THE IMPACT of TOUCH SCREEN VOTING MACHINES on VOTER ROLL-OFF by MATTHEW STEVEN JENNINGS (Under the Direction of Charles S. Bullo

THE IMPACT OF TOUCH SCREEN VOTING MACHINES ON VOTER ROLL-OFF

MATTHEW STEVEN JENNINGS

(Under the Direction of Charles S. Bullock III)

ABSTRACT

Since the 2002 midterm elections, the State of Georgia has used touch screen voting machines in its elections. Among other things, these voting machines include a feature that notifies voters of contests in which the voter has yet to cast a vote. This study seeks to determine the effects of these machines on voter roll-off, which occurs when a voter casts votes for offices at the beginning of the ballot and fails to register a vote for offices farther along the ballot. Analyzing seven statewide offices over six elections, I find strong evidence that roll-off has dropped precipitously since the state’s adoption of the touch screen machines.

This decline seems to have been influenced by the change in voting technology, although the effects are not uniform.

INDEX WORDS: Elections; Voting behavior; Ballot roll-off; Voting technology; Touch screen voting machines

THE IMPACT OF TOUCH SCREEN VOTING MACHINES ON VOTER ROLL-OFF

MATTHEW STEVEN JENNINGS

BS, Kennesaw State University, 2010

A Thesis Submitted to the Graduate Faculty of The University of Georgia in Partial Fulfillment of

the Requirements for the Degree

MASTER OF ARTS

ATHENS, GEORGIA

2012

MATTHEW STEVEN JENNINGS

THE IMPACT OF TOUCH SCREEN VOTING MACHINES ON VOTER ROLL-OFF

MATTHEW STEVEN JENNINGS

Major Professor: Charles S. Bullock III

Committee: M.V. Hood III James Monogan

Electronic Version Approved:

Maureen Grasso Dean of the Graduate School The University of Georgia August 2012

TABLE OF CONTENTS

Page

LIST OF TABLES ...... v

LIST OF FIGURES ...... vi

CHAPTER

1 Introduction ...... 1

2 Literature Review...... 5

Theories of Roll-off...... 5

The Contextual Influences on Roll-off...... 7

3 Data and Methods ...... 12

4 Findings ...... 17

Univariate Analysis ...... 17

Multilevel Models of Roll-off ...... 22

5 Discussion ...... 28

REFERENCES 31

LIST OF TABLES

Page

Table 1: Roll-off by Office by Year (Contested Elections Only) ...... 21

Table 2: Hierarchical Linear Models of Roll-off ...... 27

LIST OF FIGURES

Page

Figure 1: Predicted Roll-off by Ballot Type ...... 24

CHAPTER 1

INTRODUCTION

The 2000 election cycle in Georgia passed by relatively quietly. In the presidential contest, George W. Bush easily won the state’s thirteen electoral votes. Senator Zell Miller, appointed to the Senate following the death of incumbent Paul Coverdale, was successful in his bid for the right to serve out the remainder of Coverdale’s term, securing enough votes to avoid a runoff. All eleven U.S. House incumbents won re-election. Democrats maintained their majorities in both houses of the state legislature.

Florida, Georgia’s neighbor to the south, was a different story altogether. There, the presidential contest was exceedingly close. During the course of the night, the major networks made multiple projections and retractions for the state’s twenty-five electoral votes, calling the state for both George W. Bush and Al Gore at different points. Election Night 2000 ended with the fate of Florida’s electoral votes still undecided. The presidential contest at the national level was likewise very tight. As the night wore on, it became clear that Florida would be the decisive state. Ultimately, the final result was not known until weeks later after an acrimonious process that involved recounts and lawsuits involved multiple levels of the judiciary.

With every single vote being critical, this ordeal would also serve to highlight numerous flaws in the Florida election system, flaws that prevented votes from being cast and counted accurately. In some areas, the presidential ballot spanned two pages while the directions instructed voters to vote every page, causing some voters to over-vote, or cast more votes than

allowed in the presidential contest. Other areas used a ballot layout that caused some voters to mark their ballot in the wrong place, effectively casting their vote for the wrong candidate.

In those counties that used punch card machines, even if the voters correctly marked their ballots for their intended candidate, their vote may still not have been counted correctly because the ballot did not fully perforate.

Following this debacle, federal and state governments moved to implement reforms, seeking to prevent such occurrences from happening again. One such reform was Georgia’s statewide adoption of touch screen voting machines beginning with the 2002 election. Prior to this, each of Georgia’s 159 counties chose their own voting technology, creating a mish-mash of ballot types across the state, ranging from lever machines to optical scan ballots to punch card ballots like the ones that had caused so much trouble in Florida.

This new technology can potentially have broad effects on election outcomes and voting behavior. One such way is on ballot roll-off, the phenomenon that occurs when fewer votes are cast for some items on the ballot (usually those farther down the ballot) compared to others.

Two primary features of the touch screen voting machines can serve to reduce roll-off. First, they eliminate the possibility of over-voting, which happens when a voter casts more votes than allowed in a given contest, resulting in the disqualification of all of the votes cast for that contest. 1 Second, Georgia’s touch screen voting machines may reduce roll-off by decreasing the number of undervotes, or instances in which the voter registers no vote in a given contest.

