Table 4 here 6. Conclusions

This study examined the monetary value of social capital using the shadow price

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approach. It extends previous research (Colombo & Stanca, 2014; Powdthavee, 2008) because it considers the multifaceted nature of social capital and covers more countries than previous

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single-country studies. From a statistical point of view, a generalized ordered probit model is applied which takes into account the heterogeneity of covariates across SWB levels.

PT

Furthermore, the model is applied to various subsamples to identify possible heterogeneity

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across different population groups with respect to social capital indicators. Standardized shadow prices are presented that allow comparisons between the different social capital

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indicators. For example, a one standard deviation increase in interpersonal trust (people’s helpfulness) is worth on average an extra € 8,497 per year in terms of foregone income and the same increase in the importance of meeting nice people in one’s leisure time is worth an extra € 2,373 on average. This study contributes to the increasing body of research on estimating the monetary value of intangible and non-market goods. Studies like the present research are relevant because policy makers increasingly look for such monetary equivalents which may help justifying government subsidies.

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The findings of this study are also economically relevant. They indicate that social capital has significant monetary value to individuals. This should be considered when designing government policies aiming at e.g., labor market mobility because they may weaken the social ties with family and friends (Dolan et al., 2008) and, thus, reduce the level of social capital. Paradoxically, the allocation idea behind labor market mobility is that an

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individual is employed where he/she produces the highest marginal revenue product. However, research has shown that rising incomes are accompanied with increasing

workloads, rising social problems, and consequently stagnant SWB (Facci & Chartier, 2008). Thus, the development of social capital is prohibited which is problematic: as outlined earlier,

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social capital is positively associated with economic development and the democratic structure of a country and, thus, such policies may in turn negatively affect those

developments. It can therefore be recommended that policy makers rather invest in policies

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that foster the development of social capital. In addition, policy makers should take care of the institutions they are involved in themselves (e.g., political parties, government) or which they

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can exert influence on (e.g., health care system, education system) in terms of ensuring that these institutions can be trusted.

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This study has some limitations that represent avenues for future research. First, it is

CE

only based on cross-sectional data because the variables required for the analysis were only assessed in the last wave of the EVS. Future surveys (also the EVS) should be aware of the

AC

value of panel data and take care of the continuing presence of important variables in each wave of the survey. Having said this, it must be acknowledged that the estimated shadow prices do not take into account that individuals adapt to both income and trust. For example, an increase in interpersonal trust in the first year will likely result in higher shadow prices than the long-term effect of interpersonal trust. Panel data would be helpful to control for adaptation. Second, the operationalization of some social capital facets and the subsequent analysis was limited to the variables which were available in the survey. In some cases other

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measures would have been preferred. Specifically, the frequency of meeting family, friends, and nice people would have been preferred over an importance measurement, but this was not available. Moreover, this study suffers from the comparability of monetary values because of the use of different scales for social capital measures. Future research should enhance the comparability of measures by applying similar scales. Third, the shadow price approach also

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has some limitations because of its reliance on individual income. This implies that the social capital of low income people is of lower value, although their stock of social capital may be higher. The hedonic approach shares similar problems. Future research may look for an

approach that relies less on individual income. One option would be the contingent valuation

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method (Carson, 2000) which may provide measures that are less determined by individual income, but also has some shortcomings (Mentzakis, 2011).

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Acknowledgements This research received no funding.

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The authors declare that they have no conflicts of interest.

