Andrew Dowdle

The New Hampshire Effect in Presidential Nominations

In order to demonstrate challenges to conventional wisdom (Aldrich 1980a, b; Bartels 1985 1988; Orren and Polsby 1987), this article develops several forecasting models of the presidential primary vote to compare to a baseline model of the aggregate primary vote (APV) that uses pre-primary and New Hampshire primary data. The models indicate that candidates’ Gallup poll position and cash reserves are significant positive predictors of a candidates’ primary vote share, though there are differences between forecasting models of the primary vote in Democratic and Republican nomination campaigns. Parallel models incorporating results of the New Hampshire primary improve the predictive power of the baseline model, indicating that the bellwether primary has a “correcting” effect on the relative standings of some candidates seeking a presidential nomination. This effect is substantially greater for Democrats than for Republicans.

How Important Are Iowa and New Hampshire to Winning Post-Reform Presidential Nominations?

While conventional wisdom holds that the first delegate selection events in Iowa and New Hampshire are important influences on the outcome of the presidential selection process, scholars increasingly question whether victories in these ‘bellwether’ contests are sufficient to propel darkhorse candidates to the nomination. This study utilizes four OLS regression models to predict nomination outcomes from 1980 to 1996 where the incumbent president did not sit for reelection. Earlier research demonstrated the possibility of forecasting presidential nominations by examining the results of (1) public opinion polls; FEC records regarding (2) money raised; and (3) cash reserves; and (4) whether candidates were southern Democrats (Mayer 1996a; Adkins and Dowdle 2000). Utilizing measures representing the outcome of the Iowa caucuses and the New Hampshire primary, this study contrasts the effect of momentum from these early contests on final primary vote totals. Evidence suggests that New Hampshire plays a role in determining the ordinal ranking of candidate finishes, but not necessarily the winner of the party nomination.

The Viability Primary Modeling Candidate Support before the Primaries

Public support before the primaries is the strongest predictor of presidential candidate attrition and of the aggregate primary vote. Yet little is known about the factors that drive candidate preferences before the primaries. This article examines pre-primary candidate support in national Gallup polls for open presidential nomination races from 1976 to 2004. The study finds that candidate background characteristics have marginal effects on mass partisan support during the earliest phase of the nomination campaign and that campaign-related factors significantly affect pre-primary candidate support once the campaign begins. Prior levels of support, network news coverage, and party elite endorsements are significant factors in explaining variation in mass partisan support for candidates throughout the nomination campaign. The decisions of well-known, party “heavyweights” to enter or not enter the race affect the choices available to partisan voters and the overall competitiveness of the nomination campaign.

Civil Wars, International Conflicts and Other Determinants of Paramilitary Strength in Sub-Saharan Africa

Previous research on African military spending suggests the existence of civil strife as the best predictor of high levels of military spending. However, little is known about why some African nations maintain strong ‘auxiliary’ or paramilitary organizations while others do not. This study finds that the presence of civil or interstate war does not strengthen reserve or irregular forces. Civilian governments promote strong paramilitary organizations to counter any threat the regular military might pose to regime survivability as a form of clientelist politics.

The Political Geography of Campaign Finance: Contributions to 2008 Republican Presidential Candidates

In fundraising, potential candidates who do not collect sizable amounts of “early money” may be effectively eliminated even before the start of the Iowa Caucus. This winnowing raises concern about the impact money has on narrowing the field of candidates from whom voters can choose. To better grasp patterns of successful fundraising, we explore where candidates obtain funds during the preprimary and primary periods. We use individual contributions data from the Federal Election Commission during the preprimary and primary periods of the 2008 Republican presidential nomination contest. Findings suggest that although California, New York, and Texas provide disproportionate amounts of early financing, the ability of presidential aspirants to broaden their support is indicative of campaign success.

The Political Geography of Campaign Contributions

By all accounts, presidential elections are costly undertakings. Will Rogers once stated, “Politics has got so expensive that it takes lots of money to even get beat with nowadays” (Rogers 1931). While Rogers comically exaggerated the cost of elections nearly a century ago, today campaigns and elections take substantial amounts of money, a reality that is often underestimated in American politics. One estimate of the combined cost of the 2012 presidential nomination and general election was

Forecasting Presidential Nominations in 2016: #WePredictedClintonANDTrump

2.6 billion (Choma 2013). This raises the obvious question: Where does this money come from? Surprisingly, even though spending by wealthy individuals and outside groups has risen dramatically in recent years, the majority of the money raised still comes from individual donors (Christenson and Smidt 2012).

