319 research outputs found
Even if it's not Bribery: The Case for Campaign Finance Reform
We develop a dynamic multidimensional signaling model of campaign finance
in which candidates can signal their ability by enacting policy and/or by raising
and spending campaign funds, both of which are costly. Our model departs
from the existing literature in that candidates do not exchange policy influence
for campaign contributions; rather, they must decide how to allocate their
efforts between policymaking and fundraising. If high-ability candidates are
better policymakers and better fundraisers, then they will raise and spend
campaign funds even if voters care only about legislation. Campaign finance
reform alleviates this phenomenon and improves voter welfare at the expense
of politicians. Thus, we expect successful politicians to oppose true campaign
finance reform. We also show that our model is consistent with findings in the
empirical and theoretical campaign finance literature
Explaining the Favorite-Longshot Bias: Is it Risk-Love or Misperceptions?
The favorite–long shot bias describes the long-standing empirical regularity
that betting odds provide biased estimates of the probability
of a horse winning: long shots are overbet whereas favorites are underbet.
Neoclassical explanations of this phenomenon focus on rational
gamblers who overbet long shots because of risk-love. The competing
behavioral explanations emphasize the role of misperceptions
of probabilities. We provide novel empirical tests that can discriminate
between these competing theories by assessing whether the models
that explain gamblers’ choices in one part of their choice set (betting
to win) can also rationalize decisions over a wider choice set, including
compound bets in the exacta, quinella, or trifecta pools. Using a new, large-scale data set ideally suited to implement these tests, we find evidence in favor of the view that misperceptions of probability drive the favorite–long shot bias, as suggested by prospect theory
Explaining the Favorite-Longshot Bias: Is it Risk-Love or Misperceptions?
The favorite-longshot bias describes the longstanding empirical regularity that betting odds provide biased estimates of the probability of a horse winning – longshots are overbet, while favorites are underbet. Neoclassical explanations of this phenomenon focus on rational gamblers who overbet longshots due to risk-love. The competing behavioral explanations emphasize the role of misperceptions of probabilities. We provide novel empirical tests that can discriminate between these competing theories by assessing whether the models that explain gamblers' choices in one part of their choice set (betting to win) can also rationalize decisions over a wider choice set, including compound bets in the exacta, quinella or trifecta pools. Using a new, large-scale dataset ideally suited to implement these tests we find evidence in favor of the view that misperceptions of probability drive the favorite-longshot bias, as suggested by Prospect Theory.pricing under risk, probability weighting, compound lotteries, favorite-longshot bias
Explaining the Favorite-Longshot Bias: Is it Risk-Love or Misperceptions?
The favorite-longshot bias describes the longstanding empirical regularity that betting odds provide biased estimates of the probability of a horse winning—longshots are overbet, while favorites are underbet. Neoclassical explanations of this phenomenon focus on rational gamblers who overbet longshots due to risk-love. The competing behavioral explanations emphasize the role of misperceptions of probabilities. We provide novel empirical tests that can discriminate between these competing theories by assessing whether the models that explain gamblers’ choices in one part of their choice set (betting to win) can also rationalize decisions over a wider choice set, including compound bets in the exacta, quinella or trifecta pools. Using a new, large-scale dataset ideally suited to implement these tests we find evidence in favour of the view that misperceptions of probability drive the favorite-longshot bias, as suggested by Prospect Theory.pricing under risk, probability, weighting, compound lotteries, favourite-longshot bias
A MultiDimensional Signaling Model of Campaign Finance
We develop a dynamic multi-dimensional signaling model of campaign finance in which candidates can signal their ability by enacting policy and/or raising and spending campaign funds, both of which are costly. Our model departs from the existing literature in that candidates do not need to exchange policy influence for campaign contributions, rather, they must decide how to allocate their efforts between policymaking and fundraising. If highability candidates are better policymakers and fundraisers then they will raise and spend campaign funds even if voters care only about legislation. Voters’ inability to reward or punish politicians based on past policy allows fundraising to be used to signal quality at the expense of voter welfare. Campaign finance reform alleviates this phenomenon and improves voter welfare at the expense of high-ability politicians. Thus, we expect successful politicians to oppose true campaign finance reform. We also show our model is consistent with findings in the empirical and theoretical campaign finance literature.Campaign Finance, Multi-Dimensional Signaling, Repeated Elections