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Running Head: MONETARY VALUE OF SOCIAL CAPITAL Table 1 Overview of variables and summary statistics (total sample, n=38,963)

Social capital Family Friends Meeting_people

Scale Ordinal

Mean 7.0009

SD 2.2641

How important is it in your life? Family (1=not at all important; 4=very important) How important is it in your life? Friends (1=not at all important; 4=very important) Importance of meeting nice people in leisure time (1=not at all important; 4=very important) Number of memberships in voluntary organizations; sum of the following 15 variables: Please look carefully at the following list of voluntary organizations and activities and say which, if any, do you belong to? Social welfare services for the elderly, handicapped or deprived people; religious or church organizations; education, arts music or cultural activities; trade unions; political parties or groups; local community action on issues like poverty, employment, housing, racial equality; third world development or human rights; conservation, the environment, ecology, animal rights; professional associations; youth work (e.g. scouts, guides, youth clubs etc.); sports or recreation; women’s groups; peace movement; voluntary organizations concerned with health; other groups (1=yes; 0=no) Number of voluntary organizations the individual works voluntarily for; sum of the following 15 variables: Please look carefully at the following list of voluntary organizations and activities and say which, if any, are you currently doing unpaid voluntary work for? Same organizations as above (1=yes; 0=no) Generally speaking, would you say that most people can be trusted or that you can’t be too careful in dealing with people? (0=can’t be too careful; 1=most people can be trusted) Do you think that most people would try to take advantage of you if they got the chance, or would they try to be fair? (1=most people would try to take advantage of me; 10=most people would try to be fair) Would you say that most of the time people try to be helpful or that they are mostly looking out for themselves? (1=people mostly look out for themselves; 10= people mostly

Ordinal Ordinal Ordinal

3.8421 3.3613 3.3898

0.4196 0.6519 0.6653

Metric

0.8386

1.6385

Metric

0.4001

1.2538

Dummy 0.3101

0.4625

Ordinal

5.3326

2.5369

Ordinal

4.5281

2.4595

Trust_people_fair

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Trust_people_help

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Trust_people

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Voluntary_work

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Membership

Description All things considered, how satisfied are you with your life as a whole these days? (1=dissatisfied; 10=satisfied)

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Variable Satisfaction

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Edu_none Edu_basic Edu_sec Edu_tert Employed

2.4423

0.5259

Metric

8.7360

1.3091

Annual net income per capita (in TSD Euros corrected for PPP)=Monthly net household income*12/Household_size Gender (1=male) Year of survey-year of birth Age squared (=Age*Age) Migration background=either individual or father or mother do not have the country’s nationality where they currently live (1=yes) What is the highest level you have completed in your education? Pre-primary education or none education (1=yes) Primary education or first stage of basic education; lower secondary or second stage of basic education (1=yes) (Upper) secondary or post-secondary non-tertiary education (1=yes) First stage or second stage of tertiary education (1=yes) Please select from the card the employment status that applies to you: Paid employment (1=yes) Self-employed (1=yes) Unemployed (1=yes) Military service (1=yes) Retired/pensioned (1=yes) Housewife not otherwise employed (1=yes) Student (1=yes)

Metric

6.1670

7.4912

Dummy Metric Metric Dummy

0.4518 41.3168 1883.65 0.1369

0.4977 13.2883 1111.16 0.3437

AC

Self_employed Unemployed Military_service Retired Housewife Student

Metric

AN US

Male Age Age2 Migrant

SD

M

Controls Income

Mean

ED

Trustworth

Scale

PT

Trust_inst

Description try to be helpful) Mean value of the following 18 variables: How much confidence you have in the church; armed forces; education system; press; trade unions; police; parliament; civil service; social security system; European Union; NATO; UNO; health care system; justice system; major companies; environmental organizations; political parties; government? (1=none at all; 4=a great deal) Mean value of the following 9 variables: Do you justify claiming state benefits; cheating on tax; joyriding; taking soft drugs; lying in own interest; adultery; accepting a bribe; paying cash to avoid taxes; avoiding fare public transport? (10=never, 1=always)

CE

Variable

32

Dummy 0.0160

0.1254

Dummy 0.2095

0.4070

Dummy 0.5104 Dummy 0.2641 Dummy 0.5499

0.4999 0.4408 0.4975

Dummy Dummy Dummy Dummy Dummy Dummy

0.2518 0.3232 0.0295 0.2881 0.2876 0.2413

0.0680 0.1185 0.0009 0.0913 0.0910 0.0621

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Running Head: MONETARY VALUE OF SOCIAL CAPITAL

