Browsing by Author "Seim, Brigitte"

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Democracy and Corruption: A Global Time-Series Analysis with V-Dem Data
(2017) McMann, Kelly M.; Seim, Brigitte; Teorell, Jan; Lindberg, Staffan I.; V-Dem Institute
Theory predicts democracy should reduce corruption. Yet, numerous scholars have found empirically that corruption decreases at high levels of democracy but actually increases at low levels. A key weaknesses of studies that aim to explain this inverted curvilinear relationship, however, is that they do not disaggregate the complex concept of democracy. By contrast, this working paper disaggregates democracy theoretically and empirically. Our theoretical framework shows how components of democracy affect costs and benefits of engaging in corruption and, therefore, the level of corruption overall. Whereas other studies examine only how democratic accountability imposes costs on those engaging in corruption and thus illuminate only the downward curve of the relationship, we also examine the transaction costs and political support benefits of corruption and therefore can explain the initial uptick in corruption at low levels of democracy. Using measures of democratic components from Varieties of Democracy, we examine 173 countries from 1900 to 2012 and find that freedoms of expression and association exhibit the inverted curvilinear relationship with corruption, and that judicial constraints have a negative linear relationship. Moreover, the introduction of elections and the quality of elections act jointly, but each in a linear fashion. The mere introduction of elections increases corruption, thus accounting for the upward sloping segment of the inverted curve. Once the quality of elections begins to improve, corruption decreases, resulting in the downward-sloping segment of the curve.
Experts, Coders, and Crowds: An analysis of substitutability
(2017) Marquardt, Kyle L.; Pemstein, Daniel; Sanhueza Petrarca, Constanza; Seim, Brigitte; Wilson, Steven Lloyd; Bernhard, Michael; Coppedge, Michael; Lindberg, Staffan I.; V-Dem Institute
Recent work suggests that crowd workers can replace experts and trained coders in common coding tasks. However, while many political science applications require coders to both and relevant information and provide judgment, current studies focus on a limited domain in which experts provide text for crowd workers to code. To address potential over-generalization, we introduce a typology of data producing actors - experts, coders, and crowds - and hypothesize factors which affect crowd-expert substitutability. We use this typology to guide a comparison of data from crowdsourced and expert surveys. Our results provide sharp scope conditions for the substitutability of crowd workers: when coding tasks require contextual and conceptual knowledge, crowds produce substantively dierent data from coders and experts. We also find that crowd workers can cost more than experts in the context of cross-national panels, and that one purported advantage of crowdsourcing - replicability - is undercut by an insucient number of crowd workers.
Introducing the Historical Varieties of Democracy Dataset: Political Institutions in the Long 19th Century
(2018) Knutsen, Carl Henrik; Teorell, Jan; Cornell, Agnes; Gerring, John; Gjerløw, Haakon; Skaaning, Svend-Erik; Wig, Tore; Ziblatt, Daniel; Marquardt, Kyle L.; Pemstein, Dan; Seim, Brigitte; V-Dem Institute
The Historical Varieties of Democracy Dataset (Historical V-Dem) is a new dataset containing about 260 indicators, both factual and evaluative, describing various aspects of political regimes and state institutions. The dataset covers 91 polities globally – including most large, sovereign states, as well as some semi-sovereign entities and large colonies – from 1789 to 1920 for many cases. The majority of the indicators are also included in the Varieties of Democracy dataset, which covers the period from 1900 to the present – and together these two datasets cover the bulk of “modern history”. Historical V-Dem also includes several new indicators, covering features that are pertinent for 19th century polities. We describe the data, the process of coding, and the different strategies employed in Historical V-Dem to cope with issues of reliability and validity and ensure inter-temporal- and cross-country comparability. To illustrate the potential uses of the dataset we provide a descriptive account of patterns of democratization in the “long 19th century.” Finally, we perform an empirical investigation of how inter-state war relates to subsequent democratization.
State Capacity, Incumbent Turnover and Democratic Change in Authoritarian Elections
(2017) van Ham, Carolien; Seim, Brigitte; V-Dem Institute
Under what conditions do elections lead to democratization or conversely, sustain authoritarianism? State capacity may be a crucial intervening variable affecting the democratizing power of elections in authoritarian regimes. In regimes with limited state capacity, manipulating elections, co-opting elites, and repressing opposition is more difficult than in regimes with more extensive state capacity, rendering turnover in elections more likely in weak states. Yet, while increasing the chances of turnover, if the new incumbent has limited capacity to deliver public services and make policy changes after coming to power, democratic change is unlikely to be sustainable. Hence, state capacity may be a double-edged sword. This paper tests these expectations using Varieties of Democracy data for 460 elections in 110 authoritarian regimes from 1974 to 2012, and finds that state capacity is negatively associated with incumbent turnover but positively associated with democratic change after incumbent turnover in electoral authoritarian regimes.
Strategies of Validation: Assessing the Varieties of Democracy Corruption Data
(2016) McMann, Kelly; Pemstein, Daniel; Seim, Brigitte; Teorell, Jan; Lindberg, Staffan I.; V-Dem Institute
Social scientists face the challenge of determining whether their data are valid, yet they lack prac- tical guidance about how to do so. Existing publications on data validation provide mostly abstract information for creating one’s own dataset or establishing that an existing one is adequate. Fur- ther, they tend to pit validation techniques against each other, rather than explain how to combine multiple approaches. By contrast, this paper provides a practical guide to data validation in which tools are used in a complementary fashion to identify the strengths and weaknesses of a dataset and thus reveal how it can most effectively be used. We advocate for three approaches, each incorporat- ing multiple tools: 1) assessing content validity through an examination of the resonance, domain, differentiation, fecundity, and consistency of the measure; 2) evaluating data generation validity through an investigation of dataset management structure, data sources, coding procedures, aggre- gation methods, and geographic and temporal coverage; and 3) assessing convergent validity using case studies and empirical comparisons among coders and among measures. We apply our method to corruption measures from a new dataset, Varieties of Democracy. We show that the data are generally valid and we emphasize that a particular strength of the dataset is its capacity for analysis across countries and over time. These corruption measures represent a significant contribution to the field because, although research questions have focused on geographic differences and temporal trends, other corruption datasets have not been designed for this type of analysis.
What Makes Experts Reliable?
(2018) Marquardt, Kyle L.; Pemstein, Daniel; Seim, Brigitte; Wang, Yi-ting; V-Dem Institute
Many datasets use experts to code latent quantities of interest. However, scholars have not explored either the factors affecting expert reliability or the degree to which these factors influence estimates of latent concepts. Here we systematically analyze potential correlates of expert reliability using six randomly selected variables from a cross-national panel dataset, V-Dem v8. The V-Dem project includes a diverse group of over 3,000 experts and uses an IRT model to incorporate variation in both expert reliability and scale perception into its data aggregation process. In the process, the IRT model produces an estimate of expert reliability, which affects the relative contribution of an expert to the model. We examine a variety of factors that could correlate with reliability, and find little evidence of theoretically-untenable bias due to expert characteristics. On the other hand, there is evidence that attentive and condent experts who have a basic contextual knowledge of the concept of democracy are more reliable.