Economic research shows that increased uncertainty can lead to significant reductions in hiring, investment, consumption, and output in the economy. Among many types of uncertainty, policy uncertainty has gained increased attention during recent years. In a recent working paper, Tara Sinclair and I constructed a new time series measure of uncertainty around regulatory policy. The measure tracks changes in regulatory uncertainty in the U.S. since 1985 based on the degree of uncertainty expressed in relevant newspaper articles.
A text-based measurement approach has been used to capture other types of policy related uncertainty. Baker et al. (2016) developed a measure of economic policy uncertainty (EPU) based on the frequency of news articles that mention predefined sets of terms related to the economy, policy, and uncertainty. Using the same approach, they also built EPU indexes for policy categories, including categories on regulation and financial regulation specifically. Numerous studies have been published subsequently to develop similar uncertainty measures for other countries and specific policy areas such as trade policy and monetary policy. Another closely related measure is the firm-level political risk measure developed by Hassan et al. (2019). They quantified political risk faced by individual U.S. firms using quarterly earnings conference calls. Risks associated with politics cover concerns about regulation, ballot initiatives, government funding, and other relevant issues. Although relying on different data and developed in different ways, these text-based measures are closely related to each other and likely to contain overlapping information about policy uncertainty. In general, I refer to these measures as policy uncertainty measures in this article.