Working Paper: NBER ID: w14349
Authors: S. Boragan Aruoba; Francis X. Diebold; Chiara Scotti
Abstract: We construct a framework for measuring economic activity at high frequency, potentially in real time. We use a variety of stock and flow data observed at mixed frequencies (including very high frequencies), and we use a dynamic factor model that permits exact filtering. We illustrate the framework in a prototype empirical example and a simulation study calibrated to the example.
Keywords: business conditions; economic activity; dynamic factor model; high frequency measurement
JEL Codes: C01; C22; E32; E37
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| dynamic factor model (C22) | exact filtering of latent business conditions (E37) |
| variety of stock and flow data (Y10) | optimal extraction of real activity indicators (E23) |
| dynamic factor model (C22) | smoother and more timely estimates of economic conditions (E37) |
| dynamic factor model (C22) | more rigorous nowcasting tool (C53) |
| dynamic factor model (C22) | captures turning points in economic activity (E32) |