Party cohesion in presidential races Applying social network theory to the preprimary multiple donor networks of 2004 and 2008

A number of scholars successfully modeled and predicted presidential nomination outcomes from 1996–2008. However, dramatic changes occurred in subsequent years that would seem to make replicating these results challenging at best. Building on those earlier studies, we utilize a series of OLS models that included measures of preprimary resources and early campaign successes or failures to forecast that Hillary Clinton and Donald Trump would win the Democratic and Republican presidential nominations in 2016. This outcome suggests that some fundamental factors governing nomination outcomes have not changed despite the conventional wisdom. Numerous models forecast general election outcomes by employing a variety of economic and political measures to make accurate predictions about whether the party in control of the White House will retain or lose the presidency (for an overview see Campbell 2012 ). In many ways forecasting presidential nominations presents a more challenging task. Important individual-level cues such as partisanship or systemic-level factors such as economic growth or the popularity of the incumbent are helpful in understanding why a voter might choose Bill Clinton over George W. Bush in 1992. Unfortunately, they are not useful in explaining why the same individual picked Paul Tsongas over Bill Clinton or Tom Harkin nine months earlier in the New Hampshire primary (Steger, Dowdle, and Adkins 2012 ). While the McGovern-Fraser reform movement of the early 1970s created a new system of presidential nominations designed to increase the role of voters in picking party nominees, a period of stability in the nomination process of both parties’ emerged by the end of the 1980s (Barilleaux and Adkins 1993 ). As these contests became more routinized, a number of scholars attempted to forecast the results of the presidential primary season by utilizing factors such as polling, fi nancial resources, and elite support (Adkins and Dowdle 2000 , 2001a , 2001b , 2005 ; Mayer 1996 ; Steger 2000 ; see Steger 2008 for a comparison of the forecasts generated by the diff erent models). Momentum from performing well in early primaries was also found to play an important role in determining nomination outcomes (Bartels 1988 ), though there is some controversy about the precise eff ect of particular contests (Adkins and Dowdle 2001a ; Christenson and Smidt 2012 ; Hull 2008 ). At first glance, current events appear to have altered this equilibrium in at least two important ways. First, super PACs, a relatively new type of political committee that arose from the Speechnow v FEC and Citizens United v FEC court decisions in 2010, should alter the impact of traditional sources of campaign fi nance (Dwyre and Braz 2015 ). Second, the Republican elite has arguably fragmented in recent years, which should aff ect elite support on the process (Steger 2015 ). Since traditional forecasting models encountered diffi culty predicting the 2004 Democratic nomination correctly (Steger 2008 ), these new factors should make predicting recent nomination outcomes even more challenging. MODEL SPECIFICATION To forecast presidential nomination outcomes this research employs two OLS regression models that use the “open” presidential nomination contests from 1980–2012 and then applies the estimates to the 2016 Democratic and Republican presidential nomination contests to create forecasts for each. 1 The models examine Democratic and Republican contests from 1980 to 2012 inclusive, with the exception of the 1980, 1996 and 2012 Democratic Andrew J. Dowdle is a professor in the department of political science at the University of Arkansas. He can be reached at adowdle@uark.edu . Randall E. Adkins is a professor in the department of political science and associate dean of the College of Arts & Sciences at the University of Nebraska at Omaha. He can be reached at radkins@unomaha.edu . Karen Sebold is a clinical assistant professor in the department of political science at the University of Arkansas. She can be reached at ksebold@uark.edu . Jarred Cuellar is a graduate student at the University of Arkansas. He can be reached at jcuellar@uark.edu .

Party cohesion in presidential races: applying social network theory to the 2011 preprimary

Scholars have long been examining the presidential nomination process in the United States. In addition to studies considering the selection mechanism itself, there has been a movement towards analysing the contest even before voting begins. Campaign finance allows for a reliable and valid means to examine the year prior to the nomination with data that are not just vast in quantity but also consistent across time. Donors who gave to multiple campaigns represent a particularly important subset of elite participants in elections whose behaviour shed light on phenomena of parties functioning as a network. We find only rare instances of multiple donors giving across party and that Democratic contributors function as a far more cohesive unit. Also, without any supervising entity, the candidate that amasses the most shared donors goes on to win the nomination in the 2004 and 2008 presidential elections.

Conclusion and Discussion

In this paper we analyze individual contributions data from the 2012 Republican Party preprimary that was collected by the Federal Elections Commission (FEC). We use the basic principles of Social Network Analysis of multiple donors to discern patterns concerning presidential candidates and the Republican Party as a whole.