News, Noise, and Fluctuations: An Empirical Exploration

Blanchard, Olivier; L’Huillier, Jean-Paul; Lorenzoni, Guido

doi:10.3386/w15015

Cited by 87 publications

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“…Propagation via sticky prices is essential for the expectation shocks of Lorenzoni (2009) and Blanchard, L'Huillier and Lorenzoni (2013) to have real effects. In a previous draft of this paper (Chahrour and Ulbricht, 2017), we show how including nominal frictions helps generating sizeable output fluctuations in a narrative similar to the one explored here.…”

Section: Response To Consumer Sentiment Shocksmentioning

confidence: 99%

“…While the literature is mostly theoretical, there are now a few studies with a quantitative focus. In particular, Angeletos, Collard and Dellas (2015) and Huo and Takayama (2015a) explore a version of Angeletos and La'O (2013) ;Blanchard, L'Huillier and Lorenzoni (2013) estimate a simplified version of Lorenzoni (2009);Melosi (2014Melosi ( , 2016 estimates a variant of Woodford (2003);and Maćkowiak and Wiederholt (2015) calibrate a particular DSGE model with rational inattention. A notable difference with respect to these papers is the flexibility of expectation dynamics considered in this paper.…”

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confidence: 99%

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Information-Driven Business Cycles: A Primal Approach

Chahrour,

Ulbricht

2017

SSRN Journal

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We develop a methodology to characterize equilibrium in DSGE models, free of parametric restrictions on information. First, we define a "primal" economy in which deviations from full information are captured by wedges in agents' expectations. Then, we provide conditions ensuring some information-structure can implement these wedges.We apply the approach to estimate a business cycle model where firms and households have dispersed information. The estimated model fits the data, attributing the majority of fluctuations to a single shock to households' expectations. The responses are consistent with an implementation in which households become optimistic about local productivities and gradually learn about others' optimism.

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Section: Response To Consumer Sentiment Shocksmentioning

confidence: 99%

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confidence: 99%

Information-Driven Business Cycles: A Primal Approach

Chahrour,

Ulbricht

2017

SSRN Journal

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“…Business cycles are driven to a considerable extent by news about expected fundamentals (Barsky and Sims, 2011;Blanchard, L'Huillier, and Lorenzoni, 2013;Jaimovich and Rebelo, 2009;Walker and Leeper, 2011). 1 The way agents process and update this new information is key for the optimizing behavior of the individual and hence for aggregate macroeconomic variables (Eusepi and Preston, 2011).…”

Section: Introductionmentioning

confidence: 99%

Imperfect information about financial frictions and consequences for the business cycle

Hollmayr

Kühl

2016

Review of Economic Dynamics

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Reproduction permitted only if source is stated.ISBN 978-3-95729-134-9 (Printversion) Non-technical summary Research QuestionFinancial linkages between savers and borrowers are exposed to agency problems which may arise for several reasons. Imperfect information about an investment project can cause moral hazard behavior of borrowers if lenders do not have sufficient information about them. Our aim is to introduce imperfect information in a contract related to a limited enforcement problem. The way agents process and update new information is key for the optimizing behavior of the individual and hence for aggregate macroeconomic variables. In this paper we ask what the consequences for the business cycle are when agents have to learn about the behavior of banks. ContributionThe idea of our paper is to implement imperfect information into the banking sector of an otherwise standard New-Keynesian model, in which limited enforcement creates an agency problem. In our setting, economic agents learn about the size of changes in the diverting behavior of bankers. Everything else in the economy, i.e. both the structure and the parameter values, is known. Then we contrast the learning approach to full information rational expectations and analyze their respective roles for the business cycle. ResultsFor the period during which agents learn about the economy, the whole economy exhibits higher volatility and different outcome paths for macroeconomic variables compared with rational expectations. In particular, the introduction of imperfect information amplifies the responses of variables as the leverage ratio in the economy is higher for a longer period. Output is also higher due to a boost in investment before it undershoots the rational expectations benchmark outcomes. This goes hand in hand with an increase in uncertainty and higher volatility of all macro-variables. Compared with rational expectations output, investment and the leverage ratio display an increase in their respective volatility of between 1% and 8%. Output becomes even slightly more persistent in the learning case. Nichttechnische Zusammenfassung AbstractIn this paper, we discuss the consequences of imperfect information about financial frictions on the macroeconomy. We rely on a New Keynesian DSGE model with a banking sector in which we introduce imperfect information about a limited enforcement problem. Bank managers divert resources and can increase the share of diversion. This can only be observed imperfectly by depositors. The ensuing imperfect information generates a higher volatility of the business cycle. Spillovers from the financial sector to the real economy are higher and shocks in general are considerably amplified in the transition period until agents' learning is complete. Volatility and second-order moments also display an amplification under the learning setup compared with the rational expectations framework.

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“…By this logic, the results found in my model should carry over if I impose a similar framework. A version of his model was also applied more recently in Blanchard et al [8], and they find that noise shocks play a significant role in short-run fluctuations using a structural parametrization of their model. Angeletos and La'O [1], [2] have also explored the role and implications of noise shocks using a model comparable to Lorenzoni's example model.…”

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confidence: 99%

The Role of Capital on Noise Shocks

Amberger

2013

SSRN Journal

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An important topic in recent macroeconomic literature is the potential effects of noise, or expectational, shocks on aggregates. Most of the past analysis has used some derivative of a New Keynesian model with labor as the only input, but doing so fails to consider that some input decisions may not have their returns realized today.To capture and explore this possibility under a noise shock framework, I incorporate endogenous capital accumulation in a New Keynesian model and solve for explicit dynamics using the method of undetermined coefficients. Results show that the qualitative predictions hold between my model and that without capital, but inclusion of capital significantly dampens the size of noise shocks: excluding capital raises the initial response of output to a noise shock by more than double. As usable capital on impact is fixed, labor responds less than the no-capital equivalent because it faces diminishing returns to scale. Coupling this effect with quasi-fixed capital accumulation leads to a muted output response in comparison to labor-only models. In addition, noise shocks are transient compared to a permanent shock. This is due to noise shocks being predominantly consumption driven opposed to investment driven. These results suggest that models without capital may overstate the significance of noise shocks.

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News, Noise, and Fluctuations: An Empirical Exploration

Abstract: We explore empirically models of

Cited by 87 publications

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Information-Driven Business Cycles: A Primal Approach

Information-Driven Business Cycles: A Primal Approach

Imperfect information about financial frictions and consequences for the business cycle

The Role of Capital on Noise Shocks

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