Vergrijzing en collectieve pensioenuitgaven

__Abstract__ \n \nWij schatten het verband tussen het beloop van de collectieve uitgaven voor het ouderdomspensioen en de vergrijzing van de bevolking. De analyse maakt gebruik van paneldata voor drie\xc3\xabntwintig OECD-landen voor zeven peiljaren uit de periode 1980-2010. Uit de resultaten blijkt dat een toename van het aantal mensen van 65 jaar en ouder met \xc3\xa9\xc3\xa9n persoon \xe2\x80\x93 ten opzichte van tien mensen uit de leeftijdsgroep 15-64 jaar \xe2\x80\x93 gepaard gaat met een stijging van de bedoelde pensioenuitgaven met 2,14 procent van het bruto binnenlands product (bbp). Uitgaande van recente CBS-ramingen van de groei en de leeftijdsopbouw van de Nederlandse bevolking, loopt de grijze druk op. Dientengevolge zouden de overheidsuitgaven voor het collectief georganiseerde en gefinancierde ouderdomspensioen \n\xe2\x80\x93 afgaande op onze schattingsresultaten, en bij ongewijzigd voortgezet overheidsbeleid \xe2\x80\x93 tot 2040 kunnen stijgen met 5,18 procent van het bbp. Dit vooruitzicht kan verklaren waarom de AOW-gerechtigde leeftijd met ingang van 2013 stapsgewijze wordt verhoogd

Comparison of on-farm progeny performances from local and imported boar semen used in the South African pig industry

The widespread use of artificial insemination in the pig industry has provided breeders with access to genetic material from superior boars from around the world. Selection of parent stock is based on estimated breeding values (EBVs), which are regularly computed in all countries performing genetic evaluations. The purpose of this study was to evaluate the value of foreign sires in the South African (SA) pig industry by comparing the on-farm performances of progeny for average daily gain (ADG), feed conversion ratio (FCR) and back fat thickness (BF) from progeny sired by USA and Canadian born sires to the performance of progeny from local sires and to progeny with paternal USA grandsires (F1-US sires). The breeds analysed comprised of Duroc, Landrace and Large White pigs. Males outperformed females for all traits measured (P <0.0001). Large differences (P <0.0001) were observed between on-farm performances which had similar climatic regions for all traits except Duroc BF (P <0.05). Farm differences were consequently attributed to management rather than environmental influences. The effect of country was significant (P <0.05) in all the models tested with the USA-sired progeny having the best overall performance. However, as measured by a stepwise R2, country remained the smallest contributor to variation across all models (except BF in Landrace), with farm, sex and year-season contributing larger portions to the variation observed in the on-farm performances of progeny. These results indicate that most of the variation observed could be attributed to differences in farm as explained by management, rather than superiority of the imported boar semen.Keywords: Average daily gain, back fat thickness, feed conversion ratio, on-farm performanc

Aligning order picking methods, incentive systems, and regulatory focus to increase performance

A unique controlled field experiment investigates order picking performance (in terms of productivity and quality). We examined three manual picker-to-parts order picking methods (parallel, zone, and dynamic zone picking) under two different incentive systems (competition- based versus cooperation-based) for pickers with different regulatory foci (prevention-focus versus promotion-focus). The study was carried out in a warehouse erected especially for the purposes of order picking research. Our results show that when using a parallel picking method a competition- based incentive system increases productivity and quality compared to a cooperation-based incentive system, and that when using a zone picking method it is more productive to use a cooperation- based incentive system. This pattern of results was especially pronounced for pickers with a dominant promotion focus. Dominantly prevention focused pickers, however, were more productive with a cooperation-based incentive system, irrespective of the picking method. Additionally, a cooperation-based incentive system delivered a low quality performance in zone picking, but a high quality performance in dynamic zone picking. The analyses demonstrate that by aligning order picking methods, incentive systems and regulatory focus, warehouses can improve productivity and quality, and reduce wage costs by up to 20%

Accidents will happen: do hazard-reducing systems help?

In the summer of 2009, soon after the winners of the annual Safest Warehouse of the Year Awards were being lauded at an industry conference, journalist Marcel te Lindert wondered out loud in his regular column for the Dutch magazine Logistiek, why it was that there were more questions raised about safety issues than there were answers

Biologische effectiviteit van bespuitingen: effecten van druppelgrootte en waterkwaliteit

Deze rapportage beschrijft de invloed van watervolume, druppelgrootte en kwaliteit van het tankmengsel op de biologische effectiviteit van bespuitingen. Onder kwaliteit van het tankmengsel wordt in dit verband verstaan: temperatuur, hardheid, pH en zoutgehalte (chloor en ijzerzouten) van de spuitvloeistof

