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Public Management ReviewPublication details, including instructions for authorsand subscription information:http://www.tandfonline.com/loi/rpxm20
Bonding and BridgingAssociational Social Capital andthe Financial Performance ofLocal Authorities in IsraelGila Menahem a , Gideon Doron b & David Itzhak Haimb
a Department of Public Policy , Tel-Aviv University ,Tel-Aviv, Israel E-mail:b Department of Political Science , Tel-Aviv University ,Tel-Aviv, Israel E-mail:c Department of Political Science , Tel-Aviv University ,Tel-Aviv, Israel E-mail:Published online: 13 Jun 2011.
To cite this article: Gila Menahem , Gideon Doron & David Itzhak Haim (2011)Bonding and Bridging Associational Social Capital and the Financial Performanceof Local Authorities in Israel, Public Management Review, 13:5, 659-681, DOI:10.1080/14719037.2010.532962
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BONDING ANDBRIDGINGASSOCIATIONALSOCIAL CAPITAL ANDTHE FINANCIALPERFORMANCE OFLOCAL AUTHORITIESIN ISRAEL
Gila Menahem, Gideon Doron andDavid Itzhak Haim
Gila MenahemDepartment of Public PolicyTel-Aviv UniversityTel-Aviv, Israel
E-mail: [email protected]
Gideon DoronDepartment of Political ScienceTel-Aviv UniversityTel-Aviv, Israel
E-mail: [email protected]
David Itzhak HaimDepartment of Political ScienceTel-Aviv UniversityTel-Aviv, Israel
E-mail: [email protected]
Abstract
This study explores whether bridging and
bonding social capital differ in their impacts
on government performance at the local level
and the extent to which these impacts vary
between localities exhibiting differing socio-
economic resources. The study is based on
an analysis of 256 local authorities in Israel.
The findings show that bridging and bonding
social capital do differ in their respective
effects on government performance and that
the nature of the relationship of each type of
capital with government performance varies
by the community’s socioeconomic profile.
Poor communities with high densities of
bridging social capital were characterized by
lower deficits as a percentage of total
municipal budgets, more accurate expendi-
ture forecasts and greater spending on
services per capita.
Key wordsBonding social capital, bridging social capital,
local government, municipal performance,
social capital
Vol. 13 Issue 5 2011 659–681
Public Management Review ISSN 1471-9037 print/ISSN 1471-9045 online
� 2011 Taylor & Francis
http://www.tandf.co.uk/journals
DOI: 10.1080/14719037.2010.532962
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INTRODUCTION
Why are some governments more effective and better managed than are others? In thewake of Putnam’s (1993) influential study in Italy, social capital – conceptualized associal networks and participation in voluntary associations, trust and reciprocitynorms – has emerged as a major perspective for addressing the issue of governmentperformance on two levels, the national level (Evans 1996; Knack and Keefer 1997;Woolcock 1998; Paxton 2002) as well as local (John and Dowding 1998; Cusack 1999;Maloney et al. 2000; Pennington and Rydin 2000; Taylor 2000; Tavits 2006; Andrews2007).
Previous research has provided evidence for the positive correlation of socialcapital with institutional and government performance (Knack and Keefer 1997;Whiteley 2000; Rice 2001; Knack 2002). The three basic components of socialcapital – trust, reciprocity norms and participation in social associations – have beenexamined in most empirical studies. However, some pieces in the puzzle are stillmissing. While evidence has been found of a relationship between trust andperformance, little or no correlation has been observed between the associationalcomponent of social capital and measures of public performance (Knack and Keefer1997).
The present study suggests that the failure to distinguish between bonding andbridging social capital, a recent theoretical development in the study of social capital(Putnam 2000; Zmerli 2003; Messner et al. 2004; Rydin and Holman 2004; Beyerleinand Hipp 2005), may be one source of these results. The literature posits that bondingassociations ‘bring together people who are like one another in important respects(ethnicity, age, gender, social class, and so on)’, whereas bridging social networks‘bring together people who are unlike one another’ (Putnam and Goss 2002: 11).Previous studies have in fact claimed that not all associations are ‘the same’, to quoteStolle and Rochon (1998); they found that associations based on homogeneousmembership often tend to express attitudes promoting the exclusion of minoritygroups. This possible ‘dark’ side of social capital has not been adequately researched asmuch of the literature assumes the inherent goodness of social capital and its use(Osborne 2009). By applying the distinction between bonding and bridging socialcapital, this study attempts to explain this and other previously inconsistent results inaddition to discussing some lesser addressed issues.
The main argument to be empirically examined here is, therefore, that bondingand bridging associations are differentially associated with governmentalperformance.
This study extends previous research in several respects. Since Putnam’s (1993)study in Italy the relationship between government performance and social capital hasbeen widely researched (Keefer and Knack 1997; Rice 2001; Knack 2002; Casey andChrist 2005) and some studies examined the relationship between the different types of
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social capital and attitudes towards democracy (Paxton 2002; Coffe and Geys 2007) andcrime rates (Messner et al. 2004; Beyerlein and Hipp 2005). However, the studies thatempirically examine the link between social capital and local government performance(Cusack 1999; Rice 2001; Coffe and Geys 2005; Tavits 2006; Andrews 2007) did notdistinguish between the two types of social capital.
An additional aspect of the research on social capital expanded in this study is that oflocal non-profit organizations. As Tsukamoto and Nishimura (2006: 573) argue, therole of the non-profit sector at the local level in the building social capital has beenrelatively neglected for many years. The present study therefore attempts to add torecent efforts (Cnaan 2009) to examine the contribution of voluntary associations to thepublic sphere.
