Place of study, field of study and labour-market region: What matters for wage differences among higher-education graduates?

This paper focuses on the structure and extent of wage differences among graduates of different higher-education institutions in Germany. We ask how large these differences are and how they relate to fields of study and regional labour markets. The results from our application of cross-classified random-effects models to a cohort of the DZHW Graduate Panel show that there is a considerable amount of wage variation depending on the graduates’ alma mater. However, this variation can be fully explained by structural characteristics: Selection based on individual characteristics is of only minor importance, while regional labour markets do matter. Most of all, however, the differences relate to fields of study.

What drives wages differentials in Greece: workplaces or workers?

Using a micro-aggregated dataset that contains gross wages as well as employer and employee characteristics, we investigate whether observed wage differentials in Greece reflect mostly the underlying variation in employer characteristics, i.e. the structure of the Greek production, or worker and job characteristics. Our results show that both employer and worker characteristics are important contributors to the observed wage dispersion of full-time private sector jobs in Greece. Occupation and workplace effects alone explain around 52% of the overall wage variation in Greece. An additional 11% is explained by controlling for the impact of workplace-occupation matching. Other observable characteristics of the workers such as age, gender and type of job contract add up to 23.5% more explanatory power. Finally, our results also show that both the observed gender and contract type wage gaps are more prevalent among high-skilled occupations, acting thus as a disincentive to the acquisition of skills.

Estimation of a Roy/Search/Compensating Differential Model of the Labor Market

In this paper, we develop a model that captures key components of the Roy model, a search model, compensating differentials, and human capital accumulation on‐the‐job. We establish which components of the model can be non‐parametrically identified and which ones cannot. We estimate the model and use it to assess the relative contribution of the different factors for overall wage inequality. We find that variation in premarket skills (the key feature of the Roy model) is the most important component to account for the majority of wage variation. We also demonstrate that there is substantial interaction between the other components, most notably, that the importance of the job match obtained by search frictions varies from around 4% to around 29%, depending on how we account for other components. Inequality due to preferences for non‐pecuniary aspects of the job (which leads to compensating differentials) and search are both very important for explaining other features of the data. Search is important for turnover, but so are preferences for non‐pecuniary aspects of jobs as one‐third of all choices between two jobs would have resulted in a different outcome if the worker only cared about wages.

Assessing location attractiveness for manufacturing automobiles

Purpose: Evaluating country manufacturing location attractiveness on various performance measures deepens the analysis and provides a more informed basis for manufacturing site selection versus reliance on labor rates alone. A short list of countries can be used to drive regional considerations for site-specific selection within a country.Design/methodology/approach: The two-step multi attribute decision model contains an initial filter layer to require minimum values for low weighted attributes and provides a rank order utility score for twenty three countries studied. The model contains 11 key explanatory variables with Labor Rate, Material Cost, and Logistics making up the top 3 attributes and representing 54% percent of the model weights.Findings: We propose a multi attribute decision framework for strategically assessing the attractiveness of a country as a location for manufacturing automobiles.Research limitations/implications: Consideration of country level wage variation, specific tariffs, and other economic incentives provides a secondary analysis after the initial list of candidate countries is defined.Practical implications: The results of our modeling shows China, India, and Mexico are currently the top ranked countries for manufacturing attractiveness. These three markets hold the highest utility scores throughout sensitivity analysis on the labor rate attribute weight rating, highlighting the strength and potential of manufacturing in China, India, and Mexico.Originality/value: Combining MAUT with regression analysis to simplify model to core factors then using a “must have” layer to handle extreme impacts of low weight factors and allowing for ease of repeatability.

On the cyclicality of real wages and wage differentials

Previous empirical literature suggests that estimated wage cyclicality depends on the structure of the relationship between real wages and an observed indicator of the business cycle that econometric models impose prior to estimation. This paper, alleviates the problem of imposing such structure by searching directly for the largest common cycles in longitudinal microdata using a Bayesian dynamic latent factor model. We find that the comovement of real wages is related to a common factor that exhibits a significant but imperfect correlation with the national unemployment rate. Among others, our findings indicate that the common factor explains, on average, no more than 9% of wage variation, it accounts for 20% or less of the wage variability for 88% of the workers in the sample and roughly half of the wages move procyclically while half move countercyclically. These facts are inconsistent with claims of a strong systematic relationship between real wages and business cycles.

Workplace Heterogeneity and the Rise of West German Wage Inequality*

We study the role of establishment-specific wage premiums in generating recent increases in West German wage inequality. Models with additive fixed effects for workers and establishments are fit into four subintervals spanning the period from 1985 to 2009. We show that these models provide a good approximation to the wage structure and can explain nearly all of the dramatic rise in West German wage inequality. Our estimates suggest that the increasing dispersion of West German wages has arisen from a combination of rising heterogeneity between workers, rising dispersion in the wage premiums at different establishments, and increasing assortativeness in the assignment of workers to plants. In contrast, the idiosyncratic job-match component of wage variation is small and stable over time. Decomposing changes in mean wages between different education groups, occupations, and industries, we find that increasing plant-level heterogeneity and rising assortativeness in the assignment of workers to establishments explain a large share of the rise in inequality along all three dimensions.