Children Death_children

AC

CE

PT

Death_father Death_mother Divorce_children Divorce_parents Divorce_relative

AN US

Married Partnership Widowed Divorced Separated Never_married Household_size

M

Life_control

Description Disabled (only if respondent does not work because of disability) (1=yes) All in all, how would you describe your state of health these days? (1=very poor; 4=very good) How much freedom of choice and control you feel you have over the way your life turns out? (1=none at all; 10=a great deal) What is your current legal marital status? Married (1=yes) Registered partnership (1=yes) Widowed (1=yes) Divorced (1=yes) Separated (1=yes) Never married and never registered partnership (1=yes) Number of people living in household=1+partner, husband or wife+children+parents+ grandparents+other relatives+other non-relatives How many children do you have? Have you ever experienced any of the following events? Death of your own children (1=yes) Death of your father (1=yes) Death of our mother (1=yes) Divorce of one of your children (1=yes) Divorce of your parents (1=yes) Divorce of another relative (1=yes)

ED

Variable Disabled Health

33

Scale Mean Dummy 0.0183 Ordinal 3.7883

SD 0.1340 0.8980

Ordinal

6.7222

2.3453

Dummy Dummy Dummy Dummy Dummy Dummy Metric

0.5721 0.0220 0.0458 0.0753 0.0156 0.2692 3.2914

0.4948 0.1467 0.2091 0.2639 0.1239 0.4436 1.6257

Metric 1.4941 Dummy 0.0333

1.3271 0.1795

Dummy Dummy Dummy Dummy Dummy

0.4923 0.4433 0.1721 0.2843 0.4081

0.4123 0.2687 0.0306 0.0887 0.2112

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Running Head: MONETARY VALUE OF SOCIAL CAPITAL Table 2

34

Marginal probability effects for generalized ordered probit model for all variables (total sample; n=38,963)

Voluntary_work Trust_people Trust_people_fair Trust_people_help Trust_inst Trustworth Male Age Age2

AC

Migrant

5 -0.0008*** (0.0003) -0.0048 (0.0041) 0.0033 (0.0024) 0.0004 (0.0022) -0.0029** (0.0014) 0.0015 (0.0025) -0.0100* (0.0054) -0.0029*** (0.0010) -0.0036*** (0.0010) -0.0134*** (0.0040) -0.0007 (0.0017) 0.0008 (0.0047) 0.0040*** (0.0008) -0.0000*** (0.0000) 0.0107**

6 -0.0007* (0.0004) -0.0165*** (0.0033) -0.0025 (0.0036) -0.0050** (0.0025) 0.0005 (0.0022) -0.0022 (0.0029) -0.0038 (0.0039) -0.0020** (0.0008) 0.0016 (0.0010) -0.0030 (0.0043) -0.0032** (0.0015) -0.0002 (0.0028) 0.0029*** (0.0008) -0.0000*** (0.0000) 0.0045

7 0.0011*** (0.0003) -0.0072 (0.0044) 0.0061* (0.0036) -0.0078*** (0.0025) -0.0025 (0.0022) 0.0013 (0.0026) 0.0120** (0.0048) -0.0003 (0.0012) 0.0009 (0.0009) -0.0014 (0.0059) -0.0062*** (0.0021) 0.0047 (0.0034) 0.0019** (0.0009) -0.0000* (0.0000) 0.0069

AN US

Membership

4 -0.0007** (0.0003) -0.0069*** (0.0025) -0.0028 (0.0019) 0.0006 (0.0021) -0.0016 (0.0013) -0.0001 (0.0015) -0.0095** (0.0037) -0.0020*** (0.0007) -0.0013* (0.0008) -0.0012 (0.0026) -0.0049*** (0.0012) -0.0001 (0.0024) 0.0007 (0.0007) -0.0000 (0.0000) -0.0050

