A Machine-Learning History of English Caselaw and Legal Ideas Prior to the Industrial Revolution I: Generating and Interpreting the Estimates

Peter Grajzl and Peter Murrell

No 8774, CESifo Working Paper Series from CESifo

Abstract: The history of England’s institutions has long informed research on comparative economic development. Yet to date there exists no quantitative evidence on a core aspect of England’s institutional evolution, that embodied in the accumulated decisions of English courts. Focusing on the two centuries before the Industrial Revolution, we generate and analyze the first quantitative estimates of the development of English caselaw and its associated legal ideas. We achieve this in two companion papers. In this, the first of the pair, we build a comprehensive corpus of 52,949 reports of cases heard in England's high courts before 1765. Estimating a 100-topic structural topic model, we name and interpret all topics, each of which reflects a distinctive aspect of English legal thought. We produce time series of the estimated topic prevalences. To interpret the topic timelines, we develop a tractable model of the evolution of legal-cultural ideas and their prominence in case reports. In the companion paper, we will illustrate with multiple applications the usefulness of the large amount of new information generated by our approach.

Keywords: English history; institutional development; machine learning; caselaw; idea diffusion (search for similar items in EconPapers)
JEL-codes: C80 K10 N00 P10 Z10 (search for similar items in EconPapers)
Date: 2020
New Economics Papers: this item is included in nep-big, nep-cmp, nep-his, nep-hpe and nep-law
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Journal Article: A machine-learning history of English caselaw and legal ideas prior to the Industrial Revolution I: generating and interpreting the estimates (2021)
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