Nowcasting unemployment insurance claims in the time of COVID-19.

ABSTRACT: Near-term forecasts, also called nowcasts, are most challenging but also most important when the economy experiences an abrupt change. In this paper, we explore the performance of models with different information sets and data structures in order to best nowcast US initial unemployment claims in spring of 2020 in the midst of the COVID-19 pandemic. We show that the best model, particularly near the structural break in claims, is a state-level panel model that includes dummy variables to capture the variation in timing of state-of-emergency declarations. Autoregressive models perform poorly at first but catch up relatively quickly. The state-level panel model, exploiting the variation in timing of state-of-emergency declarations, also performs better than models including Google Trends. Ou

SUBMITTER: Larson WD 

PROVIDER: S-EPMC8846950 | biostudies-literature | 2022 Apr-Jun

REPOSITORIES: biostudies-literature