My name is David Muhlhausen. I am Senior Policy Analyst in the Center for Data Analysis at The Heritage Foundation. I thank Chairwoman Zoe Lofgren, Ranking Member Kevin McCarthy, and the rest of the subcommittee for the opportunity to testify today. My testimony presents preliminary findings from a forthcoming Center for Data Analysis report on the relationship between welfare caseloads and voter registrations at state public assistance offices. The views I express in this testimony are my own and should not be construed as representing any official position of The Heritage Foundation.
The National Voter Registration Act of 1993 required states to allow eligible persons to register to vote at various government locations, including public assistance offices. Starting in 1995, states reported the number of voter registrations by registration location in two-year intervals.
Since the initial reporting period (1995-1996), the number of persons registering to vote at public assistance offices has declined. This trend has led some to speculate that the states are failing to provide welfare recipients the opportunity to register to vote at public assistance offices. A recent report by Project Vote and Demos, two organizations devoted to voting rights advocacy, performed a descriptive analysis of trends in public assistance registrations. Their study suggests that the number of voter registrations from public assistance offices declined by 79 percent from the reporting period of 1995-1996 to that of 2005-2006. However, this estimate does not explain why registrations decreased. Moreover, it does not control for factors that influence voter registration rates, such as the passage and implementation of welfare reform in 1996.
Other possible explanations for the decline include (1) that voter registration drives by community mobilization organizations replaced the need for welfare recipients to register to vote at public assistance offices and (2) that welfare reform caused the decline in registrations.
The analysis presented in my testimony directly tests the hypothesis that the Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA) of 1996 contributed to the decline in public assistance voter registrations. PRWORA replaced Aid to Families with Dependent Children (AFDC) with Temporary Assistance for Needy Families (TANF). Research by Professors June E. O'Neill and M. Anne Hill of Baruch College strongly suggests that welfare reform accounts for more than half of the decline in AFDC/TANF participation of single mothers during the 1990s.Welfare reform led to a substantial decrease in welfare caseloads, which, in turn, may have led to fewer voters registering at public assistance offices.
Chart 1 plots the trends in average AFDC/TANF participation and the average number of voter registrations at public assistance offices in the states from 1995 to 2006. As illustrated in the chart, the decline in voter registrations closely follows the decline in AFDC/TANF participation. While the association between welfare caseloads and voter registrations seems obvious, other factors that may explain the relationship were also tested.
Data and Modeling
To check for other possible explanations for the decline in voter registrations, a state-level panel data set of public assistance registrations, welfare participation rates, socioeconomic factors, and political election cycles was constructed. Using panel analysis allows this study to test the relative influence of varying AFDC/TANF participation rates on the number of voter registrations while controlling for other factors thought to influence registrations.
The data set contains 12 years of data for 45 states and the District of Columbia. During the time frame of this analysis, several states either failed to report voter registration or were not required to do so. Six states did not report any data during the time frame of the analysis, while 11 states reported public assistance registrations intermittingly. The data set is an unbalanced panel because of incomplete voter registration reporting by some states in certain years.
Methodology. The longitudinal nature of the panel data allows researchers to analyze important policy questions that descriptive studies cannot address. The previous research by Project Vote and Demos failed entirely to take into account important policy and socioeconomic factors that vary across states and over time and that affect registration rates.
Variables. For this analysis, the dependent variable is the number of public assistance registrations per 100,000 residents age 18 or over. The independent variables are AFDC/TANF recipients per 100,000 residents, Food Stamp participants per 100,000 residents, Women, Infants and Children (WIC) participants per 100,000 residents, income per capita, unemployment rate, minority population percent, 18 and older population percent, presidential elections, U.S. Senate elections, gubernatorial elections, off-year congressional elections, and state fixed effects. Table 1 presents the means and standard deviations for the variables presented in the analysis.
