Forecasting the 2008 U.S. House, Senate and Presidential Elections at the District and State Level

2008 ◽  
Vol 41 (04) ◽  
pp. 723-728 ◽  
Author(s):  
Carl Klarner
Keyword(s):  
House Of Representatives ◽  
Presidential Elections ◽  
State Level ◽  
Barack Obama ◽  
The State ◽  
Popular Vote ◽  
White House ◽  
Forecasting Models ◽  
The U.S

This paper applies the forecasting models of Klarner and Buchanan (2006a) for the U.S. Senate and Klarner and Buchanan (2006b) for the U.S. House of Representatives to the upcoming 2008 elections. Forecasts are also conducted for the 2008 presidential race at the state level. The forecasts presented in this article, made July 28, 2008 (99 days before the election), predicted an 11-seat gain for the Democrats in the House of Representatives, a three-seat gain for the Democrats in the Senate, and that Barack Obama would obtain 53.0% of the popular vote and 346 electoral votes. Furthermore, Obama was forecast to have an 83.6% chance of winning the White House and an 85.9% chance of winning the popular vote.

Presidential Coattails and Midterm Losses in State Legislative Elections

1986 ◽  
Vol 80 (1) ◽  
pp. 45-63 ◽  
Author(s):  
James E. Campbell
Keyword(s):  
House Of Representatives ◽  
Presidential Elections ◽  
State Legislatures ◽  
The State ◽  
Legislative Elections ◽  
Aggregate State ◽  
Midterm Elections ◽  
State Legislative Elections ◽  
State Legislative ◽  
The U.S

The president's party consistently loses partisan control of state legislatures in midterm elections, a pattern similar to the loss of seats in the U.S. House of Representatives in midterms. This study examines presidential coattails as a possible explanation of these losses. Aggregate state legislative election outcomes between 1944 and 1984 in 41 states are examined. The analysis indicates that the president's party gains seats in presidential elections in proportion to the presidential vote in a state, and subsequently loses seats in midterm elections also in proportion to the prior presidential vote in the state. The presidential coattail and the midterm repercussion effects are evident even when gubernatorial coattail effects are introduced, but are fairly modest in states lacking competitive parties.

Forecasting the 2012 Presidential Election with State-Level Economic Indicators

2012 ◽  
Vol 45 (04) ◽  
pp. 669-674 ◽  
Author(s):  
Michael J. Berry ◽  
Kenneth N. Bickers
Keyword(s):  
Presidential Election ◽  
Presidential Elections ◽  
State Level ◽  
Forecast Model ◽  
Vice President ◽  
Electoral College ◽  
Popular Vote ◽  
Major Party ◽  
White House ◽  
Forecast Models

Nearly all forecast models of US presidential elections provide estimates of the national two-party vote (Campbell 2008). Each of the nine forecasts published in the 2008 forecasting issue ofPS: Political Science and Politicsmade national popular vote total predictions for the major party candidates, while only one provided an expected result in the Electoral College (Klarner 2008). These national vote models are assumed to be reliable forecasts of who is likely to win the general election. In most cases, this assumption is reasonable. It becomes problematic, however, at precisely the point that forecasts are most interesting: when elections are close. In tight elections, national forecasts can and have produced a “winner” different from the actual winner. Consider the forecasts and ultimate outcome of the 2000 election. Each of the 2000 presidential election forecasts predicted vice president Al Gore to win a majority of the two-party popular vote, which he did, but none correctly predicted governor George W. Bush to assume the presidency (Campbell 2001). Never in US history have White House residents been determined through a national popular vote. Presidential elections are decided through contests in the states and the District of Columbia. The forecast model we developed explicitly models the presidential contest based on factors inherent to these 51 jurisdictions. This modeling approach allows us to make a projection of the Electoral College result, which popular vote estimates cannot.

scholarly journals A Panel Evaluation of the Changes in the General Public’s Social-Media-Following of United States’ Public Health Departments during COVID-19 Pandemic

2021 ◽  
Vol 12 ◽  
pp. 215013272199545
Author(s):  
Areej Khokhar ◽  
Aaron Spaulding ◽  
Zuhair Niazi ◽  
Sikander Ailawadhi ◽  
Rami Manochakian ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
State Level ◽  
The State ◽  
Public Health Department ◽  
Health Departments ◽  
The Public ◽  
Public Health Departments ◽  
The Social ◽  
The U.S