M

Meeting_people

3 -0.0010*** (0.0003) -0.0101*** (0.0025) 0.0016 (0.0018) -0.0060* (0.0034) 0.0009 (0.0009) -0.0017* (0.0010) -0.0019 (0.0039) -0.0031*** (0.0006) -0.0026*** (0.0006) -0.0016 (0.0035) -0.0020* (0.0011) 0.0010 (0.0025) 0.0005 (0.0008) -0.0000 (0.0000) -0.0051

ED

Friends

2 -0.0001 (0.0002) -0.0029 (0.0023) -0.0018 (0.0014) -0.0002 (0.0014) 0.0010 (0.0009) -0.0016* (0.0010) -0.0033 (0.0025) -0.0021*** (0.0005) -0.0010* (0.0005) -0.0065*** (0.0017) -0.0010 (0.0007) 0.0016 (0.0021) 0.0003 (0.0004) -0.0000 (0.0000) 0.0029

PT

Family

SWB level 1 -0.0003 (0.0002) -0.0023 (0.0018) -0.0005 (0.0019) -0.0004 (0.0016) 0.0002 (0.0010) -0.0002 (0.0010) -0.0030 (0.0024) -0.0021*** (0.0005) -0.0039*** (0.0008) -0.0090*** (0.0020) -0.0015 (0.0009) 0.0023 (0.0019) 0.0013*** (0.0005) -0.0000** (0.0000) 0.0047

CE

Variables Income

8 0.0013*** (0.0005) 0.0346*** (0.0054) -0.0057 (0.0046) -0.0046 (0.0033) 0.0018 (0.0020) -0.0016 (0.0023) 0.0129** (0.0059) 0.0027* (0.0015) 0.0039** (0.0016) 0.0154*** (0.0046) 0.0044** (0.0021) -0.0022 (0.0057) -0.0011 (0.0012) 0.0000 (0.0000) -0.0157**

9 0.0009* (0.0005) 0.0149** (0.0063) -0.0051 (0.0072) 0.0074*** (0.0025) 0.0010 (0.0019) 0.0040* (0.0021) 0.0240*** (0.0049) 0.0038*** (0.0010) 0.0049*** (0.0010) 0.0133* (0.0070) 0.0069*** (0.0018) -0.0028 (0.0036) -0.0049*** (0.0011) 0.0000*** (0.0000) -0.0054

10 0.0003 (0.0003) 0.0012 (0.0078) 0.0073** (0.0037) 0.0156*** (0.0034) 0.0017 (0.0017) 0.0007 (0.0022) -0.0175*** (0.0046) 0.0078*** (0.0010) 0.0010 (0.0008) 0.0074* (0.0044) 0.0082*** (0.0030) -0.0051 (0.0043) -0.0056*** (0.0010) 0.0001*** (0.0000) 0.0015

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Unemployed Military_service Retired Housewife Student Disabled Health Life_control Partnership Widowed Divorced

AC

Separated

5 (0.0045) -0.0119 (0.0088) -0.0175*** (0.0039) -0.0326*** (0.0048) 0.0028 (0.0066) 0.0102* (0.0054) -0.0248 (0.0333) -0.0054 (0.0062) -0.0058 (0.0050) 0.0117 (0.0139) 0.0064 (0.0104) -0.0230*** (0.0020) -0.0136*** (0.0011) 0.0127 (0.0135) 0.0146** (0.0064) 0.0105* (0.0057) 0.0363*** (0.0119)

6 (0.0059) -0.0161 (0.0110) 0.0055 (0.0037) 0.0021 (0.0047) -0.0074 (0.0062) 0.0063 (0.0044) -0.0630** (0.0297) -0.0047 (0.0058) -0.0024 (0.0048) -0.0103 (0.0089) -0.0021 (0.0106) -0.0152*** (0.0019) -0.0078*** (0.0010) 0.0167* (0.0095) 0.0095 (0.0093) 0.0248*** (0.0049) 0.0283*** (0.0103)

