Sharks and minnows in a shoal of words: Measuring latent ideological positions based on text mining techniques

We scale theoretical/ideological positions of economic research institutes over debates. Using only parts of German research institutes’ business cycle reports that deal with economic policy advice as an example, we extract sections from these reports dealing with monetary and fiscal policy issues from 1999 to 2020. To these corpora, we apply methods of unsupervised text scaling (Slapin and Proksch, 2008; Lauderdale and Herzog, 2016), namely Wordfish and Wordshoal. Roughly, results are in line with common sense in the public policy discourse. For monetary policy texts, we observe a strong, but short-lived consensus in debate-specific positions at the height of the financial crisis in 2008 and a larger polarization thereafter compared to the sample period before. For the fiscal policy text corpus, the polarization was similarly high before and after the crisis and decreases somewhat during the COVID-19 pandemic. For both policy areas, the German Institute of Economic Research (DIW), Berlin, and the Institute for World Economics (IfW), Kiel, tend to be the most diverse institutes within the spectrum of latent ideological positions. We argue that text-mining techniques might be useful to scale underlying ideological positions in policy-related publications.