Forecasting output gaps in the G‐7 countries: The role of correlated Innovations and structural breaks.

Trend GDP and output gaps play an important role in fiscal and monetary policy formulation, often including the need for forecasts. In this paper we focus on fore- casting trend GDP and output gaps with Beveridge-Nelson (1981) trend-cycle decompositions and investigate how these are affected by assumptions concern- ing correlated innovations and structural breaks. We evaluate expanding win- dows, one-step-ahead forecasts indirectly for the G-7 countries on the basis of real GDP growth rate forecasts. We find that correlated innovations affect real GDP growth rate forecasts positively, while allowing for structural breaks works for some countries but not for all. In the face of uncertainty the evidence supports that in making forecasts of trends and output gap policy makers should focus on allowing for the correlation of shocks as an order of priority higher than unknown structural breaks

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Why are initial estimates of productivity growth so unreliable?

This paper argues that initial estimates of productivity growth will tend to be much less reliable than those of most other macroeconomic aggregates, such as output or employment growth. Two distinct factors complicate productivity measurement. (1) When production increases, factor inputs typically increase as well. Productivity growth is therefore typically less variable than output growth, meaning that measurement errors will tend to be relatively more important. (2) Revisions to published estimates of production and factor inputs tend to be less highly correlated than the published estimates themselves. This further increases the impact of data revisions on published productivity estimates. To assess the extent of these problems in practice, we detail the importance of historical revisions to the most commonly-used measures of US aggregate productivity growth, expanding on previous empirical work by Aruoba (2008) and Anderson and Kliesen (2006). We find that such revisions have contributed substantially to policymakers' forecast errors for US productivity growth.</p

Forecasting output gaps in the G-7 countries:The role of correlated Innovations and structural breaks.

Trend GDP and output gaps play an important role in fiscal and monetary policy formulation, often including the need for forecasts. In this paper we focus on fore- casting trend GDP and output gaps with Beveridge-Nelson (1981) trend-cycle decompositions and investigate how these are affected by assumptions concern- ing correlated innovations and structural breaks. We evaluate expanding win- dows, one-step-ahead forecasts indirectly for the G-7 countries on the basis of real GDP growth rate forecasts. We find that correlated innovations affect real GDP growth rate forecasts positively, while allowing for structural breaks works for some countries but not for all. In the face of uncertainty the evidence supports that in making forecasts of trends and output gap policy makers should focus on allowing for the correlation of shocks as an order of priority higher than unknown structural breaks