Missing the Target

Buffalo is the nation’s third most impoverished city. Buffalo’s East Side and West Side neighborhoods are two of Buffalo’s most impoverished areas. If any two neighborhoods are in need of economic development, it is these two. And yet, despite spending billions of dollars on economic development programs each year, the State, County, and City have largely ignored these neighborhoods and their increasingly desperate residents. Programs, funds, and subsidies meant to help blighted neighborhoods have instead subsidized sprawl, rewarded large, non-local companies, and, even within Buffalo, done more for downtown law firms and upscale condos than for the East and West Side

Rebuilding our Neighborhoods: Improving New York State Housing Policy to Better Meet Upstate Needs

New York faces a wide variety of housing challenges. While in the New York City region, where the population is growing, availability and affordability are the most pressing concerns, upstate regions have a different set of problems stemming from population loss, housing vacancy, abandonment, and deterioration. To address the full range of issues, state housing policy needs a variety of tools in its tool box. This policy brief discusses four ways that state housing policy can better address the needs of upstate regions such as Buffalo: Support holistic neighborhood revitalization, using Buffalo’s award-winning Green Development Zone as a model; Restore and enhance funding streams for small projects and housing repairs; Adjust New York’s Low Income Housing Tax Credit Qualified Allocation Plan to better address upstate needs; and Revise the DHCR Design Handbook to better facilitate rehabilitation projects

Design of a processor to support the teaching of computer systems

Teaching computer systems, including computer architecture, assembly language programming and operating system implementation, is a challenging occupation. At the University of Waikato this is made doubly true because we require all computer science and information systems students study this material at second year. The challenges of teaching difficult material to a wide range of students have driven us to find ways of making the material more accessible. The corner stone of our strategy for delivering this material is the design and implementation of a custom CPU that meets the needs of teaching. This paper describes our motivation and these needs. We present the CPU and board design and describe the implementation of the CPU in an FPGA. The paper also includes some reflections on the use of a real CPU rather than a simulation environment. We conclude with a discussion of how the CPU can be used for advanced classes in computer architecture and a description of the current status of the project

The potential impact of trade policy changes on Caribbean sugar

This study of the Caribbean Sugar Industry summarizes its sugar trading activities and evaluates the potential impact of changes in preferential trading arrangements with the European Union (EU) on the six countries that makes up the Sugar Association of the Caribbean, namely: Jamaica, Barbados, Belize, Guyana, St. Kitts-Nevis, and Trinidad & Tobago. The trading policies that govern sugar trade between these countries and developed countries such as the EU, the United States of America (US) and to a limited extent trade among them is discussed. The report briefly describes how the Caribbean sugar industry is organized, including supply and demand determinants, marketing of its sugar via the EU Sugar Protocol, and the US tariff rate quota system, and safeguards within the Caribbean Common Market (Caricom) from extra-regional sugar producers. The study then analyses the impact of price changes based on different price scenarios that may occur after preferential prices disappear. Data and estimated model specifications are described, elasticities of dependent variables responses to independent variables changes are calculated, and these results, in addition to different price simulations are presented. The analysis shows that modest decreases in prices to Caribbean sugar producers would not result in huge changes in the structure of the Caribbean sugar industry since responses of production, consumption, imports and exports are inelastic to prices changes in the short-run. This could be due of asset fixity within the industry. This industry requires huge capital investments, thus, after these investments are made producer are forced to operate at full capacity to minimize fix costs. Secondly, the industry within this region is a mass employer of labor and a huge contributor to their country\u27s Gross Domestic Product (GDP), therefore, any major changes with this industry could result in massive social instability

Statnote 7: chi-square contingency tables

When the data are counts or the frequencies of particular events and can be expressed as a contingency table, then they can be analysed using the chi-square distribution. When applied to a 2 x 2 table, the test is approximate and care needs to be taken in analysing tables when the expected frequencies are small either by applying Yate’s correction or by using Fisher’s exact test. Larger contingency tables can also be analysed using this method. Note that it is a serious statistical error to use any of these tests on measurement data

Statnote 6: post-hoc ANOVA tests

If data are analysed using ANOVA, and a significant F value obtained, a more detailed analysis of the differences between the treatment means will be required. The best option is to plan specific comparisons among the treatment means before the experiment is carried out and test them using ‘contrasts’. In some circumstances, post-hoc tests may be necessary and experimenters should think carefully which of the many tests available should be used. Different tests can lead to different conclusions and careful consideration as to the appropriate test should be given in each circumstance

Statnote 4: what if the data are not normal?

When testing the difference between two groups, if previous data indicate non-normality, then either transform the data if they comprise percentages, integers or scores or use a non-parametric test. If there is uncertainty whether the data are normally distributed, then deviations from normality are likely to be small if the data are measurements to three significant figures. Unless there is clear evidence that the distribution is non-normal, it is more efficient to use the conventional t-tests. It is poor statistical practice to carry out both the parametric and non-parametric tests on a set of data and then choose the result that is most convenient to the investigator