12,013 research outputs found
Neighborhoods by Assessment: An Analysis of Non-Ad Valorem Financing In California
Non-ad valorem assessments on property are a fiscal innovation born from financial stress. Unable to raise property taxes due to limitations, many localities have turned to these charges as an alternative method to fund local services. In this paper, we seek to explain differential levels of non-ad valorem assessment financing through the analysis of property tax records of a large and diverse set of single family homes in California. We theorize that assessments, as opposed to other forms of taxation, will be used when residents hold anti-redistributive preferences. We show that assessment financing is most common in cities with high median household incomes and greater ethnic diversity. We also show that certain types of assessments, those with narrow geographic range, are frequently levied on expensive homes in poorer communities. We argue that this new form of financing exacerbates economic inequality by creating additional inequities in public service provisions
Hearing the Victim\u27s Voice: Analysis of Victims\u27 Advocate Participation in the Trial Proceeding of the International Criminal Court
Appropriate technology for Aboriginal Enterprise Development
RADG has been developing appropriate health technology for use in remote communities in Australia. The greatest need for these technologies has been in Aboriginal communities. In developing appropriate technical artifacts, RADG has confronted two problems. Firstly we require good contact with remote communities for consultation and feedback. Secondly, part of making artifacts appropriate for under-developed countries or regions, is the need to include employment and self-determination as part of the benefits of a technology
On the convergence of spectral deferred correction methods
In this work we analyze the convergence properties of the Spectral Deferred
Correction (SDC) method originally proposed by Dutt et al. [BIT, 40 (2000), pp.
241--266]. The framework for this high-order ordinary differential equation
(ODE) solver is typically described wherein a low-order approximation (such as
forward or backward Euler) is lifted to higher order accuracy by applying the
same low-order method to an error equation and then adding in the resulting
defect to correct the solution. Our focus is not on solving the error equation
to increase the order of accuracy, but on rewriting the solver as an iterative
Picard integral equation solver. In doing so, our chief finding is that it is
not the low-order solver that picks up the order of accuracy with each
correction, but it is the underlying quadrature rule of the right hand side
function that is solely responsible for picking up additional orders of
accuracy. Our proofs point to a total of three sources of errors that SDC
methods carry: the error at the current time point, the error from the previous
iterate, and the numerical integration error that comes from the total number
of quadrature nodes used for integration. The second of these two sources of
errors is what separates SDC methods from Picard integral equation methods; our
findings indicate that as long as difference between the current and previous
iterate always gets multiplied by at least a constant multiple of the time step
size, then high-order accuracy can be found even if the underlying "solver" is
inconsistent the underlying ODE. From this vantage, we solidify the prospects
of extending spectral deferred correction methods to a larger class of solvers
to which we present some examples.Comment: 29 page
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