The last screen gives voters the option to review their ballots and make changes, highlighting in

1 This was not a feature of most voting methods in Georgia prior to 2002. Only counties using lever machines (46% of Georgia counties) precluded over-voting in the ballot booth (Bullock and Hood 2002). Additionally, some optical scan machines had a feature that would return the ballot if the voting had cast more votes than allowed, but this feature was not present in all counties using optical scan machines nor was the vote required to re-vote.

red any contests in which they have not yet registered a choice. This along with the prevention of over-votes can serve to further the ideals of democracy by helping to ensure that the ballot submitted accurately reflects the voter’s will. However, some voters may mistakenly interpret the review screen to indicate that they are actually required to enter a vote or their ballot will not count, inducing them to return to their ballot to enter votes.

To date, the effect of electronic voting machines on roll-off has seen only limited attention by political scientists. Studies by Nichols (1998) and Nichols and Strizek (1995) have examined the impact of electronic voting machines on roll-off, finding that electronic machines are associated with lower roll-off compared to manual voting machines. In addition to studying a different time frame and geographic area, two features of my study provide sharp departures from these works. The previous studies rely on natural experiments to test their hypotheses, comparing roll-off in counties or precincts using electronic machines to areas using manual voting technology. In contrast, I compare the post-adoption roll-off rate to their pre-adoption roll-off rates. Second, like Georgia, the voting machines studied in the previous literature notify voters of uncast votes. However, Georgia’s notification is more subtle, highlighting contests lacking votes in red as opposed a flashing light beneath every contest, and presents all of the contests together while the machines studied previously feature blinking lights near every item on the ballot that only stop blinking once a vote is cast. Therefore, Georgia provides a more stringent test for the possible effects of the new machines.

To test the hypothesis that Georgia’s touch screen voting machines have diminished roll-off, I examine roll-off for seven down-ballot, statewide offices for six election cycles occurring between 1990 and 2010 (three before Georgia adopted touch screen voting machines

and three after). I present three multilevel, linear models. Roll-off for the three post-adoption cycles is substantially lower compared to elections occurring before the switch. However, support is mixed for the hypothesis that touch screen machines have reduced roll-off. As expected, when touch screen machines are used, roll-off is lower compared to when lever machines or paper ballots are in use. However, roll-off actually appears to be lower when optical scan machines or punch cards are used than when touch screen machines are used.

These results are unaffected by the inclusion of controls for other factors that may influence roll-off, such as campaign expenditures, incumbency, and the racial composition of the electorate.

CHAPTER 2

LITERATURE REVIEW

Theories of Roll-Off

Political scientists have identified several possible, individual-level causes for roll-off.

Many scholars (e.g., Nichols and Strizek; Walker 1966; Wattenberg, McAllister, and Salvanto

2000) portray roll-off as resulting from a disparity in information between contests on the ballot, with voters feeling that they have sufficient information to make a decision in certain contests but not for others. According to the models of voting decision-making presented by

Aldrich (1995) and by Downs (1957), prospective voters weigh the potential costs of voting against the potential benefits. Should the benefits be greater than the costs, the models predict that the potential voter will choose to go to the polls. However, if the costs of voting outweigh the benefits, then the prospective voter will choose not to vote. Among the costs of voting is the cost of obtaining information: learning about the candidates, their platforms, and the relevant issues. Although Aldrich and Downs’ models focus on turnout as the dependent variable, voters can repeat this process in the voting booth, casting votes in contests in which they have sufficient information while forgoing contests in which they lack such information.

Not only does a relative dearth of information fail to decrease the costs of voting, the lack of information can actually add to the costs of voting because voters lacking information may be fearful of making the wrong decision if they vote out of ignorance (Wattenberg, McAllister, and

Salvanto 2000).

Another possible explanation for voters failing to cast votes in some contests but not others is due to perceived differences in the saliency and prestige between the offices on the ballot (Harris and Zipp 1999; Milton 1983; Vanderleeuw and Engstrom 1987). Contests closer to the beginning of the ballot tend to be for the offices that are seen as the most important and the most prestigious and tend to be the most visible to voters, such as the president.

Conversely, contests for offices receiving less visibility and seen as comparatively less important such as county coroner typically appear farther down the ballot.

Alternatively, roll-off may be a result of voters becoming physically or mentally unable or unwilling to complete their ballot (Bullock and Dunn 1996; Southwell 2009; Walker 1966). In fact, “voter fatigue” is sometimes used as a synonym for roll-off. Although to some it may seem silly to think that the act of voting can be physically or mentally tiresome, many voters have to stand in line for some time before they get to the voting booth (possibly in less than ideal weather, especially in the case of general elections) and have to remain standing while voting. Additionally, time factors into the costs of voting (Downs 1957). Voters do not have unlimited time to vote. They may need to hurry home to make dinner for their families or may be on their lunch break. Under these situations, voters may opt to forgo the latter part of the ballot in the name of expediency.

Finally, some have put forth a confusion explanation, stating that aspects of the ballot confuse voters, causing them to miss items on the ballot. This can include higher roll-off for items printed on the back of the ballot (Darcy and Schneider 1989), confusion due to changes in voting technology (Nichols and Strizek 1995), or confusion due to complex ballots (Walker

1966).

The Contextual Influences on Roll-Off

From these four potential causes, we can draw some predictions about how specific contextual factors can influence roll-off. First, the presence or absence of party labels on the ballot should have an effect on roll-off. Indeed, a battery of evidence exists indicating that roll- off is lower in partisan elections than for nonpartisan elections (Hall 2007; Hall and Bonneau

2005, 2008; Nichols and Strizek 1995; Schaffner and Streb 2002; Streb, Frederick, and LaFrance

2009; Watternberg, McAllister, and Salvanto 2000). Party serves as an important heuristic for voters, allowing them to project their views of the political parties onto the parties’ candidates.

