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House price-to-rent (P-t-R) ratios are among the most widely used measures of housing market conditions. Given the theoretical and apparent bidirectional, causal relationships and imbalances between the housing market, broader economy and financial market determinants, it is important to understand the relationship between macro- and micro-economic characteristics in relation to the P-t-R ratio to enhance the understanding of housing market dynamics. This paper studies the joint dynamics and persistence of house prices and rents and examines the temporal interactions of the P-t-R ratio and economic and financial determinants.

The authors examine the lead–lag relationships between the P-t-R ratios and a spectrum of macroeconomic variables using cointegration and causality methods, initially at the aggregate position and also across housing types within the Northern Ireland housing market to establish whether there are subtle differences in how various housing segments react to changes in economic activity and market fundamentals.

The findings reveal price switching dynamics and some very distinct long- and short-run relationships between macroeconomic and financial indicators and the P-t-R ratios across the various housing segments. The results exhibit monetary supply, foreign exchange markets and the stock market to be important drivers of the P-t-R ratio, with P-t-R movements seemingly tied, or are in tandem, with the overall economy, particularly with the construction sector.

The study shows that the P-t-R ratio can be used as an early measure for establishing the effects of macroprudential policy changes and how these may manifest across housing tiers and quality, which can further act as a signal for preventing or at least mitigating future irrational price cyclicity. These insights serve to inform housing and economic policy and macroprudential policy design, principally within lending policy and the effect of regulatory interventions and further enhance the understanding of the P-t-R ratio on housing market structure and dynamics.

This study is the first in the housing literature that examines the causal relationships between the P-t-R ratio and macroeconomic activity at the sub-market level. It investigates whether and how money supply, inflation, foreign exchange markets, general economic productivity and other important macroeconomic factors interact with the pricing of different property types over time.

The role of energy efficiency and particularly energy performance certificates (EPCs) has emerged as a topical and important aspect of real estate markets. Various studies have been carried out investigating the perceived capitalisation effects of energy efficiency on property prices. There, however, remains divergence of opinion whether the capitalisation effect is truly in existence with extant research showing differing magnitudes of effects, if any. To date, no study (that the authors are aware of) has investigated the nature of the transition between EPC bands and price effects. The purpose of this study is to add to the research of the energy efficiency of housing to examine the nature of the likelihood of property characteristics being associated with higher EPC scores and value.

This research undertakes a suite of methodological tests to investigate the more latent relationships between EPC bands and pricing behaviour using 3,797 achieved sales prices within the Belfast housing market. Binary logit regression models are specified in conjunction with a Polytomous Universal Model to examine the likelihood of EPC bands falling within a particular property type and the likelihood of any pricing effects.

The findings show the differing property types to comprise very distinct and complex relationships in terms of price and EPC banding. The binary logit model estimations for both terrace properties and apartments reveal an increased likelihood to obtain higher EPC scores, with the semi-detached sector displaying a “mixed effect” with detached property revealing decreased probability of having superior energy performance and decreased likelihood of having poorer energy performance. The ordinal model estimations indicate that sales price comprises no relationship with energy performance, inferring that there is no increased probability of an increase in sales price with higher EPC rating.

This research offers new insights and focus on achieving a better understanding of the nexus between energy performance and property characteristics using alternative modelling approaches. This provides more exploratory insights into the complex relationships and offers awareness for policy discourse in terms of targeting properties which will tend to be poorer in energy efficiency.

Air quality, noise and proximity to urban infrastructure can arguably have an important impact on the quality of life. Environmental quality (the price of good health) has become a central tenet for consumer choice in urban locales when deciding on a residential neighbourhood. Unlike the market for most tangible goods, the market for environmental quality does not yield an observable per unit price effect. As no explicit price exists for a unit of environmental quality, this paper aims to use the housing market to derive its implicit price and test whether these constituent elements of health and well-being are indeed capitalised into property prices and thus implicitly priced in the market place.

A considerable number of studies have used hedonic pricing models by incorporating spatial effects to assess the impact of air quality, noise and proximity to noise pollutants on property market pricing. This study presents a spatial analysis of air quality and noise pollution and their association with house prices, using 2,501 sale transactions for the period 2013. To assess the impact of the pollutants, three different spatial modelling approaches are used, namely, ordinary least squares using spatial dummies, a geographically weighted regression (GWR) and a spatial lag model (SLM).

The findings suggest that air quality pollutants have an adverse impact on house prices, which fluctuate across the urban area. The analysis suggests that the noise level does matter, although this varies significantly over the urban setting and varies by source.