Importance: Social media is widely used by various segments of society. Its role as a tool of communication by the Public Health Departments in the U.S. remains unknown. Objective: To determine the impact of the COVID-19 pandemic on social media following of the Public Health Departments of the 50 States of the U.S. Design, Setting, and Participants: Data were collected by visiting the Public Health Department web page for each social media platform. State-level demographics were collected from the U.S. Census Bureau. The Center for Disease Control and Prevention was utilized to collect information regarding the Governance of each State’s Public Health Department. Health rankings were collected from “America’s Health Rankings” 2019 Annual report from the United Health Foundation. The U.S. News and World Report Education Rankings were utilized to provide information regarding the public education of each State. Exposure: Data were pulled on 3 separate dates: first on March 5th (baseline and pre-national emergency declaration (NED) for COVID-19), March 18th (week following NED), and March 25th (2 weeks after NED). In addition, a variable identifying the total change across platforms was also created. All data were collected at the State level. Main Outcome: Overall, the social media following of the state Public Health Departments was very low. There was a significant increase in the public interest in following the Public Health Departments during the early phase of the COVID-19 pandemic. Results: With the declaration of National Emergency, there was a 150% increase in overall public following of the State Public Health Departments in the U.S. The increase was most noted in the Midwest and South regions of the U.S. The overall following in the pandemic “hotspots,” such as New York, California, and Florida, was significantly lower. Interesting correlations were noted between various demographic variables, health, and education ranking of the States and the social media following of their Health Departments. Conclusion and Relevance: Social media following of Public Health Departments across all States of the U.S. was very low. Though, the social media following significantly increased during the early course of the COVID-19 pandemic, but it still remains low. Significant opportunity exists for Public Health Departments to improve social media use to engage the public better.

Legislative Department

2020 ◽  
pp. 73-104
Author(s):  
Danny M. Adkison ◽  
Lisa McNair Palmer
Keyword(s):  
Supreme Court ◽  
House Of Representatives ◽  
The State ◽  
Legislative Authority ◽  
The People ◽  
Definition Of ◽  
The Right ◽  
Supreme Court Rulings ◽  
The U.S

This chapter assesses Article V of the Oklahoma constitution, which concerns the legislative department. Section 1 states that “the Legislative authority of the State shall be vested in a Legislature, consisting of a Senate and a House of Representatives.” However, “the people reserve to themselves the power to propose laws and amendments to the Constitution and to enact or reject the same at the polls independent of the Legislature, and also reserve power at their own option to approve or reject at the polls any act of the Legislature.” Section 2 provides for the designation and definition of reserved powers. Initiative means the power of the people to propose bills, and to enact or reject them at the polls. Referendum is the right of the people to have bills passed by the legislature submitted to the voters for their approval. Meanwhile, in May 1964, the Oklahoma constitution was amended to conform to the U.S. Supreme Court rulings. The amendment passed and Sections 9 through 16 were replaced with Sections 9A through 11E. The chapter then details the provisions for the Senate and the House of Representatives.

The 2016 Election: Like 1888 but not 1876 or 2000

2018 ◽  
Vol 52 (1) ◽  
pp. 20-24 ◽  
Author(s):  
Fabrice Barthélémy ◽  
Mathieu Martin ◽  
Ashley Piggins
Keyword(s):  
House Of Representatives ◽  
Presidential Election ◽  
Presidential Elections ◽  
Anomalous Behavior ◽  
Electoral College ◽  
Popular Vote ◽  
The Us ◽  
2016 Election ◽  
Us Presidential Election ◽  
House Size

ABSTRACTDonald J. Trump won the 2016 US presidential election with fewer popular votes than Hillary R. Clinton. This is the fourth time this has happened, the others being 1876, 1888, and 2000. In earlier work, we analyzed these elections (and others) and showed how the electoral winner can often depend on the size of the US House of Representatives. This work was inspired by Neubauer and Zeitlin (2003, 721–5) in their paper, “Outcomes of Presidential Elections and the House Size.” A sufficiently larger House would have given electoral victories to the popular vote winner in both 1876 and 2000. An exception is the election of 1888. We show that Trump’s victory in 2016 is like Harrison’s in 1888 and unlike Hayes’s in 1876 and Bush’s in 2000. This article updates our previous work to include the 2016 election. It also draws attention to some of the anomalous behavior that can arise under the Electoral College.