We also find a gap in the literature regarding how bridging and bonding social capitaloperate in the context of disparate communities. Of major interest here is the questionof whether and to what extent the differences in the impact intensify in communitieshaving differing socioeconomic resources. Based on theoretical arguments presentedbelow, we claim that bonding social capital has more negative – and bridging socialcapital more positive – impacts in poor as compared with more affluent communities.In other words, we propose investigating the stratification dimension of both types ofsocial capital, a subject yet to be addressed in the literature, in communities that vary bysocioeconomic status.
We do so by exploring the relationship between the density of associational bondingversus bridging social capital and a series of objective measures of financial andadministrative performance as observed in 256 local authorities in Israel, differentiatedby their socioeconomic characteristics.
The remainder of this article is structured as follows: the theoretical introductiondiscusses why bonding and bridging social capital can be expected to have differentimpacts on societal outcomes in general and on government performance in particular;it also discusses why community context matters. The methodology section describesthe classification methods applied, the performance measures applied and the databasesused in the analysis. The subsequent section presents the findings, followed by adiscussion and conclusions.
THE THEORETICAL LITERATURE AND THE QUESTIONS POSED
The narrow fit between the normative and associational components of socialcapital and government performance
Previous studies have revealed only a narrow fit between the positive effect of trust, thenormative dimension of social capital and associational components of social capital ongovernment performance. In a study of 114 localities in Iowa, Rice (2001), who found
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that trust was related to higher measures of government performance, found nocorrelation of the associational factor – density of participation in civic organizations –with the same measures of performance. Knack (2002), in his study of the performanceof US state governments, found that while trust was related to quality government,participation in civil organizations was not.
Knack and Keefer (1997) attribute the apparent insignificance of the associationaldimension of social capital to two opposing forces: the positive effect ofassociations, posited by Putnam, could be offset by the negative effect of groupsacting as rent-seekers or lobbying for self-serving policies that impose costs on therest of society.
The present study refines this suggestion by incorporating the distinction betweenbonding and bridging social capital in research on the relationship between associationalsocial capital and municipal performance.
The potential fruitfulness of distinguishing between bonding and bridgingsocial capital
The recent recognition of the potentially negative effect of homogenousand exclusionary social networks and associations (Levi 1996; Portes 1998; Stolleand Rochon 1998; Foley and Edwards 1999; Putnam 2000: 350–63; Woolcock andNarayan 2000; Paxton 2002; Adam and Roncevic 2003) has motivated a theoreticaldistinction between bonding and bridging social capital (Putnam 2000; Putnam andFeldstein 2003). Bonding social capital is defined as networks exhibiting connectionsestablished primarily or entirely among members of the same group; that is, suchassociations are ‘inward-looking and tend to reinforce exclusive identities andhomogeneous groups’ (Putnam 2000: 22). In contrast, bridging social capital consists ofnetworks or associations that are connected to or crosscut a variety of associationstogether with the larger community. They are ‘outward-looking and encompass peopleacross diverse social cleavages’ (Putnam 2000: 22). In conjunction with this refinement,it was hypothesized that bonding social capital may negatively impact on therecruitment of broader social resources. It was further suggested that bridging socialcapital was ‘better for linkage of external assets and for information diffusion’ (Putnam2000: 22). Bridging social capital thus tended to positively impact on the largercollective as well as on any specific group (Woolcock and Narayan 2000; Smith andKulynych 2002; Rydin and Holman 2004).
In the present article we go one step further and argue that bridging and bondingsocial capital differ in their relationship to government performance. In elaboratingthis claim we first address the differences in those social mechanisms, embedded inthe inherent disparities distinguishing the two types of capital. We summarily reviewthe explanations offered to account for the relationship between social capital andgovernment performance and then argue that they are insufficient to explain
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differences in government performance. We close by elucidating how the distinctionbetween bonding and bridging social capital facilitates evaluation of the acceptedexplanations.
Linking social capital with government performance
Boix and Posner (1998) categorize the explanations for the observed relationshipbetween social capital and government performance into five distinct models, each ofwhich flows from a different political theory. Three of the models pertain to voterbehavior and civic virtues and can be considered to belong to the sphere of civil society:the rational voter model argues that social capital turns citizens into more sophisticatedpolitical consumers who demand services and accountability from elected leaders; therule compliance model suggests that social capital reduces the costs of enforcing andimplementing government policies and regulations; finally, the civic virtues modelcontends that in communities rich in social capital, voter preferences represent not onlyparticularistic but also community-wide interests.
Boix and Posner (1998) argue that some of the explanations found in the literatureare based on elite accommodation models, which suggest that social capital makes it possiblefor political and bureaucratic leaders to cooperate and compromise without fearof losing their constituents’ support. Other explanations, as Boix and Posner show,represent models of bureaucratic efficiency, in which social capital promotesorganizational effectiveness by attenuating the principal–agent problem. These twoexplanations relate to organizational dimensions of the public administration andgovernment.
This study argues that the characteristics of bonding social capital do not adequatelyexplain how these models work. A more satisfactory explanation must incorporate thedistinction between bonding and bridging social capital as well as demonstrate theimplications of each type for explanations of government performance. We suggest thatthe importance of bridging social capital for performance lies in the nature ofgovernment, in its essence as a mechanism for mediating between the creation of publicvalues and the imposition of private costs, for weighing private preferences againstpublic interests. We therefore argue that the more expansive bridging networks aremore appropriate to managing these conflicting missions.
Support for this argument is found in Patulny and Svendsen (2007), who claim thatbonding organizations tend to transform non-excludable into excludable goods. That is,they are more liable to transmit better-quality services and information along privaterather than public channels, a process that channels the benefits flowing from thesolution of collective action problems to a limited number of parties. Bridgingnetworks, that are broadly linked, tend to distribute the benefits to a wider range ofgroups. Doing so endows them with the potential to promote broader production ofpublic goods and thereby overcome collective action problems.
