Evidence map›Paper›PMID 32277025›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2020

Confidence collapse in a multihousehold, self-reflexive DSGE model.

Federico Guglielmo Morelli, Michael Benzaquen, Marco Tarzia, Jean-Philippe Bouchaud

Open access · bronzeAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact, top 91% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 0 citations in OpenAlex.

  1. Radical Complexity.Entropy (Basel, Switzerland) · 2021
    Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Federico Guglielmo MorelliLaboratoire de Physique Théorique de la Matière Condensée, UMR CNRS 7600, Sorbonne Université, 75252 Paris Cedex 05, France.
Michael BenzaquenLaboratoire d'Hydrodynamique de l'X, UMR CNRS 7646, Ecole Polytechnique, 91128 Palaiseau Cedex, France; michael.benzaquen@polytechnique.edu.ORCID 0000-0002-9751-7625
Marco TarziaLaboratoire de Physique Théorique de la Matière Condensée, UMR CNRS 7600, Sorbonne Université, 75252 Paris Cedex 05, France.
Jean-Philippe BouchaudChair of Econophysics and Complex Systems, Ecole Polytechnique, 91128 Palaiseau Cedex, France.
Capital Fund Management (France) · FRÉcole Polytechnique · FRLaboratoire de Physique Théorique de la Matière Condensée · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We investigate a multihousehold dynamic stochastic general equilibrium (DSGE) model in which past aggregate consumption impacts the confidence, and therefore consumption propensity, of individual households. We find that such a minimal setup is extremely rich and leads to a variety of realistic output dynamics: high output with no crises; high output with increased volatility and deep, short-lived recessions; and alternation of high- and low-output states where a relatively mild drop in economic conditions can lead to a temporary confidence collapse and steep decline in economic activity. The crisis probability depends exponentially on the parameters of the model, which means that markets cannot efficiently price the associated risk premium. We conclude by stressing that within our framework, narratives become an important monetary policy tool that can help steer the economy back on track.

Indexed as

confidence collapseDSGEeconomic crisesmultihousehold

Identifiers

PMID32277025
PMCPMC7196764
OpenAlexW2958710374

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.