Nonprofits and Political Activity: A Joint Consideration of the Political Activities, Programs, and Organizational Characteristics of Social Service Nonprofits

ABSTRACT

Nonprofit social service agencies are essential to the safety net assisting Americans with low incomes. These agencies also fulfill important civic functions through political activities such as policy advocacy and public education. To learn more about nonprofit political behavior, we analyze unique survey data drawn from 1,205 faith-based and secular nonprofit social service agencies across the United States. We distinguish between six different types of political activity while also considering program service areas. Our findings indicate that there is substantial variation in the type of political activity undertaken by social service nonprofits, and organizational characteristics can help explain this variation.

KEYWORDS:

• Advocacy
• nonprofits
• political activity

Funding

This project was supported by research grants from the Brookings Institution, Brown University, the Center for Policy Research at Syracuse University, the Department of Housing and Urban Development, and the West Coast Poverty Center at the University of Washington and by support from the Institute for Research on Poverty at the University of Wisconsin– Madison, the Institute for Policy Research at Northwestern University, the RUPRI Rural Poverty Center, and the National Poverty Center at the University of Michigan.

Notes

¹ The Multi-City Survey of Social Service Providers (MSSSP) and Rural Survey of Social Service Providers (RSSSP) were conducted by Scott W. Allard through the John Hazen White Public Opinion Laboratory at Brown University The MSSSP conducted interviews with government and nonprofit social service agencies in three cities (Chicago/Cook County, Los Angeles/Los Angeles County, and metropolitan Washington, DC). Metropolitan Washington, DC, included the District of Columbia; Prince George’s County and Montgomery County in Maryland; and Alexandria, Arlington, Loudoun County, Fairfax County, and Prince William County in Northern Virginia. The RSSSP was completed in four multicounty regions: south-central Georgia (Atkinson, Bacon, Ben Hill, Berrien, Coffee, Jeff Davis, Pierce, and Ware counties); southeastern Kentucky (Bell, Clay, Harlan, Jackson, Knox, Laurel, Rockcastle, and Whitley counties); southeastern New Mexico (Chaves, Curry, Debaca, Eddy, Lea, and Roosevelt counties); and an Oregon-California border site composed of 10 counties (Del Norte, Modoc, and Siskiyou counties in California; Coos, Curry, Douglas, Jackson, Josephine, Klamath, and Lake counties in Oregon).

² The MSSSP sampling frame contained 2,953 service organizations in the three study sites. Between November 2004 and August 2005, a survey team contacted each of the 2,953 potential participants using a five-callback minimum rule. Efforts to complete the longer telephone survey identified 770 agencies not eligible for the survey (e.g., no longer operational, did not provide services at their location, or did not offer programs to low-income persons at low or no cost). Telephone surveys were then completed with 1,487 of the remaining 2,183 social service providers, for a response rate of 68 %. The RSSSP database contained 1,270 agencies and churches eligible for the telephone survey. Again, 186 agencies were deemed ineligible for the survey as efforts to complete the longer telephone survey progressed. Surveys were completed with 724 of the remaining 1,084 social service providers between November 2005 and August 2006, for a response rate of 66.8%. Rather than interview managers at administrative offices, the MSSSP and RSSSP sought to interview managers of office sites where services were delivered. As a result, it is possible for an agency with multiple service delivery sites to have multiple observations in the data. In addition, the MSSSP and RSSSP interviews only nonprofits listed in community directories and confirmed as offering direct services on site to poor populations. Thus, the data that follow do not reflect small agencies with informal programs or agencies that primarily focus on advocacy activity. Rather, the study sample and analyses here reflect nonprofits for which direct services are a primary or the primary component of the organization’s mission.

³ Analyses here focus on six specific questions from the MSSSP and RSSSP: (1) How often—frequently, occasionally, or not at all—do you contact or communicate with your elected representatives to city or county government? (2) How often—frequently, occasionally, or not at all—do you contact or communicate with your elected representatives to the state legislature? (3) How often—frequently, occasionally, or not at all—do you contact or communicate with your elected representatives to the state legislature? (4) Does your organization publicly advocate for particular programs on behalf of poor populations? (5) Does your organization seek to educate the public about issues particularly relevant to the interests of poor populations? (6) Do you help to register, educate, or mobilize voters?

⁴ Respondents were asked about changes in funding over a 3-year period to minimize the distortion of year-to-year changes in any given source. Given the potential overlap in the categories and the difficulty of parsing funding precisely in complex organizations, respondents were not forced to total the share of funding from each source to 100%. If two sources were reported to constitute over 50% of revenue, each organization was classified as dependent on that revenue source.

⁵ Although not included in Table 1, about 40% of nonprofit providers in the MSSSP that experienced an increase in demand reported that increase being “significant” or reflecting at least a 25% increase during that time period. Not surprisingly, given these trends in need, three-quarters of nonprofit providers also expected demand to continue to rise in the coming year.

⁶ We transform the number of clients served in a typical month because the raw numbers are skewed and the natural log transformation creates a more normal distribution for the measure. Taking the natural log of the number of clients in a typical month also allows us to examine the relationship between a percentage change in the number of clients and self-reports of a given political activity.

⁷ Similar findings are reached when we model organizational size as a function of annual revenue.

⁸ The odds ratio in this instance reflects the change in odds for a one-unit increase in the natural log of monthly caseload, which is the equivalent of scaling the number of clients served by a factor e1, or 2.718.

⁹ With regard to labor market policies, the cities of Chicago and Los Angeles enacted recent minimum wage laws that would require most employers to pay several dollars above the federal minimum wage. Chicago’s ordinance will increase the minimum wage to $13 an hour by 2019; Los Angeles enacted a law that will increase the minimum wage for all firms to $15 by 2021. See City of Chicago; City of Los Angeles.