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With respect to the leadership dimension, following the logic of the eliteaccommodation model, we argue that in contexts evidencing abundant bonding andsparse bridging networks, leaders will be threatened with the loss of constituentsupport should they wish to cooperate or compromise surrounding conflict resolution.When regarding government as an organizational entity, bridging social capital, whichconnects diverse groups within an organization, may plausibly be essential forovercoming principal–agent problems.
Combining these arguments, we propose the following theoretical argument forlinking bridging and bonding social capital to government performance. In polities highwith bonding social capital, citizens who demand public services may attempt totransform non-excludable into excludable goods and confine the positive outcomes ofthese efforts to their own membership group. This situation hampers administrativeelites in their efforts to cooperate with a wide spectrum of groups. Political leaders, ontheir part, may find their policy choices limited because of the increased difficulty ofnegotiation between the different groups.
Alternatively, an abundance of bridging networks in a community may promotecooperation among groups, leaders and among officials, an attitude conducive to moreprudent management of group demands and more efficient mitigation of the pressuresto channel benefits along private routes.
Linking bonding and bridging social capital with community attributes andgovernment performance
To what extent does context determine the relationship between bonding versusbridging social capital and government performance? Stated differently, does the effectof bonding versus bridging social capital differ in groups or communities that aresocioeconomically different?
We suggest that the impact of social capital on government performance is morecrucial in social contexts marked by meager socioeconomic resources. In affluentcommunities, for example, political leaders and administration may have ready access toprofessional consultants (e.g. organizational development experts) and other resources(e.g. private police) when seeking to compensate for poor government performance.Correspondingly, government in these communities may be able to provide residentswith a wider array of services, which may mitigate the need to compromise amonggroup demands. In contrast, in poor communities having no spare economic resources,high stocks of social capital, especially of the bridging type, may be necessary to ensuregreater leadership cooperation and greater citizen mobilization to arrive at creativecompromises among competing demands. Bridging social capital may also facilitatemobilization of resources throughout the community, thereby exposing all parties tonew knowledge and ideas for dealing with public issues when they have no access toexternal assistance.
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Linking bonding and bridging social capital with government performance
What aspects of government performance are susceptible to the impact of social capital?Wallis and Dollery (2002) present a taxonomy of minimal, intermediate and activistgovernments, which they relate to stocks of social capital. Activist governments arethose that assume many functions, design innovative policies and coordinate public–private partnerships. The authors suggest that low stocks of social capital constraingovernment’s ability to adopt more activist policies, whereas high stocks of socialcapital facilitate such a stance. In line with this argument, Tavits (2006) suggests thatgovernment performance should not be viewed as unidimensional. She employs a two-dimensional measure of performance that distinguishes between policy activism,measured by the size of allocations to policy domains, and bureaucratic efficiency. Hercomparison of previous findings on German and American cities reveals that socialcapital is associated with policy activism but not with bureaucratic efficiency. However,although discerning different dimensions of government performance, Tavits (2006)does not distinguish between bonding and bridging social capital, a distinction thatappears especially salient for public service provision.
Following the civic virtues model (Putnam 1993; Boix and Posner 1998), we suggest thatin localities having more abundant social capital, more intensive demands for accountabilitywill compel leaders to adopt more activist policies so as to provide improved services for theirconstituents. Accordingly, it seems plausible to argue that broad constituent consent and wideelite accommodation are also required. Bridging social capital appears to be essential for suchchoices. Hence, it appears reasonable to hypothesize that in polities low in bridging socialcapital, policy activism will be lower than in those polities exhibiting high bridging socialcapital. In addition, as such policies may require the allocation of greater resources to selectedpolicy domains, bridging social capital may be imperative for activism in communities havingmeager socioeconomic resources. Given their inability to mobilize additional financialresources, such communities may be more prone to recruiting resources through bettercooperation, network use and compromises regarding revised policy preferences. Moreover,bridging social capital may also support improved administrative efficiency (Boix and Posner1998).
We therefore posit that the failure to distinguish between the two types of socialcapital may have led to the inconclusive results found in the literature. Based on theabove theoretical considerations, the present study addressed the following researchquestions and hypotheses.
Research questions
1 Do bonding and bridging social capital differ in their relationships with localgovernment performance along the dimensions of efficiency and activism? If so,what is the nature of this difference?
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2 Does local context matter? In other words, does the relationship of the twotypes of social capital – bridging and bonding – with local governmentperformance (i.e. activism and administrative efficiency) depend on the locality’ssocioeconomic characteristics?
Research hypotheses
1 Bonding and bridging social capital differ in their relationship with localgovernment performance.
2 Social capital differs in its relationship to performance in localities with highsocioeconomic resources as compared with localities with low socioeconomicresources (socioeconomic ranking).2a Bridging social capital is more strongly correlated with improved municipal
performance in localities having a low socioeconomic ranking than inlocalities having a high socioeconomic ranking.
2b Bonding social capital makes a smaller contribution to municipalperformance than does bridging social capital in localities of lowsocioeconomic status.
2c Bridging social capital is more strongly correlated with activist government inpoorer than in wealthier localities.
THE STUDY
Methodological considerations, research population and data sources
The study focused on the associational dimension of social capital as measured by thenumber and types of social organizations per capita in a community. Following Putnam(1993, 2000; see also Beyerlein and Hipp 2005), this aggregate-level measure hasbecome a major instrument for measuring social capital (Svendsen and Bjørnskov2007). Such community-level measures correspond to the reality that policy makersencounter when confronting with demands or support conveyed by local civicorganizations and their individual members; hence, they fit the theoreticalargumentation guiding the study.
