Nonprofit and Voluntary Sector Quarterly

This article describes how the largest labor market survey in the United Kingdom has been used to compare employment in the third sector with other sectors. This is based on employees’owninternal definition of their employers’sector, an approach that it is argued can usefully supplement the dominant external approach. The dimensions along which the (self-defined) third sector emerges as distinctive include its rather small absolute size, its relatively high concentration of part-time and temporary staff, the greater proportion of its workers who work unpaid overtime, the relatively high proportion of employees who are women, the tendency for its respondents to have high levels of educational qualifications, and its distinctive composition. At least some of these features seem to be shared with the third sector in other developed countries, although it is very difficult to be confident in these comparisons for the reasons discussed in the article.

The IRS 990 Return is becoming an increasingly prominent source of financial data underlying descriptions of the nonprofit sector and studies of nonprofit organizations. However, questions about the quality of the data continue to be of concern. This study of 350 nonprofit organizations investigates the adequacy, reliability, and appropriate interpretation of IRS 990 Return data through comparisons of selected entries with corresponding measures from each organization’s audited financial statements. Both quantitative and qualitative methods are used to examine and explain the consistency between the two data sources. The study concludes that the IRS 990 Return can be considered an adequate and reliable source of financial information for many types of investigations, but preparers and users of the data need a clearer understanding of its purposes to enable appropriate interpretations.

The authors identify differences in performance among for-profit, nonprofit, and government-owned nursing homes in Minnesota. They investigate whether homes of diverse ownership types distribute their surpluses differently, if those differences narrow over time, and if the various ownership types react differently to changes in the regulatory environment. Government-owned and nonprofit homes spend more per resident day for nursing care costs than do independent for-profit homes. Chain affiliation is important in explaining persistent spending differences. There is an agency problem: Nursing homes belonging to chains behave differently from their independent counterparts. Secular non-profits belonging to national chains spend less of their surplus on nursing care costs after regulations allowed more of this form of spending to be recouped in rates charged to the residents. The secular firms affiliated with national chains spend less on nursing care than the control group. As the predicted surpluses of for-profit chains increase, the owners’ compensation falls.

Agency theory has long been studied in the corporate setting and used to explain performance in management and in boards of directors. However, little has been done to extend this research into the area of not-for-profits. Using data collected from member institutions of the Council of Independent Colleges, relationships between boards of trustees and presidential demography and institutional performance were examined. Data were analyzed using panel regression with a separate panel for each year’s data and for each of the responding schools. Using revenue and gift income as dependent variables, it was found that increases in the size, average tenure, and level of business executive background on a board led to subsequent increases in performance for the institution. Diversity of the board had mixed results, whereas presidential tenure improved performance. These findings partially support the hypotheses and extend the explanatory reach of agency theory into the not-for-profit sector.

Data from the National Center for Charitable Statistics (NCCS) and other secondary sources was used to examine the nonprofit sectors of nine metropolitan regions. The results indicate that nonprofit sectors vary widely in terms of the numbers of organizations in them and the proportions of different types of providers. Moreover, the findings showed complex and intriguing relationships between nonprofit sectors and political culture, generosity, wealth, poverty, and heterogeneity. Traditionalistic sites had sectors with the opposite characteristics. The sectors in individualistic sites lay between these two patterns. Wealthier sites had larger, better-supported and secure sectors. Sites with higher poverty had less well supported sectors with smaller human service components. The most and least heterogeneous sites had the largest and smallest nonprofit sectors respectively. These findings bolster confidence in the use of NCCS data.