This article provides an overview of the methods used for algorithmic text analysis in
economics, with a focus on three key contributions. First, we introduce methods for …

The great losses caused by financial fraud have attracted continuous attention from
academia, industry, and regulatory agencies. More concerning, the ongoing coronavirus …

The debate over how firm stakeholder engagement is tied to preserving shareholder wealth
has received growing attention in recent years, especially in the wake of the COVID-19 …

We develop a method that identifies the attention paid by earnings call participants to firms'
climate change exposures. The method adapts a machine learning keyword discovery …

We synthesize the literature on the recent rise of populism. First, we discuss definitions and
present descriptive evidence on the recent increase in support for populists. Second, we …

Global supply chains have come under unprecedented stress as a result of US-China trade
tensions, the Covid-19 pandemic, and geopolitical shocks. We document shifts in the pattern …

We construct text-based measures of the primary concerns listed firms associated with the
spread of COVID-19 and other epidemic diseases. We identify which firms perceive to lose …

Natural language is a key form of business communication. Textual analysis is the
application of natural language processing (NLP) to textual data for automated information …

Nowadays, digital transformation has become an urgent strategic task for traditional
commercial banks. Due to the lack of measurement of banks' digital transformation, whether …

This paper studies the effects of unexpected changes in trade policy uncertainty (TPU) on
the US economy. Three measures of TPU are constructed using newspaper coverage, firms' …