Skip to main content
Log in

Operationalizing the Salience of Race to State Social Policy: A Comparison of Approaches with Application to TANF

  • Original Paper
  • Published:
Journal of Policy Practice and Research Aims and scope Submit manuscript

Abstract

The USA’s system of dual federalism affords states substantial discretion over the design and implementation of important social welfare programs. Social theory posits causal mechanisms through which the politics of race and racism might influence state policy, and a substantial body of empirical scholarship links the salience of race in state politics to policy design. There is no single accepted method for operationalizing the salience of race to policy and policymaking in quantitative studies, however. How do different measures relate, and what are the implications for analysis? I compare multiple possible variables for measuring racial salience in state policy, including measures of population and social program demographics and measures of White racial attitudes. Attitudinal measures are constructed using both disaggregation and multi-level regression and post-stratification. I consider their convergent and discriminant validity through correlations and use them as predictors in models of state Temporary Assistance for Needy Families policy. The predictors generally, though not exclusively, demonstrate high convergent validity and lead to similar inferences in empirical modeling. The high convergence of most measures means studies of the relationship between race and policy at the state level will often lead to similar conclusions regardless of method used to operationalize racial salience. By extension, however, it is difficult to evaluate theories regarding underlying causal mechanisms.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Data Availability

Data are public use data. Analysis files available upon request.

Code Availability

Available upon request.

Notes

  1. Some scholars argue the US welfare state is not underdeveloped relative to other democracies. Rather, it more often operates through different means, such as tax credits and services (Garfinkel et al., 2010; Howard, 2007; Mettler, 2011).

  2. For Black respondents, Whites are the reference group for the outgroup attitudes questions.

  3. This sample size refers to the online sample. The NAES also has a telephone survey with an even larger sample, approximately 60,000 respondents, but does not include the racial attitudes questions. The sample is restricted to non-Hispanic White respondents for this analysis.

  4. The thermometer is top-coded in the publicly reported data, with a code of “97” indicating a response of 97 to 100.

References

  • Administration for Children and Families. (2017). Characteristics and financial circumstances of TANF recipients, fiscal year 2016. Retrieved March 4, 2018, from https://www.acf.hhs.gov/ofa/resource/characteristics-and-financial-circumstances-of-tanf-recipients-fiscal-year-2016-0

  • Alesina, A., Glaeser, E., & Sacerdote, B. (2001). Why doesn’t the United States have a European-style welfare state? Brookings Papers on Economic Activity, 2001(2), 187–254.

    Article  Google Scholar 

  • American National Election Studies. (2019). ANES: American National Election Studies. Retrieved April 3, 2019, from https://electionstudies.org/

  • Annenberg Public Policy Center. (2010). National annenberg election survey. Retrieved May 15, 2015, from http://www.annenbergpublicpolicycenter.org/political-communication/naes/

  • Beland, D. (2005). Social security: History and politics from the new deal to the privatization debate. University Press of Kansas.

    Google Scholar 

  • Bentele, K. G., & Nicoli, L. T. (2012). Ending access as we know it: State welfare benefit coverage in the TANF era. Social Service Review, 86(2), 223–268. https://doi.org/10.1086/666735

    Article  Google Scholar 

  • Berry, W., Fording, R., Ringquist, E., Hanson, R., & Klarner, C. (2013). A new measure of state government ideology, and evidence that both the new measure and an old measure are valid. State Politics & Policy Quarterly, 13(12), 164–182. https://doi.org/10.1177/1532440012464877

    Article  Google Scholar 

  • Brace, P., Sims-Butler, K., Arceneaux, K., & Johnson, M. (2002). Public opinion in the American states: New perspectives using national survey data. American Journal of Political Science, 46(1), 173–189.

    Article  Google Scholar 

  • Branton, R. P., & Jones, B. S. (2005). Reexamining racial attitudes: The conditional relationship between diversity and socioeconomic environment. American Journal of Political Science, 49(2), 359–372.

