The Dynamics of (De-)Listing Decisions – The Impact of Regulatory Changes and Economic Policy Events in Germany 1870-1933

Projekt Start:01/2017
Status:Beendet
Forscher:Andrej Gill, Marius Liebald, Uwe Walz
Kategorie: Financial Markets
Finanziert von:LOEWE

Topic and Objective

The main objective of the research project is to investigate the determinants of (de-)listing decisions in historical Germany in the 1870-1933 period. Thereby, we aim to investigate to which extent these decisions are driven by firm-specific factors and general trends or by policy interventions and regulatory changes. In order to do so, we will separately analyze the going-public decisions and the going-private decisions which together in Germany in the 1870-1933 period (at that time one of financially most advanced economies) mimic very much the corresponding dynamics in the US in the last decades (since the 1980s).

The key input into this research is the extensive collection of firm-level data for this historic time period. For this reason, we underwent through a very extensive data collection in order to collect all relevant data for the German Joint stock companies during this time. This data collection process which is also supported by SAFE’s EurHisFirm project is not only an input into this project but provides – when ready – a very broad and promising data base for many potential projects on historical and long-term development of German companies pre-WWII.

The data collection is based on the “Handbücher der Deutschen Aktiengesellschaften” from which the data is digitized and structured based on machine learning algorithm and appropriate data base framework. The main steps and elements of the large data production and data base establishment project are summarized in SAFE WP 300. After the completion of the data base for the 1870-1933 period the main content-oriented project (addressing delisting decisions) will be initiated – starting in 2022.

Key Findings

Our analysis paves the way for dealing with historical European sources, the majority of which are non-harmonized, unstructured, and highly heterogeneous. Thus, we contribute with new insights and tested approaches to the book-to-database paradigm.

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