Wage inequality in the Netherlands: Evidence, trends and explanations

Using detailed micro data on the entire wage distribution in the Netherlands, this paper examines trends in Dutch (real pre-tax) wage inequality between 2000 and 2008. For many years, the Netherlands has been considered an exception to the general trend of growing wage inequality that most OECD countries have experienced since the 1980s. This OECD trend is generally explained by increasing relative demand for skilled labour due to skill biased technological progress and – to a lesser extent – by globalization. Using detailed micro data on the entire wage distribution in the Netherlands, this paper examines trends in Dutch (real pre-tax) wage inequality between 2000 and 2008. We show that the aggregate flatness of the distribution hides dynamics between different groups and regions. We find that inequality, after correcting for observed worker characteristics, decreased somewhat at the lower half of the wage distribution, while increasing slightly at most of the upper half (both before and after correcting for differences in human capital). Residual wage inequality is high and increasing in most larger cities, which is in line with recent evidence on the increasing importance of agglomeration externalities.

Regional wage differences in the Netherlands: Micro-evidence on agglomeration externalities

Based on micro-data on individual workers for the period 2000–2005, we show that regional wage differentials in the Netherlands are small but present. A large part of these differentials can be attributed to individual characteristics of workers. Remaining effects are partially explained by variations in employment density, with an elasticity of about 3.8 percent and by Marshall-Arrow-Romer externalities, where doubling the share of a (2-digit NACE) industry results in a 2.4 percent higher productivity. We find evidence for a negative effect of competition (associated with Porter externalities) and diversity (associated with Jacobs externalities).

Estimating the Skill Bias in Agglomeration Externalities and Social Returns to Education:Evidence from Dutch Matched Worker-Firm Micro-Data

This paper employs a unique set of micro-data covering almost one-third of the Dutch labor force, to estimate the heterogeneity of agglomeration externalities across education levels. This paper shows that there is substantial heterogeneity in the relationship between agglomeration and productivity of workers (proxied by their hourly wage) with different educational background. Apart from estimating the impact of the aggregate density of regional labor markets, we also estimate whether the composition of the local labor market in terms of education is related to the productivity of different types of workers. Using the presence of universities as an instrument, we estimate the effect of the supply of university graduates on wages, i.e. the social return to education. We find that agglomeration externalities are substantially higher for high- and medium skilled than for low-skilled employees. We find no positive effects from the presence of high-skilled on the productivity of low-skilled

Effects of Concurrent Continuous Visual Feedback on Learning the Lane Keeping Task

This study investigated the training effectiveness of continuous visual feedback in a simulator-based lane keeping task. Two groups of student drivers (total of 30 participants) were instructed to drive as accurately as possible in the center of the right lane in a self-paced driving task during five 8-min sessions. One group received visual feedback using a horizontal compensatory display positioned on the dashboard, which provided an indication of the momentary distance to the lane center during the three training sessions. During two retention sessions (immediate and one day delayed) both groups drove without the augmented feedback. The augmented feedback resulted in improved performance on a measure lane keeping accuracy, but this effect disappeared during retention. Furthermore, the augmented feedback resulted in increased steering wheel activity during all sessions, and increased driver workload in the delayed retention session. These results provide support for the guidance hypothesis and have possible implications for the use of continuous concurrent feedback in simulatorbased driver training

Variation in use of targeted therapies for metastatic renal cell carcinoma

__Background:__ For patients with metastatic renal cell carcinoma (mRCC), targeted therapies have entered the market since 2006. The aims of this study were to evaluate the uptake and use of targeted therapies for mRCC in The Netherlands, examine factors associated with the prescription of targeted therapies in daily clinical practice and study their effectiveness in terms of overall survival (OS). __Methods:__ Two cohorts from PERCEPTION, a population-based registry of mRCC patients, were used: a 2008-2010 Cohort (n = 645) and a 2011-2013 Cohort (n = 233). Chi-squared tests for trend were used to study time trends in the use of targeted therapy. Patients were grouped based on the eligibility criteria of the SUTENT trial, the trial that led to sunitinib becoming standard of care, to investigate the use of targeted therapies amongst patients fulfilling those criteria. Multi-level logistic regression was used to identify patient subgroups that are less likely to receive targeted therapies. __Results:__ Approximately one-third of patients fulfilling SUTENT trial eligibility criteria did not receive any targeted therapy (29 % in the 2008-2010 Cohort; 35 % in the 2011-2013 Cohort). Patients aged 65+ years were less likely to receive targeted therapy in both cohorts and different risk groups (odds ratios range between 0.84-0.92); other factors like number of metastatic sites were of influence in some subgroups. Amongst treated patients, there was a decreasing trend in sunitinib use over time (p = 0.0061), and an increasing trend in pazopanib use (p = 0.0005). __Conclusions:__ Targeted therapies have largely replaced interferon-alfa as first-line standard of care. Nevertheless, many eligible patients in Dutch daily practice did not receive targeted therapies despite their ability to improve survival. Reasons for their apparent underutilisation should be examined more carefully