7 (0.0056) -0.0155 (0.0096) 0.0112** (0.0047) 0.0160*** (0.0055) 0.0076 (0.0069) 0.0010 (0.0066) 0.1146* (0.0674) -0.0111 (0.0069) -0.0032 (0.0063) -0.0009 (0.0081) -0.0287** (0.0135) -0.0088*** (0.0023) -0.0056*** (0.0011) 0.0005 (0.0122) 0.0121 (0.0092) -0.0032 (0.0073) 0.0343** (0.0163)

AN US

Self_employed

4 (0.0047) -0.0052 (0.0097) -0.0003 (0.0037) 0.0026 (0.0052) 0.0018 (0.0074) 0.0094** (0.0037) 0.0231 (0.0313) 0.0005 (0.0036) 0.0055 (0.0061) 0.0067 (0.0066) 0.0166 (0.0116) -0.0164*** (0.0015) -0.0087*** (0.0007) -0.0071 (0.0078) 0.0127*** (0.0036) 0.0208*** (0.0059) 0.0203*** (0.0069)

M

Edu_tertiary

3 (0.0038) -0.0052 (0.0071) -0.0043 (0.0034) -0.0038 (0.0032) -0.0098* (0.0051) 0.0095** (0.0039) 0.0522 (0.0439) -0.0103*** (0.0040) -0.0091* (0.0049) 0.0003 (0.0065) 0.0058 (0.0056) -0.0209*** (0.0015) -0.0088*** (0.0008) 0.0025 (0.0084) 0.0196*** (0.0045) 0.0144*** (0.0041) 0.0290*** (0.0082)

ED

Edu_secondary

2 (0.0031) 0.0102*** (0.0033) -0.0034 (0.0028) -0.0073*** (0.0026) 0.0020 (0.0034) 0.0075*** (0.0020) -0.0018 (0.0162) 0.0062** (0.0031) 0.0006 (0.0028) 0.0011 (0.0048) 0.0050 (0.0056) -0.0086*** (0.0012) -0.0039*** (0.0006) 0.0083 (0.0084) 0.0125*** (0.0034) 0.0056 (0.0036) 0.0108** (0.0048)

PT

Edu_none

SWB level 1 (0.0031) 0.0184*** (0.0056) -0.0079*** (0.0023) -0.0073** (0.0034) 0.0005 (0.0038) 0.0183*** (0.0030) 0.0077 (0.0188) 0.0031 (0.0038) -0.0004 (0.0042) -0.0126** (0.0060) 0.0053 (0.0057) -0.0137*** (0.0015) -0.0052*** (0.0007) 0.0020 (0.0073) 0.0151*** (0.0029) 0.0129*** (0.0033) 0.0199*** (0.0043)

CE

Variables

8 (0.0071) -0.0094 (0.0172) 0.0346*** (0.0059) 0.0543*** (0.0092) 0.0027 (0.0100) -0.0327*** (0.0083) -0.0403 (0.0623) -0.0194** (0.0092) -0.0115 (0.0086) -0.0032 (0.0121) -0.0149 (0.0167) 0.0171*** (0.0027) 0.0080*** (0.0012) -0.0307** (0.0152) -0.0225*** (0.0087) -0.0350*** (0.0090) -0.0568*** (0.0171)

9 (0.0080) 0.0245** (0.0097) 0.0068 (0.0052) 0.0200*** (0.0067) -0.0118 (0.0084) -0.0249*** (0.0071) -0.0138 (0.0621) 0.0166* (0.0087) 0.0054 (0.0071) 0.0037 (0.0128) -0.0414*** (0.0127) 0.0394*** (0.0025) 0.0182*** (0.0022) 0.0014 (0.0154) -0.0352*** (0.0095) -0.0256*** (0.0076) -0.0575*** (0.0164)

