5,011 research outputs found
Partisan Impacts on the Economy: Evidence from Prediction Markets and Close Elections
Analyses of the effects of election outcomes on the economy have been hampered by the problem that economic outcomes also influence elections. We sidestep these problems by analyzing movements in economic indicators caused by clearly exogenous changes in expectations about the likely winner during Election Day. Analyzing high frequency financial fluctuations following the release of flawed exit poll data on Election Day 2004, and then during the vote count, we find that markets anticipated higher equity prices, interest rates and oil prices and a stronger dollar under a Bush presidency than under Kerry. A similar Republican-Democrat differential was also observed for the 2000 Bush-Gore contest. Prediction market based analyses of all Presidential elections since 1880 also reveal a similar pattern of partisan impacts, suggesting that electing a Republican President raises equity valuations by 2 3 percent, and that since Reagan, Republican Presidents have tended to raise bond yields.
Partisan impacts on the economy: evidence from prediction markets and close elections
Analyses of the effects of election outcomes on the economy have been hampered by the problem that economic outcomes also influence elections. We sidestep these problems by analyzing movements in economic indicators caused by clearly exogenous changes in expectations about the likely winner during election day. Analyzing high frequency financial fluctuations following the release of flawed exit poll data on election day 2004, and then during the vote count we find that markets anticipated higher equity prices, interest rates and oil prices, and a stronger dollar under a George W. Bush presidency than under John Kerry. A similar Republican–Democrat differential was also observed for the 2000 Bush–Gore contest. Prediction market based analyses of all presidential elections since 1880 also reveal a similar pattern of partisan impacts, suggesting that electing a Republican president raises equity valuations by 2–3 percent, and that since Ronald Reagan, Republican presidents have tended to raise bond yields
Partisan impacts on the economy: evidence from prediction markets and close elections
Political economists interested in discerning the effects of election outcomes on the economy have been hampered by the problem that economic outcomes also influence elections. We sidestep these problems by analyzing movements in economic indicators caused by clearly exogenous changes in expectations about the likely winner during election day. Analyzing high frequency financial fluctuations on November 2 and 3 in 2004, we find that markets anticipated higher equity prices, interest rates, and oil prices and a stronger dollar under a Bush presidency than under Kerry. A similar Republican-Democrat differential was also observed for the 2000 Bush-Gore contest. Prediction market based analyses of all presidential elections since 1880 also reveal a similar pattern of partisan impacts, suggesting that electing a Republican president raises equity valuations by 2-3 percent, and that since Reagan, Republican presidents have tended to raise bond yields.Federal government ; Political science ; Economic policy
Can electoral popularity be predicted using socially generated big data?
Today, our more-than-ever digital lives leave significant footprints in
cyberspace. Large scale collections of these socially generated footprints,
often known as big data, could help us to re-investigate different aspects of
our social collective behaviour in a quantitative framework. In this
contribution we discuss one such possibility: the monitoring and predicting of
popularity dynamics of candidates and parties through the analysis of socially
generated data on the web during electoral campaigns. Such data offer
considerable possibility for improving our awareness of popularity dynamics.
However they also suffer from significant drawbacks in terms of
representativeness and generalisability. In this paper we discuss potential
ways around such problems, suggesting the nature of different political systems
and contexts might lend differing levels of predictive power to certain types
of data source. We offer an initial exploratory test of these ideas, focussing
on two data streams, Wikipedia page views and Google search queries. On the
basis of this data, we present popularity dynamics from real case examples of
recent elections in three different countries.Comment: To appear in Information Technolog
"i have a feeling trump will win..................": Forecasting Winners and Losers from User Predictions on Twitter
Social media users often make explicit predictions about upcoming events.
Such statements vary in the degree of certainty the author expresses toward the
outcome:"Leonardo DiCaprio will win Best Actor" vs. "Leonardo DiCaprio may win"
or "No way Leonardo wins!". Can popular beliefs on social media predict who
will win? To answer this question, we build a corpus of tweets annotated for
veridicality on which we train a log-linear classifier that detects positive
veridicality with high precision. We then forecast uncertain outcomes using the
wisdom of crowds, by aggregating users' explicit predictions. Our method for
forecasting winners is fully automated, relying only on a set of contenders as
input. It requires no training data of past outcomes and outperforms sentiment
and tweet volume baselines on a broad range of contest prediction tasks. We
further demonstrate how our approach can be used to measure the reliability of
individual accounts' predictions and retrospectively identify surprise
outcomes.Comment: Accepted at EMNLP 2017 (long paper
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