The research populationThe present study included all of the 256 urban municipalities in Israel in the year 2000.Of these, 178 had an almost totally Jewish population; a small minority (seven) had amixed Jewish-Arab population. The remaining eighty-two municipalities had entirelyArab populations. One reservation should be noted here. The unique characteristics of
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the Arab-Israeli population require special consideration when defining and measuringbonding and bridging social capital in localities where all the residents are Arab-Israelis.A major characteristic distinguishing Arab from Jewish localities and of much relevancefor the current study is the important role played by the extended family (hamula) inlocal politics (Al-Haj and Rosenfeld 1990; Herzog and Yahia-Younis 2007). Theextended family is the Arab community’s major bonding network on the one hand andthe cause of the low participation rate in a community’s formal (non-familial)associations on the other. As can be seen from Table A in the Appendix, Arab-Israelilocalities rank lowest among all the communities in the sample on measures of bondingand bridging social capital, far below the lowest scores obtained for Jewishcommunities. In consequence, the formal measures we used for identifying the densityof social capital among Jewish and mixed localities may not be adequate for measuringsocial capital in Arab localities. Another factor distinguishing between the Jewish andArab localities is that of socioeconomic ranking. The majority of Arab-Israeli localitiesare found at the lowest ranks of the socioeconomic scale. In comparison, Jewishlocalities are distributed throughout all the socioeconomic clusters. We thereforeconducted two separate analyses, one for localities where most of the population isJewish and one for localities where the entire population are Arab citizens of Israel.Because of the socio-cultural differences cited, we did not expect the researchhypotheses to hold in exclusively Arab localities.
Data sourcesThree databases were employed for the construction of the three main variables:
1 Characterization and Classification of Local Authorities by Socioeconomic Status (SES) ofthe Population (CBS 2000). This database, constructed by Israel’s Central Bureauof Statistics (CBS), contains data on the socio-demographic variables used by theCBS to compute each locality’s socioeconomic ranking: percentage of income-maintenance recipients; percentage of unemployed; percentage of earners abovetwice the average wage; percentage of sub-minimum wage earners; averageyears of schooling; average earnings per capita; percentage of new motorvehicles; rate of motorization; percentage of families with 4þ children;dependency ratio; and median age.
2 Administrative and Financial Performance of Local Authorities (State of Israel, Ministry ofthe Interior 2000–3). Israel’s Ministry of the Interior provides data on annualfinancial and administrative indicators for all local authorities. The indicatorsused to measure administrative performance include budgetary deficit, quality oflocal authority economic forecasts in terms of the gap between predicted andactual income and expenditures in addition to total expenditure per capita. Thedata for the performance variables used in this study were drawn from thisdatabase.
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3 Third Sector Nonprofit Organization Database (http://w3-new.bgu.ac.il/ictr). Thisdatabase was constructed by the Israeli Center of Third Sector OrganizationsResearch, Ben Gurion University (ICTR), which periodically updates it. Thedatabase includes all nonprofit civic organizations in the country. It containsinformation for each locality with respect to the number of nonprofitassociations, classified by type according to their aims and activities (e.g.religious organizations, health and disease-related organizations, philanthropicorganizations, cultural organizations, educational organizations). This databasewas used when estimating the number of bonding and bridging social capitalorganizations per capita in each locality and computing the density of socialcapital per capita, as will be explained below.
VARIABLES AND MEASURES
Dependent variables: Municipal financial and administrative performance
There is no single, widely accepted definition or measure of government performanceavailable in the literature; studies vary widely with respect to the conceptualization ofperformance and the measurement strategies used, which range from subjective toobjective tools (for a review see Tavits 2006). The current study, which focused onfinancial and administrative dimensions of performance, employed quantitativeobjective measures of financial performance. This strategy allowed use of comparabledata for a large number of localities. The measures of municipal performance usedreplicated those applied in previous studies of local performance (Carmeli 2002; Knack2002; Coffe and Geys 2005). To avoid bias from annual fluctuations in the data thatmay reflect temporary conditions in the separate localities, we used an average of theresults for four consecutive years (2000–3) when computing the variables, based on thedata published annually by Israel’s Ministry of the Interior. The following performancevariables were used in the study:
1 The ratio of budgetary surplus (deficit) as a percentage of the locality’s total revenues(2000–3). According to Hendrick (2004: 83) and Coffe and Geys (2005), highersurpluses (or, equivalently, lower deficits) are important indicators of efficientgovernment performance. Expanding deficits counter legislative stipulations andalso increase the municipality’s financial fragility (Carmeli 2002). In this study,we measured the surplus (deficit) as a percentage of the locality’s total revenuesto control for socioeconomic ranking (richer and poorer localities). Ourhypothesis that budgetary surpluses (deficits) may be correlated to social capitalfollowed the Boix and Posner (1998) suggestion that social capital transformscitizens into more sophisticated political consumers who then demandaccountability from their elected leaders. As deficits may no doubt derive from
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a locality’s economic circumstances, we controlled for the economic standing ofthe communities.
2 Accuracy of municipal revenue forecasts, measured as the gap between forecast andactual revenues (2000–3). The literature refers to accurate forecasts ofeconomic and financial activity as an important indicator of a local authority’sperformance (Paths to Performance in State & Local Government 2003: 49–52). Inorder to produce credible forecasts, officeholders and administrators arerequired to adhere to highly professional standards, adopt the rules of goodgovernance and accept accountability.
Institutionalization of effective performance and evaluation criteria isconsidered a core dimension of good governance (Cheol-Sung 2007).