35

10 (0.0054) 0.0102 (0.0077) -0.0246*** (0.0056) -0.0440*** (0.0081) 0.0118** (0.0054) -0.0046 (0.0057) -0.0538 (0.0389) 0.0245*** (0.0084) 0.0209*** (0.0079) 0.0036 (0.0087) 0.0480*** (0.0144) 0.0502*** (0.0036) 0.0275*** (0.0024) -0.0063 (0.0092) -0.0384*** (0.0096) -0.0253*** (0.0082) -0.0646*** (0.0139)

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36

SWB level 1 2 3 4 5 6 7 8 9 10 0.0073** 0.0047 0.0102** 0.0047 0.0108** 0.0154*** 0.0162*** -0.0059 -0.0197** -0.0438*** (0.0031) (0.0031) (0.0047) (0.0038) (0.0052) (0.0044) (0.0058) (0.0074) (0.0097) (0.0056) Household_size -0.0000 -0.0002 -0.0007 -0.0008 -0.0023* -0.0013 -0.0016 0.0039** 0.0009 0.0021 (0.0007) (0.0005) (0.0008) (0.0010) (0.0013) (0.0013) (0.0013) (0.0015) (0.0014) (0.0013) Children -0.0018* -0.0004 0.0004 -0.0014 -0.0018 -0.0012 0.0004 0.0005 0.0019 0.0034** (0.0010) (0.0013) (0.0012) (0.0009) (0.0013) (0.0017) (0.0017) (0.0021) (0.0017) (0.0017) Death_children 0.0083** 0.0030 0.0074 -0.0037 0.0089 -0.0129** -0.0236** -0.0037 0.0034 0.0130 (0.0042) (0.0025) (0.0072) (0.0056) (0.0083) (0.0058) (0.0104) (0.0145) (0.0107) (0.0085) Death_father -0.0000 -0.0010 0.0032 0.0008 0.0015 -0.0037 0.0006 -0.0005 -0.0029 0.0021 (0.0025) (0.0022) (0.0036) (0.0030) (0.0043) (0.0028) (0.0041) (0.0053) (0.0060) (0.0042) Death_mother 0.0001 0.0003 -0.0063** -0.0014 0.0060* -0.0040 -0.0021 -0.0069 0.0093* 0.0050 (0.0028) (0.0021) (0.0028) (0.0029) (0.0032) (0.0045) (0.0063) (0.0077) (0.0051) (0.0048) Divorce_children -0.0001 -0.0016 0.0154* 0.0028 0.0183** -0.0064 -0.0105 -0.0115 -0.0185* 0.0121 (0.0058) (0.0048) (0.0081) (0.0068) (0.0091) (0.0077) (0.0096) (0.0113) (0.0102) (0.0111) Divorce_parents 0.0078** 0.0029 0.0022 0.0051 0.0047 -0.0033 0.0094 -0.0110 -0.0123* -0.0055 (0.0034) (0.0031) (0.0034) (0.0036) (0.0048) (0.0056) (0.0060) (0.0068) (0.0068) (0.0054) Divorce_relative -0.0001 -0.0039* 0.0026 -0.0029 0.0022 -0.0026 0.0074* 0.0004 0.0087** -0.0119** (0.0023) (0.0021) (0.0034) (0.0043) (0.0042) (0.0038) (0.0040) (0.0054) (0.0038) (0.0046) Observations 38,963 38,963 38,963 38,963 38,963 38,963 38,963 38,963 38,963 38,963 Note. Marginal probability effects based on estimated GOProbit coefficients; robust standard errors in parentheses; standard errors clustered by country; country dummies included (reference: Sweden); ***p<0.01; **p<0.05; *p<0.1.