In some contests, party labels may be the only source of information for many voters. Likewise, spending by the candidates has been found to exert a negative influence on roll-off in state assembly races (Kousser and Mullin 2009), contests for the U.S. House (Winburn and Wagner

2010), and for state Supreme Court elections (Hall and Bonneau 2008). Spending has also been found to affect roll-off for ballot propositions (Bowler, Donovan, and Happ 1992). Although there is no guarantee that spending will go toward advertising or other forms of direct contact with voters, a very large portion does go toward direct contact with voters. Therefore, higher levels of campaign spending should improve levels of voter information about the candidates and thus reduce roll-off. Finally, roll-off may also be affected by an incumbent running for re- election (Vanderleeuw and Sowers 2007). In their interactions with their constituents and the media and previous elections, incumbents would be expected to build up some store of name recognition, an important source of information for voters.

Related to salience, having a contested election can serve to reduce roll-off (Streb,

Frederick, and LaFrance 2009). Although the intrinsic salience of the office in question does not

change, the salience for the particular electoral contest increases. The voting models from

Aldrich (1995) and Downs (1957) postulate that prospective voters consider the probability that their vote can decide the outcome. When prospective voters believe that their vote will be decisive, they should have a greater probability of voting. When an election is uncontested, both of these values are zero because there are no candidates to compare and no chance that any one vote would make a difference in the outcome. Additionally, the presence of a third- party or independent candidate on the ballot can also reduce roll-off (Wattenberg, McAllister, and Salvanto 2000). This may be because a third party challenger affords voters a choice beyond just the two major parties.

Skirting the boundary between information and salience is the influence of presidential elections on downballot roll-off. Previous research has shown that roll-off tends to be higher in presidential election years than in non-presidential years (Hall 2007; Hall and Bonneau 2005,

2008; Southwell 2009). The presidential election receives copious amounts of media coverage from a multitude of sources. By comparison, local contests receive far less news coverage from far fewer news sources. The presidency is also the most prestigious office in the country, as evidenced by the fact that the president is routinely referred to as “the Leader of the Free

World.” Offices such as the clerk of the county court pale in comparison. Therefore, it would be expected that elections for offices sharing the same ballot as the presidential race would have higher levels of roll-off than contests during midterm elections and off-year elections because of the influx of voters activated by the presidential race lacking knowledge and/or concern for down-ballot contests.

One of the theorized causes of roll-off states that some voters become fatigued to the point that they forgo finishing their ballot. If this is true, then one would expect that fatigue to increase as the length of the ballot increases. The previous literature has yielded mixed results on this claim. Several authors (e.g., Kousser and Mullin 2006; McDonald 2004; Wattenberg,

McAllister, and Salvanto 2000) find evidence that roll-off does not follow a linear pattern.

Wattenberg, McAllister, and Salvanto (2000) find that certain races and referenda had much higher turnout than their placement on the ballot would indicate while McDonald (2004) finds evidence of some contests listed relatively higher on the ballot having fewer votes cast than contests listed farther down the ballot. However, others (e.g., Reilly, Walker, and Barrett 2008;

Southwell 2009) find a positive correlation between number of items on the ballot and roll-off.

Whereas the previous literature regarding the impact of ballot position is rather conflicted, the literature on the effects on roll-off from voter race is mostly in agreement.

Numerous studies (e.g., Bullock and Dunn 1996; Darcy and Schneider 1989; Vanderleeuw and

Engstrom 1987; Vanderleeuw and Utter 1993; Walker 1966; Wattenberg, McAllister, and

Salvanto 2000; although see Winburn and Wagner 2010) have indicated that non-whites, usually blacks specifically, are more likely to roll-off than whites. Darcy and Schneider (1989) find that this relationship persists even after controlling for socioeconomic status.

Vanderleeuw and Engstrom (1987) find it exists even when there is relative parity in registration and turnout between whites and blacks.

Most important to the underlying question of this study are the effects on roll-off from ballot design and voting technology. One early study by Walker (1966) compares roll-off from states using the party column ballot style (where candidates are listed in rows by party) to

states using the office block style (where candidates are listed by office), finding greater roll-off for the office block style. Similarly, the option to vote a straight party ticket (i.e., voting for all of the candidates from a party in one fell swoop instead of going through each office one-by- one) can serve to reduce roll-off (Walker 1966; although see Austin et al. 1991). Evidence also exists that roll-off is higher for items printed on the back of the ballot (Darcy and Schneider

1989), for more complex ballot forms (Walker 1966), and when new ballot forms are adopted

(Nichols and Strizek 1995). In these three cases, it is assumed that voters become confused.

Research has also been conducted on how the actual method of voting, how the voter actually records his or her vote, affects roll-off and other types of uncounted votes. Studying the 2000 Georgia presidential contest, Bullock and Hood (2002) find that uncounted votes for president were lower in counties using lever machines and those using “fill in the oval” optical scan ballots compared to counties using punch cards. Darcy and Schneider (1989) find, all else equal, that optical scan ballots have lower roll-off than paper ballots. Additionally, mail ballots in theory should reduce roll-off by giving voters more time to research candidates and issues and to fill in unforeseen gaps in their knowledge. At the same time, it may reduce fatigue by allowing voters to make their choices at their leisure without standing in line, again reducing roll-off. Southwell (2009)’s study of mail voting in Oregon before and after a statewide switch to mail-only ballots does indicate a slight decrease in roll-off, apparently due to voting by mail.