3 Expenditure per capita (2000–3). Following Tavits (2006), we employed a localauthority’s allocation of resources for the distribution of public goods andservices or expenditure per capita, as a measure of local government activismbecause the figure summarizes all local government outputs. As we controlledfor the community’s socioeconomic status, we could interpret this measure as anexpression of policy choices.
Table B in the Appendix provides descriptive data regarding the independent anddependent variables.
Independent variables: Density of bonding and bridging associations percapita
In the current study, the independent variable, social capital, was measured usingaggregate-level data, that is, the number of a community’s not-for-profit associations per1,000 residents. Such a measure was used by Coffe and Geys (2005) in their study ofsocial capital and government in Belgium. The main challenge presented by this variableinvolves the accuracy with which associations are sorted (as bonding or bridging). Anyattempt to identify particular groups or associations with only one type of social capitalwas bound to be imprecise because many groups exhibit attributes of both types.
In order to create a classification based on previous research while taking the Israelicontext into account, we proceeded as follows. We began with the Putnam andFeldstein (2003: 12–15) study, which classified religious associations (churches,synagogues, religious reading groups, etc.) as primarily bonding associations. Paxton(2002: 270–1) similarly assigned religious associations to what she characterizedisolated (bonding in our terms) associations. In contrast, she rated community,environmental, human rights and peace associations as highly connected (bridging in ourterms). Coffe and Geys (2007) also provided a typology of bridging and bondingassociations; however, while their typology resembled that of Paxton for most groups,it treated religious organizations as mainly bridging organizations.
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Based on these classifications, together with our attempt to include the Israelicontext, we adapted the Evans and Rauch (1999) method for our study. Evans andRauch used a panel of experts in each country studied to assess the degree to which thelocal bureaucracy fits the Weberian model. We, in turn, enrolled forty Master’s degreestudents participating in two seminars on social capital to classify the associations as partof their course requirements.
In most cases, the students, like Putnam and Feldstein (2003), treated religiousassociations as bonding associations. In addition, they also considered two othercategories as expressing bonding social relations: relief-seeking organizations comprisedof people with similar needs, problems or disadvantages (in contrast to philanthropicassociations); and health associations, most of which focus on a single health-relatedissue. The classification of bonding associations that emerged resembled thatconstructed by Paxton (2002) and by Putnam and Feldstein (2003).
Bridging associationsBased on the literature and the procedure described above, we included the followingtypes of organizations in the bridging category: civic organizations and organizations forthe protection of citizens’ rights in substantive areas such as consumer protection;organizations promoting political and social change; advocacy organizations; interna-tional organizations; and philanthropic organizations.
The remaining associations exhibit attributes of both bonding and bridging capital andwere therefore termed: hybrid organizations. They included unions, memorialassociations, cultural and recreational associations and educational organizations.
Table A, in the Appendix, shows the results of the measures of social capital for eachsocioeconomic cluster.
Control variables
Socioeconomic ranking of localitiesThis ordinal variable, complied by the Central Bureau of Statistics as describedabove, ranks all localities into ten clusters based on their socioeconomic anddemographic characteristics. The lowest socioeconomic cluster is ranked 1. Includingthis variable in the analysis allowed controlling for numerous socioeconomiccharacteristics of the communities, such as level of education, income anddemographic characteristics.
Population sizePopulation size, measured as the number of residents in the community in 2001, wasentered as a control variable because population size may affect the dependent variables.
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For instance, large localities may differ from small ones in administrative complexity.Hence, they may employ more professional staff, which can be expected to impact ontheir administrative capacities.
Appendix Tables C presents the correlations between the variables analyzed for thelocalities with primarily Jewish populations.
The statistical analysis
The results are based on a series of OLS stepwise regressions conducted to test for mainand interaction effects.
For each dependent variable, three models were examined, as described here. Model1 included the control variables: socioeconomic ranking and population size. In Model2, bonding and bridging variables were introduced while in Model 3, the interactionvariables – type of social capital and the locality’s socioeconomic rank – wereintroduced to examine the differential effects of social capital on localities located indifferent socioeconomic clusters. The study’s main hypotheses are examined in thethird model, which tests for the interaction effect between the types of social capitaland a community’s socioeconomic ranking on the various performance measures.
FINDINGS
Financial performance of local authorities and social capital
We first present the results regarding the organizational dimension of government,expressed here in the accuracy of a local authority’s financial forecasts and by itsmaintenance of a balanced budget, followed by an analysis of policy activism as reflectedin the level of local expenditure on public services delivery.
Social capital and budgetary deficitsTable 1 presents the results of the OLS regression of the effect of bonding and bridgingcapital on budgetary deficits as a percentage of total government revenues in primarilyJewish localities. Model 1 shows a significant main effect of community socioeconomicranking, which is related to smaller deficits. Population size per se was found to have nosignificant effect on deficits. In Model 2, which introduces the social capital variables,bridging associations are negatively associated with local deficits, as predicted by thehypotheses, and so are also hybrid associations.
Model 3, which introduced the interaction between socioeconomic ranking and thesocial capital variables while controlling for socioeconomic ranking and population size,points to bridging social capital as being significantly correlated with reduced local
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budgetary deficits, especially in the lower-ranked communities (indicated by a negativesign). This means that in poorer communities, bridging social capital seems to berelated to smaller deficits. Bonding social capital does not show such relationship asexpected. This model is significant, explaining 35.6 percent of the variance. Theaverage variance inflation factor (VIF) scores for all the independent variables are below3, implying that the results are not distorted by multicollinearity (Bowerman andO’Connell 1990).
