MétaCan
Menu
Retour à la cohorte
Enregistrement W3049107291

Norway’s road to inflation targeting : Overcoming the fear of floating – counterfactual analyses of four episodes

2020· book· en· W3049107291 sur OpenAlexaboutno aff
Øyvind Eitrheim, Jan F. Qvigstad, Erling Motzfeldt Kravik, Yasin Mimir

Notice bibliographique

RevueDuo Research Archive (University of Oslo) · 2020
Typebook
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueMonetary Policy and Economic Impact
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCounterfactual thinkingInflation (cosmology)EconomicsPsychologyKeynesian economicsSocial psychologyPhysicsAstronomy
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Norway suffered from a deep recession with a systemic banking crisis in the early 1990s. The prevailing fixed exchange rate system at that time had procyclical properties. The fall of the Berlin Wall in 1989, the German reunification in the autumn of 1990 and the rebuilding of the East German Länder led to higher German interest rates. These higher interest rates put pressure upwards on the Norwegian interest rates as well and thus aggravated the Norwegian crisis. Norway changed its monetary policy regime to that of inflation targeting and flexible exchange rates around the turn of the millennium. When the financial crisis hit in 2008 and when oil prices fell in 2014, the exchange rate channel in both cases helped absorb the shock and cushion the effects on the Norwegian economy. To illustrate properties of the fixed and flexible exchange rate systems, which were in place before and after the turn of the century, respectively, we have made counterfactual analyses of four episodes. What would have happened if inflation targeting and flexible exchange rates had been introduced already in the early or mid 1990s? And, what if a fixed exchange rate regime was still in place in 2008 and 2014? We have used the macroeconomic models available in Norges Bank to conduct the aforementioned counterfactual simulations whose results are reported in Chapter 2 and 3. Chapter 2 reproduces a paper the two editors wrote already in the late 1990s based on counterfactual simulations using the bank’s main macromodel at that time, RIMINI. The results indicate how inflation targeting and flexible exchange rates might have dampened the recession in the early 1990s, allowing interest rates to be reduced during the prevailing deep recession. Chapter 3 is co-authored with Erling Motzfeldt Kravik and Yasin Mimir from the bank’s model unit and report counterfactual simulations using the bank’s current main macromodel, NEMO. The results indicate that for both episodes we have considered in the 2000s, the financial crisis in 2008 and the fall in oil prices in 2014, respectively, a return to the old fixed exchange rate regime would have incurred dramatic output costs following a substantial tightening of monetary policy in order to maintain a stable exchange rate. It should be stressed that today’s monetary policy regime works because of its established credibility and confidence in the nominal anchor, i.e. that the targeted level of inflation will be achieved in the medium term perspective. It can indeed be questioned whether such credibility was in place as early as in 1990. The accommodating policy of the devaluation decade 1976-1986 had weakened the confidence among the general public that monetary policy would deliver low and stable inflation. Thus, proposing a change in the monetary policy regime as early as in 1990 might have been interpreted as a reversion of the policy change four years earlier, and that the government, so to speak, was ”throwing the cards”. Although New Zealand as the first country had introduced inflation targeting effective from February 1990, the inflation targeting regime was in its infancy, and was yet neither well known nor well established as an alternative monetary policy regime. After all, there had been a considerable time for deliberations and for maturing the decision to move to inflation targeting in New Zealand, a process that started already in the early 1980s. Canada and Sweden followed suit and introduced inflation targeting as early as in 1991 and 1993 respectively, whereas it took another ten years before Norway introduced inflation targeting de jure in 2001. Monetary policy in a small open economy like Norway will always be constrained and the room for manoeuvre will always be limited. For example, the combination of high oil prices and low international interest rates in 2010-2014 turned out to yield procyclical outcomes, notwithstanding the fact that Norges Bank used the freedom to maintain higher interest rates than in the Eurozone. But in times of crisis Norway has been well-served by exchange rate flexibility, which made monetary policy more countercyclical when needed, thus providing important relief which helped smooth the process adapting to the global financial crisis in 2008 and the drop in oil prices in 2014. It is an open question whether the fear of floating exchange rates could have been overcome at an earlier point of time, such as in the midst of the 1990s after countries like New Zealand, Canada, Finland and Sweden had pioneered adopting inflation targeting and floating exchange rates, but the experiences from the past two decades tell us better late than never.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,018
score de la tête « metaresearch » (Gemma)0,045
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,022
Score d'incertitude au seuil0,093

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0180,045
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,002
Communication savante0,0020,001
Science ouverte0,0020,001
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,156
Tête enseignante GPT0,293
Écart entre enseignants0,138 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2020
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueDuo Research Archive (University of Oslo)Même sujetMonetary Policy and Economic ImpactTravaux en français237 207