The independent variables were chosen based on their anticipated influence on public assistance registrations. For example, AFDC/TANF, Food Stamp, and WIC participation rates measure the level of welfare recipients being served by public assistance offices. Increased welfare participation is anticipated to be positively associated with public assistance registrations.
State unemployment rates and income per capita help to control for the influence of the economy. Unemployment is an especially important variable to include in the analysis because it is highly likely that the sharp decline in unemployment during the 1990s decreased welfare participation. Professors O'Neill and Hill assert that "The true effect of welfare reform cannot be determined without accounting for changes in unemployment and other possible factors affecting single mothers' choices." If decreased unemployment is partially responsible for the decline in AFDC/TANF participation, then it follows that decreased unemployment would lead to fewer public assistance registrations. In addition, the election variables help to control for periods of increased political activity that are also anticipated to be positively associated with public assistance registrations.
The panel data techniques used in the analysis reduce omitted variable bias by introducing state (cross-sectional) fixed effects into the model specification. By controlling for state fixed effects (individual differences related to each state), the analysis accounts for time-invariant unobserved factors that influence public assistance registration rates in a particular state. The fixed-effects model helps to control for differences in registration rates that are not explained by the independent variables.
Table 2 presents the findings of an Ordinary Least Squares (OLS) panel regression. All standard errors are robust to heteroskedasticity and autocorrelation, and the regression is weighted by state population.
Controlling for other factors, AFDC/TANF participation has a statistically significant association with public assistance registrations. A one-unit increase in AFDC/TANF participants per 100,000 residents is associated with an increase of 0.062 additional registrations per 100,000 adult residents. Another way to interpret this finding is to calculate the elasticity. The elasticity represents the percentage change in public assistance registration rates given a 1 percent change in a particular independent variable. A 1 percent increase in AFDC/TANF participation is associated with a 0.49 percent increase in voter registrations. Conversely, a 1 percent decrease in AFDC/TANF participation is associated with a 0.49 percent decline in voter registrations.
Food Stamp and WIC participation do not appear to have any statistically measurable association with public assistance registrations. The results for income per capita, unemployment, and the adult population percentage are statistically insignificant as well.
A state's minority population percentage has a statistically significant and negative relationship with public assistance registrations. A 1 percent increase in the minority population is associated with a reduction of 12.6 registrations per 100,000 adults. Further, a 1 percent increase in the minority population is associated with a 1.1 percent decrease in registrations.
For the election cycle variables, presidential and gubernatorial election years have statistically significant and positive associations with public assistance registrations. During presidential and gubernatorial election years, registrations increased by 97.4 per 100,000 adults and 48.8 per 100,000 adults, respectively. The elasticity calculations for the election year variables represent the percentage change in registrations during a particular type of election year. During presidential and gubernatorial election years, the registration rate increased by 0.08 percent and 0.04 percent, respectively. Senate and off-year congressional elections appear to have no statistically measurable influence on registrations.
Declining AFDC/TANF caseloads from 1996 to 2006 made a substantial contribution to the decrease in public assistance voter registrations. Unlike previous research, my research used panel regression analysis to estimate the relationship between AFDC/TANF participation and other factors that influence public assistance registrations. Controlling for other factors, a 1 percent decrease in AFDC/TANF participation is associated with a 0.49 percent decrease in public assistance registrations. While research on this topic is new and in need of further analysis, Members of Congress should not dismiss the major role of welfare reform and decreased welfare participation in declining public assistance voter registrations.
 Patrick Tyrrell, a research assistant in the Center for Data Analysis at The Heritage Foundation, greatly assisted in the preparation of the data for this analysis.
 Public assistance registration data were obtained from Federal Election Commission/Election Assistance Commission, "The Impact of the National Voter Registration Act of 1993 on the Administration of Elections for Federal Office," 1995-1996, 1997-1998, 1999-2000, 2001-2002, 2003-2004, and 2005-2006. Recent reports are available at http://www.eac.gov/clearinghouse/reports-and-surveys/. Later reports are available upon request from the Election Assistance Commission.