Table 1: Results of OLS regressions of effects of bonding and bridging social capital on municipal budgetary
deficits as a percentage of total budget (localities with a mainly Jewish population, N¼ 178)
Model 1 Model 2 Model 3
B VIF B VIF B VIF
Socioeconomic ranking
of community
70.122*
(0.060)
1.018 70.068
(0.061)
1.158 70.052
(0.054)
1.195
Population size (Ln) 0.039
(0.045)
1.018 70.022
(0.047)
1.199 0.011
(0.041)
1.226
Bonding associations
per 1,000 persons (Bo)
0.032
(0.062)
1.192 70.034
(0.071)
2.074
Bridging associations
per 1,000 persons (Br)
70.176***
(0.064)
1.262 0.170*
(0.076)
2.374
Hybrid associations
per 1,000 persons (Hy)
70.144*
(0.071)
1.511 70.116
(0.062)
1.538
Interactions
Bonding * socioeconomic
ranking
0.015
(0.047)
2.128
Bridging * socioeconomic
ranking
70.336***
(0.060)
2.209
Hybrid* socioeconomic
ranking
70.155***
(0.038)
1.293
Constant 7.0506
(0.432)
0.068
(0.448)
70.147
(0.392)
R 0.176 0.357 0.597
R2 0.031 0.127 0.356
Adjusted R2 0.019 0.101 0.325
R2 Change 0.031 0.096 0.229
F F (,)¼ 2.696,
P¼ 0.070
F(,0)¼ 4.847,
P¼ 0.000
F(,)¼ 11.270,
P¼ 0.000
F Change F (,)¼ 2.696,
P¼ 0.070
F(,0)¼ 6.118,
P¼ 0.001
F(,)¼ 19.302,
P¼ 0.000
*p5 0.05; **p5 0.01; ***p5 0.001.
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Social capital and revenue forecastsTable 2 presents the results of the analysis of the effects of social capital on theaccuracy of a locality’s revenue forecasts in comparison to its actual revenues.Model 1, which includes the two control variables (i.e. socioeconomic ranking andpopulation size), shows that only socioeconomic ranking is significantly correlatedwith forecast accuracy, whereas population size is not. Not surprisingly, thenegative sign attached to the figures indicates that revenues in richer communitiesare less likely to deviate from forecasts. Model 2, which introduces the types ofassociational social capital, shows, again as expected, that forecast accuracy issignificantly related to bridging social capital but not to bonding social capital.Model 3 introduces the interaction variables: the community’s socioeconomic rankand each type of social capital. As predicted, bridging social capital is shown to bemore strongly correlated with reduced divergence from forecasted revenues inpoorer localities, indicated by the significant and negative coefficient (B¼70.034).Bonding social capital does not show a similar effect. Hybrid associations are alsocorrelated with reduced divergence from financial forecasts, although to a smallerdegree than are bridging associations. This model is also significant, explaining 29.9percent of the variance.
The findings thus support the hypothesis that bridging social capital is positivelyrelated to the improvement of a local authority’s performance as demonstrated in theaccuracy of its financial forecasts. Bonding social capital is not.
Performance as measured by government activism: Expenditure per capita andsocial capitalThis measure examines the relationship between density of social capital and localexpenditure per capita, viewed as a proxy for the volume of public services providedor, alternatively, as government activism (see Table 3). First, regarding Model 1, itshould be noted that the findings indicate that socioeconomic rank per se does notexplain expenditure per capita, a nontrivial finding. Population size, however, doeshave a significant negative effect. Furthermore, while introduction of the social capitalvariables in Model 2 does not yield significant results, introduction of the interactionvariables in Model 3 does.
As the results from Model 3 show, the main effect of bridging social capital on publicexpenditure is significant, as is the interaction between socioeconomic ranking andbridging social capital, which has a significant effect (B¼71.465, p5 .05) onexpenditure per capita. The negative sign of the interaction effect indicates that it is inthe expected direction because expenditures per capital are higher in poorercommunities having more bridging social capital. As to the main effects, the densityof bridging social capital has a significant effect and in the expected direction(B¼ 1.960, p5 .05). The interaction effect included in this model explains astatistically significant 19.9 percent of the variance and lends support to Hypothesis 2c,
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which posited that bridging social capital is more strongly correlated with activistgovernments in poorer than in wealthier localities.
The results obtained for the localities with Arab populations differ, as anticipated.None of the models were found to be significant. (Results not presented can be obtainedfrom authors upon request.) As previously explained, these results may reflect thedifferent social structure of the Arab sector, where membership in formal organizationsis rare, and bonding social capital is represented primarily by the extended family.
Table 2: Results of OLS regressions of effects of bonding and bridging social capital on divergence between
revenue forecasts and actual revenues (localities with a mainly Jewish population, N¼ 178)
Model 1 Model 2 Model 3
B VIF B VIF B VIF
Socioeconomic ranking
of community
7.018*
(0.007)
1.018 70.010
(0.007)
1.158 70.008
(0.007)
1.195
Population size (Ln) 0.009
(0.006)
1.018 0.008
(0.006)
1.199 0.011*
(0.005)
1.226
Bonding associations
per 1,000 persons (Bo)
0.004
(0.008)
1.192 70.006
(0.009)
2.074
Bridging associations
per 1,000 persons (Br)
70.037***
(0.008)
1.262 70.002
(0.010)
2.374
Hybrid associations
per 1,000 persons (Hy)
0.010
(0.009)
1.511 0.012
(0.008)
1.538
Interactions
Bonding * socioeconomic
ranking
70.003
(0.006)
2.128
Bridging * socioeconomic
ranking
70.034***
(0.008)
2.209
Hybrid* socioeconomic
ranking
70.012*
(0.005)
1.293
Constant 0.904***
(0.053)
0.918***
(0.055)
0.893***
(0.051)
R 0.234 0.412 0.547
R2 0.055 0.170 0.299
Adjusted R2 0.044 0.145 0.265
R2 Change 0.055 0.115 0.130
F F(,)¼ 4.905,
P¼ 0.008
F(,0)¼ 6.791,
P¼ 0.000
F(,)¼ 8.706,
P¼ 0.000
F Change F(,)¼ 4.905,
P¼ 0.008
F(,0)¼ 7.661,
P¼ 0.000
F(,)¼ 10.046,
P¼ 0.000
*p5 0.05; **p5 0.01; ***p5 0.001.
