*Names in bold indicate Presenter
The significance of the paper is that it extends previous models to identify observable organization factors that can be used to understand the democratic anchorage contributed by nonprofits in community reinvestment arrangements. Torfing, Sorensen and Fotel (2009) observed that there remains a need for additional empirical evidence of the structural and contingency factors influencing democratic anchorage in governance arrangements. The findings suggest that factors such as the professionalized nature of the nonprofit, political purpose, and location in an area of high need, drive CRA mobilization and provide insight on the democratic anchorage contributed.
The governance arrangements of interest in this paper are negotiated community reinvestment agreements between nonprofit organizations and lenders from 2000-2009. The Community Reinvestment Act (CRA) of 1977 is a federal Act designed to encourage lenders to meet the reinvestment needs of their community. The design of the CRA legislation provides flexibility to lenders and nonprofit organizations to develop self-governing arrangements to meet local community reinvestment needs. Although the public sector still plays a pivotal role in regulating lenders under CRA, the case of agreements provides an opportunity to consider the empirical factors that predict the mobilization of nonprofits, a more ambiguous sector in its source of accountability, to enter into self-governing arrangements with lenders to pursue CRA objectives.
Logistic regression tests the relationships between political purpose, professionalization, political advocacy and location in areas of need and the presence of a negotiated agreement. Data on the nonprofits engaged in community reinvestment agreements were obtained through a Freedom of Information Act (FOIA), yielding a list of over 300 nonprofit organizations with negotiated agreements during 2000-2009 in the largest 100 metropolitan areas in the United States. Data on the characteristics of these nonprofits were obtained from the National Center for Charitable Statistics (NCCS). NCCS data was also used to obtain a random sample of nonprofit organizations without agreements for analysis purposes. Metropolitan level socioeconomic and demographic characteristics from the American Community Survey (ACS) were used to construct measures of need and control for other factors. Metropolitan level data on lender characteristics from the Summary of Deposits (SOD) were used to control for the lending environment.
- Casey_Demo_Anchorage_APPAM_2013.pdf (352.8KB)