Abstract This paper documents large revisions in a widely used series of utilization-adjusted total factor productivity (TFP) by Fernald (2014) and shows that these revisions can materially affect empirical results about the effects of news shocks. We trace these revisions to changes in estimated factor utilization that are evocative of cyclical measurement issues with productivity. We propose an alternative identification that is robust to these measurement issues. Applied to U.S. data, the shock predicts delayed productivity growth while simultaneously generating strong responses of novel indicators of technological innovation and forward-looking variables. The shock does not lead to comovement in macroeconomic aggregates.

AbstractThis paper develops a novel dataset of weekly economic conditions indices for the 50 U.S. states going back to 1987 based on mixed-frequency dynamic factor models with weekly, monthly, and quarterly variables that cover multiple dimensions of state economies. We find considerable cross-state heterogeneity in the length, depth, and timing of business cycles. We illustrate the usefulness of these state-level indices for quantifying the main contributors to the economic collapse caused by the COVID-19 pandemic and for evaluating the effectiveness of the Paycheck Protection Program. We also propose an aggregate indicator that gauges the overall weakness of the U.S. economy.