Holger Lutz Kern

Electoral balancing, divided government and ‘midterm’ loss in German elections

This paper takes a fresh look at the midterm loss in German elections and argues that government type is a crucial determinant of midterm loss. Using panel regressions on a newly compiled data set covering all state elections during the period 1949–2004, we find that systematic midterm losses occur only when both chambers of the federal legislature (Bundestag and Bundesrat) are controlled by one party or a party coalition. Prior research has failed to discover this important regularity. These findings lend strong support to electoral balancing models while calling into doubt more traditional explanations of midterm loss.

Foreign Media and Protest Diffusion in Authoritarian Regimes: The Case of the 1989 East German Revolution

Do foreign media facilitate the diffusion of protest in authoritarian regimes? Apparently for the first time, the author tests this hypothesis using aggregate and survey data from communist East Germany. The aggregate-level analysis takes advantage of the fact that West German television broadcasts could be received in most but not all parts of East Germany. The author exploits this “natural experiment” by conducting a matched analysis in which counties without West German television are matched to a comparison group of counties with West German television. Comparing these two groups of East German counties, the author finds no evidence that West German television affected the speed or depth of protest diffusion during the 1989 East German revolution. He also analyzes a survey of East German college students. Confirming the aggregate-level results, the survey data show that, at least among college students, exposure to West German television did not increase protest participation.

Assessing Methods for Generalizing Experimental Impact Estimates to Target Populations

ABSTRACT Randomized experiments are considered the gold standard for causal inference because they can provide unbiased estimates of treatment effects for the experimental participants. However, researchers and policymakers are often interested in using a specific experiment to inform decisions about other target populations. In education research, increasing attention is being paid to the potential lack of generalizability of randomized experiments because the experimental participants may be unrepresentative of the target population of interest. This article examines whether generalization may be assisted by statistical methods that adjust for observed differences between the experimental participants and members of a target population. The methods examined include approaches that reweight the experimental data so that participants more closely resemble the target population and methods that utilize models of the outcome. Two simulation studies and one empirical analysis investigate and compare the methods’ performance. One simulation uses purely simulated data while the other utilizes data from an evaluation of a school-based dropout prevention program. Our simulations suggest that machine learning methods outperform regression-based methods when the required structural (ignorability) assumptions are satisfied. When these assumptions are violated, all of the methods examined perform poorly. Our empirical analysis uses data from a multisite experiment to assess how well results from a given site predict impacts in other sites. Using a variety of extrapolation methods, predicted effects for each site are compared to actual benchmarks. Flexible modeling approaches perform best, although linear regression is not far behind. Taken together, these results suggest that flexible modeling techniques can aid generalization while underscoring the fact that even state-of-the-art statistical techniques still rely on strong assumptions.

Combining Double Sampling and Bounds to Address Nonignorable Missing Outcomes in Randomized Experiments

Missing outcome data plague many randomized experiments. Common solutions rely on ignorability assumptions that may not be credible in all applications. We propose a method for confronting missing outcome data that makes fairly weak assumptions but can still yield informative bounds on the average treatment effect. Our approach is based on a combination of the double sampling design and non-parametric worst-case bounds. We derive a worst-case bounds estimator under double sampling and provide analytic expressions for variance estimators and confidence intervals. We also propose a method for covariate adjustment using post-stratification and a sensitivity analysis for non-ignorable missingness. Finally, we illustrate the utility of our approach using Monte Carlo simulations and a placebo-controlled randomized field experiment on the effects of persuasion on social attitudes with survey-based outcome measures.

Truth Replaced by Silence: A Field Experiment on Private Censorship in Russia

Through highly visible acts of repression, authoritarian regimes can send informative signals to private actors about what types of speech are off-limits and might draw the punitive attention of the state. These acts not only encourage private actors to censor themselves but also to censor other private actors, a behavior we refer to as regime-induced private censorship. Our paper is the first to provide systematic empirical evidence on the extent and targets of such censorship behavior. We use a field experiment conducted throughout the Russian Federation in September 2014 to investigate the private censorship behavior of private media firms. The results suggest that private actors censor the messages of other private actors when those messages include anti-regime language, calls for collective action, or both. These results are partially consistent with previous empirical findings in that they show that private actors censor content with a collective action appeal even when the message itself is non-political. Our results, however, build upon previous work by showing that anti-regime messages that do not contain a call for collective action are still censored under some authoritarian regimes. Our results highlight the importance of forms of censorship other than state censorship when discussing repression, dissent, and public opinion formation in authoritarian regimes.