WHY THE STATE-BY-STATE POLITICAL ECONOMY MODEL DID IT RIGHT

2013 ◽  
Vol 46 (01) ◽  
pp. 45-46
Author(s):  
Bruno Jerôme ◽  
Véronique Jerôme-Speziari
Keyword(s):  
Political Economy ◽  
Presidential Election ◽  
Barack Obama ◽  
The State ◽  
Popular Vote ◽  
Final State ◽  
Economy Model ◽  
Error Margin ◽  
Us Presidential Election

One hundred and forty two days before the 2012 US presidential election our final State-by-State Political-Economy Model gave an advantage to Barack Obama with 51.6% of the popular vote (error margin ± 4.47) and 324 electoral votes (Jerôme and Jerôme-Speziari 2012). On November 6, 2012, with 51.6% of the vote and 332 electoral votes, the Democratic incumbent wins a second term. Regarding certainty of an Obama plurality, the model gave a probability of victory by 64%. In 2012, it seems that this was enough to ensure a good predictability.

Using Online Search Traffic to Predict US Presidential Elections

2013 ◽  
Vol 46 (02) ◽  
pp. 271-279 ◽  
Author(s):  
Laura Granka
Keyword(s):  
United States ◽  
Economic Performance ◽  
State Level ◽  
The United States ◽  
Popular Vote ◽  
Vote Outcome ◽  
Approval Ratings ◽  
Forecasting Models ◽  
National Models ◽  
Election Results

Predictions of the United States presidential election vote outcome have been growing in scope and popularity in the academic realm. Traditional election forecasting models predict the United States presidential popular vote outcome on a national level based primarily on economic indicators (e.g., real income growth, unemployment), public approval ratings, and incumbency advantage. Many of these forecasting models are rooted in retrospective voting theory (Downs 1957; Fiorina 1981), essentially rewarding the party in office if times are good, punishing it if times are bad. These models have successfully predicted election results by modeling economic performance and incumbent approval ratings (Campbell 2012; Fair 1992; Fair 1996; Klarner 2012). For example, Abramowitz's (2004; 2005) “time for a change model” predicts election results using economic performance during the first half of the election year, the number of years the incumbent party has been in office, and presidential approval. For a full review of 13 presidential forecasts for the US 2012 election, seePS: Political Science and PoliticsOctober 2012 (45 (4): 610–75). Although national models are the most common, researchers have also started to use state-level predictions for presidential and congressional outcomes, with mostly positive success (Berry and Bickers 2012; Jerome and Jerome-Speziari 2012; Klarner 2012; Silver 2012). These models use similar predictors, such as incumbency, economic conditions, and home-state advantage, and predict the per-candidate percentage of popular vote. Unfortunately, with state-level models, many of the economic variables used in predicting national models are unavailable beyond 10–15 election cycles (compounded also by 1959 additions of Alaska and Hawaii), so state-level models naturally have a shorter period of analysis than do national models.

scholarly journals Florida in the Tipping Point: The Sunshine State in the U.S. Presidential Elections

Norteamérica ◽  
2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Ernesto Domínguez López
Keyword(s):  
Political System ◽  
Presidential Elections ◽  
Transition Period ◽  
State Level ◽  
Transition Process ◽  
The Political ◽  
Electoral Impact ◽  
Political Realignment ◽  
Definition Of ◽  
The U.S

 This article examines presidential election processes in the state of Florida. A set of criteria is proposed for the definition of its swing state condition whereby it can be observed that Florida is in compliance since the early 1990s. The electoral impact of Florida is considered in light of the growth of its electoral college and its transformation into a swing state is interpreted as a state-level expression of the political realignment that followed the transition period of the 1970s and the 1980s. An ongoing trend of changes in the composition of Hispanic communities is also observed, as well as variations in their electoral behaviors. Within the frame of a national transition process, the registered trends and data indicate the existence of suitable conditions for a new political realignment in Florida as part of a nationwide realignment. The emerging configuration of the political system in this state is undetermined. 

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