Marcelo E. Siles

Social capital and household income distributions in the United States: 1980, 1990

Abstract This paper asked if changes in social capital influence the level and disparity of household income in the United States. Social capital is defined in this paper as ones sympathy (antipathy) for others and ones idealized self. Changes in social capital are expected to produce the following economic consequences. First, increases in social capital are expected to alter the terms of trade and to increase the likelihood of trades between friends and family. Second, increases in social capital are expected to increase an economic agents concerns for the external consequences of his or her choices, internalizing what otherwise would be considered externalities. Third, increases in social capital between firms are expected to increase the likelihood that they will act in their collective interest. Fourth, increases in social capital are expected to increase the opportunities for specialization and the likelihood of trade. Finally, increases in social capital are expected to raise the average level of income and reduce the disparity of income. This paper empirically tested the relationship between changes in social capital indicator variables and changes in the average and coefficient of variation (CVs) of household income. State CVs and averages of household income were calculated for all 50 states and for different races/ethnic groups using the U.S. Census data for 1980 and 1990. Social capital indicator variables selected to measure changes in social capital included measures of family integrity including the percentages of households headed by a single female with children; educational achievement variables including high school graduation rates; crime rate variables including litigation rates; and labor force participation rates. The social capital indicator variables appeared to be significantly correlated with each other. However, in 1980, the percentages of households headed by a single female with children was not significantly related to the birth rates of single teens. By 1990, however, a strong correlation was found between the percentages of households headed by a single female with children and the birth rate of single teens. Income inequality among U.S. households measured using CVs increased between 1980 and 1990 in all 50 states. The largest increase in CVs was among white households. The smallest increase in CVs was among Asian households. The states with the largest increase in the ratio of 1990 and 1980 CVs were Arizona, Wyoming, Maine, Vermont, and Texas. Half of the states reported decreases in real household income between 1980 and 1990. Those states with the largest percentage decrease in real income were Wyoming, Alaska, Montana, Louisiana, and West Virginia. The largest percentage increase in real income was reported by Connecticut, New Jersey, Rhode Island, and Massachusetts. State CVs and averages of household income were regressed on four factors or subsets of social capital indicator variables. The four factors used to predict CVs and averages of household income were generally statistically significant. The findings of this report support the conclusion that changes in social capital have a significant effect on the disparity and level of household income.

Social Capital and the Terms of Trade for Farmland

Social capital is a person or groups sympathy for or sense of obligation to another person or group. This article introduces social capital into a neoclassical model of farmland exchange and shows how relationships alter the terms of trade. Empirical evidence from a survey of farmers shows that the type of relationship farmland sellers have with farmland buyers has a statistically significant and economically important effect on the minimum-sell price for farmland. Compared to the minimum-sell price when selling to a total stranger in an arms-length transaction, farmland sellers discount prices to friendly neighbors and relatives and require a premium from unfriendly neighbors and influential people in the community.

Socio-Economics and the Probability of Loan Approval

This study analyzes the influence of relationships on the probability of loan approval. Michigan banks located in communities with a population of less than 10,000 supplied the data for this study by responding to hypothetical loan requests. The survey results demonstrate that in addition to the usual financial performance variables, business and social relationships between lenders and prospective borrowers significantly affect the likelihood of loan approval. The effects of relationships on the loan approval decision are largest when information on the financial strength of the prospective borrower is mixed. In cases where the financial strength of the loan applicant is unambiguously strong (weak), the loan is likely to be approved (rejected) regardless of the applicants relationship with the lender.

Impacts of relationships on customer retention in the banking industry

A survey of rural Michigan banks found that building good customer relationships is an important goal. The financial success of efforts to build relationships depends on the customer loyalty associated with friendly relationships. Customer loyalty was investigated in a survey of financial institution customers located in rural areas. Compared to unfriendly relationships, friendly relationships increased the interest rate differential on deposited funds required for a customer to switch institutions by 74 basic points.