Journal ArticleDOI
How Words and Money Cultivate a Personal Vote: The Effect of Legislator Credit Claiming on Constituent Credit Allocation
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TLDR
The authors found that voters are more responsive to the total number of messages sent rather than the amount claimed by a credit-claiming message than to the amount of credit claimed by the message itself.Abstract:
the district—affect how constituents allocate credit. Legislators use credit claiming messages to influence the expenditures they receive credit for and to affect how closely they are associated with spending in the district. Constituents are responsive to credit claiming messages—they build more support than other nonpartisan messages. But contrary to expectations from other studies, constituents are more responsive to the total number of messages sent rather than the amount claimed. Our results have broad implications for political representation, the personal vote, and the study of U.S. Congressional elections. P articularistic spending, a large literature argues, cultivates a personal vote for incumbents (Cain, Ferejohn, and Fiorina 1987; Ferejohn 1974;LazarusandReiley2010;LevittandSnyder1997; Mayhew 1974). To build this support, legislators are assumed to direct projects and programs to their districts. Constituents, in turn, are thought to reward their legislator for the level of federal spending in the district (Levitt and Snyder 1997; Str¨ omberg 2004) or theread more
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“Who are these people?” Evaluating the demographic characteristics and political preferences of MTurk survey respondents:
Connor Huff,Dustin Tingley +1 more
TL;DR: As Amazon's Mechanical Turk (MTurk) has surged in popularity throughout political science, scholars have increasingly challenged the external validity of inferences made drawing upon MTurk samples as mentioned in this paper.
Journal ArticleDOI
Are samples drawn from Mechanical Turk valid for research on political ideology
TL;DR: In this article, the authors focus on the demographic differences between MTurk samples and tester data and find that there is no demographic difference between tester samples and test data.
Journal ArticleDOI
Recruiting large online samples in the United States and India: Facebook, Mechanical Turk, and Qualtrics
TL;DR: This article examined online recruitment via Facebook, Mechanical Turk (MTurk), and Qualtrics panels in India and the United States and found that online convenience samples often provide valid inferences into how partisanship moderates treatment effects, yet they are typically unrepresentative on such political variables, which has implications for the external validity of sample average treatment effects.
Journal ArticleDOI
Quantifying Social Media’s Political Space: Estimating Ideology from Publicly Revealed Preferences on Facebook
Robert M. Bond,Solomon Messing +1 more
TL;DR: In this paper, the authors developed a model to estimate the ideology of politicians and their supporters using social media data on individual citizens' endorsements of political figures, and validated the ideological estimates that result from the scaling process by showing they correlate highly with existing measures of ideology from Congress, and with individual-level self-reported political views.
Journal ArticleDOI
Estimating Heterogeneous Treatment Effects and the Effects of Heterogeneous Treatments with Ensemble Methods
TL;DR: It is shown how an ensemble of methods—weighted averages of estimates from individual models increasingly used in machine learning—accurately measure heterogeneous effects and how pooling models lead to superior performance to individual methods across diverse problems.
References
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Book
Judgment Under Uncertainty: Heuristics and Biases
Amos Tversky,Daniel Kahneman +1 more
TL;DR: The authors described three heuristics that are employed in making judgements under uncertainty: representativeness, availability of instances or scenarios, and adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available.
Book
An Economic Theory of Democracy
TL;DR: Downs presents a rational calculus of voting that has inspired much of the later work on voting and turnout as discussed by the authors, particularly significant was his conclusion that a rational voter should almost never bother to vote.
Journal ArticleDOI
Robust Locally Weighted Regression and Smoothing Scatterplots
TL;DR: Robust locally weighted regression as discussed by the authors is a method for smoothing a scatterplot, in which the fitted value at z k is the value of a polynomial fit to the data using weighted least squares, where the weight for (x i, y i ) is large if x i is close to x k and small if it is not.
Journal ArticleDOI
Amazon's Mechanical Turk A New Source of Inexpensive, Yet High-Quality, Data?
TL;DR: Findings indicate that MTurk can be used to obtain high-quality data inexpensively and rapidly and the data obtained are at least as reliable as those obtained via traditional methods.
Book
What Americans Know about Politics and Why It Matters
TL;DR: Carpini and Keeter as mentioned in this paper found that whites, men, and older, financially secure citizens have substantially more knowledge about national politics than do blacks, women, young adults, and financially less-well-off citizens.