Air quality and environmental noise pollution are important concerns for health and well-being. Noise impact seems to depend not only on the noise intensity to which dwellings are exposed but also on the nature of the noise source. This may suggest the presence of other externalities that arouse social aversion. This research presents an original study utilising advanced spatial modelling approaches. The research has value in further understanding the market impact of environmental factors and in providing findings to support local air zone management strategies, noise abatement and management strategies and is of value to the wider urban planning and public health disciplines.

This paper aims to examine the association of accruals and disaggregated pension components with future cash flows and also to investigate whether investors distinguish between pension information that is recognized (SFAS 158) versus disclosed (SFAS 132).

Regression analysis is used with a proxy for expected future cash flows as the dependent variable, and the components of pension disclosures as well as controls for the 2008-2009 financial crisis as the independent variables.

The results reveal that incorporating disaggregated pension components increases the ability to predict future cash flows, and that investors attach different pricing multiples to the various components in the models. The authors also find that during the 2008-2009 financial crisis, the signs of the coefficients on these components changed. Finally, the results indicate that investors assign more significance to pension accounting information that is recognized, as opposed to disclosed, and that disclosure affects the allocation of pension assets.

The authors provide empirical support for the conjecture posited by Amir and Benartzi (1998) that the prediction of future cash flows will be enhanced by the incorporation of the components of pension assets and liabilities. Importantly from a standard setting perspective, the authors also find evidence that investors assign more significance to pension accounting information that is recognized in the financial statements than to pension information that is disclosed.

A number of studies have investigated the relationship between energy performance certificates (EPCs) and house prices. A majority of studies have tended to model energy performance pricing effects within a traditional hedonic conditional mean estimate model. There has been limited analysis that has accounted for the relationship between EPCs and the effects across the pricing distribution. Moreover, there has been limited research examining the “standard cost improvements EPC score”, or “potential score”. Therefore, this paper aims to quantify and measure the dynamic effects of EPCs on house prices across the price spectrum and account for standardised cost-effective retrofit improvements.

Existing EPC studies produce one coefficient for the entirety of the pricing distribution, culminating in a single marginal implicit price effect. The approach within this study applies a quantile regression approach to empirically estimate how quantiles of house prices respond differently to unitary changes in the proximal effects of EPCs and structural property characteristics across the conditional distribution of house prices. Using a data set of 1,476 achieved transaction prices, the quantile regression models apply both assessed EPC score and bands and further examine the potential EPC rating for improved energy performance based on an average energy cost improvement.

The findings show that EPCs are valued differently across the quantiles and that conditional quantiles are asymmetrical. Only property prices in the upper quantiles of the price distribution show significant capitalisation effects with energy performance, and only properties with higher EPC scores display positive significant effects at the higher end of the price distribution. There are also brown discount effects evident for lower-rated properties within F- and G-rated EPC properties at the higher end of the pricing distribution. Moreover, the potential energy efficiency rating (score) also shows increased effects with sales prices and appears to minimise any brown discount effects. The findings imply that energy performance is a complex feature that is not easily “averaged” for valuation effect purposes.

While numerous studies have investigated the pricing effects of EPCs, they have tended to provide a single estimate to determine the relationship with price. This paper extends the traditional analytical insights beyond the conditional mean estimate by examining the quantiles of the relationship between EPCs and house prices to enhance the understanding of this esoteric and complex issue. In addition, this research applies the assessed energy efficiency potential to establish whether effective cost improvements enhance the relationship with sales price and capitalisation effects.

The purpose of this paper is to examine relationships of self-care behavior, illness representation and diabetes knowledge with A1C (level of glycemic control) in 124 incarcerated persons.

Using a cross-sectional design, summary scores and items from the self-care inventory revised, brief illness perception questionnaire and the spoken knowledge for low literacy in diabetes were evaluated using linear regression to assess their relationship to A1C.

Metabolic control was suboptimal for the majority of inmates with diabetes. The final regression model was statistically significant (F (3, 120)=9.51, p=0.001, R²=19.2 percent). Higher log10 HbA1C (A1C) was associated with lower personal control beliefs (B=−0.007, t (122)=−2.42, p=<0.02), higher self-report of diabetes understanding (B=0.009, t (122)=3.12, p=0.00) and using insulin (B=0.062, t (122)=2.45, p=0.02).

Similar to findings with community dwelling participants, enhancing diabetes personal control beliefs among inmates may lead to lower A1C.

Highly structured environments with limited options for self-care, personal choices and readily available health care may give some incarcerated persons with diabetes no motivation to improve diabetes control even if they have an understanding of what to do.

