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Low wage work in five European countries and the USA: the role of national institutions

2011· preprint· en· W3124127160 sur OpenAlexaff
Gerhard Bösch, Jérôme Gautié

Notice bibliographique

RevueRePEc: Research Papers in Economics · 2011
Typepreprint
Langueen
DomaineHealth Professions
ThématiqueEmployment and Welfare Studies
Établissements canadiensConfederation College
Organismes subventionnairesnon disponible
Mots-clésWageWork (physics)Demographic economicsMinimum wageLow wageWage shareEconomicsLabour economicsBusinessPolitical scienceEfficiency wageEngineering
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

This article presents some of the key findings on the impact of pay setting on the the extent of low wage work of studies in the United States and five European countries, namely Denmark, Germany, France, the Netherlands and United Kingdom, initiated and funded by the Russell Sage Foundation. National researchers used available data to draw the broader contours of low-wage work in each country. To measure the extent of low-wage work it was defined as earning a gross hourly wage of less than two-thirds of each country's median gross hourly wage. The comparaison of the national institutional structures in these countries was supplemented by case studies on specific jobs in five industries in all countries - call centers, food processing, retail outlets, hospitals, and hotels. These case studies were exploring the effects of variations in institutional structures on jobs which were typically low paid in the United States. structures on jobs which were typically low paid in the United. The result of this research were published in six country monographs and one comparative volume . In the mid-2000s, according to the coordinated analysis of separate national data-sets in each of the six countries, the United States had the highest share of low-wage employment, with about 25 percent of workers earning less than two-thirds of the national median wage. Germany, contrary to widespread expectations, was the European country in the mid-2000s with the next-highest share of low-wage work (22.7 percent), followed closely by the United Kingdom (21.7 percent). The Netherlands (17.6 percent) fell about midway between these three low-wage-intensive economies, on the one hand, and France (11.1 percent) and Denmark (8.5 percent), on the other hand, both of which had substantially smaller low-wage shares. As important as the incidence of low wage work is the development over the last decades. Since the 1970s, the low-wage employment share has been falling steadily in France. Over the same period, low-wage shares were relatively constant in Denmark (at a low level) and the United States (at a high level, with some cyclical variation). In the remaining three countries, however, low-wage employment was much higher in the mid-2000s than it had been at the end of the 1970s. The Netherlands and the United Kingdom both saw large increases in the low-wage share over the 1980s and 1990s, with no further increases in the 2000s. In Germany, before reunification, the low-wage share was flat or falling, but from the mid-1990s, the German low-wage share also increased steadily (Mason/Salverda 2010). One of the main challenges of the research presented here is to explain these substantial and enduring international differences in the prevalence of low-wage work as well as it different development over the last decades. Such different developments cannot be explained with timeless and universal explanations like the hypothesis of skill-biased technological developments for two reasons. First there is no indication that this bias is substantially lower in countries with a lower incidence in low wage work. Secondly low wage work is not necessarily unskilled work. In Germany for example about 80% of low wage worker are skilled. Also country-specific, long-run, economic structural factors seem to have played little role in explaining international differences in low-wage work. National shares of low-wage work do not appear to be correlated with a country's GDP per capita, GDP growth rate, hourly labor productivity, productivity growth rate, or a range of long-term demographic factors, including female employment rates. Nor do between-country differences in the labor share of total value-added appear to play a decisive role in explaining the incidence of low-wage work. The incidence of low pay, however, is strongly related to the distribution of income within the labor share of value-added in each country, a phenomenon on which we hope our findings here shed some light (Mason and Salverda 2010). The analysis of the overall incidence of low pay in the six countries and the results of the case studies in five industrie suggest that institutions play a central role in explaining international differences in low-wage work. By pay-setting institutions, we mean the formal and sometimes informal mechanisms used to determine the (and benefits) received by workers in different industries and occupations within each country. More specifically, we mean collective-bargaining arrangements, minimum wages, and other labor and product market regulations that have an impact on wage determination. These with their mutual linkages may form inclusive or exclusive pay setting systems. In exclusive systems, the pay and other terms and conditions of employees with strong bargaining power have little or no effect on employees with weaker bargaining power within a company, within an industry or across industries. Inclusive systems extend the benefits of such bargaining power to workers who have relatively little bargaining power in their own right. The more inclusive the set of institutions, the better protected are those at the low end of the workforce. Inclusiveness does not depend just on the formal but also on the extent to which the various players are committed to reducing inequality. This article looks, in turn, at the inclusiveness of collective bargaining arrangements (section 2) and national minimum (section 3), product-market deregulations as opportunities for exit options from the generally more inclusive national pay-setting systems (section 4); at issues related to pay setting at the firm level through social wages (section 5) and finally at the trade-off between wage equality and employment (section 6).

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)0,004
score de la tête « metaresearch » (Gemma)0,011
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,032
Score d'incertitude au seuil0,063

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,011
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0050,011
Études des sciences et des technologies0,0010,002
Communication savante0,0040,002
Science ouverte0,0010,004
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,087
Tête enseignante GPT0,400
Écart entre enseignants0,314 · 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'étudeObservationnel
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

Citations3
Publié2011
Routes d'admission1
Résumé présentoui

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