A Simple Model of Housing Rental and Ownership with Policy Simulations

The housing market is both large and complex. This paper develops a simple model that captures the essential features of the supply and demand for housing, and which is used to evaluate the impact of a range of policy interventions. Increases in the stock of housing would reduce rents and house prices. A reduction in tax concessions for landlords would raise rents and moderate house prices. Additional subsidies for owner-occupancy would tend to reduce rents and raise house prices. Significant reductions in rents and house prices would follow a fall in the cost of housing, through, for example lower regulatory and consent costs. Falling real interest rates result in lower rents, higher house prices and lower owner-occupancy rates. Despite the widespread attention owner-occupancy rates have attracted, the paper concludes that they are not a particularly helpful guide to the state of the housing market. Typically they are quite insensitive to policy interventions, a result that follows from the integrated view of both the rental and ownership market, adopted in this study.Housing markets; New Zealand; rental and owner-occupancy; elasticities; rents; house prices; policy simulations

Mild acute stress improves response speed without impairing accuracy or interference control in two selective attention tasks: Implications for theories of stress and cognition.

Acute stress is generally thought to impair performance on tasks thought to rely on selective attention. This effect has been well established for moderate to severe stressors, but no study has examined how a mild stressor-the most common type of stressor-influences selective attention. In addition, no study to date has examined how stress influences the component processes involved in overall selective attention task performance, such as controlled attention, automatic attentional activation, decision-making, and motor abilities. To address these issues, we randomly assigned 107 participants to a mild acute stress or control condition. As expected, the mild acute stress condition showed a small but significant increase in cortisol relative to the control condition. Following the stressor, we assessed attention with two separate flanker tasks. One of these tasks was optimized to investigate component attentional processes using computational cognitive modeling, whereas the other task employed mouse-tracking to illustrate how response conflict unfolded over time. The results for both tasks showed that mild acute stress decreased response time (i.e., increased response speed) without influencing accuracy or interference control. Further, computational modeling and mouse-tracking analyses indicated that these effects were due to faster motor action execution time for chosen actions. Intriguingly, however, cortisol responses were unrelated to any of the observed effects of mild stress. These results have implications for theories of stress and cognition, and highlight the importance of considering motor processes in understanding the effects of stress on cognitive task performance

Use of stable isotopes to assess the intraspecific foraging niche of males and female colour morphs of the damselfly Enallagma hageni

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/102631/1/een12075.pd

Familial influences on the full range of variability in attention and activity levels during adolescence: A longitudinal twin study

AbstractTo investigate familial influences on the full range of variability in attention and activity across adolescence, we collected maternal ratings of 339 twin pairs at ages 12, 14, and 16, and estimated the transmitted and new familial influences on attention and activity as measured by the Strengths and Weaknesses of Attention-Deficit/Hyperactivity Disorder Symptoms and Normal Behavior Scale. Familial influences were substantial for both traits across adolescence: genetic influences accounted for 54%–73% (attention) and 31%–73% (activity) of the total variance, and shared environmental influences accounted for 0%–22% of the attention variance and 13%–57% of the activity variance. The longitudinal stability of individual differences in attention and activity was largely accounted for by familial influences transmitted from previous ages. Innovations over adolescence were also partially attributable to familial influences. Studying the full range of variability in attention and activity may facilitate our understanding of attention-deficit/hyperactivity disorder's etiology and intervention.</jats:p

Assessment of the learning curve in health technologies: a systematic review

Objective: We reviewed and appraised the methods by which the issue of the learning curve has been addressed during health technology assessment in the past. Method: We performed a systematic review of papers in clinical databases (BIOSIS, CINAHL, Cochrane Library, EMBASE, HealthSTAR, MEDLINE, Science Citation Index, and Social Science Citation Index) using the search term "learning curve:" Results: The clinical search retrieved 4,571 abstracts for assessment, of which 559 (12%) published articles were eligible for review. Of these, 272 were judged to have formally assessed a learning curve. The procedures assessed were minimal access (51%), other surgical (41%), and diagnostic (8%). The majority of the studies were case series (95%). Some 47% of studies addressed only individual operator performance and 52% addressed institutional performance. The data were collected prospectively in 40%, retrospectively in 26%, and the method was unclear for 31%. The statistical methods used were simple graphs (44%), splitting the data chronologically and performing a t test or chi-squared test (60%), curve fitting (12%), and other model fitting (5%). Conclusions: Learning curves are rarely considered formally in health technology assessment. Where they are, the reporting of the studies and the statistical methods used are weak. As a minimum, reporting of learning should include the number and experience of the operators and a detailed description of data collection. Improved statistical methods would enhance the assessment of health technologies that require learning

Assessing the learning curve effect in health technologies: Lessons from the non-clinical literature

Introduction: Many health technologies exhibit some form of learning effect, and this represents a barrier to rigorous assessment. It has been shown that the statistical methods used are relatively crude. Methods to describe learning curves in fields outside medicine, for example, psychology and engineering, may be better. Methods: To systematically search non–health technology assessment literature (for example, PsycLit and Econlit databases) to identify novel statistical techniques applied to learning curves. Results: The search retrieved 9,431 abstracts for assessment, of which 18 used a statistical technique for analyzing learning effects that had not previously been identified in the clinical literature. The newly identified methods were combined with those previously used in health technology assessment, and categorized into four groups of increasing complexity: a) exploratory data analysis; b) simple data analysis; c) complex data analysis; and d) generic methods. All the complex structured data techniques for analyzing learning effects were identified in the nonclinical literature, and these emphasized the importance of estimating intra- and interindividual learning effects. Conclusion: A good dividend of more sophisticated methods was obtained by searching in nonclinical fields. These methods now require formal testing on health technology data sets

Expanding Ethical Standards of HMR: Necessary Evils and the Multiple Dimensions of Impact

Ethical challenges abound in HRM. Each day, in the course of executing and communicating HR decisions, managers have the potential to change, shape, redirect, and fundamentally alter the course of other people\u27s lives. Managers make hiring decisions that reward selected applicants with salaries, benefits, knowledge, and skills, but leave the remaining applicants bereft of these opportunities and advantages. Managers make promotion decisions that reward selected employees with raises, status, and responsibility, leaving other employees wondering about their future and their potential. Managers make firing and lay-off decisions in order to improve corporate performance, all the while harming the targeted individuals and even undermining the commitment and energy of survivors. Even when managers complete performance appraisals and deliver performance feedback, they may inspire one employee and devastate another. For each HR practice, there are winners and there are losers: Those who get the job, or receive a portfolio of benefits, and those who do not