On the other hand, Kousser and Mullin (2006) find the opposite in their study comparing mandatory vote-by-mail precincts in California to Election Day precincts: voting by mail is actually associated with higher roll-off.

Finally, two studies have examined the impact of electronic voting machines on roll-off

(Nichols 1998; Nichols and Strizek 1995). These studies have examined differences in roll-off between counties or precincts that used electronic machines and those that used manual voting technology. Both studies find that electronic voting machines have lower roll-off compared to manual voting machines, even after controlling for factors such as socio-economic status. Additionally, these electronic machines featured a prompt notifying the voter of uncast votes. The authors admit, however, that this prompt is especially noticeable: a blinking light below each contest or item of the ballot. The prompt for the Georgia machines is more subtle and makes for a more stringent test of the effects on roll-off from voting machines. In the next two sections, I elaborate on my strategy for testing these potential effects.

CHAPTER 3

DATA AND METHODS

I employ an original dataset consisting of data for all contested elections from 1990 to

2010 for several executive branch offices in Georgia: Lieutenant Governor, Secretary of State,

Attorney General, State School Superintendent, Agriculture Commissioner, Insurance

Commissioner, and Labor Commissioner. Data for these contests come from the Georgia

Secretary of State’s website. 2 Contests for these offices occur during the midterm elections with party labels listed on the ballot. Limiting the analysis to these seven offices provides eliminates the need to add statistical controls for presidential elections and partisan labels.

The unit of analysis is a year-office-county set.

The dependent variable is the roll-off rate for each year-office-county set.

Operationalizing this variable presents somewhat of a dilemma as scholars have differed in their approaches to operationalizing roll-off. Several have measured roll-off as a function of total turnout in a given year (Aspin and Hall 1989; Bowler, Donovan, and Happ 1991; Darcy and

Schneider 1989; Harris and Zipp 1999; Kousser and Mullin 2006; Milton 1983). Another group has used the ballot item receiving the most votes as the baseline (Nichols 1998; Reilly, Walker, and Barrett 2008). Finally, some have examined roll-off by referring to the ballot item at the top of the ballot (Hall and Bonneau 2005; Vanderleeuw and Liu 2002; Vanderleeuw and Sowers

2007).

2 http://sos.ga.gov/elections

Using the first contest as the baseline is problematic here because the 1990 ballot in

Georgia began with an uncontested race for the U.S. Senate. Previous research has found that roll-off for a particular office is increased when there is no opposition on the ballot (Streb,

Frederick, and LaFrance 2009); in other words, uncontested races receive fewer votes than contested races. One would therefore expect that an uncontested race for any office would yield fewer votes than would occur if the race were contested. If this is the case, then using an uncontested race as the baseline to measure down-ballot roll-off may bias the roll-off values downward. Indeed, every contested race for statewide, partisan office in 1990 (and even one of the uncontested races) garnered substantially more votes than the uncontested senatorial election that year. Because 1990 was the only year in which this was the case, the roll-off values for 1990 may be deflated compared to those of the other five cycles.

Therefore, I operationalize the roll-off for each observation as the percent decline in total votes from the contest on the ballot receiving the most votes statewide that year so that higher values indicate greater roll-off.3 For example, if a county cast 100 votes for Governor and 90 votes for Lieutenant Governor, then this county’s roll-off for Lieutenant Governor is 10, or [(100-90)/100]*100. Using the office receiving the most votes helps to promote consistency between the six election cycles under study in that, in each year, the contest receiving the most votes was contested by both major political parties. Five of the six cycles also saw at least one third party or independent challenger on the ballot for the contest garnering the most votes statewide.

3 For five of the six cycles, the gubernatorial contest received the most votes statewide. The exception was 1998, where the senatorial contest received the most votes. Even then, the difference in the number of votes cast in 2002 for Senate and for Governor is just over 0.2%.

I measure the potential effect of the state’s adoption of touch screen voting machines through the use of dummy variables for voting method used in each county for each year.

These represent lever machines, optical scan ballots, punch cards, and paper ballots with touch screen machines used as the reference category. Data for these variables were graciously made available by Charles Bullock and Trey Hood. I expect the coefficient for each of these variables to have a positive sign, indicating that each of the previous voting methods yielded a higher level of roll-off than touch screen machines.

Other factors apart from the change in voting technology may explain changes in roll- off from year-to-year. Therefore, I include controls for several other contextual factors that have been found to affect roll-off in previous literature. I measure campaign spending as the sum of the expenditures by all of the candidates on the general election ballot for that particular contest. These amounts come from the most recent filing statement for each candidate, generally the statement filed at the end of the election year. To control for inflation,

I convert the amounts for the three post-adoption election years into 1998 dollars. These figures are presented in hundreds of thousands of dollars. Campaign expenditure data for 1998 and 2002 comes from the Secretary of State’s website while data for 2006 and 2010 comes from the official website of the Georgia Ethics Commission. 4 Data for prior years is not available.

I measure the competitiveness of each contest as the difference between the percentage of the vote garnered statewide by the winning candidate and the percentage of the

4 http://ethics.ga.gov

vote earned by the second-place finisher. The relative placement of an office on the ballot can vary from year to year due to the presence of a contest for Senate or changes in ordering.

