Quality, trustworthiness and authenticity

Estimation of the multinomial logit model implies that we can have different base categories, for example we may want to compare accessibility to credit from Traders‘

Association versus Cooperative or ROSCAS, etc. The calculation of odds ratio of all the other responsive categories was done relative to the base line that is the coefficient of probabilities. An odds ratio equal to 1 suggests that the explanatory variable leaves the dependent variable unchanged. If the odds ratio is greater (less) than 1, it implies that the effect of explanatory variable is to increase (reduce) the dependent variable (Long, 1997) for example, an odds ratio of 2 implies that the effect of the explanatory variable is to double the dependent variable. The advantage with this is that the factor change in odds for a unit change in each explanatory variable is not dependent on the level of the variable or the level of any other variable (Long, 1997). The positive coefficient implies the probability of respondent falling in the numerator category or odds are greater than the probability of falling in base category.

The review shows the importance of social capital in the different facets of human endeavour. However, empirical investigations of the various dimensions of social capital and effects on profitability has not been given due consideration in Nigeria. This study intends to fill this inherent vacuum by carrying out an empirical analysis of the effects of social capital on profitability of grain traders using south west state of Nigeria.

insurance is largely unavailable and institutions for contract enforcement are weak.

Consistent with this idea, Guiso et al (2004) found that in Italy, the level of social capital has higher investments in the stock market and more access to formal financial institutions. Similarly, Hong kubik and Stein (2004) found that in the United States

―people who knew their neighbor‖ have higher stock market participating rates.

Bastaeler (2000) observed that social capital is the solution of information uncertainties in finance market for the poor. He informs that many credit programmes for the poor based on individual collateral saw low repayment as the incentives structure was weak and the delivery process was mired in bureaucratization and politicization. However, microcredit based instead on social collateral where social capital becomes instrumental for microcredit. Generally, bonding and bridging social capital through horizontal social networks are most visible in microcredit. He identifies two main elements: joint liability for loans of small self-selected and homogenous borrowers‘ groups and ―contingent renewal principle‖ or denial of access to future credit to all group members in the case of default by any group members.

Bastaeler (2000) opined that credit arrangements rely on several classes of social capital identified as horizontal, vertical and ethnic based relationship. Grameen Bank relies on the horizontal network of borrowers. The money lenders which are often another source of credit to the poor in developing countries especially in rural areas rely on hierarchical social interaction, a reminiscent of the vertical dimensions of Coleman‘s (1988) definition of social capital. Bastelaer (2000); Grootaert and Van Bastelaer (2002);

Grootaert (1999 and 2001) presented evidence that social networks are important elements of most types of formal; or informal programmes that provide credit access to the poor through the implementation of relationship between programme officers and borrowers (on trust) and vertical social ties between programme, traditional patrons and clients (loan officers). Grootaert (2001) reported that membership and active participation in other local associations whose prime objective is not financial also contribute to credit access. This is perhaps the sense in which social capital is truly ―social‖ in that the building of trust and network among members in the context of a social setting spills over into financial benefits. This interpretation of social capital has being proposed by several authors such as Putman (1993); Dasgupta (1988); and Fukuyama (1995).

Seibel (2000) studied the relationship between social capital and microfinance in the Philippines. He evaluated the effectiveness of using Grameen type norms such as regular attendance in the meeting, insistence on timely repayment, etc among Grameen

replications in the Philippines. The author concluded that successful replicators use ―hard core social capital of the original Grameen approach‖ – high moral commitment of leaders based on values enforced true training, peer selections and peer enforcement, and credit discipline. However he suggested that to be successful, microfinance institutions (MFIS) in the countries outside of Bangladesh need to cultivate additional and localized dimensions of social capital. Using data collected from FINCA, Peru Karlan (2001) found that social capital helps members distinguish between willful defaults and defaults due to the true negative personal shocks and that social capital generates higher repayment and higher savings. In the case of Indonesia, Grootaert (1999) concluded that household with higher social capital are better able to obtain credit than non-members and the obtained credit amounts were much larger. All local associations whatever its prime objectives are important to increase access to credit. As argued by Bastelear (2000), the social networks are important elements of most type of formal or informal programs that provide credit access to the poor.

