Working Paper: NBER ID: w15015
Authors: Olivier J. Blanchard; Jean-Paul Lhuillier; Guido Lorenzoni
Abstract: We explore empirically models of aggregate fluctuations with two basic ingredients: agents form anticipations about the future based on noisy sources of information; these anticipations affect spending and output in the short run. Our objective is to separate fluctuations due to actual changes in fundamentals (news) from those due to temporary errors in the private sector's estimates of these fundamentals (noise). Using a simple model where the consumption random walk hypothesis holds exactly, we address some basic methodological issues and take a first pass at the data. First, we show that if the econometrician has no informational advantage over the agents in the model, structural VARs cannot be used to identify news and noise shocks. Next, we develop a structural Maximum Likelihood approach which allows us to identify the model's parameters and to evaluate the role of news and noise shocks. Applied to postwar U.S. data, this approach suggests that noise shocks play an important role in short-run fluctuations.
Keywords: news; noise; fluctuations; aggregate fluctuations
JEL Codes: C32; D83; E32
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| news shocks (G14) | aggregate activity (E10) |
| noise shocks (R41) | aggregate activity (E10) |
| noise shocks (R41) | forecast error variance (C53) |
| permanent technology shocks (E39) | forecast error variance (C53) |
| noise-demand shocks (C69) | short-run volatility (G17) |
| permanent productivity shocks (O49) | short-run volatility (G17) |
| signal extraction problem (C20) | structural VAR identification failure (C32) |
| permanent shocks (E32) | agents' expectations (D84) |
| transitory shocks (E32) | agents' expectations (D84) |
| noise shocks (R41) | agents' expectations (D84) |
| agents' expectations (D84) | demand (R22) |
| demand (R22) | output (C67) |