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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract By incorporating the Harvey accumulator into the large approximate dynamic factor framework of Doz et al. (2006), we are able to construct a coincident index of financial conditions from a large unbalanced panel of mixed frequency financial indicators. We relate our financial conditions index, or FCI, to the concept of a "financial crisis" using Markov-switching techniques. After demonstrating the ability of the index to capture "crisis" periods in U.S. financial history, we present several policy-geared threshold rules for the FCI using Receiver Operator Characteristics (ROC) curve analysis. Terms of use: Documents in EconStor mayJEL Code: G01, G17, C22

We leverage an event-study research design focused on the seven costliest hurricanes to hit the US mainland since 2004 to identify the elasticity of unemployment insurance filings with respect to search intensity. Applying our elasticity estimate to the state-level Google Trends indexes for the topic "unemployment," we show that out-of-sample forecasts made ahead of the official data releases for March 21 and 28 predicted to a large degree the extent of the Covid-19 related surge in the demand for unemployment insurance. In addition, we provide a robust assessment of the uncertainty surrounding these estimates and demonstrate their use within a broader forecasting framework for US economic activity.

This article looks at the relationships between internet searches for unemployment-related terms, unemployment insurance (UI), and the public health orders issued in the U.S. during the Covid-19 pandemic. We find that Google searches for unemployment-related subjects surged before the record increase in initial UI claims, which in turn peaked before the public health orders were implemented. As of mid-April 2020, these orders covered the vast majority of the U.S. population. Since then, the rates of increase in both search activity and initial UI claims have slowed. In this Chicago Fed Letter, we explore the relationships between daily Google searches for unemployment-related subjects, weekly initial unemployment insurance claims, and public health orders (stay-at-home, shelter-in-place, and nonessential business closure orders) imposed by U.S. state and local governments in response to the Covid-19 pandemic. A sizable increase in search interest in unemployment and similar terms preceded the historic increase in initial UI claims in late March and early April of 2020 by several days. Growth in initial UI claims in turn peaked several days before state and local public health orders went into effect. By mid-April 2020, these orders had covered close to 95% of the U.S. population. 1 Since then, the rates of increase in both Google search activity for unemployment-related subjects and initial UI claims have slowed. A historic surge in new UI claims As the Covid-19 pandemic led to the widespread shutdown of nonessential businesses, over 30 million new unemployment insurance claims (seasonally adjusted) were filed during the six-week period between March 15 and April 25, 2020. By comparison, just over 1.2 million claims were filed in a similar six-week period during February and early March of this year. Previously, the six-week record for seasonally adjusted initial UI claims was 3.9 million