    Article  Google Scholar 

  • Brown, H. E. (2013). Racialized conflict and policy spillover effects: The role of race in the contemporary U.S. welfare state. American Journal of Sociology, 119(2), 394–443.

  • Brueckner, J. K. (2000). Welfare reform and the race to the bottom: Theory and evidence. Southern Economic Journal, 66(3), 505–525.

    Google Scholar 

  • Carlson, K. D., & Herdman, A. O. (2012). Understanding the impact of convergent validity on research results. Organizational Research Methods, 15(1), 17–32.

    Article  Google Scholar 

  • Center on Budget and Policy Priorities. (2013). TANF emerging from the downturn a weaker safety net: State-by-state fact sheets. Washington, DC: Center on Budget and Policy Priorities. Retrieved from http://www.cbpp.org/cms/index.cfm?fa=view&id=3378.

  • Center on Budget and Policy Priorities. (2018). State fact sheets: How states have spent funds under the TANF block grant. Retrieved April 8, 2018, from https://www.cbpp.org/research/family-income-support/state-fact-sheets-how-states-have-spent-funds-under-the-tanf-block

  • Davies, G., & Derthick, M. (1997). Race and social welfare policy: The social security act of 1935. Political Science Quarterly, 112(2), 217–235.

    Article  Google Scholar 

  • Elmendorf, C. S., & Spencer, D. M. (2014). The geography of racial stereotyping: Evidence and implications for VRA preclearance after Shelby County. California Law Review, 102, 1123–1180.

    Google Scholar 

  • Fairbrother, M., & Martin, I. W. (2013). Does inequality erode social trust? Results from multilevel models of US states and counties. Social Science Research, 42(2), 347–360. https://doi.org/10.1016/j.ssresearch.2012.09.008

    Article  Google Scholar 

  • Falk, G. (2017). The Temporary Assistance for Needy Families (TANF) block grant: A primer on TANF financing and federal requirements. D.C., DC.

    Google Scholar 

  • Fellowes, M., & Rowe, G. (2004). Politics and the new American welfare states. American Journal of Political Science, 48(2), 362–373.

    Article  Google Scholar 

  • Firth, D. (1993). Bias reduction of maximum likelihood estimates. Biometrika, 80(1), 27–38.

    Article  Google Scholar 

  • Fording, R. C. (2003). “Laboratories of democracy” or symbolic politics? The racial origins of welfare reform. In S. Schram, J. Soss, & R. Fording (Eds.), Race and the Politics of Welfare Reform (pp. 72–97). University of Michigan Press.

    Google Scholar 

  • Fox, C. (2004). The changing color of welfare? How whites’ attitudes toward Latinos influence support for welfare. American Journal of Sociology, 110(3), 580–625. https://doi.org/10.1086/422587

    Article  Google Scholar 

  • Fusaro, V. A. (2020). State politics, race, and “welfare” as a funding stream: State cash assistance spending under Temporary Assistance for Needy Families. Early online publication. https://doi.org/10.1111/psj.12390

    Book  Google Scholar 

  • Gais, T., & Weaver, R. (2002). State policy choices under welfare reform. Welfare Reform and Beyond.

    Google Scholar 

  • Garfinkel, I., Rainwater, L., & Smeeding, T. (2010). Wealth and welfare states: Is America a laggard or leader? Oxford University Press.

    Google Scholar 

  • Gelman, A., & Hill, J. (2007). Data analysis using regression and multilevel/hierarchical models. Cambridge University Press.

    Google Scholar 

  • Gelman, A., Lee, D., & Ghitza, Y. (2010). Public opinion on health care reform. The Forum, 8(1). https://doi.org/10.2202/1540-8884.1355

  • Gilens, M. (1999). Why Americans hate welfare: Race, media, and the politics of antipoverty policy. Yale University Press.

