Man-Bites-Dog Business Cycles

Abstract

Abstract. The newsworthiness of an event is partly determined by how unusual it is and this paper investigates the business cycle implications of this fact. We present a tractable model that features an information structure in which some types of signals are more likely to be observed after unusual events. Counterintuitively, more signals may then increase uncertainty. When embedded in a simple business cycle model, the proposed information structure can help us understand why we observe (i) large changes in macro economic aggregate variables without a correspondingly large change in underlying fundamentals (ii) persistent periods of high macroeconomic volatility and (iii) a positive correlation between absolute changes in macro variables and the cross-sectional dispersion of expectations as measured by survey data. These results are consequences of optimal updating by agents when the availability of some signals is positively correlated with tail-events. The model is estimated by likelihood based methods using raw survey data and a quarterly time series of total factor productivity along with standard aggregate time series. The estimated model suggests that there have been episodes in recent US history when the impact on output of innovations to productivity of a given magnitude were up to twice as large compared to normal times.

Disagreement and Monetary Policy

“…Table 1 specifies the baseline calibration of the model. Most values are commonly used in the literature and are also similar to the estimates in Nimark (2014); Melosi (2017), and Blanchard, L'Huillier, and Lorenzoni (2013). Among these papers there is To examine the implied disagreement about inflation expectations in the low-and high-disagreement regime, Figure 1 shows kernel density estimates of the distribution of disagreement about one-quarter-ahead inflation expectations for the high-and lowdisagreement regime.…”

“…Models where information is dispersed only about exogenous variables, among these Lorenzoni (2009); Nimark (2008Nimark ( , 2014, also imply systematic forecast errors and can account for different levels of disagreement about inflation expectations. However, these models predict that the effects of a monetary policy shock are identical (or very similar as the endogenous interest rate response can differ) for different levels of disagreement.…”

Endogenous Uncertainty and Credit Crunches

“…Related to the latter, Kozlowski, Veldkamp and Venkateswaran (2015) explore a model where agents learn about tail-risks and where belief revisions after short-lived financial shocks can have long-lasting effects. Similar, Nimark (2014) presents a mechanism that increases uncertainty after rare events, if news selectively focus on outliers. fundamentals are perceived by investors.…”

Inflation expectations, disagreement, and monetary policy

“…In contrast to the dispersed information models of Nimark (2008Nimark ( , 2014; Lorenzoni (2009); Mackowiak and Wiederholt (2009);La'O (2009, 2013) our model contains an endogenous public signal, the nominal interest rate, that conveys additional information of the central bank about the economy. 3 This is a plausible assumption as nominal interest rates are publically announced and widely reported by news media.…”