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DISCUSSION AND CONCLUSIONS
This study set out to examine issues resulting from the lack of differentiation betweenbridging and bonding social capital and the different relationships observed betweensocial capital and government performance in communities exhibiting differentsocioeconomic characteristics (SES rankings). The study assumed variation in thedemands and inputs that bonding versus bridging associations introduce into the public
Table 3: Results of OLS regressions of effects of bonding and bridging social capital on total expenditure in
NIS per capita (localities with a mainly Jewish population, N¼ 178)
Model 1 Model 2 Model 3
B VIF B VIF B VIF
Socioeconomic ranking
of community
7.0651
(0.612)
1.018 71.154
(0.647)
1.158 7.1.176
(0.652)
1.195
Population size (Ln) 72.447***
(0.462)
1.018 72.176***
(0.467)
1.199 72.057***
(0.499)
1.226
Bonding associations
per 1,000 persons (Bo)
71.242
(0.654)
1.192 71.239
(0.856)
2.074
Bridging associations
per 1,000 persons (Br)
0.580
(0.628)
1.262 1.960*
(0.915)
2.374
Hybrid associations
per 1,000 persons (Hy)
0.998
(0.754)
1.511 1.153
(0.755)
1.538
Interactions
Bonding * socioeconomic
ranking
0.231
(0.564)
2.128
Bridging * socioeconomic
ranking
71.465*
(0.726)
2.209
Hybrid* socioeconomic
ranking
70.323
(0.464)
1.293
Constant 34.303***
(4.403)
31.762***
(4.728)
31.076***
(4.742)
R 0.378 0.415 0.446
R2 0.143 0.173 0.199
Adjusted R2 0.133 0.148 0.160
R2 Change 0.143 0.030 0.026
F F(,)¼ 14.067,
P¼ 0.000
F(,0)¼ 6.922,
P¼ 0.000
F(,)¼ 5.058,
P¼ 0.000
F Change F(,)¼ 14.067,
P¼ 0.000
F(,0)¼ 1.993,
P¼ 0.117
F(,)¼ 1.787,
P¼ 0.152
*p5 0.05; **p5 0.01; ***p5 0.001.
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sphere and examined their consequent effect on government performance. These issueshave received little attention in the literature so far.
In general, the findings confirm the main hypotheses. They reinforce the need todifferentiate between bonding and bridging social capital. First, the findingsdemonstrate that bridging and bonding social capital do differ in their respectiveeffects on performance. Second, they show that the relationship between bonding asopposed to bridging networks and government performance varies by the community’ssocioeconomic ranking. Bridging social capital is related to government performance inpoor communities as measured by size of budgetary deficits, the accuracy of financialforecasting and higher spending per capita, while no such relationship was found in thewealthier communities. Bonding social capital, it was found, has no such significanteffect on these performance measures in both types of communities.
This study therefore offers some additional insight into social capital as a factorimpacting on local government performance. The differences found in the relationshipof bonding versus bridging social capital with the performance of public bureaucraciesmay help explain why previous studies failed to show a significant relationship betweenthe associational component of social capital and government performance.Notwithstanding previous explanations alluding to the impact of other factors – forinstance, the negative effect of group rent-seeking (Knack and Keefer 1997) – this studyshows that the combination of both types of social capital – bonding and bridging –under one rubric can obscure the precise relationship holding between the separatetypes of association and government performance.
Our findings regarding the relationship between social capital and policy activismresemble those obtained by Tavits (2006) yet extend them by showing that bridgingrather than bonding social capital is responsible for the stated relationship; we also showthat this effect is more pronounced in poorer communities. Policy activism in poorcommunities requires significantly more cooperation and compromise as public servicesrepresent a more critical share of total services provided locally given the limitedrecourse to private sources of supply. In the absence of options, bridging social capitalbecomes more crucial as a resource in supporting local government attempts to cater todiverse group demands.
Our findings also extend the explanatory models described by Boix and Posner(1998): the rational voter model, the rule compliance model, the civic virtues model,the elite accommodation model and the principal–agent problem attenuation model.Based on the findings of this study we claim that the qualities attributed by Boix andPosner as contributing to government performance are unique to bridging social capital.
We can now present an integrated argument relating the two types of social capitalwith government performance, incorporating the three dimensions relevant forunderstanding the operation of social capital.
With respect to civil society and community, localities with more abundant bridgingsocial capital will exhibit improved ability to deal with collective issues due to strongercompliance with rule and weaker tendencies to transform non-excludable into
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excludable goods. In such a context, government, as an organizational system may enjoygreater access to and make better use of more heterogeneous sources of information andsupport that may enhance performance. Bridging as opposed to bonding social capitalis more salient along this dimension particularly in poor communities, which are less ableto pay for external expertise and are forced to rely on internal capabilities. Finally, incontexts with more abundant bridging social capital, leaders from both the publicand private sectors will find it easier to compromise without losing legitimacy, a featurelikely to positively impact on the choice of collectively oriented policy options.