    Book  Google Scholar 

  • Hero, R. E., & Tolbert, C. J. (1996). A racial/ethnic diversity interpretation of politics and policy in the states of the U S. American. Journal of Political Science, 40(3), 851–871.

    Article  Google Scholar 

  • Highton, B. (2011). Predjudice rivals partisanship and ideology when explaining the 2008 presidential vote across states. PS: Political Science and Politics, 44(3), 530–535.

    Google Scholar 

  • Howard, C. (2007). The welfare state nobody knows: Debunking myths about U.S. social policy. Princeton, NJ: Princeton University Press.

  • Hussey, L. S., & Pearson-Merkowitz, S. (2012). The changing role of race in social welfare attitude formation: Partisan divides over undocumented immigrants and social welfare policy. Political Research Quarterly, 66(3), 572–584. https://doi.org/10.1177/1065912912453506

    Article  Google Scholar 

  • Johnson, M. (2001). The impact of social diversity and racial attitudes on social welfare policy. State Politics & Policy Quarterly, 1(1), 27–49.

    Article  Google Scholar 

  • Kastellec, J. P., Lax, J. R., & Phillips, J. (2014). Estimating state public opinion with multi-level regression and poststratification using R. Unpublished Manuscript. Retrieved from http://ejournal.narotama.ac.id/files/Estimating state public opinion with multi-level regression and poststratification using R.pdf.

  • Kinder, D., & Sanders, L. (1996). Divided by color: Racial politics and democratic ideals. University of Chicago Press.

    Google Scholar 

  • Kollman, K., Miller, J. H., & Page, S. E. (2000). Decentralization and the search for policy solutions. Journal of Law, Economics, and Organization, 16(1), 102–128. https://doi.org/10.1093/jleo/16.1.102

    Article  Google Scholar 

  • Kreuter, F., Presser, S., & Tourangeau, R. (2008). Social desirability bias in CATI, IVR, and web surveys. Public Opinion Quarterly, 72(5), 847–865. https://doi.org/10.1093/poq/nfn063

    Article  Google Scholar 

  • Lax, J. R., & Phillips, J. H. (2009a). Gay rights in the states: Public opinion and policy responsiveness. American Political Science Review, 103(03), 367–386. https://doi.org/10.1017/S0003055409990050

    Article  Google Scholar 

  • Lax, J. R., & Phillips, J. H. (2009b). How should we estimate public opinion in the states? American Journal of Political Science, 53(1), 107–121. https://doi.org/10.1111/j.1540-5907.2008.00360.x

    Article  Google Scholar 

  • Lee, W., & Roemer, J. (2006). Racism and redistribution in the United States: A solution to the problem of American exceptionalism. Journal of Public Economics, 90(6–7), 1027–1052.

    Article  Google Scholar 

  • Lieberman, R. (1998). Shifting the color line: Race and the American welfare state. President and Fellows of Harvard College.

    Google Scholar 

  • Lieberman, R. (1995). Race, institutions, and the administration of social policy. Social Science History, 19(4), 511. https://doi.org/10.2307/1171478

    Article  Google Scholar 

  • Mas, A., & Moretti, E. (2009). Racial bias in the 2008 presidential election. The American Economic Review, 99(2), 323–329. https://doi.org/10.1257/aer.99.2.323

    Article  Google Scholar 

  • Mettler, S. (2011). The submerged state: How invisible government policies undermine American democracy. University of Chicago Press.

    Book  Google Scholar 

  • Orr, L. (1976). Income transfers as a public good: An application to AFDC. American Economic Review, 66(3), 359–371.

    Google Scholar 

  • Percival, G. L. (2009). Testing the impact of racial attitudes and racial diversity on prisoner reentry policies in the US states. State Politics & Policy Quarterly, 9(2), 176–203. https://doi.org/10.2307/40421635

    Article  Google Scholar 

  • Population Studies Center. (2016). New racial segregation measures for large metropolitan areas: Analysis of the 1990–2010 decennial censuses. Retrieved February 2, 2016, from http://www.psc.isr.umich.edu/dis/census/segregation2010.html

  • Quadagno, J. (1994). The color of welfare: How racism undermined the war on poverty. University of Chicago Press.

