The research funded by the National Research, Development, and Innovation Fund (No. K-146803) will conduct a comprehensive empirical analysis of the practice of the Hungarian Constitutional Court from the beginning of its decision-making practice to the present. The research is a continuation of an earlier NRDIF-funded work entitled The Empirical Analysis of the Decision-Making of the Hungarian Constitutional Court 2005-2017. Our main objective is to supplement the database with decisions before 2005 and after 2017, which will fundamentally change the nature of the current database, transforming the "historic" database into a current, "living" database.

The US Supreme Court case law database has served as our primary model, but there are many differences between the two courts, such as their jurisdiction, procedure and place in the legal system. One of the most important differences is that the Hungarian Constitutional Court typically deals with several analytically distinct legal issues in each of its decisions. For this reason, the basic unit of the database is not the individual decisions, but the individual points of the decisions contained in the operative part of the Constitutional Court decision, which are called Constitutional Court provisions. A decision of the Constitutional Court, if it is a decision on the merits of a case, usually states whether a particular provision is in conformity with the Constitution.

The database makes it possible to analyse the practice of the Constitutional Court from different perspectives, as it contains data on many aspects of practice. For each decision of the Constitutional Court, more than 40 characteristics (variables) are recorded, such as the petitioners, the jurisdiction exercised in the case, the subject matter of the decision, the legal consequence established by the Constitutional Court and the votes of the judges. A detailed list of the variables analysed and their explanations can be found in the codebook that accompanies the database.

The HunConCourt database is available here.

Participating researchers: Éva Boda-Balogh, Nóra Chronowski, Izabella Deák, Flóra Fazekas, Tamás Győrfi, Péter Sólyom