Pluralism and Political Conflict in Indonesia

Page range: 81-10

Piety and Redistributive Preferences in the Muslim World

This article tests two competing theories of the relationship between piety and redistributive preferences in the Muslim world. The first, drawn from the new political economy of religion, holds that more pious individuals of any faith should oppose redistributive economic policies. The second, drawn from Islamic scripture, holds that pious Muslims should favor more redistributive economic policies. Employing survey data from twenty-five countries, the authors find that there is no clear relationship between piety and redistributive preferences among Muslims. The authors find that more pious Muslims are less likely to favor government efforts to eliminate income inequality, but they find only inconsistent evidence that more pious Muslims support governments taking responsibility for the well-being of the poor. The findings offer little evidence to suggest that either scriptural or organizational factors unique to Islam create distinct economic policy preferences

Methods for Modeling Social Factors in Language Shift

In this paper we expand our understanding of language endangerment by shifting the focus from small language communities to minority language communities with speaker populations in the millions. We argue for a methodological shift toward examining language shift scenarios more broadly and quantitatively for two main reasons: 1) it is becoming increasingly clear that a large speaker population does not protect against language shift (Anderbeck 2013); 2) we need to make a distinction between the symptoms and the causes of language shift, where factors such as a dwindling number of child speakers should be seen as symptoms of language shift that are caused by other factors (Himmelmann 2010). In this paper we use Indonesia as a case study and analyze a sample of the 2010 census. We treat language choice as a sociolinguistic variable and analyze the correlation between six social factors and language choice (local languages vs. the national language, Indonesian). These results provide a starting point for creating more comprehensive models of the sociolinguistics of language shift

Lagged Explanatory Variables and the Estimation of Causal Effects

Across the social sciences, lagged explanatory variables are a common strategy to confront challenges to causal identification using observational data. We show that "lag identification"--the use of lagged explanatory variables to solve endogeneity problems--is an illusion: lagging independent variables merely moves the channel through which endogeneity biases causal estimates, replacing a "selection on observables" assumption with an equally untestable "no dynamics among unobservables" assumption. We build our argument intuitively using directed acyclic graphs, then provide analytical results on the bias resulting from lag identification in a simple linear regression framework. We then present simulation results that characterize how, even under favorable conditions, lag identification leads to incorrect inferences. These findings have important implications for current practice among applied researchers in political science, economics, and related disciplines. We conclude by specifying the conditions under which lagged explanatory variables are appropriate for identifying causal effects

Lagged Explanatory Variables and the Estimation of Causal Effects

Across the social sciences, lagged explanatory variables are a common strategy to confront challenges to causal identification using observational data. We show that "lag identification"--the use of lagged explanatory variables to solve endogeneity problems--is an illusion: lagging independent variables merely moves the channel through which endogeneity biases causal estimates, replacing a "selection on observables" assumption with an equally untestable "no dynamics among unobservables" assumption. We build our argument intuitively using directed acyclic graphs, then provide analytical results on the bias resulting from lag identification in a simple linear regression framework. We then present simulation results that characterize how, even under favorable conditions, lag identification leads to incorrect inferences. These findings have important implications for current practice among applied researchers in political science, economics, and related disciplines. We conclude by specifying the conditions under which lagged explanatory variables are appropriate for identifying causal effects

Beyond Oligarchy? Critical Exchanges on Political Power and Material Inequality in Indonesia

Page range: 1-1