Jamie Lenney and Biagio Rosso propose a flexible departure from FIRE in a Bank of England working paper

Jamie Lenney and Biagio Rosso propose a flexible departure from FIRE in a Bank of England working paper

Published on 17 July 2026, Jamie Lenney and Biagio Rosso propose a way to represent departures from full information rational expectations (FIRE) in DSGE models using the sequence space framework. Their approach lets agents overreact or underreact to current economic conditions and underreact to news, while remaining agnostic about the source of these belief frictions. The authors say their expectations process can accommodate several existing models as special cases and can be used with a wide class of DSGE and HANK models. They apply it to a medium-scale two-asset HANK model, jointly estimating its dynamic and behavioural parameters using US business cycle data, including inflation expectation data. The authors report that behavioural expectations improve the model’s empirical fit and the qualitative properties of its impulse response functions. The paper’s practical contribution is a flexible way to represent different patterns of expectations within models used to study economic dynamics. The page describes the work as research in progress intended to encourage comments and debate; it does not provide detailed estimates or results beyond the abstract. How much does the improved fit depend on including inflation expectation data?

Publication: 536d2837-fda5-ec2d-536c-38d381562d86

attribution — pass: The reading correctly attributes the paper to Jamie Lenney and Biagio Rosso as a Bank of England Staff Working Paper. Its findings are kept as the authors' claims ('the authors say', 'the authors report').

Staff Working Paper No. 1,197 Jamie Lenney and Biagio Rosso

summary — uncertain: The summary is faithful to the abstract, but several central terms are left unexplained for a non-specialist reader: DSGE, HANK, two-asset, sequence space framework, impulse response functions and belief frictions. FIRE is expanded but never explained in plain language. The definitions list is empty, so none of these terms is explained beside the reading. Smallest repair: add plain-language glosses or term-library tooltips for these terms. The reading also never says why the work matters beyond modelling, but the abstract gives little basis for more.

apply it to a medium-scale two-asset HANK model and jointly estimate the model’s dynamic and behavioural parameters on US business cycle data

date — pass: The reading's 17 July 2026 matches the page dateline and the UTC day of evidence.originalPublished. The sidebar lists later working papers dated October 2026, which are likely later additions to the page. The reading neither uses nor relies on them. There is no hindsight framing, and the source is a publisher page, not an archive copy.

Published on 17 July 2026

support — pass: Every claim is stated in the abstract: the overreact/underreact process, nesting several expectations models as special cases, use across a wide class of DSGE and HANK models, and the improved fit and impulse response functions. The 'practical contribution' sentence is a modest restatement of the abstract. The closing question follows from the inclusion of inflation expectation data and is not a leading claim. The limitations correctly note that only an abstract is available.

we derive an associated behavioural expectations solver deployable to a wide class of DSGE and HANK models

media — pass: No media was selected and none was supplied or verified, so this is appropriate.