Low wage work in five European countries and the USA: the role of national institutions
Bibliographic record
Abstract
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).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".