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Floating Catchment Area (FCA) methods are a popular tool to investigate accessibility to public facilities, in particular health care services. FCA approaches are attractive because, unlike other accessibility measures, they take into account the potential for congestion of facilities. This is done by 1) considering the population within the catchment area of a facility to calculate a variable that measures level of service, and then 2) aggregating the level of service by population centers subject to catchment area constraints. In this paper we discuss an effect of FCA approaches, an artifact that we term demand and level of service inflation. These artifacts are present in previous implementations of FCA methods. We argue that inflation makes interpretation of estimates of accessibility difficult, which has possible deleterious consequences for decision making. Next, we propose a simple and intuitive approach to proportionally allocate demandand and level of service in FCA calculations. The approach is based on a standardization of the impedance matrix, similar to approaches popular in the spatial statistics and econometrics literature. The result is a more intiuitive measure of accessibility that 1) provides a local version of the provider-to-population ratio; and 2) preserves the level of demand and the level of supply in a system. We illustrate the relevant issues with some examples, and then empirically by means of a case study of accessibility to family physicians in the Hamilton Census Metropolitan Area (CMA), in Ontario, Canada. Results indicate that demand and supply inflation/deflation affect the interpretation of accessibility analysis using existing FCA methods, and that the proposed adjustment can lead to more intuitive results. [ABSTRACT FROM AUTHOR]

Quigley derived his hybrid price model to improve the precision of predicted prices of sold homes by statistically merging data of resold homes in a repeat sales model with that of once-sold homes in a single sales hedonic price model. The literature has few applications of the hybrid model aside from those by Quigley and his collaborators. Two reasons for this underuse may be its computational intensiveness and its marginal empirical improvement in comparison with two other models. This paper first demystifies this computational intensiveness by calibrating models in Microsoft Excel with transferable procedures into other software. It second evaluates the hybrid price model’s empirical improvement as a reason for its underuse by predicting prices of 2,559 sold and resold homes observed in two inner-city neighbourhoods in Windsor, Ontario, during a 30-year period. The results as hypothesized are its lower standard errors of regression coefficients and higher simple R-squared than those of a single sales hedonic price model. Moreover, the hybrid model’s predictions have higher correlations than those of the single sales model with not only in-sample observed prices or changes in prices but also out-of-sample ones. The conclusion speculates in plans for future research about reasons for two models’ similar or dissimilar regression coefficients and standard errors predicting correspondingly similar or dissimilar sale prices of homes through time. [ABSTRACT FROM AUTHOR]

Objectives: We aimed to explore whether mortality data are consistent with the view that aging is accelerated for people with a history of incarceration compared to the general population, using data on mortality rates and life expectancy for persons in Ontario, Canada. Methods: We obtained data from the Ontario Ministry of Community Safety and Correctional Services on all adults admitted to provincial correctional facilities in Ontario in 2000, and linked these data with death records from provincial vital statistics between January 1, 2000 and December 31, 2012. We used life table methods to calculate mortality rates and life expectancies for this cohort by sex and 5-year age group. We similarly generated population comparison rates using publicly available data for the general population of Ontario in 2006 as the midpoint of the follow up period. We compared these mortality indices between the 2000 Ontario prison cohort and the general population by age group and sex. Results: The difference in all-cause mortality rates between the 2000 Ontario prison cohort and the general population was greatest for younger adults, with the prison cohort experiencing rates of death that would be expected for persons at least 15 years older at ages 20 to 44 for men and ages 20 to 59 for women. Life expectancy in the 2000 Ontario prison cohort was most similar to life expectancy of persons five years older in the general population at age intervals 20 to 45 in men and 20 to 30 in women. Conclusions: For most of adulthood, life expectancy and mortality rates are worse for adults with a history of incarceration than for the general population in Ontario, Canada. However, the association between mortality and incarceration status is modified by age, with the greatest relative burden of mortality experienced by younger persons with a history of incarceration and modified by sex, with worse relative mortality in women. Future research should explore the association between incarceration status and markers of aging including mortality, morbidity and physical appearance. [ABSTRACT FROM AUTHOR]