Vegetation on and around large-scale buildings positively influences native tropical bird abundance and bird species richness

High population growth in the tropics is driving urbanisation, removing diverse natural ecosystems. This is causing native species to suffer while introduced synanthropes flourish. City planners are developing urban greenspace networks, in part trying to address this issue. Architects contribute to these greenspace networks by designing elevated and ground level green spaces on large-scale buildings. However, little evidence is available on whether building green spaces support native fauna. This is true for birds in tropical Singapore that support important ecosystem services and have existence value. Therefore, in this study, we conducted bird surveys and statistical analyses to determine, if and how vegetation on three building green space types (ground gardens, roof gardens and green walls) have a positive impact on native or introduced bird species. We found that elevated greenery (roof gardens and green walls) on large-scale buildings supported a higher richness of birds and abundance of urban native birds than control roofs and walls without vegetation. Ground gardens supported similar levels of native species as roof gardens but also a larger proportion of generalist synanthropes. However, we found no tropical forest habitat specialists across any space type. Therefore, we recommend roof gardens and ground gardens as a potential space for urban natives outside of a less competitive ground-level urban environment. Our study also found certain building design elements (height of elevated space, presence of specific plants) supported different species groups. Therefore, we suggest that these ecological requirements for different species groups are considered when designing a building’s green space.

     

The Opportunities and Constraints to Collaboration in Public Sector Management

Public Organization Review - This article synthesizes current insights about the opportunities and constraints to collaborative public management. Despite the swath of research on...     

Pensions in the European Union: Adapting to Economic and Social Changes

Throughout the European Union, pension schemes are undergoing a process of adaptation to a completely different context. Some of the main stumbling blocks to this process are the great number of issues involved and the diversity of questions that these raise: demographic changes, the labour market, economic growth, social justice, the ways of regulating the established provisions and decision-making in their regard. These dimensions do not offer ready-made answers, from the standpoint of pension financing. Apart from the complexity of the situation, however, a fundamental component of European societies is definitely at stake here: the ability to guarantee a decent level of security to all citizens when they reach retirement age.     

The Optimal Income Taxation of Couples

This paper analyzes the general nonlinear optimal income tax for couples, a multidimensional screening problem. Each couple consists of a primary earner who always participates in the labor market, but makes an hours‐of‐work choice, and a secondary earner who chooses whether or not to work. If second‐earner participation is a signal of the couple being better (worse) off, we prove that optimal tax schemes display a positive tax (subsidy) on secondary earnings and that the tax (subsidy) on secondary earnings decreases with primary earnings and converges to zero asymptotically. We present calibrated microsimulations for the United Kingdom showing that decreasing tax rates on secondary earnings is quantitatively significant and consistent with actual income tax and transfer programs.     

Nonparametric Identification of Risk Aversion in First‐Price Auctions Under Exclusion Restrictions

This paper studies the nonparametric identification of the first‐price auction model with risk averse bidders within the private value paradigm. First, we show that the benchmark model is nonindentified from observed bids. We also derive the restrictions imposed by the model on observables and show that these restrictions are weak. Second, we establish the nonparametric identification of the bidders' utility function under exclusion restrictions. Our primary exclusion restriction takes the form of an exogenous bidders' participation, leading to a latent distribution of private values that is independent of the number of bidders. The key idea is to exploit the property that the bid distribution varies with the number of bidders while the private value distribution does not. We then extend these results to endogenous bidders' participation when the exclusion restriction takes the form of instruments that do not affect the bidders' private value distribution. Though derived for a benchmark model, our results extend to more general cases such as a binding reserve price, affiliated private values, and asymmetric bidders. Last, possible estimation methods are proposed.     

Use of a historical control group in a noninferiority trial assessing a new antibacterial treatment: A case study and discussion of practical implementation aspects

When recruitment into a clinical trial is limited due to rarity of the disease of interest, or when recruitment to the control arm is limited due to ethical reasons (eg, pediatric studies or important unmet medical need), exploiting historical controls to augment the prospectively collected database can be an attractive option. Statistical methods for combining historical data with randomized data, while accounting for the incompatibility between the two, have been recently proposed and remain an active field of research. The current literature is lacking a rigorous comparison between methods but also guidelines about their use in practice. In this paper, we compare the existing methods based on a confirmatory phase III study design exercise done for a new antibacterial therapy with a binary endpoint and a single historical dataset. A procedure to assess the relative performance of the different methods for borrowing information from historical control data is proposed, and practical questions related to the selection and implementation of methods are discussed. Based on our examination, we found that the methods have a comparable performance, but we recommend the robust mixture prior for its ease of implementation.     

Care-giving Coping Strategies Among Mothers with Chronically Ill Children

ABSTRACT

The purpose of the study is to identify the types of stresses experienced and the coping strategies used by mothers who are responsible for providing care to their chronically ill and disabled children. A qualitative approach was selected to systematically document the experiences and highlight individual coping strategies. Purposive sampling was used in this qualitative pilot study, fifteen (15) mothers who were known to the researcher as well as two schools that specifically cater for children with disabilities were selected to participate in the study. Thirty questionnaires were handed out of which fifteen were returned. Data was collected using the coping Health Inventory for Parents (CHIP) to measure the extent to which parents perceived a number of coping strategies to be helpful in coping with the chronic illness of their child (ren). The scale comprised 45 items with 3 subscales. The results highlighted the types of stresses that were experienced by the mothers and the coping strategies practiced by these mothers when caring for their disabled children. Mothers who care for chronically ill children are faced with daily stress that relates to care as well as their personal life.     

Analysis of adaptive directional stratification for the controlled estimation of rare event probabilities

In the context of structural reliability, a small probability to be assessed, a high computational time model and a relatively large input dimension are typical constraints which brought together lead to an interesting challenge. Indeed, in this framework many existing stochastic methods fail in estimating the failure probability with robustness.