This section contains a brief discussion of the variables used in the statistical analysis. The unit of analysis is a state-year (N = 670), and the study covers the period from 1975 to 1992. The observation starts in 1975, the year the first motor voter model was adopted in Michigan, and ends in 1992, the year before the NVRA passed, after which any state-level legislation would become superfluous. Table 1.5 shows the descriptive statistic of dependent and
independent variables. Note that all the variables that take non-discrete values are expressed in terms of percentage instead of proportion. Table 1.6 displays the pairwise correlations among these variables. The relatively high and negative correlations between the Human SERVE activity measures and the turnout rate may suggest that the organization targeted low turnout states.
< Insert Table 1.5 about here > < Insert Table 1.6 about here >
Dependent variables. There are two sets of dependent variables, and both represent the
first motor voter legislation in each state. The first represents whether the legislation was accompanied by ABR. It is coded 1 if the legislation was not accompanied by ABR (MV-only) and 2 if it was accompanied by ABR (MV-ABR). The second represents the implementation type that followed the legislation. It is coded 1 if active implementation followed and 2 if passive implementation followed. For both variables, it is coded 0 for the years without any event up to the first legislation, and the state drops out of the dataset once the event has taken place (i.e., the variable is coded as missing for the rest of the observed period). Because I argue that MV-only and MV-ABR, as well as active and passive implementation, are qualitatively different from
each other, the two outcomes for each dependent variable should not be treated as if we can impose a hierarchical order between them. Therefore, I use multinomial logit to estimate the models. North Dakota is omitted from the dataset because no voter registration is required in that state. Nebraska is also omitted from the analysis because its unicameral legislature operates without partisan designation. Some states had biennial sessions during the period (part or whole) under observation.13 Because those states in no-session years should be considered not at risk of
the event, I dropped those no-session state-year observations from the dataset.
Independent variables. The explanatory variables include those necessary for testing the
hypotheses (partisan control of state government, electoral competitiveness, and ideology). In addition to measurement of Human SERVE activity, those factors that can be considered to have affected the necessity of reform (poverty rate, size of African American population, and turnout rate) are included. The region (South) dummy is included in the models using the data of all states in order to control for the potential impact that the historical and cultural background unique to the South had on the reform prospect. Also, a separate regression with the data excluding the Southern states was run for each specification, because the implication of having a
13 There were 31 states with biennial sessions after WWII, but the number fell to nine by the mid-1970s. The
following states have eliminated biennial sessions (years in parentheses show when they started annual
sessions): Washington (1981), New Hampshire (1985), Kentucky (2001), Arkansas (2009), and Oregon (2011). Montana, Nevada, North Dakota, and Texas have maintained the biennial sessions to the present.
unified Democratic government could have been quite different within and outside the South. The last is a time counter to capture any time trend. Because the Human SERVE variables have been discussed previously, I explain the remaining variables below.
To measure the impact of partisan institutional control of the state government, I use two separate dummy variables for a unified state Democratic government and a unified state Republican government, respectively, rather than a trichotomous variable (Medoff et al. 2011), which combines the two into one variable.14 Using the trichotomous version imposes the
assumption that unified governments by both parties have symmetrical effects on the outcome, while in reality, they may not. The use of two unified government dummy variables makes a divided government the base category. These variables are used to test Hypothesis 1.
To test Hypothesis 2, I created a variable representing electoral competition at the district level in the form of percentage of state legislators from competitive districts.15 Competitive
districts are those in which the winner received less than 60% of the total vote. As discussed
14 The trichotomous version would “equal to 1 if the Republican Party controls both houses of the state
legislature and the governor’s office, 0 if there is divided government (i.e. one political party controls one or two branches of the state government—senate, house or governor’s office—but not all three), and -1 if the Democratic Party controls both houses of the state legislature and the governor’s office in year t” (Medoff et al. 2011).
15 The variable is created from ICPSR21480 State Legislative Election Returns, 1967–2003. Observations for
Vermont are missing in the original data prior to 1986. Therefore, the entries for the state in the subsequent statistical analysis cover only the years between 1986 and 1992.
earlier, incumbents from safe seats would have no incentive to change the electoral regulations. However, incumbents from competitive districts might have hoped to claim credit for introducing the popular reform. They may have opted to gamble on the (potentially) positive impact of the reform if the reform was popular and considered partisan-neutral. To test Statements 2b and 2d, I also use the percentage of Democratic incumbents from competitive districts in separate models.
With the general political ideology of the citizens of the state, I test Hypothesis 3, the impact the political culture of the state had on expansive voter registration reform. People in more liberal states might have thought that access to voter registration should be open to as many citizens as possible and the government should guarantee it, while people in conservative states could have been more likely to think that the right to vote was a civic privilege and that people should make a personal effort to exercise it. State politicians were likely to have a general idea of the ideological predispositions of their constituents, and this recognition might have influenced or limited the way they reacted to electoral reform proposals. For this variable, I use Erikson, Wright, and McIver’s (1993) measure of state political ideology, which is the percentage of the
state’s population who identified themselves as liberal minus the percentage who identified themselves as conservative, in the CBS/New York Times poll conducted annually for each state.16
The dummy variable for the Southern states measures the impact of political culture as well as the region-specific historical background. The Southern states are known for their history of restrictive electoral regulations, which targeted African Americans specifically. Because ABR was originally conceptualized by its advocates to open up access to voter registration to the socioeconomically less advantaged, I also use the percentage of the population who lived in poverty and the percentage of the African American population in each state. Turnout rate (in the form of the percentage of the highest vote to voting age population) is another variable that might have potentially affected decision making regarding voter registration reform.17 States
with low turnout may have had an incentive to improve their electoral regulation.
Finally, the time counter is included to account for the impact of time. Although the first motor voter reform took place in Michigan in 1975, the time counter created for this paper does not start ticking until 1983, when Human SERVE came into place. (The variable takes the value
16 I have also tried the time-invariant policy liberalism measure built by Erikson, Wright, and McIver (1993)
under many different model specifications, but the outcome patterns were consistent with the results from using the citizen ideology measurement. Thus, I use the citizen liberalism measurement in the rest of the paper.
17 Turnout data is taken from Michael P. McDonald (2012), “Presidential Voter Turnout Rates, 1948–2008,”
of 0 between 1975 and 1982, and takes 1 for 1983, 2 for 1984, and so on.) It is clear that voter registration reform saw a different level of momentum after 1983, largely due to the nationwide “voter registration war” (Piven and Cloward 2000), and Human SERVE was organized in the same context. Therefore, distinguishing the pre-1983 and post-1983 periods by setting the time counter accordingly should capture the realistic time trend if it existed.