Party influence in congress and the economy
To understand the extent to which partisan majorities in Congress influence economic policy, we compare financial market responses in recent midterm elections to Presidential elections. We use prediction markets that track election outcomes as a means of precisely timing and calibrating the arrival of news, allowing substantially more precise estimates than a traditional event study methodology. We find that equity values, oil prices, and Treasury yields are slightly higher with Republican majorities in Congress, and that a switch in the majority party in a chamber of Congress has an impact that is only 10%-30% of that of the Presidency. We also find evidence inconsistent with the popular view that divided government is better for equities, finding instead that equity valuations increase monotonically, albeit slightly, with the degree of Republican control
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Assortative Mating By Diet In A Phenotypically Unimodal But Ecologically Variable Population Of Stickleback
Speciation with gene flow may be driven by a combination of positive assortative mating and disruptive selection, particularly if selection and assortative mating act on the same trait, eliminating recombination between ecotype and mating type. Phenotypically unimodal populations of threespine stickleback (Gasterosteus aculeatus) are commonly subject to disruptive selection due to competition for alternate prey. Here we present evidence that stickleback also exhibit assortative mating by diet. Among-individual diet variation leads to variation in stable isotopes, which reflect prey use. We find a significant correlation between the isotopes of males and eggs within their nests. Because egg isotopes are derived from females, this correlation reflects assortative mating between males and females by diet. In concert with disruptive selection, this assortative mating should facilitate divergence. However, the stickleback population remains phenotypically unimodal, highlighting the fact that assortative mating and disruptive selection do not guarantee evolutionary divergence and speciation.Integrative Biolog
Sociotropic Voting and the Media
The literature on economic voting notes that voters' subjective evaluations
of the overall state of the economy are correlated with vote choice, whereas
personal economic experiences are not (Kinder and Kiewiet 1979, 1981). Missing
from this literature is a description of how voters acquire information about
the general state of the economy and use that information to form perceptions.
To begin understanding this process, we asked a series of questions on the 2006
ANES Pilot Study about respondents' perceptions of the average price of gas
and the unemployment rate in their home states. In this chapter, we analyze
both the determinants and political consequences of respondents' perceptions
of these economic variables.
Questions about gas prices and unemployment show differences in respondents'
sources of information about these two economic variables. We found
evidence consistent with the idea that information about unemployment rates
comes from media sources, and is biased by partisan factors, and that information
about gas prices comes only from everyday experiences. While information
about both indicators shows effects from demographics, only estimates of
unemployment rates are correlated with a respondent's political outlook. Moreover,
perceptions of unemployment rates can be used to isolate the effect of
economics on partisan preferences
How Prediction Markets can Save Event Studies
Event studies have been used in political science to study the cost of regulation
(Schwert, 1981), the value of political connections (Roberts, 1990a; Fisman,
2001), the effect of political parties on defense spending (Roberts, 1990b), the
importance of rules in congressional committees (Gilligan and Krehbiel, 1988),
the reaction of different interests to trade legislation (Schnietz, 2000), how party
control in parliamentary systems affects broad-based stock indices (Herron,
2000), the value of defense contracts (Rogerson, 1989), the effect of the political
party of the US President and congressional majorities on particular industry
segments (Mattozzi, 2008; Knight, 2006; Herron et al., 1999; Den Hartog and
Monroe, 2008; Monroe, 2008; Jayachandran, 2006), and other questions
Information (In)Efficiency in Prediction Markets
We analyze the extent to which simple markets can be used to aggregate dispersed information into efficient forecasts of unknown future events. From the examination of case studies in a variety of financial settings we enumerate and suggest solutions to various pitfalls of these simple markets. Despite the potential problems, we show that market-generated forecasts are typically fairly accurate in a variety of prediction contexts, and that they outperform most moderately sophisticated benchmarks. We also show how conditional contracts can be used to discover the markets belief about correlations between events, and how with further assumptions these correlations can be used to make decisions
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