AC

CE

PT

ED

M

AN US

Variables Never_married

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Running Head: MONETARY VALUE OF SOCIAL CAPITAL Table 3 Monetary value of social capital in TSD Euros (PPP) per year (total sample; n=38,963)

AC

CE

PT

ED

M

AN US

SWB level 1 2 3 4 5 6 7 8 9 10 Mean Participation in civil society (informal) Family 2.9770 14.8329 4.1558*** 4.3277*** 2.4302 10.2098*** -2.7478 11.1148*** 6.7455** 1.8330 7.3107 Friends 1.00935 14.1819 -1.0537 2.7301 -2.5697 2.3738 3.6469* -2.8589 -3.5813 16.9937 3.6469 Meeting_people 0.7944 1.3205 3.9373* -0.5870 -0.3447 4.9520** -4.7308*** -2.3578 5.3338*** 36.9538 2.3731 Participation in civil society (formal) Membership -1.0889 -19.2449 -1.3848 4.0141 5.8101** -1.3114 -3.7072 2.2979 1.7811 9.7173 5.8101 Voluntary_work 0.7232 25.3417 2.1046* 0.1317 -2.2868 4.1641 1.4422 -1.5051 5.3757* 3.0334 3.7401 Interpersonal trust Trust_people 4.1936 18.9310 0.8594 6.5139** 5.5707* 2.6039 5.0879** 4.5649** 12.0069*** -28.8022 6.7489 Trust_people_fair 15.948 65.0491 7.8242*** 7.6777*** 8.8270*** 7.3024** -0.6201 5.3179* 10.5276*** 70.9935 7.9128 Trust_people_help 29.090 30.0771 6.2887*** 4.8480* 10.7624*** -5.9373 2.0682 7.4204** 13.1636*** 8.7665 8.4966 Institutional trust Trust_inst 14.4067 42.0560 0.8328 0.9060 8.4600*** 2.3487 -0.6587 6.1959*** 7.5589* 13.8258 7.4049 Trustworthiness Trustworth 5.7900 16.5906 2.5394* 9.5162*** 1.0928 6.0963** -7.4627*** 4.3774** 9.7101*** 38.2938 4.1294 Note: Mean is calculated as the mean of all significant monetary values; shadow prices for a one standard deviation increase in the respective social capital indicator are reported; ***p<0.01; **p<0.05; *p<0.1.

37

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Running Head: MONETARY VALUE OF SOCIAL CAPITAL Table 4 Mean monetary values of social capital by gender and age group in TSD Euros (PPP) per year Gender Male

Age groups 16-25

26-35 36-45 46-55 56-65 Participation in civil society (informal) Family 6.5190 0.9268 n.s. 4.3946 7.0158 n.s. 7.5417 Friends 6.9772 n.s. n.s. 5.3240 5.6664 n.s. n.s. Meeting_people 0.9344 5.0070 n.s. n.s. 1.3971 n.s. n.s. Participation in civil society (formal) Membership -17.4481 n.s. n.s. n.s. 8.8749 n.s. n.s Voluntary_work 13.9192 n.s. n.s. n.s. n.s. 13.9469 n.s Interpersonal trust Trust_people n.s. 2.0132 n.s. n.s. -9.2600 n.s. n.s Trust_people_fair 8.7734 16.576 n.s. n.s. 16.3724 n.s. 13.4985 Trust_people_help 7.2800 8.1967 n.s. 4.9115 4.9280 n.s. n.s Institutional trust Trust_inst 6.6405 n.s. n.s. n.s. 6.1367 n.s. 5.6605 Trustworthiness n.s Trustworth 0.2822 6.5407 n.s. 5.3929 5.0129 -7.4061 n.s Observations 17,605 21,358 6,087 8,236 8,766 8,699 7,175 Note: Means are calculated as the mean of all significant monetary values across SWB levels (n.s. means that none of the obtained monetary values across SWB levels were significant); shadow prices for a one standard deviation increase in the respective social capital indicator are reported.

AC

CE

PT

ED

M

AN US

Female

38