Therefore, I include a variable for ballot position. I also include four controls for candidate characteristics that may influence roll-off. These are dichotomous variables indicating if the incumbent sought re-election, whether a third party or independent candidate was on the ballot for that office, if either or both of the two major party candidates was African-American, and whether one or both candidates was female. 5

Additionally, I control for two county-level effects. Just as candidate demographics can affect roll-off, numerous studies have indicated that the race of the voter can influence roll-off

(Bullock and Dunn 1996; Darcy and Schneider 1989; Vanderleeuw and Engstrom 1987;

Vanderleeuw and Utter 1993; Walker 1966; Wattenberg, McAllister, and Salvanto 2000). Using data from the Secretary of State’s website, I control for the racial composition of each county’s electorate in a given year. 6 This variable represents the African-American percentage of all voters going to the polls in each county that in each year. I also control for the education level in the county. This represents the percentage of adults twenty-five years and older with at least a high school diploma. Data for this variable come from the decennial U.S. Census Bureau as well as the estimates from the Census Bureau’s American Community Survey (ACS). I interpolated the values for the election cycles not coinciding with official census data.

5 Research has found that the presence of two African-American candidates on the ballot can actually serve to increase roll-off (Vanderleeuw and Sowers 2007). Such a scenario has not occurred in any of the general election contests in this study.

6 Georgia is one of a handful of states that tracks voter registration and turnout by race. Many previous studies on the effects of race on roll-off have relied on Census data of the overall population to measure racial composition. Basing this measure on the electorate thus makes for a more precise measure.

Finally, because unmeasured, time-related factors may affect roll-off I include a variable to control for time. This represents the difference between election year and 1998, divided by two.

CHAPTER 4

FINDINGS

Univariate Analysis

I begin by examining the measures of central tendency and dispersion for roll-off broken down by election cycle. These are presented in Table 1. Overall, these measures provide strong evidence that roll-off has declined precipitously since Georgia’s adoption of touch screen voting machines in 2002. The first six rows of the table show the statistics aggregated across all seven offices. For all three election cycles since the adoption of touch screen voting machines, the mean level of roll-off has been less than three percent. The highest mean for a post- adoption election was 2006 with a mean of 2.83. By comparison, the lowest pre-adoption mean was almost seven (6.85 in 1998). These figures, however, do indicate that ballot roll-off in Georgia appears to have been declining even before the state began using touch screen voting machines. However, the decline since the 2002 election cycle, when the new machines were put into place, exceeds what would otherwise be expected based on trends alone. There was only a 9% decline in the mean from 1990 to 1994. In 1998, the decline from the previous cycle was larger at 25%. Even then, the total decline from 1990 to 1998 was only about 31%.

By comparison, the decline from 1998 to 2002 was 64%, and even though the mean level of roll-off in 2006 actually rose from the previous election, it still represented a 59% decrease from 1998 and a 72% decline from 1990.

Similar conclusions can be drawn from comparing the medians for the six election cycles. For two of the three post-adoption cycles, the median level of roll-off was less than half of the median for 1998, the pre-adoption cycle with the lowest median. The exception was

2006, and even then, it still marked a 44% decrease in the median level of roll-off reduction from 1998. As was the case with the means, there appears to have been a downward trend of the medians. Again, however, the decline appears to have intensified since the state began using touch screen machines. Between 1990 and 1994, the median level of roll-off declined by a mere 15%. The decline from 1994 to 1998 was much larger at 42%. Although this reduction is quite large, it is outstripped by the 51% median reduction seen in 2002.

There appears to have been an even more dramatic decline in the third quartile and maximum values. For every election cycle before the switch to touch screen machines, the third quartile was above eleven. The third quartile would decline by more than two-thirds for the three post-adoption cycles to less than four in each case. Similarly, 2002 marked a large decrease in the maximum level of roll-off. This number was more than thirty for all three pre- adoption cycles. This number has plummeted since Georgia began using touch screen machines, the largest value being 12.59 seen in 2002. Additionally, these do not display the same marked, downward trend seen in the mean and median values for the pre-adoption years. The trend is rather slight for the third quartile values (only a ten percent reduction from year to year), and there appears to be no year-to-year trend in maximum values for the pre- implementation years.

These results generally hold up when examining each office individually, although idiosyncratic factors such as competitiveness may play a larger role. For every office, the mean

roll-off decreased substantially over the three post-adoption elections compared to the means for the pre-adoption years. No post-adoption election for any office has had a higher mean compared to a pre-adoption mean. In all but two cases, the mean level of roll-off for post- adoption elections has been less than half of the 1998 baseline. The examination of the medians over time results in the same conclusion. In only one case does the median level of roll-off for a post-adoption contest exceed the median for a pre-adoption contest for the same office: the 2006 Secretary of State contest exceeds the 1998 median. With only a few exceptions, the median level of roll-off post-adoption has been less than half of that in 1998.

Examining the minimum values, maximum values, first quartiles, and third quartiles reveals that the decrease in roll-off seems to have taken place more toward the upper end of the range than in the lower end. In 1998, the maximum roll-off value for all seven contests was in double-digits. Contests in these counties received less than eighty percent of the votes cast in the gubernatorial contest. Since then, there has been an across-the-board decrease in the maximum roll-off. No contest has seen maximum roll-off above its maximum roll-off in 1998.