While there is abundant research in the community describing how these factors influence A1C levels, research of this nature with incarcerated persons with diabetes is limited. Findings will inform diabetes programming during incarceration to better prepare inmates for reentry.

This paper analyses how disaster risk management paradigms have gradually developed since the 1960s, shaped by practical experience of-and the debate about-the rising number of disasters, growing urbanization, and changing climatic conditions. In this context, climate change is shown as driving an urban pro-poor adaptation agenda, which could allow current shortcomings in urban risk reduction to be overcome. However, as past lessons in disaster risk management are rarely considered, any potential for improvement remains untapped. Possible ways of rectifying this situation are discussed, and a comprehensive framework for the reduction of both disaster and climate risks is presented.

Numerous geo-statistical methods have been developed to analyse the spatial dimension and composition of house prices. Despite these advances, spatial filtering remains an under-researched approach within house price studies. This paper aims to examine the spatial distribution of house prices using an eigenvector spatial filtering (ESF) procedure, to analyse the local variation and spatial heterogeneity.

Using 2,664 sale transactions over the one year period Q3 2017 to Q3 2018, an eigenvector spatial filtering approach is applied to evaluate spatial patterns within the Belfast housing market. This method consists of using geographical coordinates to specify eigenvectors across geographic distance to determine a set of spatial filters. These convey spatial structures representative of different spatial scales and units. The filters are incorporated as predictors into regression analyses to alleviate spatial autocorrelation. This approach is intuitive, given that detection of autocorrelation in specific filters and within the regression residuals can be markers for exclusion or inclusion criteria.

The findings show both robust and effective estimator consistency and limited spatial dependency – culminating in accurately specified hedonic pricing models. The findings show that the spatial component alone explains 14.6 per cent of the variation in property value, whereas 77.6 per cent of the variation could be attributed to an interaction between the structural characteristics and the local market geography expressed by the filters. This methodological step reduced short-scale spatial dependency and residual autocorrelation resulting in increased model stability and reduced misspecification error.

Eigenvector-based spatial filtering is a less known but suitable statistical protocol that can be used to analyse house price patterns taking into account spatial autocorrelation at varying (different) spatial scales. This approach arguably provides a more insightful analysis of house prices by removing spatial autocorrelation both objectively and subjectively to produce reliable, yet understandable, regression models, which do not suffer from traditional challenges of serial dependence or spatial mis-specification. This approach offers property researchers and policymakers an intuitive but comprehensible approach for producing accurate price estimation models, which can be readily interpreted.

The purpose of this paper is to propose a combined reordering scheme with a wide range of application, called Reversed Cuthill-McKee-approximate minimum degree (RCM-AMD), to improve a preconditioned general minimal residual method for solving equations using Lagrange multiplier method, and facilitates the choice of the reordering for the iterative method.

To reordering the coefficient matrix before a preconditioned iterative method will greatly impact its convergence behavior, but the effect is very problem-dependent, even performs very differently when different preconditionings applied for an identical problem or the scale of the problem varies. The proposed reordering scheme is designed based on the features of two popular ordering schemes, RCM and AMD, and benefits from each of them.

Via numerical experiments for the cases of various scales and difficulties, the effects of RCM-AMD on the preconditioner and the convergence are investigated and the comparisons of RCM, AMD and RCM-AMD are presented. The results show that the proposed reordering scheme RCM-AMD is appropriate for large-scale and difficult problems and can be used more generally and conveniently. The reason of the reordering effects is further analyzed as well.

The proposed RCM-AMD reordering scheme preferable for solving equations using Lagrange multiplier method, especially considering that the large-scale and difficult problems are very common in practical application. This combined reordering scheme is more wide-ranging and facilitates the choice of the reordering for the iterative method, and the proposed iterative method has good performance for practical cases in in-house and commercial codes on PC.

This research examines the effects of organizational change (i.e., change of the hospital name, chief executive officer (CEO), and ownership) on objective performance measures of customer services (hospital beds, payroll, full-time employees, and patients served) in the health care industry. Archival data were collected from 155 Hospitals in the State of Tennessee for four consecutive years. During that time period, there were a lot of mergers and acquisitions (M&A) and organizational changes in the health care industry in Tennessee. Results suggested that there was a significant reduction of hospital beds and a significant increase of payroll during the four-year period. These changes were more significant in urban hospitals than in rural hospitals. In the four-year period, a change of the hospital name resulting from a merger had increased the efficiency of serving customers (patient/FTE ratio), while those without the change had decreased the efficiency. Our results reveal some evidences that acquisitions may be related to short-term financial benefits as expected