Objective Since 2008, the Standardized World Income Inequality Database (SWIID) has provided income inequality data that seek to maximize comparability while providing the broadest possible coverage of countries and years. This article describes the current SWIID's construction, highlighting differences from its original version, and reevaluates the SWIID's utility to cross‐national income inequality research in light of recently available alternatives. Methods Coverage of inequality data sets is assessed across country‐years; comparability is evaluated in terms of success in predicting the Luxembourg Income Study (LIS), recognized in the field as the gold standard in comparability, before those data are released. Results The SWIID offers coverage double that of the next largest income inequality data set, and its record of comparability is three to eight times better than those of alternate data sets. Conclusions As its coverage and comparability far exceed those of the alternatives, the SWIID remains better suited for broadly cross‐national research on income inequality than other available sources.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract Cross-national research on the causes and consequences of income inequality has been hindered by the limitations of existing inequality datasets: greater coverage across countries and over time is available from these sources only at the cost of significantly reduced comparability across observations. This article presents the Standardized World Income Inequality Database (SWIID), which standardizes the United Nations University database (UNU-WIDER 2008) while minimizing reliance on problematic assumptions by using as much information as possible from proximate years within the same country. The resulting series of gross and net income inequality data maximize comparability for the largest possible sample of countries and years and so are better suited to broadly cross-national research than other sources. Terms of use: Documents in EconStor may

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte.

Objective: This article documents wide-ranging revisions to the Standardized World Income Inequality Database (SWIID), which seeks to maximize the comparability of income inequality estimates for the broadest possible coverage of countries and years. Methods: Two k-fold cross-validations, by observation and by country, are used to evaluate the SWIID's success in predicting the Luxembourg Income Study (LIS), recognized in the field as setting the standard for comparability. Results: The cross-validations indicate that the new SWIID's estimates and their uncertainty are even more accurate than previous versions, extending its advantage in comparability over alternate income inequality datasets. Conclusion: Given its superior coverage and comparability, the SWIID remains the optimum source of data for broadly cross-national research on income inequality.

Nearly a half-century ago, E.E. Schattschneider wrote that the high abstention and large differences between the rates of electoral participation of richer and poorer citizens found in the United States were caused by high levels of economic inequality. Despite increasing inequality and stagnant or declining voting rates since then, Schattschneider's hypothesis remains largely untested. This article takes advantage of the variation in inequality across states and over time to remedy this oversight. Using a multilevel analysis that combines aspects of state context with individual survey responses in 144 gubernatorial elections, it finds that citizens of states with greater income inequality are less likely to vote and that income inequality increases income bias in the electorate, lending empirical support to Schattschneider's argument.

Objective. This article documents wide-ranging revisions to the Standardized World Income Inequality Database (SWIID), which seeks to maximize the comparability of income inequality estimates for the broadest possible coverage of countries and years. Methods. Two k-fold crossvalidations, by observation and by country, are used to evaluate the SWIID's success in predicting the Luxembourg Income Study (LIS), recognized in the field as setting the standard for comparability. Results. The cross-validations indicate that the new SWIID's estimates and their uncertainty are even more accurate than previous versions, extending its advantage in comparability over alternate income inequality data sets. Conclusion. Given its superior coverage and comparability, the SWIID remains the optimum source of data for broadly cross-national research on income inequality. From its origins now over a decade ago, the goal of the Standardized World Income Inequality Database (SWIID) has been to provide estimates of income inequality for as many countries and years as possible while ensuring that these estimates are as comparable as the available data allow (see Solt, 2009). That is to say, the SWIID's first priority is breadth of coverage, and its second priority is comparability. The starting point for the SWIID estimates is a data set with the complementary priorities: the Luxembourg Income Study (LIS), which aims to maximize comparability and, given that primary concern, to include as many countries and years as possible. 1 Then, the SWIID routine estimates the relationships between Gini indices based on the LIS and all of the other Ginis available for the same country-years, and it uses these relationships to estimate what the LIS Gini would be in country-years not included in the LIS but available from other sources. This approach has made the SWIID a preferred source of income inequality data for researchers pursuing broadly cross-national work across a wide range of disciplines, including not only economics (e.g., Berg et al.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract What accounts for differences in the extent of nationalist sentiments across countries and over time? One prominent argument is that greater economic inequality prompts states to generate more nationalism as a diversion that discourages their citizens from recognizing economic inequality and mobilizing against it. This article provides a first empirical test of this theory against rival explanations based on international conflict and the development of new nations using survey data on national pride in the advanced democracies over two decades, data on economic inequality from the Luxembourg Income Study, and data on international conflict from the Correlates of War project. Only the diversionary theory of nationalism is supported. This conclusion is an important contribution to our understanding of nationalism as well as of the effects of economic inequality on society. Terms of use: Documents in

Objective. What effect does the extent of economic inequality within a country have on the religiosity of the people who live there? As inequality increases, does religion serve primarily as a source of comfort for the deprived and impoverished or as a tool of social control for the rich and powerful? Methods. This article examines these questions with two complementary analyses of inequality and religiosity: a multilevel analysis of countries around the world over two decades and a time-series analysis of the United States over a half-century. Results. Economic inequality has a strong positive effect on the religiosity of all members of a society regardless of income. Conclusions. These results support relative power theory, which maintains that greater inequality yields more religiosity by increasing the degree to which wealthy people are attracted to religion and have the power to shape the attitudes and beliefs of those with fewer means.Recent work in the sociology of religion has largely neglected the role of economic inequality. This study illustrates the benefits to be gained by reincorporating economic inequality into our understanding of religion by examining whether and how greater inequalities in the distributions of economic resources within societies affect the religiosity of their members. We examine two competing theories of how the extent of economic inequality may influence levels of religiosity: deprivation theory and relative power theory. The first focuses on religion's value to the poor, the second on its utility to the rich. As a result, they yield distinctly different predictions of inequality's effects. We also consider whether increased religiosity could be the source of greater inequality rather than its consequence.To test these rival theories, we present a multilevel analysis of religiosity across dozens of countries over two decades and a time-series analysis of trends in religiosity over half a century in the United States. Our findings provide strong support only for the relative power theory, which maintains n