From 2002 onward, the maximum level of roll-off has reached double digits in only four of twenty-one contests: Attorney General in 2002 and Secretary of State, Insurance

Commissioner, and Labor Commissioner in 2006. A similar pattern can be seen when comparing the third quartiles for each office over time. In 1998, the seventy-fifth percentile for every contest was over seven percentage points. Five of the six contests in 1998 had Q3 values in double digits. In the three elections after the adoption of the touch screen machines, the Q3 value has been more than halved from the 1998 baseline. No contest has had a Q3 value in the double digits.

By comparison, while examination of the minimum values and the first quartiles also indicate a reduction in roll-off, the evidence is more mixed. Examination of the Q1 values shows a general decline in roll-off in each of the three post-adoption elections compared to

1998. However, five of the twenty-one post-adoption contests had higher Q1 values than their

1998 counterparts. One contest (Secretary of State in 2006) actually had a Q1 value more than double that which occurred in 1998. The reduction in roll-off is also smaller compared to the other descriptive statistics. The minimum values, provide even more counterfactuals. Thirteen of the twenty-one post-adoption contests had minimum levels of roll-off in excess of the 1998 baselines. No office has seen an across-the-board reduction in their minimum level of roll-off.

In addition to a downward shift in voter roll-off, the variation in roll-off across counties has dropped dramatically. All seven contests had a standard deviation of at least four percentage points in 1998. Three of those seven had standard deviations above six points.

From 2002 onward, none of the contests has had a standard deviation above two percentage points.

TABLE 1 Roll-off by Office by Year (Contested Elections Only) Office Year Min Q1 Med Mean Q3 Max Sd 1990 -0.99 3.10 9.07 9.97 15.61 30.58 7.53 1994 -3.27 2.70 7.70 9.09 14.07 38.53 7.20 1998 -1.17 1.82 4.48 6.85 11.20 37.33 5.87 All Offices 2002 -0.66 1.39 2.19 2.50 3.26 12.58 1.55 2006 0.40 1.67 2.49 2.83 3.73 11.02 1.61 2010 -1.34 0.59 1.15 1.43 1.99 7.64 1.23 1990 -0.18 2.54 9.15 10.25 16.30 30.58 8.14 1994 -0.20 1.87 6.40 7.25 11.54 26.65 5.88 1998 -0.25 1.03 2.89 4.44 7.13 37.33 4.63 Lt. Governor 2002 -0.66 0.84 1.24 1.45 1.99 4.68 0.89 2006 0.41 1.06 1.63 1.92 2.54 6.75 1.13 2010 -1.34 0.12 0.53 0.85 1.16 5.92 1.11 1990 ------1994 -3.27 1.60 7.04 6.99 10.83 26.06 5.83 Secretary of 1998 -1.17 1.44 3.14 6.68 11.20 26.52 6.10 State 2002 -0.42 1.03 1.44 1.62 2.09 4.39 0.82 2006 1.61 2.95 4.03 4.24 5.23 11.02 1.73 2010 -0.51 0.71 1.30 1.59 2.09 7.24 1.23 1990 ------1994 0.89 3.02 12.16 12.02 19.05 38.53 9.08 Attorney 1998 -0.17 1.86 4.73 6.70 11.00 24.54 5.51 General 2002 1.60 2.74 3.65 4.12 4.88 12.58 1.87 2006 1.26 2.18 3.09 3.33 4.22 9.62 1.45 2010 -0.51 0.72 1.36 1.60 2.18 7.57 1.36 1990 ------1994 1.12 3.56 10.72 11.05 16.43 35.34 7.87 School 1998 -0.05 2.19 5.29 7.34 11.70 22.26 5.89 Superintendent 2002 -0.36 1.09 1.45 1.58 2.02 3.73 0.71 2006 0.54 1.01 1.35 1.62 2.02 4.77 0.84 2010 -0.85 0.53 1.04 1.22 1.77 5.27 1.00 1990 -0.99 2.66 6.86 7.65 11.57 25.13 5.89 1994 -2.45 2.17 7.00 7.53 11.83 25.09 5.78 Insurance 1998 0.57 2.01 5.24 7.50 12.80 21.77 6.13 Commissioner 2002 0.87 1.77 2.69 2.87 3.70 7.25 1.29 2006 1.29 1.95 2.58 3.00 3.73 10.69 1.40 2010 -0.17 0.73 1.41 1.67 2.17 6.78 1.26 1990 0.11 3.87 12.23 12.01 17.46 30.15 7.77 1994 ------Agriculture 1998 -0.53 1.59 3.88 5.89 9.68 20.05 5.05 Commissioner 2002 0.54 1.59 2.02 2.28 2.87 5.52 0.99 2006 0.40 1.69 1.69 1.94 2.44 6.90 1.05 2010 -0.71 0.56 0.89 1.13 1.56 5.72 0.96 1990 ------1994 1.55 3.39 9.35 9.68 14.29 28.00 6.60 Labor 1998 1.12 3.48 6.53 9.37 14.70 29.95 6.49 Commissioner 2002 1.18 2.54 3.31 3.60 4.28 8.16 1.40 2006 1.74 2.83 3.48 3.78 4.37 10.31 1.39 2010 -0.51 1.12 1.71 1.98 2.61 7.64 1.27

Multilevel Models of Roll-off

While illustrative, the univariate statistics presented above do not provide conclusive evidence that roll-off has been affected by Georgia’s adoption of touch screen machines. The changes in seen in Table 1 roll-off may be a result of factors other than the apparatus in which voters use to cast their ballot. To examine this possibility, I turn to multivariate modeling. In particular, I use hierarchical, linear modeling because the data is clustered by year and by office. Due to variations in data availability, I present three specifications to test my hypothesis that the advent of touch screen voting machines in Georgia has decreased roll-off.