De invloed van contractuele en relationele aspecten op stakeholdermanagement:Een casusstudie van de A9 en A16 DBFM-infrastructuurprojecten

In the past decade, large infrastructure projects in the Netherlands have often been implemented through Public-Private Partnerships (PPPs), specifically using Design-Build-Finance-Maintain (DBFM) contracts. While the decision to implement projects through PPPs is based on expected advantages for internal parties – the public and private partners in the PPP –, there is a call for more focus on the advantages and disadvantages of PPPs for external stakeholders. External stakeholder management in DBFM projects is based on a contractual division of risks and responsibilities between the partners. However, it is clear from the literature that the contract does not guarantee successful stakeholder management. Relational aspects are important. Little research has been done, however, into the interplay of contractual and relational aspects in achieving successful stakeholder management. This article addresses this research need. A comparative case study was conducted into the PPP projects A9 Gaasperdammerweg and A16 Rotterdam. The study first shows that sanctions, when combined with a relational approach, have a positive effect on the relationships with stakeholders. Second, external stakeholder management cannot be simply outsourced to the private partner and continuous involvement of the public partner is important for success

Health-related quality of life and its determinants in patients with metastatic renal cell carcinoma

__Purpose:__ Based on improvements of progression-free survival (PFS), new agents for metastatic renal cell carcinoma (mRCC) have been approved. It is assumed that one of the benefits is a delay in health-related quality of life (HRQoL) deterioration as a result of a delay in progression of disease. However, little data are available supporting this relationship. This study aims to provide insight into the most important determinants of HRQoL (including progression of disease) of patients with mRCC. __Methods:__ A patient registry (PERCEPTION) was created to evaluate treatment of patients with (m)RCC in the Netherlands. HRQoL was measured, using the EORTC QLQ-C30 and EQ-5D-5L, every 3 months in the first year of participation in the study, and every 6 months in the second year. Participation started as soon as possible following a diagnosis of (m)RCC. Random effects models were used to study associations between HRQoL and patient and disease characteristics, symptoms and treatment. __Results:__ Eighty-seven patients with mRCC completed 304 questionnaires. The average EORTC QLQ-C30 global health status was 69 (SD, 19) before progression and 61 (SD, 22) after progression of disease. Similarly, the average EQ-5D utility was 0.75 (SD, 0.19) before progression and 0.66 (SD, 0.30) after progression of disease. The presence of fatigue, pain, dyspnoea, and the application of radiotherapy were associated with significantly lower EQ-5D utilities. __Conclusions:__ Key drivers for reduced HRQoL in mRCC are disease symptoms. Since symptoms increase with progression of disease, targeted therapies that increase PFS are expected to postpone reductions in HRQoL in mRCC

A hybrid deep learning framework for integrated segmentation and registration: evaluation on longitudinal white matter tract changes

To accurately analyze changes of anatomical structures in longitudinal imaging studies, consistent segmentation across multiple time-points is required. Existing solutions often involve independent registration and segmentation components. Registration between time-points is used either as a prior for segmentation in a subsequent time point or to perform segmentation in a common space. In this work, we propose a novel hybrid convolutional neural network (CNN) that integrates segmentation and registration into a single procedure. We hypothesize that the joint optimization leads to increased performance on both tasks. The hybrid CNN is trained by minimizing an integrated loss function composed of four different terms, measuring segmentation accuracy, similarity between registered images, deformation field smoothness, and segmentation consistency. We applied this method to the segmentation of white matter tracts, describing functionally grouped axonal fibers, using N=8045 longitudinal brain MRI data of 3249 individuals. The proposed method was compared with two multistage pipelines using two existing segmentation methods combined with a conventional deformable registration algorithm. In addition, we assessed the added value of the joint optimization for segmentation and registration separately. The hybrid CNN yielded significantly higher accuracy, consistency and reproducibility of segmentation than the multistage pipelines, and was orders of magnitude faster. Therefore, we expect it can serve as a novel tool to support clinical and epidemiological analyses on understanding microstructural brain changes over time.Comment: MICCAI 2019 (oral presentation

Heterotic SO(32) model building in four dimensions

Four dimensional heterotic SO(32) orbifold models are classified systematically with model building applications in mind. We obtain all Z3, Z7 and Z2N models based on vectorial gauge shifts. The resulting gauge groups are reminiscent of those of type-I model building, as they always take the form SO(2n_0)xU(n_1)x...xU(n_{N-1})xSO(2n_N). The complete twisted spectrum is determined simultaneously for all orbifold models in a parametric way depending on n_0,...,n_N, rather than on a model by model basis. This reveals interesting patterns in the twisted states: They are always built out of vectors and anti--symmetric tensors of the U(n) groups, and either vectors or spinors of the SO(2n) groups. Our results may shed additional light on the S-duality between heterotic and type-I strings in four dimensions. As a spin-off we obtain an SO(10) GUT model with four generations from the Z4 orbifold.Comment: 1+37 pages LaTeX, some typos in table 4 corrected, and we have included some discussion on exceptional shift vectors which ignored in the previous version