Kommentar |
A central normative justification for representative democracy is that elections are a means for citizens to exercise control over the actions of their representatives. In this course we will examine to what extent and under what conditions elections give citizens control over their leaders. The seminar will combine a methodological session introducing a causal inference method with a substantive session introducing students to the basic concepts, theoretical frameworks, and recent papers from the field of electoral accountability.
Substantively, the course will cover important barriers to accountability in democratic polities: (1) access to information, (2) voter coordination problems, (3) institutional barriers, (4) the availability of strong competence signals, and (5) behavioral constraints. In addition to its substantive content, the course provides an introduction to the design-based approach to causal inference that will be used to evaluate whether citizens are able to hold politicians accountable. Topics include (1) randomised experiments, (2) matching, (3) regression, (4) difference-in-differences, and (5) regression discontinuity designs. The course encourages students to think about the assumption necessary to make causal claims, to become a critical consumer of causal claims in the social sciences, and equip them to conduct their own research. Prior knowledge of hypothesis testing and linear regression is required, knowledge of the statistical software R is an advantage.
https://agnes.hu-berlin.de/lupo/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&veranstaltung.veranstid=173358&menuid=&topitem=lectures&subitem=editlecture |
Literatur |
Ashworth, S. (2012). Electoral accountability: recent theoretical and empirical work. Annual Review of Political Science, 15:183–201
Imai, K. (2017). Quantitative Social Science: An Introduction. Princeton University Press, Princeton
Angrist, J. D. and Pischke, J.-S. (2014). Mastering’metrics: The path from cause to effect. Princeton University Press |