The first model includes all of the explanatory variables. Because data for the black share of the county electorate and campaign expenditure variables are unavailable for 1990 and 1994, this model only analyzes roll-off for the seven offices from 1998 to 2010. The model estimates appear in the first column of Table 2. These results provide some evidence that strongly supports the hypothesis that roll-off has decreased due to the adoption of touch screen voting machines. However, some of the results directly contradict the hypothesis. The coefficients for all four of the indicator variables for previous method reach high levels of statistical significance. However, only two have the expected sign.

As expected, lever machines tended to yield higher roll-off compared to touch screen voting machines. All else equal, roll-off was about 7.336 percentage points higher on average in counties that used lever machines than in counties that used touch screen voting machines.

Paper ballots were likewise associated with higher levels of roll-off than touch screen machines.

Counties using paper ballots experienced a level of roll-off that was around 6.303 percentage

points higher on average than that of counties that used touch screen machines. The coefficient for both of these methods meets a high level of statistical significance.

However, two of the four previous voting methods directly contradict the hypothesis.

The negative coefficients indicate that roll-off is actually lower when counties used optical scan ballots or punch card ballots than when touch screen voting machines were used. When optical scan ballots were used instead of touch screen machines, roll-off was about 0.448 percentage points lower on average. Counties that used punch card ballots likewise experienced lower roll- off compared to counties using touch screen machines. When punch cards were used, roll-off was more than a percentage point lower than when touch screen machines were used.

Further illustration of the effects of voting method on roll-off can be found in Figure 1 below. This shows the predicted roll-off for each of the five voting methods in 1998, holding all continuous predictors at their means and using the modal category for the dichotomous predictors. 7 For touch screen machines, a county with 73.1% of residents age twenty-five and over having at least a high school diploma and an electorate that is 21.88% black would be expected to have a roll-off rate of 2.64 percentage points for an all-white, all-male contest for the office listed sixth on the ballot in 1998 that features an incumbent and a third party candidate and where the candidates spent a combined $1.965 million. 8 Counties using lever machines would have a much higher predicted roll-off rate of about 9.97 percentage points.

Similarly, counties using paper ballots would have a much higher roll-off rate: about 8.94 percentage points. However, the predicted rates for counties using optical scan ballots and

7 The mean ballot position is 5.75. Because ballot position can only be a natural number, I round this up to 6.

punch cards would be lower than that for touch screen machines: 2.19 percentage points for optical scan machines and 1.62 points for punch cards. This of course is merely hypothetical as no counties used touch screen machines in 1998. However, it corroborates the findings of the model in Table 2: touch screen machines have a lower predicted roll-off than or lever machines or paper ballots but a slightly higher value than for optical scan machines or punch cards.

While presenting strong evidence indicating that touch screen machines have served to reduce roll-off in Georgia, the first model is limited to just three elections with only one election occurring before Georgia’s adoption of the touch screen machines. Would the results differ by including more pre-adoption cycles? To examine this possibility, I expand the time frame to include the 1990 and 1994 election cycles. Campaign expenditures data are unavailable for these cycles, so this variable has been omitted. The data for the black share of the county

electorate variable are also unavailable for these years. Instead, I include a variable representing the black share of the total county population. 9 These data come from the U.S.

Census Bureau and are interpolated for the cycles that did not coincide with a decennial census.

The results for this model are reported in the second column of Table 2.

These results mostly corroborate those of the previous model. The substantive findings from the first model remain unchanged. Lever machines and paper ballots again bring about much higher roll-off on average than touch screen machines. Both variables again achieve very high levels of statistical significance. Roll-off is about 7.767 percentage points higher on average for lever machines compared to touch screen machines. Roll-off is

More than seven percentage points higher for paper ballots than it is for touch screen machines. As with the first model, however, optical scan ballots and punch cards yield the opposite of what is expected, indicating that the switch from these methods to touch screen machines actually increased roll-off slightly. In both cases, roll-off was lower by about 0.46 percentage points. The coefficient for the punch card indicator is not statistically discernible from zero, however.

The final model I present examines the possibility that any difference in the findings from the first two models comes as a result of different specifications (i.e., the presence of the campaign expenditures variable and using black share of the total population in the second model) and different time frames. This third model examines the effects of the predictors from the second model while using the time frame of the first model. These results appear in the third column of Table 2. Once again, the substantive results remain mostly unchanged.

9 This alternative measure correlates highly with the black share of the county electorate variable (r = 0.933).

The coefficients for both of the indicators for lever machines and paper ballots have the expected sign and reach high levels of statistical significance. For both of these methods, roll- off was much higher compared to roll-off for touch screen machines (about 7.558 percentage points higher on average for lever machines and about 6.52 points higher for paper ballots).

Optical scan ballots and punch cards again tended to yield lower roll-off on average than touch screen machines. Roll-off was about 0.227 percentage points lower on average for optical scan ballots than it was for touch screen machines. For counties using punch cards, roll-off was approximately 0.787 percentage points lower compared to those using touch screen machines.

