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Enregistrement W159677738

Permanent and Transitory Movements in Output and Unemployment: Okun’s Law Persists

2004· article· en· W159677738 sur OpenAlexaboutno aff
Tara M. Sinclair, Michael T. Owyang, Jens Søndergaard

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueEconomic Theory and Policy
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésNAIRUUnemploymentNatural rate of unemploymentEconomicsOkun's lawInflation (cosmology)Full employmentKeynesian economicsPhillips curveRecessionBivariate analysisUnemployment rateEconometricsMacroeconomicsMathematicsStatistics
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

This paper develops a bivariate correlated unobserved components model to investigate the interaction between output and unemployment. The model separates these two key macroeconomic variables into permanent and transitory components and provides estimates of the correlations among these components. The results for the US indicate that fluctuations in both output and unemployment are largely permanent and there exists a negative relationship between these permanent components similar to the Okun’s Law relationship between the transitory components. These results call into question macroeconomic theories that imply zero correlation between the different components, as well as theories that consider recessions as purely transitory movements in either output or unemployment. The author wishes to thank James Morley for constant help and guidance, Gaetano Antinolfi, Lee Benham, Marcus Berliant, Art Carden, Steve Fazzari, Neville Francis, Ed Greenberg, Tom King, Michael Owyang, Jens Sondergaard, Houston Stokes, and the participants in the Applied Time-Series Research Group at Washington University, the Midwest Economics Association 68 Annual Meeting in Chicago, and the Western Economic Association International 79 Annual Conference in Vancouver. I especially thank Christoph Schleicher for help with the proof of identification of the model. All remaining errors are my own. Section 1: Introduction Many macroeconomic models and theories separate the study of economic growth from that of fluctuations. They also often separate the study of permanent movements in the unemployment rate (the natural rate of unemployment or the NAIRU—NonAccelerating Inflation Rate of Unemployment) from the study of transitory unemployment. The connection between output and unemployment comes through Okun’s Law which suggests that an increase in transitory output is accompanied by a decrease in transitory unemployment. Thinking of the economy in this manner implicitly assumes that the components of output and unemployment are uncorrelated except for a negative correlation between the two transitory components. Theories do exist, however, which suggest the existence of additional nonnegative correlations between the components of output and unemployment. For example, some real business cycle theories, such as the one presented by Kydland and Prescott (1982), imply a negative correlation between the permanent and transitory components of output. In these theories, transitory movements in the series arise primarily from adjustment to permanent changes. Other theories suggest a positive correlation between permanent and transitory movements. For example, a temporary increase in investment may lead to both transitory and permanent increases in output. Hysteresis may also imply a positive correlation between transitory and permanent movements where, for instance, a temporary increase in unemployment may partially persist and become permanent (e.g. Blanchard and Summers 1986). Economists thus need empirical evidence to distinguish between these different theories. Until recently, however, time series models of output and unemployment have primarily reflected the thinking that the components of major macroeconomic time series are uncorrelated. Clark (1987), Stock and Watson (1988), and others supposed that 1 Some researchers (for example Blanchard and Quah 1989) assume that the unemployment rate is stationary and thus does not have a permanent component. This assumption will be considered in Section 4.4. 2 One major exception to this is the Beveridge and Nelson decomposition (1981), which does not assume anything about the correlation between the components. The innovations in the estimated components of the Beveridge and Nelson decomposition are perfectly negatively correlated, however the implied correlation between the true components can take on any value. It is possible to solve for this correlation in the univariate case, as shown by Morley, Nelson, and Zivot (2003). The multivariate case has been examined by Schleicher (2003) and will be discussed here in Section 3.

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Comment cette classification a été obtenuedéplier

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Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,101
Score d'incertitude au seuil0,504

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,026
Tête enseignante GPT0,212
Écart entre enseignants0,185 · 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 tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeThéorique ou conceptuel
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

Citations17
Publié2004
Routes d'admission1
Résumé présentoui

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