231 research outputs found
Historic amenities, income and sorting of households
We test the impact of historic amenities on house prices and sorting of households within cities. Conservation area boundaries enable us to employ a semiparametric regression-discontinuity approach to measure the impact of historic amenities. The approach allows for household-specific preferences. Conditional on neighbour attributes, the price difference at the conservation boundary is about 3 percent. Internal historic amenities are also important, as listed houses are about 6 percent more expensive. It is shown that rich households sort themselves in conservation areas and in listed buildings, because they have a higher willingness to pay for historic amenities. The results contribute to an explanation for the substantial spatial income differences within cities
Time-limited and k-limited polling systems: a matrix analytic solution
In this paper, we will develop a tool to analyze polling systems with the autonomous-server, the time-limited, and the k-limited service discipline. It is known that these disciplines do not satisfy the well-known branching property in polling system, therefore, hardly any exact result exists in the literature for them. Our strategy is to apply an iterative scheme that is based on relating in closed-form the joint queue-length at the beginning and the end of a server visit to a queue. These kernel relations are derived using the theory of absorbing Markov chains. Finally, we will show that our tool works also in the case of a tandem queueing network with a single server that can serve one queue at a time
Delay in a tandem queueing model with mobile queues : an analytical approximation
In this paper, we analyze the end-to-end delay performance of a tandem queueing system with mobile queues. Due to state-space explosion there is no hope for a numerical exact analysis for the joint-queue length distribution. For this reason, we present an analytical approximation that is based on queue length analysis. Through extensive numerical validation, we find that the queue length approximation exhibits excellent performance for light and moderate traffic load
The cost-effectiveness of banning highly hazardous pesticides to prevent suicides due to pesticide self-ingestion across 14 countries:a model-based economic evaluation
Background: Reducing suicides is a key Sustainable Development Goal target for improving global health. Highly hazardous pesticides are among the leading causes of death by suicide in low-income and middle-income countries. National bans of acutely toxic highly hazardous pesticides have led to substantial reductions in pesticide-attributable suicides across several countries. This study evaluated the cost-effectiveness of implementing national bans of highly hazardous pesticides to reduce the burden of pesticide suicides.Methods: A Markov model was developed to examine the costs and health effects of implementing a national ban of highly hazardous pesticides to prevent suicides due to pesticide self-poisoning, compared with a null comparator. We used WHO cost-effectiveness and strategic planning (WHO-CHOICE) methods to estimate pesticide-attributable suicide rates for 100 years from 2017. Country-specific costs were obtained from the WHO-CHOICE database and denominated in 2017 international dollars (I0·007 per capita (95% UI 0·006–0·008). In the population-standardised results for the base case analysis, national bans produced cost-effectiveness ratios of 237 per HLYG (95% UI 191–303) across upper-middle-income and high-income countries. Bans were more cost-effective in countries where a high proportion of suicides are attributable to pesticide self-poisoning, reaching a cost-effectiveness ratio of $75 per HLYG (95% UI 58–99) in two countries with proportions of more than 30%.Interpretation: National bans of highly hazardous pesticides are a potentially cost-effective and affordable intervention for reducing suicide deaths in countries with a high burden of suicides attributable to pesticides. However, our study findings are limited by imperfect data and assumptions that could be improved upon by future studies.Funding: WHO
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