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1 – 10 of over 1000John Struthers and Alistair Young
In seeking to extend rational choice theory from“market” to “political” behaviour, economistshave encountered a paradox: namely, that the act of voting itselfappears to be…
Abstract
In seeking to extend rational choice theory from “market” to “political” behaviour, economists have encountered a paradox: namely, that the act of voting itself appears to be inconsistent with the assumption of rationality. This is true not only when self‐interest is assumed, but also when altruistic behaviour (at least in its non‐Kantian form) is allowed for. This article surveys the theoretical and empirical literature on the determinants of the decision to participate in voting, and concludes that this decision is responsive to changes in the expected benefits and costs of voting; even though the expected costs of voting must normally outweigh the expected benefits. Interpretations of this behaviour include the possibility that voters act rationally, but are misinformed about the likely effectiveness of their votes; alternatively, the electorate may include more Kantians than economists have generally been willing to admit.
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Points out that there were 50 nationally published political pollsduring the British 1992 election campaign period – 39 of which,converted into seats, would have given a hung…
Abstract
Points out that there were 50 nationally published political polls during the British 1992 election campaign period – 39 of which, converted into seats, would have given a hung Parliament, eight of which suggested an outright win for Labour, and three of which gave the Conservatives a victory. Addresses why so many opinion polls apparently got it wrong, and takes the reader through some of the reasons for the discrepancy, such as the nature of opinions, sampling considerations, non‐response, and the effect of opinion poll results themselves. Tries to inform the uninformed reader in order that the results of future opinion polls might be evaluated more clearly.
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The purpose of this paper is the better understanding of the increasing relation between big data 2.0 and neuromarketing, particularly to influence election outcomes, along with a…
Abstract
Purpose
The purpose of this paper is the better understanding of the increasing relation between big data 2.0 and neuromarketing, particularly to influence election outcomes, along with a special aim to discuss some raised doubts about Trump’s presidential campaign 2016 and its ability to hijack American political consumers’ minds, and to direct their votes.
Design/methodology/approach
This paper combines deductive/inductive methodology to define the term of political neuromarketing 2.0 through a brief literature review of related concepts of big data 2.0, virtual identity and neuromarketing. It then applies a single qualitative case study by presenting the history and causes of online voter microtargeting in the USA, and analyzing the political neuromarketing 2.0 mechanisms adopted by Trump’s political campaign team in the 2016 presidential election.
Findings
Based on Trump’s political marketing mechanisms analysis, the paper believes that big data 2.0 and neuromarketing techniques played an unusual role in reading political consumers’ minds and helping the controversial candidate to meet one of the most unexpected victories in the presidential elections. Nevertheless, this paper argues that the ethics of using political neuromarketing 2.0 to sell candidates and its negative impacts on the quality of democracy are and will continue to be a subject of ongoing debates.
Originality/value
The marriage of big data 2.0 and political neuromarketing is a new interdisciplinary field of inquiry. This paper provides a useful introduction and further explanations for why and how Trump’s campaign defied initial loss predictions and attained victory during this election.
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Joseph Ben‐Ur and Bruce I. Newman
The purpose of this paper is to provide an evaluation of a newspaper insert survey and web‐based voter surveys associated with the same newspaper, conducted before and after the…
Abstract
Purpose
The purpose of this paper is to provide an evaluation of a newspaper insert survey and web‐based voter surveys associated with the same newspaper, conducted before and after the 2004 US presidential election.
Design/methodology/approach
The study compares response rates, demographics, and political profiles of voters responding to these two different channels of communication and evaluates the success of each in predicting the election outcome.
Findings
The study results show some significant differences between the two methods of voter data collection; nevertheless, each is useful in a comprehensive system that attempts to follow voter attitudes and intentions before the election and predict election outcome.
Origiality/value
The study relies on the use of an innovative marketing poll that goes beyond simple prediction of a voter's behavior and offers an explanatory component useful in the development of marketing strategies during a campaign.
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Kamal Upadhyaya, Raja Nag and Demissew Ejara
The purpose of this paper is to study the impact of the 2016 presidential election polls on the stock market.
Abstract
Purpose
The purpose of this paper is to study the impact of the 2016 presidential election polls on the stock market.
Design/methodology/approach
The empirical model includes daily stock returns as the dependent variable and past asset prices, 10-year treasury rates, opinion polls and VIX (market uncertainty) as explanatory variables with a one-year lag. The model was estimated using two sets of daily polling data: from July 1, 2015, to November 8, 2016, and from June 1, 2016, to November 8, 2016. Additional descriptive statistics, such as means and standard deviations, were also calculated.
Findings
The estimated results did not reveal any statistically significant effects of opinion polls in favor of one candidate over another on stock returns. Simple statistical tests, however, show that the market performed better when Trump held a polling advantage over Clinton.
Originality/value
To the best of the authors’ knowledge, this is the only study that has examined the effects of the 2016 presidential election polls on the US stock market. This study adds value to the understanding of the relationship between election polls and the stock market in the USA.
