Does Finance Benefit Society? A Language Embedding Approach

Abstract

We measure popular sentiment toward finance using a computational linguistics approach applied to millions of books published in eight countries over hundreds of years. We document persistent differences in finance sentiment across countries despite ample time-series variation. Books written in the languages of more capitalist countries discuss finance in a more positive context. Finance sentiment declines one year before rather than after financial crises. Positive shocks to finance sentiment lead to greater GDP and credit growth.

Keywords: sentiment, text analysis, word embedding, BERT, transfer learning, financial crises

JEL Classification: C82, E44, G52, N40, Q54