For Peer Review Only
Network based social capital and individual loan repayment
performance
Journal:
Journal of Development Studies
Manuscript ID:
FJDS-2009-Dec-0033.R2
Manuscript Type:
Original Manuscripts
Keywords:
Asia < Geographical Area, Agricultural development < Economics,
Rural < Human Geography, Social Capital < Social Issues
URL: http://mc.manuscriptcentral.com/fjds
Journal of Development Studies
For Peer Review Only
1
Network based social capital and individual loan repayment
performance
This study analyses the effects of social capital on the repayment behaviour of borrowers in Thailand.
In the context of agricultural economics, an innovative data collection approach is used that originates
from the field of sociology. A personal network survey is carried out to measure the individual social
capital of borrowers. Social capital variables are defined according to: tie strength (bonding/bridging)
and social distance (linking) between the respondent and his/her network member. Bonding social
capital has a significant and positive influence on repayment performance. However, we find no
significant evidence for an effect of bridging and linking social capital.
I Introduction
Social capital can facilitate access to credit, but also affect repayment behaviour of
borrowers (van Bastelaer, 2003).
i
Many studies link repayment performance to social
capital (for example Cassar et al., 2007), or to social ties (for example Ahlin and
Townsend, 2007). However, these authors use credit groups as the unit of analysis.
Little research exists on repayment performance of individual borrowers and social
capital or social ties.
ii
Studies focus predominantly on social ties crossing power
differentials where powerful individuals exploit the credit program. In addition, they
are often anecdotal (Vaessen, 2001). Research in agricultural economics has only
recently begun to pay heed to social relations or ties. Often, measurement of these ties
has been rather crude, focussing on role relationships like friends, relatives, or
neighbours. Our approach to measuring social ties is more elaborate. We use a survey
tool from the field of sociology that has so far rarely been used in the field of
agricultural economics.
iii
This technique involves the use of instruments referred to as
‘name generator’ and ‘position generator’ to measure the personal network of the
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respondent’s personal network. These network data are then used to create measures
of the individual social capital of borrowers.
The empirical part of this work focuses on the rural credit market in Thailand and on
the repayment behaviour of individual borrowers in particular. A number of papers
have been published on the rural credit market in Thailand, including Coleman (2006)
or Siamwalla et al. (1990). Ahlin and Townsend (2007) have applied the concept of
social capital to the rural credit market in Thailand, but using a different definition
and a different unit of analysis, namely joint liability credit groups. No research so far
has applied the concept of social capital specifically to individual loans in Thailand.
To better understand the relevance of social capital to the functioning of rural credit
intermediation, the Thai rural financial market is briefly outlined here. The
government provides various credit lines to support rural households. Most of these
credit lines are administered by the Bank for Agriculture and Agricultural
Cooperatives (BAAC). Furthermore, the government manages different lending
schemes such as the One Million Baht Village Fund and the Poverty Eradication
Fund. About 80 per cent of all villages in Thailand have access to the One Million
Baht Village Fund (NSO, 2003). Almost all players in the rural credit market provide,
or have in the past provided, group loans. However, such group loans are negligible in
number. For instance, they constitute less than 10 per cent of current BAAC loans in
northern Thailand (BAAC, 2008). Formal and semiformal lenders have enormous
outreach. Survey results reveal that more than 50 per cent of households have an
effective credit demand. This enormous outreach has a trade-off: (1) many of the
borrowers are not creditworthy if conventional measures of creditworthiness are
applied; (2) rescheduling of loans is not uncommon, ultimately adding to the total
amount of nonperforming loans.
iv
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This study focuses on the loan performance of individual rural borrowers of formal or
semiformal lenders, taking into account their social capital and its influence on loan
performance.
v
In general, the smaller an individual’s network is, the lower the level of
social capital s/he has. But this view is too simplistic. Social capital is not a
homogeneous entity (Woolcock and Narayan, 2000). We base our measurements of
social capital on three different forms: bonding, bridging, and linking.
vi
Furthermore,
we investigate the relationship between the number of people an individual knows
who have poor repayment performance and the individual’s own repayment
performance.
The paper is organised as follows. Section II gives a brief review of the theory of
social capital and sets out how various forms of social capital and social ties may
influence repayment performance. Section III describes the sample, the measurement
of different forms of social capital, the data collection, and reference group creation.
Section IV then introduces the econometric model and discusses the results. The
paper concludes with a brief summary and policy recommendations.
II Different forms of social capital and loan performance
The standard criticism levelled at the social capital concept is that it is usually defined
too broadly and is thus analytically useless. We therefore emulate scholars such as Lin
(1999a), defining social capital more narrowly and leanly as interpersonal networks
(ties) plus resources. It is the resource that turns the social structure into social
capital. As mentioned before, three different forms of social capital are applied.
Bonding and bridging social capital are distinguished by tie strength, while linking
social capital is distinguished by social distance between the respondent and the
personal network member. Bonding social capital relates to ‘strong ties’, bridging
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social capital to ‘weak ties’ (Woolcock and Narayan, 2000). Weak ties are
characteristic of the infrequent interactions and peripheral relationships among more
or less dissimilar individuals and strong ties of the intimate social circle of individuals
with rather similar characteristics, for example relatives (Lin, 1982). Linking social
capital refers to a person’s ties to people in positions of authority, such as
representatives of public (for example police) and private (for example banks)
institutions. It can be connected either to bridging social capital, when the link is
connected by way of a weak tie, or to bonding social capital, when the link is
connected via a strong tie. Consequently, we have four different measures of social
capital: 1. bonding, 2. bridging, 3. bonding
link
, and 4. bridging
link
.
Indirect effects: Social capital can affect repayment positively via income. Sanders
and Nee (1996) outline three mechanisms of social capital that positively affect
economic success. In general social capital can offer 1. instrumental support (for
example free labour or informal loans), 2. productive information, and 3.
psychological aid. Bonding capital provides an individual with information that helps
preserve his/her interest even when the individual has not actively searched for this
information (Lai and Wong, 2002). Wellman and Wortley (1990) state, moreover, that
people obtain most of their social support and psychological aid through a small
number of strong ties. It may also help households to surmount difficult times and in
this way it may reduce the probability of malperforming loans. However, it is
assumed that information or resources accessed through strong ties are redundant; in
other words, everybody in the core network of strong ties often has similar resources
available. Thus, the strength of bridging social capital lies in facilitating access to
additional resources that are outside the core network (Lin, 1982). Hence, households
with a large amount of bridging social capital may do better as entrepreneurs, and
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