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In US political reporting, the top story has become the public opinion polls that purport to state the voters’ evaluations of potential candidates, current office holders or the…
Abstract
Purpose
In US political reporting, the top story has become the public opinion polls that purport to state the voters’ evaluations of potential candidates, current office holders or the impact of current events. Many politicians, in turn, often develop their campaign positions in response to the polls. This discussion aims to address how year after year, despite increasing spending by news organizations to predict election results, the polls are repeatedly unable to predict election outcomes. Excuses are made, while the misuse and misunderstanding of marketing research spreads to other types of public organizations.
Design/methodology/approach
Points out the contradictions between public opinion polling predictions of election results and actual events, with explanations of the usually unstated qualitative limitations to survey data.
Findings
Qualitative research bias could have a greater impact on outcomes than statistical margins of error, although it is only the latter that is reported or discussed by the news media.
Practical implications
This abuse and misuse of marketing research lowers the credibility of all marketing research, and the people in marketing research, should speak out. The pollsters want to keep their methods as having a mystical value as they sell their research information to the public and other data users. At worst, this is a misleading selling of marketing insight to the public and research experts should start to speak out, encouraging journalists to report more properly the reality of public opinion polls.
Originality/value
The popular metaphor of public opinion polls has been to call them a “snapshot” of public views. This offers a more realistic metaphor of survey data, an impressionistic painting that is influenced by numerous researchers or respondent biases that cannot be controlled.
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'Brexit' polling.
Details
DOI: 10.1108/OXAN-DB212112
ISSN: 2633-304X
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Francis P. Barclay, C. Pichandy, Anusha Venkat and Sreedevi Sudhakaran
Do public opinion and political sentiments expressed on Twitter during election campaign have a meaning and message? Are they inferential, that is, can they be used to estimate…
Abstract
Purpose
Do public opinion and political sentiments expressed on Twitter during election campaign have a meaning and message? Are they inferential, that is, can they be used to estimate the political mood prevailing among the masses? Can they also be used to reliably predict the election outcome? To answer these in the Indian context, the 2014 general election was chosen.
Methodology/approach
Tweets posted on the leading parties during the voting and crucial campaign periods were mined and manual sentiment analysis was performed on them.
Findings
A strong and positive correlation was observed between the political sentiments expressed on Twitter and election results. Further, the Time Periods during which the tweets were mined were found to have a moderating effect on this relationship.
Practical implications
This study showed that the month preceding the voting period was the best to predict the vote share with Twitter data – with 83.9% accuracy.
Social implications
Twitter has become an important public communication tool in India, and as the study results reinstate, it is an ideal research tool to gauge public opinion.
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R. Karina Gallardo, B. Wade Brorsen and Jayson Lusk
The purpose of this paper is to use prediction markets to forecast an agricultural event: United States Department of Agriculture's number of cattle on feed (COF). Prediction…
Abstract
Purpose
The purpose of this paper is to use prediction markets to forecast an agricultural event: United States Department of Agriculture's number of cattle on feed (COF). Prediction markets are increasingly popular forecast tools due to their flexibility and proven accuracy to forecast a diverse array of events.
Design/methodology/approach
During spring 2008, a market was constructed comprised of student traders in which they bought and sold contracts whose value was contingent on the number of COF to be reported on April 18, 2008. During a nine‐week period, students were presented three types of contracts to forecast the number of COF. To estimate forecasts a uniform price sealed bid auction mechanism was used.
Findings
The results showed that prediction markets forecasted 11.5 million head on feed, which was about 1.6 percent lower than the actual number of COF (11.684 million). The prediction market also fared slightly worse than analysts' predictions, which on average suggested there would be about 11.795 million head (an over‐estimate of about 1 percent).
Originality/value
The contribution of this study was not to provide conclusive evidence on the efficacy of using prediction markets to forecast COF, but rather to present an empirical example that will spark interest among agricultural economists on the promises and pitfalls of a research method that has been relatively underutilized in the agricultural economics literature.
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While it has been claimed in many empirical studies that the political futures market can forecast better than the polls, it is unclear upon which our forecast should be based…
Abstract
While it has been claimed in many empirical studies that the political futures market can forecast better than the polls, it is unclear upon which our forecast should be based. Standard practice seems to suggest the use of the closing price of the market, as a reflection of the continuous process of information revealing and aggregation, but we are unsure that this practice applies to thin markets. In this chapter, we propose a number of reconstructions of the price series and use the closing price based on these reconstructed series as the forecast. We then test these ideas by comparing their forecasting performance with the closing price of the original series. It is found that forecasting accuracy can be gained if we use the closing price based on the smoothing series rather than the original series. However, there is no clear advantage by either using more sophisticated smoothing techniques, such as wavelets, or using external information, such as trading volume and duration time. The results show that the median, the simplest smoothing technique, performs rather well when compared with all complications.