Existing literature highlights that constitutional courts influence lawmakers’ policy choices without actively intervening in the policymaking process. Lawmakers know that courts may scrutinize their acts and have incentives to amend their policies to pre-empt judicial interventions. However, evidence suggests that lawmakers are not always prepared to sacrifice policy objectives to avoid censure from courts. I develop a formal model showing how lawmakers who provoke confrontations with courts shape judicial decision-making. Drawing on an original dataset of German federal laws adopted between 1977 and 2015 that were reviewed by the German Federal Constitutional Court, I then show that the Court moderated its strike rate of laws when lawmakers had dismissed credible advice that their acts were unconstitutional. The theoretical argument and empirical evidence indicate that courts are more likely to show deference to lawmakers who push constitutional boundaries in their policy choices.

Research of judges and courts traditionally centers on judgments, treating each judgment as a unit of observation. However, judgments often address multiple distinct and more or less unrelated issues. Studying judicial behavior on a judgment level therefore loses potentially important details and risks drawing false conclusions from the data. We present a method to assist researchers with splitting judgments by issues using a supervised machine learning classifier. Applying our approach to splitting judgments by the Court of Justice of the European Union into issues, we show that this approach is practically feasible and provides benefits for text-based analysis of judicial behavior.

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