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Record W1042323499 · doi:10.1017/cbo9780511607004.005

Deflation Dynamics in Sweden: Perceptions, Expectations, and Adjustment During the Deflations of 1921–1923 and 1931–1933

2004· book-chapter· en· W1042323499 on OpenAlexaff
Klas Fregert, Lars Jonung

Bibliographic record

VenueCambridge University Press eBooks · 2004
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsPerceptionDeflationEconomicsPolitical scienceKeynesian economicsPsychologyMonetary policy

Abstract

fetched live from OpenAlex

INTRODUCTION Big deflations are more like singular events than realizations of some stable stochastic process. Thus, the historical particulars, including the perceptions and expectations of central decision-makers should be assessed to understand deflations. This approach is adopted in this study of the two major twentieth-century deflations in Sweden, a big one in 1921–1923 and a small one in 1931–1933. We examine three groups of actors: (1) economists that took part in public debate, (2) policy makers, and (3) wage-setters, as well as interactions between these three groups. The evolution of the policy recommendations of the economists, actions of the policy makers, and behavior of the labor market participants before, during, and after the two deflations is traced. We focus on how their perceptions and expectations were influenced by the experience of the past. The major reason for considering both episodes of deflations is that the two deflations were close in time. This gives an opportunity to explore how the experience during the first deflation episode in the early 1920s influenced beliefs and behavior ten years later during the second deflation. Our general framework can be represented as follows. Prevailing perceptions and expectations held by decision-makers concerning the choice and effects of economic policies are determined by the lessons from past macroeconomic episodes. These perceptions and expectations are revised when new information is obtained from new macroeconomic episodes. The economics profession, policy makers and wage setters are involved in a neverending process of adjusting their beliefs, in short in a learning process, where the interpretation of past events, that is, the lesson of the past, serves as the major source of information for revising perceptions and expectations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.035
GPT teacher head0.195
Teacher spread0.160 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations19
Published2004
Admission routes1
Has abstractyes

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