Database on: Dialogical truncation between law, economics and organizations in Brazilian Higher Education Institutions

Published: 14 June 2024| Version 2 | DOI: 10.17632/j7nt6pmfjw.2
, Matheus Libório


Data on the frequency with which key terms (economic analysis of law OR law and economics OR transaction costs OR new institutional economics) and authors (Coase OR North OR Williamson) of the economic analysis of law appear in syllabuses, teaching plans and other documents pedagogical courses of 40 undergraduate courses and 20 postgraduate courses, in the areas of administration, law and economics, from 70 Brazilian higher education institutions. Index of dialogue between law, economics and administration calculated using data collected through ordered weighted averaging. A detailed document of the process and partial results of data collection is available in the file: Database construction and analysis.


Steps to reproduce

The presence of disciplines related to the economic analysis of law in 70 higher education institutions (40 undergraduate courses and 20 postgraduate courses) was analyzed through content analysis of teaching plans, syllabuses and other pedagogical documents from 912 disciplines of these courses. The key terms and authors identified in the economic analysis of law framework were quantified through content analysis of the course documents investigated. This content analysis was carried out using N-Vivo Software. At the end of this stage, a database was built containing the following information: access date, subject title, syllabus, objective/observation of the subject, methodology, subject themes, bibliography, frequency of terms and key authors. Then, the frequency of key terms and authors present in the 912 subjects of the 428 courses were aggregated into the undergraduate or postgraduate courses of their respective higher education institutions. Finally, the frequency of key terms and authors was normalized through a function that detects and transforms outliers, avoiding underestimation of the index due to the presence of atypical values. This function is operationalized as follows: Identify superior outliers using the equation 3+1.5*(3 Quartile - 1 Quartile) Transform higher outliers into threshold values, that is, into the value obtained in step 1. Classify the frequency of key terms and authors.


Pontificia Universidade Catolica de Minas Gerais


Law, Economics


Fundação de Amparo à Pesquisa do Estado de Minas Gerais

APQ 000353/2022