Hendrik Erz: Economic Policymaking in U.S. Congress. Discursive Dynamics, 1960–1990.

13. November 2024, 17:00 Uhr

Zeit: 13. November 2024, 17:00 – 18:30 Uhr
Modus (Ort): in Präsenz
Veranstaltungsort: Universität Stuttgart
Abteilung SOWI VII
Raum: 2.067
Seidenstr. 36
70174  Stuttgart
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Ort: Seidenstraße 36, Raum: 2.067 (2. OG)

Im Rahmen des Kolloquiums der Abteilung SOWI VII freuen wir uns ganz herzlich, Henrik Erz (Linköping University, Schweden) bei uns begrüßen zu dürfen. 

Economic Policymaking in U.S. Congress. Discursive Dynamics, 1960–1990.
Hendrik Erz, Institute for Analytical Sociology (IAS) at Linköping University, Sweden

In the 1980s, the U.S. economy saw one of the biggest paradigm shifts of the 20th century. Within ten years, Congress passed two large tax cuts, deregulation bills, and several budget cuts. The literature often focuses on the role of the U.S. president during that time – Ronald Reagan –, while the role of U.S. Congress has received less attention. Understanding what the representatives said and did during this period is crucial for an understanding of the processes that underpinned this paradigm shift. Moreover, we lack an understanding of how Congressional speech relates to the legislation being passed more generally. Is speech mere idle talk, or can it help us understand how the representatives motivate and justify their behavior? My dissertation sheds light on what representatives said about the economy during the time and illuminates the relationship between speech and voting behavior on the Congressional floor. In this talk, I will present initial results and discuss the merits of using Computational Text Analysis for analyzing large corpora of parliamentary speech.

Short Bio: Hendrik Erz is a PhD Student at the Institute for Analytical Sociology (IAS) at Linköping University, Sweden. With a background in history and political sciences, he is a Political Sociologist studying the legislative process in U.S. Congress with a focus on economic policymaking during the 1980s. Methodologically, he focuses on Computational Text Analysis, using Large Language Models to analyze large corpora of parliamentary speech transcripts.

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