TABLE 2 Hierarchical Linear Models of Roll-off 1998-2010 1990-2010 1998-2010 Intercept 8.893 *** 8.790 *** 7.819 *** (0.741) (0.737) 0.747 Lever 7.336 *** 7.767 *** 7.558 *** (0.137) (0.173) 0.130 Optical Scan -0.448 ** -0.463 ** -0.227 (0.141) (0.179) 0.134 Punch Card -1.023 *** -0.461 -0.787 ** (0.244) (0.333) 0.241 Paper 6.303 *** 7.428 *** 6.520 *** (0.678) (0.951) 0.678 Incumbent -0.497 *** -0.475 *** -0.539 *** (0.063) (0.076) 0.063 Ballot Position 0.066 *** 0.096 *** 0.117 *** (0.015) (0.016) 0.012 3rd Party Candidate -1.574 *** -1.785 *** -1.623 *** (0.071) (0.080) 0.071 Margin of Victory -0.027 *** 0.016 *** -0.022 *** (0.003) (0.003) 0.003 Black Candidate 0.489 *** 0.438 *** 0.557 *** (0.061) (0.076) 0.060 Female Candidate 0.404 *** 0.467 *** 0.579 *** (0.062) (0.070) 0.051 Black Share of County Electorate 0.000 ------(0.004) ------Black Share of County Population ----- 0.001 0.005 ----- (0.004) 0.004 Education -0.056 *** -0.064 *** -0.053 *** (0.010) (0.010) 0.010 Expenditures -0.008 *** ------(0.002) ------Time -0.253 *** -0.296 *** -0.209 *** (0.036) (0.039) 0.034 County-Level Variance 3.735 4.234 3.735 Time Trend Variance 0.098 0.130 0.098 Number of Cases 4452 5883 4452 AIC 17177 27259 17188 Log-Likelihood -8569 -13611 -8576 Note: Standard errors in parentheses *** p < 0.001 ** p <0.01 27

CHAPTER 5

DISCUSSION

While there is strong evidence that voter roll-off at the county level has decreased dramatically since Georgia adopted touch screen voting machines in 2002, this decrease has not occurred evenly. In this paper, I presented three different model specifications covering two time periods. In each case, the results provide evidence that touch screen machines reduce roll-off significantly over some alternative voting methods but not others. Roll-off is lower for touch screen machines compared to lever machines and paper ballots, as was expected, but is actually higher compared to optical scan ballots and punch card ballots. These findings generally hold up even after controlling for factors that have been found to influence roll-off such as partisan contests, uncontested elections, campaign expenditures, the presence of a third party or independent candidate on the ballot, the racial composition of the county electorate, relative ballot position, incumbency, and open seats.

Beyond providing only partial confirmation for the hypothesis that touch screen machines reduce roll-off, a few other results are surprising. The results of all three models indicate that lever machines produce higher roll-off compared not only to touch screen machines but also compared to optical scan ballots and punch card ballots. This is quite surprising as lever machines, like touch screen machines, did not allow for over-voting, a feature not present for punch card ballots and many optical scan machines. These results may be explained in part by the operationalization of the dependent variable. I calculate roll-off

using the contest receiving the most votes statewide as the baseline. If the number of votes cast for the baseline race is lowered due to the use of punch card ballots or optical scan machines, as Bullock and Hood (2002) find, then roll-off could be lower in counties using these voting methods may experience lower rates of roll-off as well due to the fact that the threshold is lowered. In these cases, ballot type affects roll-off more indirectly not by affecting the number of votes cast for the baseline contest.

Future research should examine this possibility, seeing to determine why the effects of touch screen machines are inconsistent. Further research should also examine the underlying reasons for these effects. As stated previously, the touch screen machines have several features that could conceivably serve to reduce roll-off in that they eliminate over-votes while also notifying the voter of undervotes. For example, to what extent is the reduction a result of eliminating the potential for over-voting? Does the effect come more from reducing undervoting due to “honest mistakes” versus decreasing intentional undervotes? Future research should examine what importance, if any, these features have had in diminishing roll- off. The fact that lever machines yielded such high roll-off compared to touch screen machines even though both precluded over-voting could indicate the effects of the touch screen machines do not come so much from reducing over-voting. This may also indicate that roll-off in general comes less from over-voting and more from undervoting. One possible way to answer these questions is through the use of experiments or natural experiments to allow not only for more control but also more precise observation as we cannot directly observe over- voting versus undervoting or intentional undervoting versus unintentional undervoting.

These findings open up several other possible avenues for further research. This includes examining the effects on roll-off for other items on the ballot, such as nonpartisan offices. This study was limited to contested elections for seven high-level partisan offices. The effects of the voting machines may be greater for nonpartisan offices than partisan offices due simply to the fact that nonpartisan contests typically have higher roll-off than partisan races.

Alternatively, lacking the information contained in the partisan labels that, by definition, are included in partisan elections, voters may be less willing to alter their ballot to fill in a vote for a nonpartisan offices. Thus, the effects of the new machines on roll-off for nonpartisan offices may not be as great as the effect for partisan offices.

Finally, and perhaps most importantly, if there is conclusive evidence of an effect from the touch screen machines, then future research should attempt to determine the impact of such a reduction in ballot roll-off. For example, the impetus for Georgia’s adoption of touch screen voting machines was the situation in Florida during the 2000 election, a debacle that exposed flaws in the state’s election system and undermined citizen confidence in the process.

So, do voters feel more confident that their vote is being cast and counted accurately?

Additionally, there is the question of who benefits from a reduction in roll-off. Do voters who would have otherwise rolled-off tend to favor incumbents or challengers? Does a decrease in roll-off favor one party over the other?

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