Ajani and Tijani (2009) examined the role of social capital in access to microcredit in Ekiti State and found that aggregate social capital index positively affects the probability of members of networks obtaining microcredit. The study supports findings that in addition to information and other benefits derived from networks, it can be a source of obtaining credit; belonging to networks or associations, the study posits, will improve the probability of access to credit for members, which can be channeled towards improving their livelihood activities. In the same vein, Lawal et al (2009) studied the effects of social capital on credit access among cocoa farming households in Osun State and revealed that a unit increase in social capital would increase credit access of cocoa farming households by 0.36%.

Heikkila et al (2009) in their study on social capital and credit access in Uganda found that individual-level social capital is positively associated with access to loans and as regards organizational choice, they found that social capital is an important borrower screening device for more informal financial institutions. Furthermore, their results suggest individual social capital is positively associated with access to institutional loans, and it matters more for poorer and less educated people; and also that importance of individual social capital appears to increase when the formality of the institution decreases.

Microfinance has allowed credit to the poor beyond the traditional financial frontiers in so far as lack of collateralizable assets has been overcome by group lending in

tight-knit communities. Social cohesion giving rise to norms and sanctions to deter default has provided a form of social collateral in group lending situations (Kugler et al 2004). In recent years, considerable effort has been made to understand both how group lending works and the effect it may have in practice. Most studies have focused on how peer group schemes can overcome the inherent problems associated with asymmetric information in financial markets. Specifically, in a world where borrowers lack collateral, group lending has been shown to mitigate problems associated with adverse selection, moral hazard, contract enforcement, and state verification (Morduch 1999; Ghatak and Guinnane 1999).

Group lending with joint liability overcomes these problems by passing the monitoring activity on to the borrowers themselves. The idea is that group members will monitor their peers and pressurize those individuals who misuse their loans to act accordingly. While this monitoring activity is costly for the borrower, it is assumed to be much less so than for the lender, since group members will typically know each other well in advance of the date of borrowing. Assuming that monitoring costs are low and social sanctions effective, Ghatak and Guinnane (1999) show that, compared with an individual liability contract, effort will be strictly higher under joint liability. The implications of these findings also agree with the results reported in the personnel economics literature, which show that team-based production can have both sorting and incentive effects and that peer pressure within a team can have a discernible impact on worker effort and individual output (Lazear 1999 as cited by Rafael Gomez and Eric Santor (2003).

Despite the strong predictions of group lending models, there is little or no direct empirical evidence to suggest that peer group members actually outperform individual borrowers. For instance, Ahlin and Townsend (2003) test a wide range of the predictions of group lending with joint liability, such as the impact of interest rates, loan size, the degree of joint liability, group homogeneity, and the level of group monitoring and social sanctions. Although much of their evidence confirms the predictions of theory, they find evidence that proxies for strong social ties, group monitoring, and group co-operation are negatively related to repayment. On the other hand Karlan (2003) shows that higher levels of social capital are positively correlated with repayment, particularly when facilitated by the appropriate environment. Wydick (1999) suggests that groups matter, in that greater levels of social cohesion (such as knowing group members prior to group formation or living in the same neighbourhood) lead to lower levels of individual default. Wenner (1995) offers similar evidence that socially cohesive groups have higher repayment rates.

Feigenberg et al (2010) provided experimental evidence on the economic returns to social

interaction in the context of microfinance. Random variations in the frequency of mandatory meetings across first-time borrower groups were used to generate exogenous and persistent changes in clients' social ties. The results indicated that group lending is successful in achieving low rates of default without collateral not only because it harnesses existing social capital, as has been emphasized in the literature, but also because it builds new social capital among participants.