 Frank Askin, "Turning Back the Clock on Voting Rights," New Jersey Record, September 27, 2007; Michael Slater, "Compliance with the NVRA: Not Optional," National Voter, Vol. 57, Issue 2 (February 1, 2008); and Robyn Blummer, "Gaming the Voting System for the GOP," St. Petersburg Times, March 23, 2008.
 Douglas R. Hess and Scott Novakowski, Unequal Access: Neglecting the National Voter Registration Act, 1995-2007, Project Vote and Demos, February 2008.
 Ibid., p. 5.
 June E. O'Neill and M. Anne Hill, "Gaining Ground? Measuring the Impact of Welfare Reform on Welfare and Work," Manhattan Institute, Center for Civic Innovation Civic Report No. 17, July 2003, at /static/reportimages/737FE8240EF04CAD7E0373D2657B2CDF.pdf (March 26, 2008).
 Idaho, Minnesota, New Hampshire, North Dakota, Wisconsin, and Wyoming did not report any data, while Alabama, Connecticut, Maine, Massachusetts, Nevada, New Mexico, New York, Rhode Island, South Carolina, Vermont, and West Virginia provided incomplete data for one or more time periods. The following states are exempt from the NVRA: Idaho, Maine, Montana, New Hampshire, Wisconsin, and Wyoming. See Federal Election Commission/Election Assistance Commission, "The Impact of the National Voter Registration Act of 1993 on the Administration of Elections for Federal Office, 2005-2006," at http://www.eac.gov/clearinghouse/reports-and-surveys/ (March 27, 2008). States that were exempt, failed to report, or reported zero public assistance registrations were coded as missing.
 In addition, by increasing the number of data points compared to cross-sectional and time-series analyses, panel analysis increases the degrees of freedom and reduces possible collinearity among the independent variables, thus improving the efficiency of the econometric estimates.
 The original public assistance voter registration variable was divided in half and distributed by year in equal portions. For example, Alabama reported 80,096 registrations during the 1995-1996 period. The 80,096 registered voters were equally distributed into 1995 and 1996, with 40,048 registrants in each cell. After the allocation, the registrations were divided by the state's population age 18 and over and then multiplied by 100,000.
 Data for these variables were obtained from the U.S. Department of Health and Human Services, U.S. Census Bureau, U.S. Bureau of Economic Analysis, and U.S. Bureau of Labor Statistics.
 O'Neill and Hill, "Gaining Ground?" p. 15.
 Cheng Hsiao, Analysis of Panel Data (Cambridge, U.K.: Cambridge University Press, 1986).
 Several alternative regressions were estimated. The first alternative regression analyzed data from 1997 to 2006, because the 1995-1996 public assistance registration data may drastically overstate the number of registrations that can reasonably be expected from public assistance offices. During 1995-1996, the debate over welfare reform was at its peak. The political debate likely led opponents of reform to encourage welfare recipients to register to vote in an attempt to influence the policy process. This notion is supported by the fact that average state public assistance registrations dropped from 115,177 in 1995-1996 to 53,552 in 1997-1998-a decline of 54 percent. When the data are limited to 1997 to 2006, the coefficient for AFDC/TANF participants remains positive and statistically significant. The second alternative specification analyzed data from all years, while individual time period dummy variables were introduced for the 1997-1998 to 2005-2006 periods. These time period variables control for differences in reported public assistance registrations between the first reporting period (1995-1996) and later reporting periods. In this model, the coefficient for AFDC/TANF participation is statistically insignificant, while the time period dummy variables are statistically significant. The third alternative regression re-estimated the model specification of the second alternative regression, except that the data were limited to the years of 1997 to 2006. The coefficient for AFDC/TANF participation is statistically significant, while the time period dummy variable coefficients are not statistically distinguishable from zero. This result strongly indicates that the reporting of public assistance registrations was unusually high in the 1995-1996 period compared to later reporting periods.
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