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

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