    Google Scholar 

  • Rodems, R., & Shaefer, H. L. (2016). Left out: Policy diffusion and the exclusion of black workers from unemployment insurance. Social Science History, 40(3), 385–404. https://doi.org/10.1017/ssh.2016.11

    Article  Google Scholar 

  • Rodgers, H. R., Beamer, G., & Payne, L. (2008). No race in any direction: state welfare and income regimes. Policy Studies Journal, 36(4), 525–543.

    Article  Google Scholar 

  • Rodgers, H. R., & Tedin, K. (2006). State TANF spending: predictors of state tax effort to support welfare reform. Review of Policy Research, 23(3), 745–759.

    Article  Google Scholar 

  • Schickler, E. (2013). New deal liberalism and racial liberalism in the mass public, 1937–1968. Perspectives on Politics, 11(01), 75–98. https://doi.org/10.1017/S1537592712003659

    Article  Google Scholar 

  • Shipan, C. R., & Volden, C. (2012). Policy diffusion: Seven lessons for scholars and practitioners. Public Administration Review, 72(6), 788–796. https://doi.org/10.1111/j.1540-6210.2012.02610.x

    Article  Google Scholar 

  • Skocpol, T. (1992). Protecting soldiers and mothers: The political origins of social policy in the United States. President and Fellows of Harvard College.

    Google Scholar 

  • Soss, J., Fording, R. C., & Schram, S. F. (2011). Disciplining the poor: Neoliberal paternalism and the persistent power of race. University of Chicago Press.

    Book  Google Scholar 

  • Soss, J., Schram, S. F., Vartanian, T., & O’Brien, E. (2001). Setting the terms of relief: Explaining state policy choices in the devolution revolution. American Journal of Political Science, 45(2), 378–395.

    Article  Google Scholar 

  • Tausanovitch, C., & Warshaw, C. (2013). Measuring constituent policy preferences in congress, state legislatures, and cities. The Journal of Politics, 75(02), 330–342. https://doi.org/10.1017/S0022381613000042

    Article  Google Scholar 

  • U.S. Census Bureau. (2016). TheDataWeb: Data Ferrett. Retrieved May 11, 2016, from http://dataferrett.census.gov/

  • U.S. Department of Commerce Bureau of Economic Analysis. (2016). BEA regions. Retrieved May 3, 2016, from http://www.bea.gov/regional/docs/regions.cfm

  • United States Census Bureau. (2016). Table S1501: Educational attainment. Retrieved April 1, 2016, from https://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?src=bkmk

  • University of Kentucky Center for Poverty Research. (2017). UKCPR national welfare data, 1980–2016. Retrieved September 17, 2018, from http://www.ukcpr.org/data

  • Urban Institute. (2015). Welfare rules database. Retrieved from http://anfdata.urban.org/wrd/WRDWelcome.CFM

  • Volden, C. (2016). Failures: Diffusion, learning, and policy abandonment. State Politics & Policy Quarterly, 16(1), 44–77. https://doi.org/10.1177/1532440015588910

    Article  Google Scholar 

  • Ward, D. E. (2005). The white welfare state: The racialization of U.S. welfare policy. Ann Arbor, MI: University of Michigan Press.

Download references

Funding

This work was funded by the Fahs-Beck Fund for Research and Experimentation.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Vincent A. Fusaro.

Ethics declarations

Conflict of Interest

The author declares no competing interests.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fusaro, V.A. Operationalizing the Salience of Race to State Social Policy: A Comparison of Approaches with Application to TANF. J of Pol Practice & Research 2, 213–232 (2021). https://doi.org/10.1007/s42972-021-00028-z

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42972-021-00028-z

Keywords

Navigation