Publications of Simonovits, G.

Centrist by comparison: Extremism and the expansion of the political spectrum

While it is well understood that policy suggestions outside the range of mainstream debate are prevalent in various policy domains of American politics, their effects remain unexplored. In this paper, we suggest that proposing policies far from the political mainstream can re-structure voter perceptions of where alternatives lie in the ideological space. We provide support for this hypothesis using results from six survey experiments. We find that the introduction of extreme alternatives into the public discourse makes mainstream policies on the same side of the spectrum look more centrist in the public eye, thus increasing support for these moderate alternatives.

Costly Values: The Limited Benefits and Potential Costs of Targeted Policy Justifications

Can politicians use targeted messages to offset position taking that would otherwise reduce their public support? We examine the effect of a politician’s justification for their tax policy stance on public opinion and identify limits on the ability of justifications to generate leeway for incongruent position taking on this issue. We draw on political communication research to establish expectations about the heterogeneous effects of justifications that employ either evidence or values based on whether or not constituents agree with the position a politician takes. In two survey experiments, we find small changes in support in response to these types of messages among targeted groups, but rule out large benefits for politicians to selectively target policy justifications toward subsets of the public. We also highlight a potential cost to selective messaging by showing that when these targeted messages reach unintended audiences they can backfire and reduce a candidate’s support.

Underreporting in psychology experiments: Evidence from a study registry

Many scholars have raised concerns about the credibility of empirical findings in psychology, arguing that the proportion of false positives reported in the published literature dramatically exceeds the rate implied by standard significance levels. A major contributor of false positives is the practice of reporting a subset of the potentially relevant statistical analyses pertaining to a research project. This study is the first to provide direct evidence of selective underreporting in psychology experiments. To overcome the problem that the complete experimental design and full set of measured variables are not accessible for most published research, we identify a population of published psychology experiments from a competitive grant program for which questionnaires and data are made publicly available because of an institutional rule. We find that about 40% of studies fail to fully report all experimental conditions and about 70% of studies do not report all outcome variables included in the questionnaire. Reported effect sizes are about twice as large as unreported effect sizes and are about 3 times more likely to be statistically significant.

Underreporting in political science survey experiments: comparing questionnaires to published results

The accuracy of published findings is compromised when researchers fail to report and adjust for multiple testing. Preregistration of studies and the requirement of preanalysis plans for publication are two proposed solutions to combat this problem. Some have raised concerns that such changes in research practice may hinder inductive learning. However, without knowing the extent of underreporting, it is difficult to assess the costs and benefits of institutional reforms. This paper examines published survey experiments conducted as part of the Time-sharing Experiments in the Social Sciences program, where the questionnaires are made publicly available, allowing us to compare planned design features against what is reported in published research. We find that: (1) 30% of papers report fewer experimental conditions in the published paper than in the questionnaire; (2) roughly 60% of papers report fewer outcome variables than what are listed in the questionnaire; and (3) about 80% of papers fail to report all experimental conditions and outcomes. These findings suggest that published statistical tests understate the probability of type I errors.

The impact of candidate name order on election outcomes in North Dakota

A number of studies have explored the possibility that the ordering of candidates’ names on the ballot might influence how those candidates perform on election day. Strong evidence of an order effect comes from investigations of election returns in states that implemented quasi-random assignment of candidate name orders to voters. Although most such studies have identified benefits for earlier-listed candidates, much of the evidence comes from a limited set of elections in only a handful of states. This paper expands our understanding of order effects to 31 general elections held in North Dakota between 2000 and 2006; these include all state-wide races involving 2 candidates. A primacy effect appeared in 80% of the contests. The first ballot position reaped the largest benefits in nonpartisan contests and in presidential election years. These findings are consistent with earlier studies from other states and provide evidence in line with proposals that a lack of information and ambivalence underlie candidate name order effects.

Publication bias in the social sciences: Unlocking the file drawer

We studied publication bias in the social sciences by analyzing a known population of conducted studies—221 in total—in which there is a full accounting of what is published and unpublished. We leveraged Time-sharing Experiments in the Social Sciences (TESS), a National Science Foundation–sponsored program in which researchers propose survey-based experiments to be run on representative samples of American adults. Because TESS proposals undergo rigorous peer review, the studies in the sample all exceed a substantial quality threshold. Strong results are 40 percentage points more likely to be published than are null results and 60 percentage points more likely to be written up. We provide direct evidence of publication bias and identify the stage of research production at which publication bias occurs: Authors do not write up and submit null findings.