Tracking the slowdown in long-run GDP growth

Using a dynamic factor model that allows for changes in both the longrun growth rate of output and the volatility of business cycles, we document a significant decline in long-run output growth in the United States. Our evidence supports the view that most of this slowdown occurred prior to the Great Recession. We show how to use the model to decompose changes in long-run growth into its underlying drivers. At low frequencies, a decline in the growth rate of labor productivity appears to be behind the recent slowdown in GDP growth for both the US and other advanced economies. When applied to realtime data, the proposed model is capable of detecting shifts in long-run growth in a timely and reliable manner

Structural scenario analysis with SVARs

Macroeconomists seeking to construct conditional forecasts often face a choice between taking a stand on the details of a fully-specified structural model or relying on empirical correlations from vector autoregressions and remain silent about the underlying causal mechanisms. This paper develops tools for constructing ``structural scenarios'' that can be given an economic interpretation using identified structural VARs. We provide a unified and transparent treatment of conditional forecasting and structural scenario analysis and relate our approach to entropic forecast tilting. We advocate for a careful treatment of uncertainty, making the methods suitable for density forecasting and risk assessment. We also propose a metric to assess and compare the plausibility of alternative scenarios. We illustrate our methods with two applications: assessing the power of forward guidance about future interest rate policies and stress testing the reaction of bank profitability to an economic recession

Replication data for: "Tracking the Slowdown in Long-Run GDP Growth"

Antolin-Diaz, Juan, Drechsel, Thomas, and Petrella, Ivan, (2017) “Tracking the Slowdown in Long-Run GDP Growth.” Review of Economics and Statistics 99:2, 343-356