A green-gray path to global water security and sustainable infrastructure

Sustainable development demands reliable water resources, yet traditional water management has broadly failed to avoid environmental degradation and contain infrastructure costs. We explore the global-scale feasibility of combining natural capital with engineering-based (green-gray) approaches to meet water security threats over the 21st century. Threats to water resource systems are projected to rise throughout this period, together with a significant expansion in engineering deployments and progressive loss of natural capital. In many parts of the world, strong path dependencies are projected to arise from the legacy of prior environmental degradation that constrains future water management to a heavy reliance on engineering-based approaches. Elsewhere, retaining existing stocks of natural capital creates opportunities to employ blended green-gray water infrastructure. By 2050, annual engineering expenditures are projected to triple to $2.3 trillion, invested mainly in developing economies. In contrast, preserving natural capital for threat suppression represents a potential$3.0 trillion in avoided replacement costs by mid-century. Society pays a premium whenever these nature-based assets are lost, as the engineering costs necessary to achieve an equivalent level of threat management are, on average, twice as expensive. Countries projected to rapidly expand their engineering investments while losing natural capital will be most constrained in realizing green-gray water management. The situation is expected to be most restrictive across the developing world, where the economic, technical, and governance capacities to overcome such challenges remain limited. Our results demonstrate that policies that support blended green-gray approaches offer a pathway to future global water security but will require a strategic commitment to preserving natural capital. Absent such stewardship, the costs of water resource infrastructure and services will likely rise substantially and frustrate efforts to attain universal and sustainable water security

Exposome-Wide Association Study of Body Mass Index Using a Novel Meta-Analytical Approach for Random Forest Models

BACKGROUND: Overweight and obesity impose a considerable individual and social burden, and the urban environments might encompass factors that contribute to obesity. Nevertheless, there is a scarcity of research that takes into account the simultaneous interaction of multiple environmental factors. OBJECTIVES: Our objective was to perform an exposome-wide association study of body mass index (BMI) in a multicohort setting of 15 studies. METHODS: Studies were affiliated with the Dutch Geoscience and Health Cohort Consortium (GECCO), had different population sizes (688-141,825), and covered the entire Netherlands. Ten studies contained general population samples, others focused on specific populations including people with diabetes or impaired hearing. BMI was calculated from self-reported or measured height and weight. Associations with 69 residential neighborhood environmental factors (air pollution, noise, temperature, neighborhood socioeconomic and demographic factors, food environment, drivability, and walkability) were explored. Random forest (RF) regression addressed potential nonlinear and nonadditive associations. In the absence of formal methods for multimodel inference for RF, a rank aggregation-based meta-analytic strategy was used to summarize the results across the studies. RESULTS: Six exposures were associated with BMI: five indicating neighborhood economic or social environments (average home values, percentage of high-income residents, average income, livability score, share of single residents) and one indicating the physical activity environment (walkability in formula presented buffer area). Living in high-income neighborhoods and neighborhoods with higher livability scores was associated with lower BMI. Nonlinear associations were observed with neighborhood home values in all studies. Lower neighborhood home values were associated with higher BMI scores but only for values up to formula presented . The directions of associations were less consistent for walkability and share of single residents. DISCUSSION: Rank aggregation made it possible to flexibly combine the results from various studies, although between-study heterogeneity could not be estimated quantitatively based on RF models. Neighborhood social, economic, and physical environments had the strongest associations with BMI. https://doi.org/10.1289/EHP13393.</p

Exposome-Wide Association Study of Body Mass Index Using a Novel Meta-Analytical Approach for Random Forest Models

BACKGROUND: Overweight and obesity impose a considerable individual and social burden, and the urban environments might encompass factors that contribute to obesity. Nevertheless, there is a scarcity of research that takes into account the simultaneous interaction of multiple environmental factors. OBJECTIVES: Our objective was to perform an exposome-wide association study of body mass index (BMI) in a multicohort setting of 15 studies. METHODS: Studies were affiliated with the Dutch Geoscience and Health Cohort Consortium (GECCO), had different population sizes (688-141,825), and covered the entire Netherlands. Ten studies contained general population samples, others focused on specific populations including people with diabetes or impaired hearing. BMI was calculated from self-reported or measured height and weight. Associations with 69 residential neighborhood environmental factors (air pollution, noise, temperature, neighborhood socioeconomic and demographic factors, food environment, drivability, and walkability) were explored. Random forest (RF) regression addressed potential nonlinear and nonadditive associations. In the absence of formal methods for multimodel inference for RF, a rank aggregation-based meta-analytic strategy was used to summarize the results across the studies. RESULTS: Six exposures were associated with BMI: five indicating neighborhood economic or social environments (average home values, percentage of high-income residents, average income, livability score, share of single residents) and one indicating the physical activity environment (walkability in formula presented buffer area). Living in high-income neighborhoods and neighborhoods with higher livability scores was associated with lower BMI. Nonlinear associations were observed with neighborhood home values in all studies. Lower neighborhood home values were associated with higher BMI scores but only for values up to formula presented . The directions of associations were less consistent for walkability and share of single residents. DISCUSSION: Rank aggregation made it possible to flexibly combine the results from various studies, although between-study heterogeneity could not be estimated quantitatively based on RF models. Neighborhood social, economic, and physical environments had the strongest associations with BMI. https://doi.org/10.1289/EHP13393.</p