Our study has thus shown that social capital is related to government performance inmore than one way. Identification of the distinctive types of social capital as one sourceof variation in government performance can therefore deepen our understanding of whyleaders in some localities, rather than others, are more successful managers, providebetter services and behave in a more accountable manner.
Limitations of the study, further research and policy implications
At the same time it should be noted that these findings are limited only to the Jewishpopulation; they do not reflect events in the traditional Arab communities, whereparticipation in formal associations is limited by cultural norms. This limitation mayrestrict the generalizability of the findings but does point to the need to examine theapplicability of the hypotheses for a range of populations and contexts. Anotherlimitation of the study stems from its use of only one component of social capital –associational capital. Further research is needed to establish whether similar results holdfor the trust component of social capital. Research adopting an agency approach may helpexplain how awareness by leaders of the presence of the two types of social capital affectspolitical as well as bureaucratic decision making and the subsequent policy outputs.
The current findings also have policy implications. The positive contribution ofbridging social capital to administrative performance, especially in poorer communities,suggests that local government as well as community activists would be advised toactively promote the formation of bridging social capital in the form of more inclusiveassociations and broad networks. Further research should investigate just how to do so.
ACKNOWLEDGEMENT
The authors thank Yasmin Alkalay for her assistance in the statistical analysis of the data.
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Appendix
Table B: Means and standard deviations of variables (localities with a mainly Jewish population, N¼ 178)
Variable N Mean Std deviation
Deficit as percentage of total budget 172 7.145 .790
Total local expenditures per capita 172 11.225 8.570
Difference between forecasted and actual revenues 172 .990 .099
Socioeconomic ranking of community 178 5.98 1.901
Population size (Ln) 172 9.426 1.332
Average no. of bonding associations per capita 177 0.836 0.816
Average no. of bridging associations per capita 177 0.321 0.466
Average no. of hybrid associations per capita 177 1.086 0.817
Interactions
Bonding * socioeconomic ranking 172 7.255 1.553
Bridging * socioeconomic ranking 172 .239 1.230
Hybrid* Socioeconomic ranking 172 .099 1.472
Table A: Bonding and bridging social capital per person: Means by socioeconomic cluster
Percentage of
Municipalities
in Cluster
Bonding Associations
per Person
Bridging Associations
per Person
Unclassified
Associations
per Person
Socio-
economic
Cluster
Mostly
Jewish
Population
Arab
Population
Mostly
Jewish
Population
Arab
Population
Mostly
Jewish
Population
Arab
Population
Mostly
Jewish
Population
Arab
Population
1 0.6 13.1 2.51 0.15 0.05 0.02 0.93 0.27
2 3.9 36.9 2.21 0.20 0.23 0.05 1.7 0.36
3 6.1 26.2 1.29 0.41 0.24 0.07 1.29 0.50
4 12.8 17.9 1.19 0.38 0.22 0.11 0.94 0.70
5 20.6 4.5 0.68 0.37 0.28 0.14 0.90 0.76
6 15.0 1.2 0.61 0.37 0.230 0.36 0.91 1.01
7 16.7 0.70 0.27 0.95
8 16.1 0.70 0.46 1.30
9 6.1 0.64 0.63 1.04
10 2.2 1.25 0.85 2.72
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Tabl
eC
:P
ears
onco
rrel
atio
ns(l
ocal
ities
with
am
ainl
yJe
wis
hpo
pula
tion,
N¼
178)
Soc
io-e
cono
mic
rank
ing
of
com
mun
ity
Pop
ulat
ion
size
Bon
ding
asso
ciat
ions
per
capi
ta
Bri
dgin
g
asso
ciat
ions
per
capi
ta
Hyb
rid
asso
ciat
ions
per
capi
ta
Bon
ding
*
soci
oeco
nom
ic
rank
ing
Bri
dgin
g*
soci
oeco
nom
ic
rank
ing
Hyb
rid*
soci
oeco
nom
ic
rank
ing
Defi
cit
aspe
rcen
tage
ofto
tal
budg
et7
.164
*.0
86.0
087
.312
***
7.2
54**
*7
.018
7.5
06**
*7
.386
***
Diff
eren
cebe
twee
nfo
reca
st
and
actu
alre
venu
e
7.2
00**
.147
*.0
747
.377
***
7.0
967
.100
7.4
81**
*7
.327
***
Tota
lex
pend
iture
s(2
000–
3)pe
rca
pita
7.0
267
.370
***
7.0
58.1
44*
.222
**.0
157
.015
7.0
36
Soc
ioec
onom
icra
nkin
gof
com
mun
ity7
.133
*7
.252
***
.236
**.1
01.2
37**
.146
*.2
55**
*
Pop
ulat
ion
size
(Ln)
7.0
587
.191
**7
.395
***
.117
7.0
667
.009
Bon
ding
asso
ciat
ions
per
capi
ta(B
o).0
30.2
81**
*7
.700
***
7.0
197
.281
***
Bri
dgin
gas
soci
atio
nspe
rca
pita
(Br)
.410
***
7.0
13.7
21**
*.2
51**
*
Hyb
rid
asso
ciat
ions
per
capi
ta(H
y)7
.274
**.3
10**
*.0
11
Inte
ract
ions
Bon
ding
*so
cioe
cono
mic
rank
ing
.004
.343
***
Bri
dgin
g*
soci
oeco
nom
icra
nkin
g.2
99**
*
Not
e.*p
50.
05;
**p5
0.01
;**
*p5
0.00
1.
Menahem et al.: Social capital and local performance 681
Dow
nloa
ded
by [
Um
eå U
nive
rsity
Lib
rary
] at
20:
18 1
8 N
ovem
ber
2014
